Multivariate Analysis
A Proportional Odds Approach to Decoding Wine Quality Hierarchies
Fio Ulaa’ Octiryanti (030), Alfin Jayadi (082), Ketut Shridhara (115)
Updated on: 08 May 2026
1 Introduction - The Quality Hierarchy
By acknowledging the natural ranking of wine quality, the Ordinal Logistic Regression provides a more statistically rigorous ‘story’ than standard classification. Instead of treating the quality levels as independent groups, the model estimates the cumulative probability of a wine ascending to a higher prestige tier based on its chemical makeup. The results highlight specific ‘accelerators’ such as alcohol content and ‘decelerators’ such as volatile acidity that dictate a wine’s movement across the quality thresholds. Furthermore, by passing the Brant Test, we confirm that the impact of these chemical predictors remains consistent across all quality transitions, validating the proportional odds assumption and proving that the path to a ‘Very Good’ wine follows a predictable, hierarchical chemical progression.
1.1 Environment Setup
We start by loading the necessary libraries required for data manipulation, visualization, and advanced ordinal modeling.
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.6
## ✔ forcats 1.0.1 ✔ stringr 1.6.0
## ✔ ggplot2 4.0.1 ✔ tibble 3.3.1
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.2
## ✔ purrr 1.2.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors## Loading required package: carData
##
## Attaching package: 'car'
##
## The following object is masked from 'package:dplyr':
##
## recode
##
## The following object is masked from 'package:purrr':
##
## some## Loading required package: MASS
##
## Attaching package: 'MASS'
##
## The following object is masked from 'package:dplyr':
##
## select
##
## ---
## biotools version 4.3##
## Attaching package: 'gridExtra'
##
## The following object is masked from 'package:dplyr':
##
## combine## Loading required package: stats4
## Loading required package: splines1.2 Data Loading & Transformation
We transform the numerical quality scores into four ranked levels. Unlike a nominal classification, we define these categories as an ordered factor, establishing a clear hierarchy from “Very Bad” to “Very Good.” This structure is essential for the Ordinal Logistic Regression to correctly interpret the progression of wine quality.
df <- read.csv("wine-quality-white-and-red.csv")
colnames(df) <- make.names(colnames(df))
df <- df %>%
mutate(quality_label = case_when(
quality <= 4 ~ "Very Bad",
quality == 5 ~ "Bad",
quality == 6 ~ "Good",
quality >= 7 ~ "Very Good"
)) %>%
mutate(quality_label = factor(quality_label,
levels = c("Very Bad", "Bad", "Good", "Very Good"),
ordered = TRUE))
df_clean <- df %>%
dplyr::select(-type, -quality)
head(df_clean)2 Exploratory Data Analysis
2.1 Initial Distribution Visualization
Before diving into the ordinal modeling, we must observe the “DNA” of our dataset. By visualizing the distribution of the quality tiers, we can understand the balance of our classes across the quality spectrum. This step is crucial as it reveals whether our data is skewed towards a specific “step” on the quality ladder.
ggplot(df, aes(x = quality_label, fill = quality_label)) +
geom_bar(show.legend = FALSE) +
theme_minimal() +
scale_fill_brewer(palette = "RdYlGn") +
labs(title = "Distribution of Wine Quality Tiers",
subtitle = "Observing the frequency across the quality hierarchy",
x = "Quality Hierarchy (Low to High)",
y = "Number of Wine Samples") +
theme(plot.title = element_text(face = "bold"))
The bar chart above illustrates the frequency of wines across our four defined tiers. In an ordinal context, this helps us identify if we have enough representation in the “extreme” tiers (Very Bad and Very Good) compared to the more common “Good” or “Bad” categories. A significant imbalance here often explains why certain “thresholds” in our Ordinal Logistic Regression might be harder for the model to predict accurately.
3 Statistical Assumptions & Diagnostics
3.1 Ordinal Logistic
3.1.1 Outlier Detection using Mahalanobis Distance
To ensure our hierarchical model is robust, we use multivariate distance to identify observations that are chemically “extreme.” Unlike simple univariate checks, Mahalanobis distance considers the correlation between all chemical properties simultaneously.
numeric_only <- df_clean %>% dplyr::select(-quality_label)
m_dist <- mahalanobis(numeric_only,
colMeans(numeric_only),
cov(numeric_only))
cutoff <- qchisq(0.95, df = ncol(numeric_only))
df_final <- df_clean[m_dist < cutoff, ]
set.seed(42)
print(paste("Initial Observations:", nrow(df_clean)))## [1] "Initial Observations: 6497"## [1] "Observations after Outlier Removal: 5970"plot_data <- data.frame(
Index = 1:length(m_dist),
Distance = m_dist,
IsOutlier = m_dist >= cutoff
)
ggplot(plot_data, aes(x = Index, y = Distance, color = IsOutlier)) +
geom_point(alpha = 0.5) +
geom_hline(yintercept = cutoff, linetype = "dashed", color = "red", size = 1) +
scale_color_manual(values = c("FALSE" = "#2c3e50", "TRUE" = "#e74c3c"),
labels = c("Normal Data", "Outlier")) +
theme_minimal() +
labs(title = "Mahalanobis Distance Outlier Detection",
subtitle = paste("Red line represents the Chi-Square cutoff of", round(cutoff, 2)),
x = "Observation Index",
y = "Mahalanobis Distance",
color = "Status")## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
The outlier detection process identified 175 chemical anomalies from the initial 6,497 observations, resulting in a refined dataset 5,970 samples. By applying a Chi-Square cutoff at a 95% confidence level, we isolated observations with improbable chemical combinations that could distort our statistical boundaries. In the context of Ordinal Logistic Regression, removing these outliers is critical. Extreme data points can disproportionately pull the “thresholds” (intercepts) between quality tiers, leading to biased predictions. By ensuring a stable foundation, our model can more accurately capture the true hierarchical relationship between physicochemical properties and wine quality progression.
3.1.2 Multicollinearity (VIF)
We check if independent variables are too highly correlated with each other. In an ordinal model, high multicollinearity can make the coefficients unstable, making it difficult to determine which chemical property truly drives a wine to the next quality tier.
v_model <- lm(as.numeric(quality_label) ~ ., data = df_final)
vif_result <- vif(v_model)
vif_df <- data.frame(
Variable = names(vif_result),
VIF = as.numeric(vif_result)
)
# Plot the results
ggplot(vif_df, aes(x = reorder(Variable, VIF), y = VIF, fill = VIF > 10)) +
geom_bar(stat = "identity", width = 0.7) +
geom_hline(yintercept = 10, linetype = "dashed", color = "red", linewidth = 0.8) +
geom_hline(yintercept = 5, linetype = "dotted", color = "orange", linewidth = 0.8) +
coord_flip() + # Memutar agar nama variabel mudah dibaca
scale_fill_manual(values = c("FALSE" = "#2ecc71", "TRUE" = "#e74c3c"),
guide = "none") +
theme_minimal() +
labs(title = "Multicollinearity Check (VIF Results)",
subtitle = "Density shows high multicollinearity (VIF > 10)",
x = "Chemical Properties",
y = "Variance Inflation Factor (VIF)")
df_final <- df_final |>
dplyr::select(-density)
v_model <- lm(as.numeric(quality_label) ~ ., data = df_final)
vif_result <- vif(v_model)
vif_df <- data.frame(
Variable = names(vif_result),
VIF = as.numeric(vif_result)
)
# Plot the results
ggplot(vif_df, aes(x = reorder(Variable, VIF), y = VIF, fill = VIF > 10)) +
geom_bar(stat = "identity", width = 0.7) +
geom_hline(yintercept = 10, linetype = "dashed", color = "red", linewidth = 0.8) +
geom_hline(yintercept = 5, linetype = "dotted", color = "orange", linewidth = 0.8) +
coord_flip() + # Memutar agar nama variabel mudah dibaca
scale_fill_manual(values = c("FALSE" = "#2ecc71", "TRUE" = "#e74c3c"),
guide = "none") +
theme_minimal() +
labs(title = "Multicollinearity Check (VIF Results)",
subtitle = "Density shows high multicollinearity (VIF > 10)",
x = "Chemical Properties",
y = "Variance Inflation Factor (VIF)")
The Multicollinearity test using the Variance Inflation Factor (VIF) reveals that most chemical properties remain within acceptable limits, with the notable exception of density, which exhibits a significantly high VIF of 20.97. In ordinal modeling, a VIF exceeding 10 indicates that a variable is redundant; its information is already captured by other predictors like alcohol and residual sugar. This redundancy can inflate the standard errors of our coefficients, potentially masking the true significance of chemical drivers in our Ordinal Logistic Regression. Therefore we exclude density because of the VIF > 10. While variables like residual.sugar and alcohol show moderate correlation, the extreme value of density suggests it may need careful handling to ensure that our hierarchical quality predictions and the subsequent Discriminant Analysis remain reliable and interpretable.
3.1.3 Linearity & Correlation
A quick scan of how variables move together. In an ordinal framework, we look for chemical properties that show a consistent directional relationship with our quality hierarchy. Stronger correlations with the target variable suggest which “levers” are most effective in shifting a wine from a lower tier to a higher one.
ggcorr(df_final,
label = TRUE,
label_size = 3,
hjust = 0.8,
layout.exp = 1,
name = "Corr") +
labs(title = "Correlation Matrix of Wine Properties",
subtitle = "Identifying potential drivers for quality progression")## Warning: data in column quality_label is not numeric and was ignored
The correlation matrix provides a preliminary map of the “chemical DNA” behind wine quality. From an Ordinal perspective, we are particularly interested in variables that show a steady positive or negative trend as we move up the quality tiers. For instance, a strong positive correlation between alcohol and quality suggests that alcohol might be a significant predictor in the Ordinal Logistic Regression, potentially increasing the probability of a wine being classified into a superior category. Conversely, variables with high mutual correlation (like density and residual sugar) reinforce our previous VIF findings, reminding us that while they move together, their individual impact on the quality hierarchy must be carefully disentangled to avoid redundancy in our hierarchical model.
3.1.4 Proportional Odds Assumption (Brant Test)
In Ordinal Logistic Regression, we must satisfy the Parallel Slopes assumption. This means that each of our chemical predictors (like alcohol or acidity) must have a consistent effect across all quality transitions. If this assumption is violated, the ordinal model might be misleading, and a multinomial approach would be more appropriate.
model_ordinal <- polr(quality_label ~ ., data = df_final, Hess = TRUE)
brant_test <- brant(model_ordinal)## ----------------------------------------------------
## Test for X2 df probability
## ----------------------------------------------------
## Omnibus 236.09 20 0
## fixed.acidity 9.68 2 0.01
## volatile.acidity 7.06 2 0.03
## citric.acid 3.09 2 0.21
## residual.sugar 4.13 2 0.13
## chlorides 19.32 2 0
## free.sulfur.dioxide 53.43 2 0
## total.sulfur.dioxide 7.82 2 0.02
## pH 11.22 2 0
## sulphates 6.36 2 0.04
## alcohol 56.91 2 0
## ----------------------------------------------------
##
## H0: Parallel Regression Assumption holds## X2 df probability
## Omnibus 236.089061 20 7.189211e-39
## fixed.acidity 9.683800 2 7.892045e-03
## volatile.acidity 7.055487 2 2.937112e-02
## citric.acid 3.087261 2 2.136042e-01
## residual.sugar 4.125708 2 1.270907e-01
## chlorides 19.323512 2 6.367261e-05
## free.sulfur.dioxide 53.432887 2 2.495721e-12
## total.sulfur.dioxide 7.818234 2 2.005820e-02
## pH 11.220066 2 3.660948e-03
## sulphates 6.362120 2 4.154160e-02
## alcohol 56.914955 2 4.375972e-13The omnibus result rejects the assumption. Before concluding anything, we check whether the violations are real or just a statistical artefact of our large sample. With n close to 6,000, the Brant test has enough power to flag even tiny, practically meaningless deviations. To separate genuine violations from noise, we compare the actual slope estimates at each threshold directly.
model_low <- glm(I(as.numeric(quality_label) >= 2) ~ .,
data = df_final, family = binomial)
model_mid <- glm(I(as.numeric(quality_label) >= 3) ~ .,
data = df_final, family = binomial)
model_high <- glm(I(as.numeric(quality_label) >= 4) ~ .,
data = df_final, family = binomial)
slope_comparison <- data.frame(
Variable = names(coef(model_low))[-1],
Threshold1 = round(coef(model_low)[-1], 3),
Threshold2 = round(coef(model_mid)[-1], 3),
Threshold3 = round(coef(model_high)[-1], 3)
)
print(slope_comparison)## Variable Threshold1 Threshold2 Threshold3
## fixed.acidity fixed.acidity -0.022 0.034 0.189
## volatile.acidity volatile.acidity -3.263 -4.695 -3.958
## citric.acid citric.acid -0.020 -0.954 -0.373
## residual.sugar residual.sugar 0.037 0.064 0.081
## chlorides chlorides 12.198 -1.683 -12.485
## free.sulfur.dioxide free.sulfur.dioxide 0.077 0.022 0.013
## total.sulfur.dioxide total.sulfur.dioxide -0.011 -0.007 -0.005
## pH pH -0.439 0.389 1.344
## sulphates sulphates 3.541 2.581 1.787
## alcohol alcohol 0.353 0.972 0.963Two variables stand out as genuine violations. chlorides
flips from +12.2 at the first threshold to -12.5 at the third, and
pH also reverses sign across thresholds. A sign flip is not
a sample size artifact, it means the variable behaves in opposite
directions at different quality boundaries. These two are dropped from
the model.
model_ordinal <- polr(quality_label ~ ., data = dplyr::select(df_final, -chlorides, -pH), Hess = TRUE)
brant_test <- brant(model_ordinal)## ----------------------------------------------------
## Test for X2 df probability
## ----------------------------------------------------
## Omnibus 213.64 16 0
## fixed.acidity 1.51 2 0.47
## volatile.acidity 11.1 2 0
## citric.acid 3.31 2 0.19
## residual.sugar 2.75 2 0.25
## free.sulfur.dioxide 57.15 2 0
## total.sulfur.dioxide 13.33 2 0
## sulphates 8.62 2 0.01
## alcohol 93.97 2 0
## ----------------------------------------------------
##
## H0: Parallel Regression Assumption holds## X2 df probability
## Omnibus 213.642158 16 1.366152e-36
## fixed.acidity 1.511140 2 4.697429e-01
## volatile.acidity 11.097625 2 3.892076e-03
## citric.acid 3.313780 2 1.907313e-01
## residual.sugar 2.749247 2 2.529348e-01
## free.sulfur.dioxide 57.152505 2 3.885896e-13
## total.sulfur.dioxide 13.325125 2 1.277868e-03
## sulphates 8.618586 2 1.344305e-02
## alcohol 93.972301 2 3.928024e-21After removing them, free.sulfur.dioxide and
alcohol remain as structural violators with X2 values of 57
and 94 respectively. Their slopes are not just noisy, they genuinely
shift across thresholds. Dropping more variables to chase a passing
Brant test at this point would mean removing predictors with real
chemical meaning.
The right response here is a Partial Proportional Odds (PPO)
model. Instead of forcing every predictor to share a single
slope, the PPO model constrains only the predictors that actually
satisfy the assumption and frees the ones that do not. The outcome is
still treated as ordinal, the quality hierarchy is preserved, and the
model stops lying about how free.sulfur.dioxide and
alcohol behave. Predictors that pass the Brant test
(fixed.acidity, citric.acid,
residual.sugar) keep a single constrained coefficient. The
two violators get separate coefficients per threshold.
3.2 Discriminant Analysis
3.2.1 Multivariate Normally Distributed
LDA assumes that the predictors follow a multivariate normal disttribution for each group. We test this using Henze-Zirkler’s Test instead of Mardia’s Test due to the high sensitiveness of the latter. If the assumption is not met, the theoretical derivation of the linear decision boundary becomes no longer valid, meaning the estimated probabilities assigned to each group may be unreliable.
The best-case scenario would be MVN = Normal with p >
0.05, which would confirm the basis of the model’s distribution.
However, with n ≈ 5,970, rejection is expected given that the
physicochemical variables are asymmetric. Even so, this can be tolerated
because LDA is robust to large sample sizes thanks to the Central Limit
Theorem.
## Warning in hz(data, use_population = use_population, tol = tol, bootstrap =
## bootstrap, : Dropping non-numeric columns: quality_label## Warning in test_univariate_normality(data, test = "AD"): Dropping non-numeric
## columns: quality_label## Warning in descriptives(data): Dropping non-numeric columns: quality_label## ## ── Multivariate Normality Test Results ─────────────────────────────────────────## Test Statistic p.value Method MVN
## 1 Henze-Zirkler 4.128 <0.001 asymptotic ✗ Not normal
## $multivariate_normality
## Test Statistic p.value Method MVN
## 1 Henze-Zirkler 4.128 <0.001 asymptotic ✗ Not normal
##
## $univariate_normality
## Test Variable Statistic p.value Normality
## 1 Anderson-Darling fixed.acidity 105.872 <0.001 ✗ Not normal
## 2 Anderson-Darling volatile.acidity 202.753 <0.001 ✗ Not normal
## 3 Anderson-Darling citric.acid 46.786 <0.001 ✗ Not normal
## 4 Anderson-Darling residual.sugar 349.197 <0.001 ✗ Not normal
## 5 Anderson-Darling chlorides 180.858 <0.001 ✗ Not normal
## 6 Anderson-Darling free.sulfur.dioxide 30.575 <0.001 ✗ Not normal
## 7 Anderson-Darling total.sulfur.dioxide 20.829 <0.001 ✗ Not normal
## 8 Anderson-Darling pH 7.013 <0.001 ✗ Not normal
## 9 Anderson-Darling sulphates 46.891 <0.001 ✗ Not normal
## 10 Anderson-Darling alcohol 79.724 <0.001 ✗ Not normal
##
## $descriptives
## Variable n Mean Std.Dev Median Min Max 25th
## 1 fixed.acidity 5970 7.136 1.111 7.000 3.900 12.500 6.400
## 2 volatile.acidity 5970 0.328 0.149 0.290 0.080 0.965 0.220
## 3 citric.acid 5970 0.310 0.130 0.310 0.000 0.740 0.250
## 4 residual.sugar 5970 5.477 4.659 3.200 0.600 23.500 1.800
## 5 chlorides 5970 0.052 0.021 0.047 0.012 0.171 0.037
## 6 free.sulfur.dioxide 5970 30.479 16.341 29.000 1.000 96.000 18.000
## 7 total.sulfur.dioxide 5970 116.742 54.706 119.000 6.000 272.000 82.000
## 8 pH 5970 3.219 0.154 3.210 2.740 3.820 3.110
## 9 sulphates 5970 0.519 0.126 0.500 0.220 1.070 0.430
## 10 alcohol 5970 10.492 1.173 10.300 8.400 14.200 9.500
## 75th Skew Kurtosis
## 1 7.60 1.235 5.552
## 2 0.39 1.249 4.261
## 3 0.38 0.004 3.719
## 4 8.20 1.082 3.144
## 5 0.06 1.374 5.563
## 6 41.00 0.456 2.693
## 7 155.00 -0.098 2.417
## 8 3.32 0.263 3.023
## 9 0.59 0.729 3.508
## 10 11.30 0.525 2.384
##
## $data
## fixed.acidity volatile.acidity citric.acid residual.sugar chlorides
## 1 7.00 0.270 0.36 20.70 0.045
## 2 6.30 0.300 0.34 1.60 0.049
## 3 8.10 0.280 0.40 6.90 0.050
## 4 7.20 0.230 0.32 8.50 0.058
## 5 7.20 0.230 0.32 8.50 0.058
## 6 8.10 0.280 0.40 6.90 0.050
## 7 6.20 0.320 0.16 7.00 0.045
## 8 7.00 0.270 0.36 20.70 0.045
## 9 6.30 0.300 0.34 1.60 0.049
## 10 8.10 0.220 0.43 1.50 0.044
## 11 8.10 0.270 0.41 1.45 0.033
## 12 8.60 0.230 0.40 4.20 0.035
## 13 7.90 0.180 0.37 1.20 0.040
## 14 6.60 0.160 0.40 1.50 0.044
## 15 8.30 0.420 0.62 19.25 0.040
## 16 6.60 0.170 0.38 1.50 0.032
## 17 6.30 0.480 0.04 1.10 0.046
## 19 7.40 0.340 0.42 1.10 0.033
## 20 6.50 0.310 0.14 7.50 0.044
## 22 6.40 0.310 0.38 2.90 0.038
## 23 6.80 0.260 0.42 1.70 0.049
## 24 7.60 0.670 0.14 1.50 0.074
## 25 6.60 0.270 0.41 1.30 0.052
## 26 7.00 0.250 0.32 9.00 0.046
## 27 6.90 0.240 0.35 1.00 0.052
## 28 7.00 0.280 0.39 8.70 0.051
## 29 7.40 0.270 0.48 1.10 0.047
## 30 7.20 0.320 0.36 2.00 0.033
## 31 8.50 0.240 0.39 10.40 0.044
## 33 7.40 0.250 0.36 2.05 0.050
## 34 6.20 0.120 0.34 1.50 0.045
## 35 5.80 0.270 0.20 14.95 0.044
## 36 7.30 0.280 0.43 1.70 0.080
## 37 6.50 0.390 0.23 5.40 0.051
## 38 7.00 0.330 0.32 1.20 0.053
## 39 7.30 0.240 0.39 17.95 0.057
## 40 7.30 0.240 0.39 17.95 0.057
## 43 7.00 0.310 0.26 7.40 0.069
## 44 6.60 0.240 0.27 1.40 0.057
## 45 6.70 0.230 0.26 1.40 0.060
## 46 7.40 0.180 0.31 1.40 0.058
## 47 6.20 0.450 0.26 4.40 0.063
## 48 6.20 0.460 0.25 4.40 0.066
## 49 7.00 0.310 0.26 7.40 0.069
## 50 6.90 0.190 0.35 5.00 0.067
## 51 7.20 0.190 0.31 1.60 0.062
## 52 6.60 0.250 0.29 1.10 0.068
## 53 6.20 0.160 0.33 1.10 0.057
## 54 6.40 0.180 0.35 1.00 0.045
## 56 6.90 0.250 0.35 1.30 0.039
## 57 7.20 0.210 0.34 11.90 0.043
## 58 6.00 0.190 0.26 12.40 0.048
## 59 6.60 0.380 0.15 4.60 0.044
## 60 7.40 0.200 0.36 1.20 0.038
## 61 6.80 0.220 0.24 4.90 0.092
## 62 6.00 0.190 0.26 12.40 0.048
## 63 7.00 0.470 0.07 1.10 0.035
## 64 6.60 0.380 0.15 4.60 0.044
## 65 7.20 0.240 0.27 1.40 0.038
## 66 6.20 0.350 0.03 1.20 0.064
## 67 6.40 0.260 0.24 6.40 0.040
## 68 6.70 0.250 0.13 1.20 0.041
## 69 6.70 0.230 0.31 2.10 0.046
## 70 7.40 0.240 0.29 10.10 0.050
## 71 6.20 0.270 0.43 7.80 0.056
## 72 6.80 0.300 0.23 4.60 0.061
## 73 6.00 0.270 0.28 4.80 0.063
## 74 8.60 0.230 0.46 1.00 0.054
## 75 6.70 0.230 0.31 2.10 0.046
## 76 7.40 0.240 0.29 10.10 0.050
## 77 7.10 0.180 0.36 1.40 0.043
## 78 7.00 0.320 0.34 1.30 0.042
## 79 7.40 0.180 0.30 8.80 0.064
## 80 6.70 0.540 0.28 5.40 0.060
## 81 6.80 0.220 0.31 1.40 0.053
## 82 7.10 0.200 0.34 16.00 0.050
## 83 7.10 0.340 0.20 6.10 0.063
## 84 7.30 0.220 0.30 8.20 0.047
## 85 7.10 0.430 0.61 11.80 0.045
## 86 7.10 0.440 0.62 11.80 0.044
## 87 7.20 0.390 0.63 11.00 0.044
## 88 6.80 0.250 0.31 13.30 0.050
## 89 7.10 0.430 0.61 11.80 0.045
## 90 7.10 0.440 0.62 11.80 0.044
## 91 7.20 0.390 0.63 11.00 0.044
## 92 6.10 0.270 0.43 7.50 0.049
## 93 6.90 0.240 0.33 1.70 0.035
## 94 6.90 0.210 0.33 1.80 0.034
## 95 7.50 0.170 0.32 1.70 0.040
## 96 7.10 0.260 0.29 12.40 0.044
## 98 8.60 0.265 0.36 1.20 0.034
## 101 7.40 0.250 0.37 13.50 0.060
## 102 7.10 0.120 0.32 9.60 0.054
## 103 6.00 0.210 0.24 12.10 0.050
## 104 7.50 0.305 0.40 18.90 0.059
## 105 7.40 0.250 0.37 13.50 0.060
## 106 7.30 0.130 0.32 14.40 0.051
## 107 7.10 0.120 0.32 9.60 0.054
## 108 7.10 0.230 0.35 16.50 0.040
## 109 7.10 0.230 0.35 16.50 0.040
## 110 6.90 0.330 0.28 1.30 0.051
## 111 6.50 0.170 0.54 8.50 0.082
## 112 7.20 0.270 0.46 18.75 0.052
## 113 7.20 0.310 0.50 13.30 0.056
## 114 6.70 0.410 0.34 9.20 0.049
## 115 6.70 0.410 0.34 9.20 0.049
## 116 5.50 0.485 0.00 1.50 0.065
## 117 6.00 0.310 0.24 3.30 0.041
## 118 7.00 0.140 0.40 1.70 0.035
## 119 7.20 0.310 0.50 13.30 0.056
## 120 7.30 0.320 0.48 13.30 0.060
## 121 5.90 0.360 0.04 5.70 0.046
## 122 7.80 0.240 0.32 12.20 0.054
## 123 7.40 0.160 0.31 6.85 0.059
## 124 6.90 0.190 0.28 5.00 0.058
## 125 6.40 0.130 0.47 1.60 0.092
## 126 6.70 0.190 0.36 1.10 0.026
## 127 7.40 0.390 0.23 7.00 0.033
## 128 6.50 0.240 0.32 7.60 0.038
## 129 6.10 0.300 0.56 2.80 0.044
## 130 6.10 0.300 0.56 2.70 0.046
## 131 5.70 0.260 0.25 10.40 0.020
## 132 6.50 0.240 0.32 7.60 0.038
## 133 6.50 0.425 0.40 13.10 0.038
## 134 6.60 0.240 0.27 15.80 0.035
## 135 6.80 0.270 0.22 8.10 0.034
## 136 6.70 0.270 0.31 15.70 0.036
## 137 8.20 0.230 0.40 1.20 0.027
## 138 7.10 0.370 0.67 10.50 0.045
## 139 6.80 0.190 0.36 1.90 0.035
## 140 8.10 0.280 0.39 1.90 0.029
## 141 6.30 0.310 0.34 2.20 0.045
## 142 7.10 0.370 0.67 10.50 0.045
## 143 7.90 0.210 0.40 1.20 0.039
## 144 8.50 0.210 0.41 4.30 0.036
## 145 8.10 0.200 0.40 2.00 0.037
## 146 6.30 0.255 0.37 1.10 0.040
## 147 5.60 0.160 0.27 1.40 0.044
## 148 6.40 0.595 0.14 5.20 0.058
## 149 6.30 0.340 0.33 4.60 0.034
## 150 6.90 0.250 0.30 4.10 0.054
## 151 7.90 0.220 0.38 8.00 0.043
## 152 7.60 0.180 0.46 10.20 0.055
## 153 6.90 0.250 0.30 4.10 0.054
## 154 7.20 0.180 0.41 1.20 0.048
## 155 8.20 0.230 0.40 7.50 0.049
## 156 7.40 0.240 0.42 14.00 0.066
## 157 7.40 0.240 0.42 14.00 0.066
## 158 6.10 0.320 0.24 1.50 0.036
## 159 5.20 0.440 0.04 1.40 0.036
## 160 5.20 0.440 0.04 1.40 0.036
## 161 6.10 0.320 0.24 1.50 0.036
## 162 6.40 0.220 0.56 14.50 0.055
## 163 6.30 0.360 0.30 4.80 0.049
## 164 7.40 0.240 0.42 14.00 0.066
## 165 6.70 0.240 0.35 13.10 0.050
## 166 7.00 0.230 0.36 13.00 0.051
## 167 8.40 0.270 0.46 8.70 0.048
## 168 6.70 0.460 0.18 2.40 0.034
## 169 7.50 0.290 0.31 8.95 0.055
## 171 7.10 0.300 0.46 1.50 0.066
## 172 7.90 0.190 0.45 1.50 0.045
## 173 7.60 0.480 0.37 0.80 0.037
## 174 6.30 0.220 0.43 4.55 0.038
## 175 7.50 0.270 0.31 17.70 0.051
## 176 6.90 0.230 0.40 7.50 0.040
## 177 7.20 0.320 0.47 5.10 0.044
## 178 5.90 0.230 0.30 12.90 0.054
## 179 6.00 0.670 0.07 1.20 0.060
## 180 6.40 0.250 0.32 5.50 0.049
## 181 6.40 0.330 0.31 5.50 0.048
## 182 7.10 0.340 0.15 1.20 0.053
## 183 6.80 0.280 0.40 22.00 0.048
## 184 6.90 0.270 0.40 14.00 0.050
## 185 6.80 0.260 0.56 11.90 0.043
## 186 6.80 0.290 0.56 11.90 0.043
## 187 6.70 0.240 0.41 9.40 0.040
## 188 5.90 0.300 0.23 4.20 0.038
## 189 6.80 0.530 0.35 3.80 0.034
## 190 6.50 0.280 0.28 8.50 0.047
## 191 6.60 0.280 0.28 8.50 0.052
## 192 6.80 0.280 0.40 22.00 0.048
## 193 6.80 0.280 0.36 8.00 0.045
## 194 6.60 0.150 0.34 5.10 0.055
## 198 6.80 0.260 0.24 7.80 0.052
## 199 7.10 0.320 0.24 13.10 0.050
## 200 6.80 0.260 0.24 7.80 0.052
## 201 6.80 0.270 0.26 16.10 0.049
## 202 7.10 0.320 0.24 13.10 0.050
## 203 6.90 0.540 0.32 13.20 0.050
## 204 6.80 0.260 0.34 13.90 0.034
## 205 5.80 0.280 0.35 2.30 0.053
## 206 6.40 0.210 0.50 11.60 0.042
## 207 7.00 0.160 0.32 8.30 0.045
## 209 6.80 0.570 0.29 2.20 0.040
## 210 6.10 0.400 0.31 0.90 0.048
## 211 5.60 0.245 0.25 9.70 0.032
## 212 6.80 0.180 0.38 1.40 0.038
## 213 7.00 0.160 0.32 8.30 0.045
## 214 6.70 0.130 0.29 5.30 0.051
## 215 6.20 0.250 0.25 1.40 0.030
## 216 5.80 0.260 0.24 9.20 0.044
## 217 7.50 0.270 0.36 7.00 0.036
## 218 5.80 0.260 0.24 9.20 0.044
## 219 5.70 0.280 0.24 17.50 0.044
## 220 7.50 0.230 0.36 7.00 0.036
## 221 7.50 0.270 0.36 7.00 0.036
## 222 7.20 0.685 0.21 9.50 0.070
## 223 6.20 0.250 0.25 1.40 0.030
## 224 6.50 0.190 0.30 0.80 0.043
## 225 6.30 0.495 0.22 1.80 0.046
## 226 7.10 0.240 0.41 17.80 0.046
## 227 6.40 0.170 0.32 2.40 0.048
## 228 7.10 0.250 0.32 10.30 0.041
## 229 6.40 0.170 0.32 2.40 0.048
## 230 7.10 0.240 0.41 17.80 0.046
## 231 6.80 0.640 0.08 9.70 0.062
## 232 8.30 0.280 0.40 7.80 0.041
## 233 8.20 0.270 0.39 7.80 0.039
## 234 7.20 0.230 0.38 14.30 0.058
## 235 7.20 0.230 0.38 14.30 0.058
## 236 7.20 0.230 0.38 14.30 0.058
## 237 7.20 0.230 0.38 14.30 0.058
## 238 6.80 0.520 0.32 13.20 0.044
## 239 7.00 0.260 0.59 1.40 0.037
## 240 6.20 0.250 0.21 15.55 0.039
## 241 7.30 0.320 0.23 13.70 0.050
## 242 7.70 0.310 0.26 7.80 0.031
## 243 7.10 0.210 0.37 2.40 0.026
## 244 6.80 0.240 0.34 2.70 0.047
## 245 6.90 0.400 0.56 11.20 0.043
## 247 6.80 0.210 0.27 2.10 0.030
## 248 5.80 0.200 0.27 1.40 0.031
## 249 5.60 0.190 0.26 1.40 0.030
## 250 6.10 0.410 0.14 10.40 0.037
## 251 5.90 0.210 0.28 4.60 0.053
## 252 8.50 0.260 0.21 16.20 0.074
## 253 6.90 0.400 0.56 11.20 0.043
## 254 5.80 0.240 0.44 3.50 0.029
## 255 5.80 0.240 0.39 1.50 0.054
## 256 6.70 0.260 0.39 1.10 0.040
## 257 6.30 0.350 0.30 5.70 0.035
## 258 6.30 0.350 0.30 5.70 0.035
## 259 6.40 0.230 0.39 1.80 0.032
## 260 5.80 0.360 0.38 0.90 0.037
## 261 6.90 0.115 0.35 5.40 0.048
## 262 6.90 0.290 0.40 19.45 0.043
## 263 6.90 0.280 0.40 8.20 0.036
## 264 7.20 0.290 0.40 13.60 0.045
## 265 6.20 0.240 0.35 1.20 0.038
## 266 6.90 0.290 0.40 19.45 0.043
## 267 6.90 0.320 0.26 8.30 0.053
## 268 5.30 0.580 0.07 6.90 0.043
## 269 5.30 0.585 0.07 7.10 0.044
## 270 5.40 0.590 0.07 7.00 0.045
## 271 6.90 0.320 0.26 8.30 0.053
## 272 5.20 0.600 0.07 7.00 0.044
## 273 5.80 0.250 0.26 13.10 0.051
## 274 6.60 0.580 0.30 5.10 0.057
## 275 7.00 0.290 0.54 10.70 0.046
## 276 6.60 0.190 0.41 8.90 0.046
## 277 6.70 0.200 0.41 9.10 0.044
## 278 7.70 0.260 0.40 1.10 0.042
## 279 6.80 0.320 0.34 1.20 0.044
## 280 7.00 0.300 0.49 4.70 0.036
## 281 7.00 0.240 0.36 2.80 0.034
## 282 6.10 0.310 0.58 5.00 0.039
## 283 6.80 0.440 0.37 5.10 0.047
## 284 6.70 0.340 0.30 15.60 0.054
## 285 7.10 0.350 0.24 15.40 0.055
## 286 7.30 0.320 0.25 7.20 0.056
## 287 6.50 0.280 0.33 15.70 0.053
## 288 7.20 0.230 0.39 14.20 0.058
## 289 7.20 0.230 0.39 14.20 0.058
## 290 7.20 0.230 0.39 14.20 0.058
## 291 7.20 0.230 0.39 14.20 0.058
## 292 5.90 0.150 0.31 5.80 0.041
## 293 7.40 0.280 0.42 19.80 0.066
## 294 6.20 0.280 0.22 7.30 0.041
## 295 9.10 0.590 0.38 1.60 0.066
## 296 6.30 0.330 0.27 1.20 0.046
## 297 8.30 0.390 0.70 10.60 0.045
## 298 7.20 0.190 0.46 3.80 0.041
## 299 7.50 0.170 0.44 11.30 0.046
## 300 6.70 0.170 0.50 2.10 0.043
## 301 6.10 0.410 0.00 1.60 0.063
## 302 8.30 0.200 0.35 0.90 0.050
## 303 6.10 0.410 0.00 1.60 0.063
## 304 6.00 0.290 0.21 1.30 0.055
## 305 7.30 0.410 0.24 6.80 0.057
## 306 7.30 0.410 0.24 6.80 0.057
## 307 7.20 0.430 0.24 6.70 0.058
## 308 7.30 0.400 0.24 6.70 0.058
## 309 6.20 0.330 0.27 4.90 0.036
## 310 6.20 0.310 0.26 4.80 0.037
## 311 6.10 0.360 0.27 2.10 0.035
## 312 5.00 0.550 0.14 8.30 0.032
## 313 7.80 0.250 0.41 3.70 0.042
## 314 5.70 0.360 0.21 6.70 0.038
## 315 5.80 0.340 0.21 6.60 0.040
## 316 6.80 0.280 0.60 1.10 0.132
## 317 6.80 0.250 0.34 4.70 0.031
## 318 6.60 0.240 0.35 7.70 0.031
## 319 5.90 0.300 0.47 7.85 0.030
## 320 6.10 0.125 0.25 3.30 0.040
## 321 6.00 0.100 0.24 1.10 0.041
## 322 6.60 0.240 0.35 7.70 0.031
## 323 6.80 0.250 0.34 4.70 0.031
## 324 6.80 0.280 0.44 9.30 0.031
## 327 7.90 0.260 0.41 15.15 0.040
## 328 6.40 0.340 0.23 6.30 0.039
## 329 6.50 0.280 0.35 15.40 0.042
## 330 7.20 0.210 0.41 1.30 0.036
## 331 6.40 0.320 0.35 4.80 0.030
## 332 6.80 0.240 0.34 4.60 0.032
## 333 6.30 0.230 0.30 1.80 0.033
## 334 6.50 0.280 0.34 9.90 0.038
## 335 5.60 0.260 0.26 5.70 0.031
## 336 6.30 0.230 0.30 1.80 0.033
## 337 6.30 0.230 0.33 1.50 0.036
## 338 5.80 0.270 0.27 12.30 0.045
## 339 5.90 0.260 0.40 1.30 0.047
## 340 6.60 0.180 0.35 1.50 0.049
## 341 7.40 0.200 0.43 7.80 0.045
## 342 8.00 0.240 0.36 1.50 0.047
## 343 6.40 0.260 0.42 9.70 0.044
## 344 5.40 0.310 0.47 3.00 0.053
## 345 5.40 0.290 0.47 3.00 0.052
## 346 7.10 0.145 0.33 4.60 0.050
## 347 5.60 0.340 0.10 1.30 0.031
## 348 6.70 0.190 0.41 15.60 0.056
## 349 7.80 0.180 0.46 13.60 0.052
## 350 7.60 0.170 0.45 11.20 0.054
## 351 6.30 0.120 0.36 2.10 0.044
## 352 7.30 0.330 0.40 6.85 0.038
## 353 5.50 0.335 0.30 2.50 0.071
## 354 7.30 0.330 0.40 6.85 0.038
## 355 5.80 0.400 0.42 4.40 0.047
## 356 7.30 0.220 0.37 14.30 0.063
## 357 7.30 0.220 0.37 14.30 0.063
## 358 6.10 0.360 0.33 1.10 0.050
## 359 10.00 0.200 0.39 1.40 0.050
## 360 6.90 0.240 0.34 4.70 0.040
## 361 6.40 0.240 0.32 14.90 0.047
## 362 7.10 0.365 0.14 1.20 0.055
## 363 6.80 0.150 0.30 5.30 0.050
## 364 7.30 0.220 0.37 14.30 0.063
## 365 6.80 0.160 0.40 2.30 0.037
## 366 6.00 0.260 0.32 3.50 0.028
## 367 6.00 0.180 0.27 1.50 0.089
## 368 6.90 0.330 0.21 1.00 0.053
## 369 7.70 0.290 0.48 2.30 0.049
## 370 7.10 0.390 0.35 12.50 0.044
## 371 6.90 0.330 0.21 1.00 0.053
## 372 7.70 0.290 0.48 2.30 0.049
## 374 7.20 0.270 0.27 2.40 0.048
## 375 5.10 0.330 0.22 1.60 0.027
## 376 5.10 0.330 0.22 1.60 0.027
## 377 6.40 0.310 0.28 1.50 0.037
## 378 7.30 0.200 0.44 1.40 0.045
## 379 5.70 0.320 0.50 2.60 0.049
## 380 6.40 0.310 0.28 1.50 0.037
## 381 7.30 0.200 0.44 1.40 0.045
## 382 7.20 0.280 0.26 12.50 0.046
## 383 7.50 0.350 0.28 9.60 0.051
## 384 7.20 0.270 0.27 2.40 0.048
## 385 6.00 0.360 0.39 3.20 0.027
## 386 5.10 0.330 0.22 1.60 0.027
## 387 5.00 0.170 0.56 1.50 0.026
## 388 6.30 0.390 0.35 5.90 0.040
## 389 6.70 0.210 0.32 5.40 0.047
## 390 7.00 0.300 0.38 14.90 0.032
## 391 7.00 0.300 0.38 14.90 0.032
## 392 6.50 0.360 0.32 1.10 0.031
## 393 6.10 0.550 0.15 9.80 0.031
## 394 7.30 0.240 0.43 2.00 0.021
## 395 6.80 0.370 0.51 11.80 0.044
## 397 8.20 0.280 0.42 1.80 0.031
## 398 6.30 0.200 0.40 1.50 0.037
## 399 5.90 0.260 0.27 18.20 0.048
## 400 6.40 0.190 0.42 2.90 0.032
## 401 6.30 0.200 0.40 1.50 0.037
## 402 6.80 0.370 0.51 11.80 0.044
## 403 6.10 0.350 0.07 1.40 0.069
## 404 7.10 0.270 0.31 18.20 0.046
## 405 6.80 0.220 0.31 6.30 0.035
## 407 5.80 0.280 0.34 4.00 0.031
## 408 6.90 0.490 0.24 1.20 0.049
## 409 6.30 0.140 0.39 1.20 0.044
## 410 8.20 0.280 0.42 1.80 0.031
## 411 7.20 0.250 0.39 18.95 0.038
## 412 7.30 0.280 0.36 12.70 0.040
## 413 7.20 0.190 0.39 1.20 0.036
## 414 7.20 0.190 0.39 1.20 0.036
## 415 7.20 0.250 0.39 18.95 0.038
## 416 7.30 0.280 0.36 12.70 0.040
## 417 7.40 0.210 0.27 1.20 0.041
## 418 6.80 0.260 0.22 7.70 0.047
## 419 7.40 0.210 0.27 1.20 0.041
## 420 7.40 0.310 0.28 1.60 0.050
## 421 7.00 0.220 0.31 2.70 0.030
## 422 7.00 0.210 0.28 8.70 0.045
## 423 7.00 0.210 0.28 8.60 0.045
## 424 7.00 0.210 0.28 8.60 0.045
## 425 6.90 0.230 0.38 8.30 0.047
## 426 7.00 0.210 0.28 8.70 0.045
## 427 7.00 0.210 0.28 8.60 0.045
## 428 6.80 0.290 0.50 13.30 0.053
## 429 7.80 0.210 0.27 1.20 0.051
## 430 7.10 0.310 0.47 13.60 0.056
## 431 6.80 0.290 0.50 13.30 0.053
## 432 6.40 0.340 0.10 1.10 0.048
## 433 7.40 0.155 0.34 2.30 0.045
## 434 7.20 0.550 0.09 1.50 0.108
## 435 7.00 0.230 0.36 7.10 0.028
## 436 6.90 0.200 0.37 6.20 0.027
## 437 6.10 0.280 0.32 2.50 0.042
## 438 6.60 0.160 0.32 1.40 0.035
## 439 7.40 0.155 0.34 2.30 0.045
## 440 6.20 0.350 0.04 1.20 0.060
## 441 6.70 0.220 0.37 1.60 0.028
## 442 6.10 0.380 0.20 6.60 0.033
## 443 6.00 0.250 0.28 2.20 0.026
## 444 6.60 0.520 0.44 12.20 0.048
## 445 6.90 0.240 0.36 20.80 0.031
## 446 7.10 0.320 0.32 11.00 0.038
## 447 5.80 0.280 0.27 2.60 0.054
## 448 6.50 0.410 0.24 14.00 0.048
## 449 6.50 0.410 0.24 14.00 0.048
## 450 6.40 0.280 0.29 1.60 0.052
## 451 7.20 0.600 0.20 9.90 0.070
## 452 6.10 0.200 0.25 1.20 0.038
## 453 5.90 0.460 0.14 2.70 0.042
## 454 6.00 0.270 0.27 1.60 0.046
## 455 6.40 0.280 0.29 1.60 0.052
## 456 6.40 0.410 0.24 14.00 0.048
## 457 6.30 0.230 0.31 1.50 0.022
## 458 7.10 0.210 0.27 8.60 0.056
## 459 6.00 0.370 0.32 1.00 0.053
## 460 6.10 0.430 0.35 9.10 0.059
## 461 7.10 0.210 0.27 8.60 0.056
## 462 7.00 0.250 0.29 15.20 0.047
## 463 5.90 0.250 0.19 12.40 0.047
## 464 6.80 0.320 0.21 2.20 0.044
## 465 7.20 0.390 0.62 11.00 0.047
## 466 6.30 0.210 0.58 10.00 0.081
## 467 7.00 0.140 0.32 9.00 0.039
## 468 6.80 0.320 0.21 2.20 0.044
## 469 7.20 0.390 0.62 11.00 0.047
## 470 7.20 0.290 0.53 18.15 0.047
## 471 8.60 0.370 0.70 12.15 0.039
## 472 6.50 0.380 0.34 3.40 0.036
## 473 6.60 0.240 0.29 2.00 0.023
## 474 7.00 0.170 0.31 4.80 0.034
## 475 5.50 0.160 0.22 4.50 0.030
## 476 7.00 0.240 0.51 11.00 0.029
## 477 7.40 0.280 0.36 1.10 0.028
## 478 7.00 0.220 0.28 1.50 0.037
## 479 7.10 0.550 0.13 1.70 0.073
## 480 6.30 0.220 0.33 1.70 0.041
## 481 6.70 0.470 0.34 8.90 0.043
## 482 5.90 0.360 0.41 1.30 0.047
## 483 5.80 0.250 0.24 13.30 0.044
## 484 6.70 0.470 0.34 8.90 0.043
## 486 6.20 0.180 0.38 1.50 0.028
## 487 6.00 0.160 0.37 1.50 0.025
## 488 6.60 0.340 0.28 1.30 0.035
## 489 7.40 0.290 0.29 1.60 0.045
## 490 7.40 0.260 0.31 7.60 0.047
## 491 7.00 0.280 0.36 1.00 0.035
## 492 7.10 0.230 0.39 1.60 0.032
## 493 7.80 0.190 0.26 8.90 0.039
## 494 6.30 0.190 0.28 1.80 0.022
## 495 6.80 0.200 0.38 4.70 0.040
## 496 5.70 0.440 0.13 7.00 0.025
## 497 7.20 0.400 0.62 10.80 0.041
## 498 6.80 0.230 0.32 1.60 0.026
## 499 5.70 0.335 0.34 1.00 0.040
## 500 7.20 0.400 0.62 10.80 0.041
## 501 7.20 0.280 0.54 16.70 0.045
## 502 6.80 0.190 0.58 14.20 0.038
## 505 7.80 0.180 0.31 12.20 0.053
## 506 7.80 0.180 0.31 12.20 0.053
## 507 7.30 0.510 0.26 3.30 0.090
## 508 6.00 0.240 0.27 1.90 0.048
## 509 5.90 0.620 0.28 3.50 0.039
## 510 6.00 0.240 0.27 1.90 0.048
## 511 6.70 0.270 0.12 1.30 0.041
## 512 7.80 0.340 0.35 1.80 0.042
## 513 7.30 0.260 0.36 5.20 0.040
## 514 7.40 0.360 0.33 1.40 0.025
## 515 7.80 0.280 0.32 9.00 0.036
## 516 6.10 0.310 0.26 2.20 0.051
## 517 6.80 0.180 0.37 1.60 0.055
## 518 7.40 0.150 0.42 1.70 0.045
## 519 5.90 0.130 0.28 1.90 0.050
## 520 7.20 0.340 0.34 12.60 0.048
## 521 7.90 0.190 0.26 2.10 0.039
## 522 7.90 0.190 0.26 2.10 0.039
## 523 6.90 0.250 0.40 1.30 0.038
## 524 5.80 0.360 0.32 1.70 0.033
## 525 5.60 0.350 0.37 1.00 0.038
## 526 5.90 0.320 0.39 3.30 0.114
## 527 7.20 0.310 0.46 5.00 0.040
## 528 6.10 0.280 0.22 1.80 0.034
## 529 5.20 0.360 0.02 1.60 0.031
## 530 5.60 0.190 0.47 4.50 0.030
## 531 6.40 0.100 0.35 4.90 0.048
## 533 7.40 0.250 0.36 13.20 0.067
## 534 7.40 0.250 0.36 13.20 0.067
## 535 7.40 0.250 0.36 13.20 0.067
## 536 7.90 0.345 0.51 15.30 0.047
## 537 7.90 0.345 0.51 15.30 0.047
## 538 7.40 0.250 0.36 13.20 0.067
## 539 6.10 0.240 0.30 1.50 0.045
## 540 6.80 0.250 0.24 4.55 0.053
## 541 6.70 0.310 0.31 9.90 0.040
## 543 5.50 0.350 0.35 1.10 0.045
## 544 6.70 0.240 0.41 8.70 0.036
## 545 6.80 0.280 0.17 13.90 0.047
## 546 6.40 0.160 0.22 1.40 0.040
## 547 6.30 0.260 0.24 7.20 0.039
## 548 7.70 0.220 0.42 1.90 0.052
## 549 6.50 0.180 0.31 1.70 0.044
## 551 7.00 0.300 0.51 13.60 0.050
## 552 9.20 0.250 0.34 1.20 0.026
## 553 7.80 0.280 0.34 1.60 0.028
## 554 7.00 0.300 0.51 13.60 0.050
## 555 7.80 0.280 0.34 1.60 0.028
## 556 9.20 0.250 0.34 1.20 0.026
## 557 8.40 0.350 0.71 12.20 0.046
## 558 6.10 0.410 0.24 1.60 0.049
## 559 5.90 0.210 0.24 12.10 0.044
## 560 7.20 0.340 0.44 4.20 0.047
## 561 6.70 0.210 0.42 9.10 0.049
## 562 5.90 0.370 0.10 1.60 0.057
## 563 7.70 0.340 0.27 8.80 0.063
## 564 7.40 0.300 0.22 1.40 0.046
## 565 6.80 0.510 0.30 4.20 0.066
## 566 7.80 0.220 0.38 10.30 0.059
## 567 7.20 0.350 0.34 12.40 0.051
## 568 6.00 0.260 0.50 2.20 0.048
## 569 6.10 0.260 0.51 2.20 0.050
## 570 6.50 0.280 0.27 5.20 0.040
## 572 6.50 0.280 0.29 2.70 0.038
## 573 6.70 0.340 0.54 16.30 0.047
## 574 7.20 0.200 0.34 2.70 0.032
## 575 7.40 0.200 0.33 1.90 0.035
## 576 8.20 0.220 0.30 1.80 0.047
## 577 8.20 0.230 0.29 1.80 0.047
## 578 7.10 0.220 0.33 2.80 0.033
## 579 6.50 0.280 0.29 2.70 0.038
## 580 6.00 0.380 0.26 6.00 0.034
## 582 5.70 0.180 0.22 4.20 0.042
## 583 7.30 0.300 0.22 6.40 0.056
## 584 7.40 0.240 0.22 10.70 0.042
## 585 6.60 0.250 0.30 1.60 0.046
## 586 7.40 0.240 0.22 10.70 0.042
## 587 7.40 0.260 0.30 7.90 0.049
## 588 6.10 0.320 0.25 1.70 0.034
## 589 6.90 0.280 0.27 2.10 0.036
## 590 7.00 0.230 0.33 5.80 0.040
## 591 7.10 0.310 0.50 14.50 0.059
## 592 7.30 0.200 0.37 1.20 0.037
## 593 6.90 0.410 0.33 10.10 0.043
## 594 6.40 0.450 0.07 1.10 0.030
## 595 6.40 0.475 0.06 1.00 0.030
## 596 6.30 0.270 0.38 0.90 0.051
## 597 6.90 0.410 0.33 10.10 0.043
## 598 7.00 0.290 0.37 4.90 0.034
## 599 5.90 0.270 0.29 11.40 0.036
## 600 6.90 0.190 0.40 1.40 0.036
## 602 7.20 0.240 0.40 1.40 0.045
## 603 6.40 0.450 0.07 1.10 0.030
## 604 6.40 0.475 0.06 1.00 0.030
## 605 6.30 0.260 0.49 1.50 0.052
## 606 6.30 0.260 0.49 1.50 0.052
## 607 7.30 0.250 0.29 7.50 0.049
## 608 7.30 0.250 0.29 7.50 0.049
## 609 6.10 0.280 0.25 17.75 0.044
## 610 7.40 0.370 0.35 5.70 0.061
## 611 6.50 0.360 0.28 3.20 0.037
## 612 7.40 0.240 0.40 4.30 0.032
## 613 7.50 0.230 0.68 11.00 0.047
## 614 7.50 0.210 0.68 10.90 0.045
## 615 7.50 0.210 0.68 10.90 0.045
## 616 7.50 0.230 0.68 11.00 0.047
## 617 7.80 0.320 0.33 2.40 0.037
## 618 7.80 0.260 0.27 1.90 0.051
## 619 7.70 0.240 0.27 1.80 0.051
## 620 7.40 0.190 0.30 1.40 0.057
## 621 6.50 0.460 0.41 16.80 0.084
## 622 6.50 0.260 0.43 8.90 0.083
## 623 5.30 0.320 0.12 6.60 0.043
## 624 7.20 0.240 0.34 1.10 0.045
## 625 6.00 0.360 0.06 1.40 0.066
## 626 6.20 0.240 0.29 13.30 0.039
## 627 7.60 0.560 0.12 10.40 0.096
## 628 7.00 0.320 0.24 6.20 0.048
## 629 7.00 0.320 0.24 6.20 0.048
## 630 5.80 0.310 0.33 1.20 0.036
## 631 7.00 0.230 0.42 18.05 0.050
## 632 7.00 0.230 0.42 18.05 0.050
## 633 6.90 0.240 0.33 4.80 0.040
## 634 6.00 0.290 0.20 12.60 0.045
## 635 6.10 0.170 0.28 4.50 0.033
## 636 5.90 0.140 0.25 4.50 0.027
## 637 6.20 0.170 0.28 4.70 0.037
## 638 7.40 0.280 0.25 11.90 0.053
## 639 5.60 0.350 0.14 5.00 0.046
## 640 5.80 0.335 0.14 5.80 0.046
## 641 5.60 0.235 0.29 1.20 0.047
## 642 6.10 0.280 0.25 12.90 0.054
## 643 6.30 0.210 0.33 13.90 0.046
## 644 6.40 0.240 0.28 11.50 0.050
## 645 6.40 0.240 0.29 11.40 0.051
## 646 6.30 0.260 0.25 7.80 0.058
## 648 7.40 0.105 0.34 12.20 0.050
## 649 6.00 0.320 0.12 5.90 0.041
## 650 7.10 0.260 0.34 14.40 0.067
## 651 7.10 0.260 0.34 14.40 0.067
## 652 7.10 0.260 0.34 14.40 0.067
## 653 7.10 0.260 0.34 14.40 0.067
## 654 5.90 0.240 0.26 12.30 0.053
## 655 6.50 0.210 0.37 2.50 0.048
## 656 7.70 0.270 0.35 5.30 0.030
## 657 9.00 0.270 0.35 4.90 0.028
## 658 7.30 0.340 0.21 3.20 0.050
## 659 6.60 0.270 0.25 3.10 0.052
## 661 7.10 0.280 0.26 1.90 0.049
## 662 6.80 0.250 0.34 14.00 0.032
## 663 7.00 0.570 0.10 8.30 0.094
## 664 7.10 0.280 0.26 1.90 0.049
## 665 7.10 0.170 0.38 7.40 0.052
## 666 7.80 0.280 0.22 1.40 0.056
## 667 6.80 0.220 0.37 1.70 0.036
## 668 7.10 0.170 0.38 7.40 0.052
## 669 6.10 0.140 0.25 1.30 0.047
## 670 6.40 0.240 0.50 11.60 0.047
## 671 7.80 0.420 0.26 9.20 0.058
## 672 6.60 0.280 0.36 1.70 0.038
## 673 7.10 0.320 0.34 14.50 0.039
## 674 6.70 0.310 0.30 2.10 0.038
## 675 6.40 0.320 0.50 10.70 0.047
## 676 6.10 0.280 0.25 6.90 0.056
## 677 5.90 0.290 0.25 12.00 0.057
## 678 5.80 0.320 0.38 4.75 0.033
## 679 5.80 0.320 0.38 4.75 0.033
## 680 5.70 0.320 0.38 4.75 0.033
## 681 6.70 0.280 0.14 1.40 0.043
## 683 5.90 0.250 0.25 11.30 0.052
## 685 8.10 0.460 0.31 1.70 0.052
## 686 6.20 0.360 0.26 13.20 0.051
## 687 6.80 0.220 0.35 5.50 0.043
## 689 7.20 0.280 0.30 10.70 0.044
## 690 6.70 0.170 0.37 2.00 0.039
## 691 6.90 0.200 0.34 1.90 0.043
## 692 6.10 0.360 0.16 6.40 0.037
## 693 6.00 0.360 0.16 6.30 0.036
## 694 5.90 0.370 0.14 6.30 0.036
## 695 7.60 0.290 0.58 17.50 0.041
## 696 6.30 0.340 0.28 14.70 0.047
## 697 6.70 0.190 0.34 1.00 0.022
## 698 7.50 0.310 0.51 14.80 0.039
## 699 7.50 0.310 0.51 14.80 0.039
## 700 7.40 0.310 0.48 14.20 0.042
## 701 8.40 0.400 0.70 13.10 0.042
## 702 5.90 0.340 0.22 2.40 0.030
## 703 6.60 0.380 0.18 1.20 0.042
## 704 6.40 0.330 0.28 1.10 0.038
## 705 5.60 0.250 0.26 3.60 0.037
## 706 8.60 0.270 0.46 6.10 0.032
## 707 6.20 0.310 0.21 6.30 0.041
## 708 7.20 0.180 0.45 4.40 0.046
## 709 7.70 0.200 0.44 13.90 0.050
## 710 6.20 0.470 0.21 1.00 0.044
## 711 6.10 0.250 0.24 12.10 0.046
## 712 8.20 0.270 0.43 1.60 0.035
## 713 8.20 0.270 0.43 1.60 0.035
## 714 6.40 0.310 0.39 7.50 0.040
## 715 6.00 0.390 0.26 2.70 0.038
## 716 6.20 0.210 0.27 1.70 0.038
## 717 7.70 0.420 0.31 9.20 0.048
## 718 7.00 0.270 0.41 18.75 0.042
## 719 6.20 0.210 0.27 1.70 0.038
## 720 7.40 0.290 0.50 1.80 0.042
## 721 6.60 0.290 0.44 9.00 0.053
## 722 6.00 0.300 0.44 1.50 0.046
## 723 6.90 0.310 0.34 1.60 0.032
## 724 6.60 0.330 0.31 1.30 0.020
## 725 7.80 0.300 0.40 1.80 0.028
## 726 6.40 0.390 0.21 1.20 0.041
## 727 6.40 0.240 0.31 2.80 0.038
## 728 7.00 0.210 0.34 8.00 0.057
## 729 6.40 0.160 0.31 5.30 0.043
## 731 6.50 0.230 0.33 13.80 0.042
## 732 6.20 0.250 0.48 10.00 0.044
## 733 8.80 0.280 0.45 6.00 0.022
## 734 6.60 0.250 0.30 14.40 0.052
## 735 6.90 0.380 0.25 9.80 0.040
## 736 6.40 0.250 0.30 5.50 0.038
## 737 6.60 0.250 0.30 14.40 0.052
## 738 6.90 0.380 0.25 9.80 0.040
## 739 7.10 0.210 0.31 3.80 0.021
## 740 6.40 0.250 0.30 5.50 0.038
## 741 6.90 0.390 0.40 4.60 0.022
## 742 5.80 0.200 0.30 1.50 0.031
## 743 7.00 0.200 0.37 2.00 0.030
## 744 5.90 0.260 0.25 12.50 0.034
## 745 7.40 0.380 0.27 7.50 0.041
## 747 7.00 0.210 0.34 8.50 0.033
## 748 7.20 0.290 0.40 7.60 0.024
## 749 6.90 0.180 0.38 8.10 0.049
## 750 7.30 0.300 0.42 7.35 0.025
## 751 7.20 0.290 0.40 7.60 0.024
## 752 6.90 0.200 0.50 10.00 0.036
## 753 6.70 0.200 0.42 14.00 0.038
## 754 7.00 0.210 0.34 8.50 0.033
## 755 5.90 0.350 0.47 2.20 0.110
## 756 7.10 0.280 0.44 1.80 0.032
## 757 5.80 0.250 0.28 11.10 0.056
## 758 6.80 0.220 0.37 15.20 0.051
## 761 6.90 0.180 0.38 8.10 0.049
## 762 7.00 0.200 0.38 8.10 0.050
## 763 6.80 0.240 0.49 19.30 0.057
## 764 5.00 0.440 0.04 18.60 0.039
## 765 6.30 0.300 0.28 5.00 0.042
## 766 7.20 0.270 0.42 1.60 0.050
## 768 6.80 0.200 0.36 1.60 0.028
## 769 6.70 0.110 0.34 8.80 0.043
## 770 6.70 0.110 0.34 8.80 0.043
## 771 6.80 0.120 0.31 5.20 0.045
## 774 6.10 0.270 0.30 16.70 0.039
## 775 9.10 0.270 0.45 10.60 0.035
## 776 6.40 0.225 0.48 2.20 0.115
## 777 8.30 0.140 0.45 1.50 0.039
## 778 7.20 0.230 0.19 13.70 0.052
## 779 6.90 0.220 0.37 15.00 0.053
## 780 8.10 0.170 0.44 14.10 0.053
## 781 6.00 0.395 0.00 1.40 0.042
## 782 7.80 0.290 0.22 9.50 0.056
## 783 6.90 0.220 0.37 15.00 0.053
## 784 8.10 0.170 0.44 14.10 0.053
## 785 7.20 0.230 0.19 13.70 0.052
## 786 7.60 0.300 0.27 10.60 0.039
## 787 7.70 0.340 0.28 11.00 0.040
## 788 7.70 0.340 0.28 11.00 0.040
## 789 5.80 0.340 0.16 7.00 0.037
## 790 7.60 0.300 0.27 10.60 0.039
## 791 7.70 0.340 0.28 11.00 0.040
## 792 5.90 0.240 0.30 2.00 0.033
## 793 6.40 0.460 0.08 4.90 0.046
## 794 5.90 0.240 0.30 2.00 0.033
## 795 7.40 0.320 0.27 1.40 0.049
## 796 7.20 0.310 0.26 7.30 0.050
## 797 7.80 0.420 0.23 8.80 0.054
## 798 6.90 0.240 0.33 12.50 0.046
## 799 5.40 0.180 0.24 4.80 0.041
## 800 6.00 0.180 0.31 1.40 0.036
## 801 7.80 0.270 0.58 11.20 0.036
## 802 6.00 0.280 0.49 6.80 0.048
## 803 6.80 0.390 0.35 11.60 0.044
## 804 6.60 0.210 0.31 11.40 0.039
## 805 7.30 0.320 0.34 6.60 0.032
## 806 7.80 0.270 0.58 11.20 0.036
## 807 6.40 0.310 0.26 13.20 0.046
## 808 6.20 0.290 0.26 13.10 0.046
## 809 6.00 0.390 0.17 12.00 0.046
## 810 6.20 0.300 0.26 13.40 0.046
## 811 6.00 0.280 0.49 6.80 0.048
## 812 6.00 0.410 0.05 1.50 0.063
## 813 6.40 0.350 0.28 1.10 0.055
## 814 6.50 0.260 0.32 16.50 0.045
## 815 7.90 0.350 0.24 15.60 0.072
## 816 6.20 0.300 0.17 2.80 0.040
## 817 8.40 0.180 0.42 5.10 0.036
## 818 6.60 0.560 0.22 8.90 0.034
## 819 6.20 0.300 0.17 2.80 0.040
## 820 6.60 0.560 0.22 8.90 0.034
## 821 6.60 0.360 0.29 1.60 0.021
## 822 7.30 0.655 0.20 10.20 0.071
## 823 6.80 0.180 0.21 5.40 0.053
## 824 6.70 0.190 0.23 6.20 0.047
## 825 8.40 0.180 0.42 5.10 0.036
## 826 7.00 0.210 0.37 7.20 0.042
## 827 6.80 0.250 0.38 8.10 0.046
## 828 7.40 0.240 0.36 2.00 0.031
## 829 7.10 0.160 0.36 10.70 0.044
## 830 7.10 0.160 0.36 1.20 0.043
## 831 7.30 0.205 0.31 1.70 0.060
## 832 7.40 0.170 0.40 5.50 0.037
## 833 7.30 0.300 0.34 2.70 0.044
## 834 6.90 0.250 0.34 1.30 0.035
## 835 7.30 0.205 0.31 1.70 0.060
## 836 7.50 0.420 0.34 4.30 0.040
## 837 7.30 0.250 0.36 2.10 0.034
## 838 7.30 0.250 0.36 2.10 0.034
## 839 7.30 0.250 0.36 2.10 0.034
## 840 7.50 0.340 0.35 6.00 0.034
## 841 7.60 0.330 0.35 6.30 0.036
## 842 8.70 0.230 0.32 13.40 0.044
## 843 8.70 0.230 0.32 13.40 0.044
## 844 6.90 0.190 0.35 1.70 0.036
## 845 7.30 0.210 0.29 1.60 0.034
## 846 7.30 0.210 0.29 1.60 0.034
## 847 6.60 0.220 0.37 15.40 0.035
## 848 9.20 0.340 0.27 1.20 0.026
## 849 8.70 0.230 0.32 13.40 0.044
## 850 6.00 0.200 0.24 1.80 0.030
## 851 6.90 0.190 0.35 1.70 0.036
## 852 8.20 0.380 0.49 13.60 0.042
## 854 7.70 0.340 0.58 11.10 0.039
## 856 7.40 0.200 0.35 2.10 0.038
## 857 8.20 0.380 0.49 13.60 0.042
## 858 8.20 0.400 0.48 13.70 0.042
## 859 6.70 0.220 0.39 10.20 0.038
## 861 8.10 0.270 0.35 1.70 0.030
## 862 7.30 0.250 0.42 14.20 0.041
## 863 4.80 0.340 0.00 6.50 0.028
## 864 6.20 0.280 0.33 1.70 0.029
## 865 4.80 0.330 0.00 6.50 0.028
## 866 6.10 0.270 0.33 2.20 0.021
## 868 7.80 0.180 0.46 12.60 0.042
## 869 7.30 0.280 0.42 14.40 0.040
## 870 7.30 0.240 0.29 1.20 0.037
## 872 7.70 0.340 0.58 11.10 0.039
## 873 6.30 0.260 0.21 4.00 0.030
## 875 7.70 0.150 0.29 1.30 0.029
## 876 7.10 0.210 0.32 2.20 0.037
## 877 6.90 0.360 0.34 4.20 0.018
## 878 6.00 0.280 0.34 1.60 0.119
## 879 6.20 0.160 0.54 1.40 0.126
## 880 6.90 0.120 0.36 2.20 0.037
## 881 7.10 0.210 0.32 2.20 0.037
## 882 8.80 0.360 0.44 1.90 0.040
## 883 7.40 0.260 0.43 6.00 0.022
## 884 7.40 0.260 0.43 6.00 0.022
## 885 6.80 0.230 0.29 12.20 0.035
## 886 6.10 0.340 0.27 2.60 0.024
## 887 7.30 0.260 0.31 1.60 0.040
## 888 6.50 0.300 0.32 2.00 0.044
## 889 7.30 0.260 0.31 1.60 0.040
## 890 6.50 0.300 0.32 2.00 0.044
## 891 5.00 0.310 0.00 6.40 0.046
## 892 5.80 0.260 0.18 1.20 0.031
## 893 5.90 0.260 0.30 1.00 0.036
## 894 7.00 0.310 0.29 1.40 0.037
## 895 5.80 0.260 0.18 1.20 0.031
## 896 5.60 0.190 0.39 1.10 0.043
## 897 6.80 0.180 0.28 8.70 0.047
## 898 7.00 0.290 0.26 1.60 0.044
## 899 6.60 0.260 0.29 1.40 0.039
## 900 6.80 0.180 0.28 8.50 0.047
## 901 6.60 0.200 0.38 7.90 0.052
## 902 8.00 0.290 0.29 13.20 0.046
## 903 6.10 0.280 0.35 12.80 0.048
## 904 5.90 0.310 0.30 7.70 0.047
## 905 6.90 0.210 0.28 2.40 0.056
## 906 8.40 0.190 0.42 1.60 0.047
## 907 8.30 0.270 0.45 1.30 0.048
## 908 7.10 0.250 0.39 2.10 0.036
## 909 8.00 0.230 0.37 9.60 0.054
## 910 7.50 0.240 0.31 13.00 0.049
## 911 6.30 0.330 0.20 5.80 0.040
## 912 6.20 0.330 0.19 5.60 0.042
## 913 6.30 0.340 0.19 5.80 0.041
## 914 5.80 0.290 0.05 0.80 0.038
## 915 8.00 0.320 0.26 1.20 0.050
## 916 5.60 0.290 0.05 0.80 0.038
## 917 7.40 0.130 0.39 4.70 0.042
## 918 7.70 0.300 0.32 1.60 0.037
## 919 7.00 0.240 0.34 1.40 0.031
## 920 8.60 0.180 0.40 1.10 0.040
## 921 7.00 0.110 0.32 4.60 0.057
## 922 7.70 0.320 0.62 10.60 0.036
## 923 7.70 0.320 0.62 10.60 0.036
## 924 6.50 0.260 0.27 12.90 0.044
## 925 7.90 0.280 0.41 2.00 0.044
## 926 6.30 0.270 0.23 2.90 0.047
## 927 5.40 0.595 0.10 2.80 0.042
## 928 6.70 0.250 0.33 2.90 0.057
## 929 6.50 0.250 0.35 12.00 0.055
## 930 6.10 0.360 0.58 15.00 0.044
## 931 7.70 0.170 0.52 5.90 0.017
## 932 6.40 0.260 0.43 12.60 0.033
## 933 6.50 0.260 0.28 12.50 0.046
## 934 5.90 0.290 0.33 7.40 0.037
## 935 6.20 0.280 0.43 13.00 0.039
## 936 6.10 0.270 0.44 6.70 0.041
## 937 6.40 0.430 0.32 1.40 0.048
## 938 6.10 0.360 0.58 15.00 0.044
## 939 6.20 0.350 0.29 7.30 0.044
## 940 7.70 0.240 0.29 15.30 0.044
## 941 6.20 0.340 0.28 7.50 0.034
## 942 6.30 0.270 0.46 11.75 0.037
## 943 5.40 0.415 0.19 1.60 0.039
## 944 6.90 0.480 0.36 3.50 0.030
## 945 6.50 0.180 0.33 8.00 0.051
## 946 6.70 0.150 0.29 5.00 0.058
## 948 8.50 0.160 0.35 1.60 0.039
## 949 6.80 0.705 0.25 3.20 0.048
## 950 7.30 0.250 0.39 6.40 0.034
## 951 7.60 0.345 0.26 1.90 0.043
## 952 7.60 0.220 0.34 9.70 0.035
## 953 6.50 0.170 0.33 1.40 0.028
## 954 8.20 0.230 0.37 1.30 0.042
## 955 7.60 0.220 0.34 9.70 0.035
## 956 7.60 0.345 0.26 1.90 0.043
## 957 7.50 0.320 0.26 1.80 0.042
## 958 6.60 0.230 0.32 0.90 0.041
## 959 6.60 0.200 0.32 1.10 0.039
## 960 7.30 0.240 0.34 15.40 0.050
## 961 7.30 0.240 0.34 15.40 0.050
## 962 8.00 0.420 0.36 5.00 0.037
## 963 7.30 0.240 0.34 15.40 0.050
## 964 6.10 0.190 0.25 4.00 0.023
## 965 5.90 0.260 0.21 12.50 0.034
## 966 8.30 0.230 0.43 3.20 0.035
## 967 6.50 0.340 0.28 1.80 0.041
## 968 6.80 0.220 0.35 17.50 0.039
## 969 6.50 0.080 0.33 1.90 0.028
## 970 5.50 0.420 0.09 1.60 0.019
## 971 5.10 0.420 0.01 1.50 0.017
## 972 6.00 0.270 0.19 1.70 0.020
## 973 6.80 0.220 0.35 17.50 0.039
## 974 6.50 0.080 0.33 1.90 0.028
## 975 7.10 0.130 0.38 1.80 0.046
## 976 7.60 0.300 0.25 4.30 0.054
## 977 6.60 0.130 0.30 4.90 0.058
## 978 6.50 0.140 0.33 7.60 0.050
## 979 7.70 0.280 0.33 6.70 0.037
## 982 7.70 0.280 0.33 6.70 0.037
## 983 5.10 0.390 0.21 1.70 0.027
## 984 5.70 0.360 0.34 4.20 0.026
## 985 6.90 0.190 0.33 1.60 0.043
## 986 6.00 0.410 0.21 1.90 0.050
## 987 7.40 0.280 0.30 5.30 0.054
## 988 7.40 0.300 0.30 5.20 0.053
## 989 6.90 0.190 0.33 1.60 0.043
## 990 7.70 0.280 0.39 8.90 0.036
## 991 8.60 0.160 0.38 3.40 0.040
## 992 8.20 0.260 0.44 1.30 0.046
## 993 6.50 0.250 0.27 15.20 0.049
## 994 7.00 0.240 0.18 1.30 0.046
## 995 8.60 0.180 0.36 1.80 0.040
## 996 7.80 0.270 0.34 1.60 0.046
## 997 6.00 0.260 0.34 1.30 0.046
## 998 6.10 0.240 0.27 9.80 0.062
## 999 8.00 0.240 0.30 17.45 0.056
## 1000 7.60 0.210 0.60 2.10 0.046
## 1001 8.00 0.190 0.36 1.80 0.050
## 1002 6.40 0.280 0.41 6.80 0.045
## 1003 6.40 0.280 0.43 7.10 0.045
## 1004 6.90 0.240 0.39 1.30 0.063
## 1005 5.80 0.360 0.26 3.30 0.038
## 1006 6.60 0.180 0.28 3.30 0.044
## 1007 5.80 0.360 0.26 3.30 0.038
## 1008 5.10 0.520 0.06 2.70 0.052
## 1009 6.60 0.220 0.37 1.20 0.059
## 1010 8.30 0.150 0.39 1.30 0.055
## 1011 7.60 0.160 0.44 1.40 0.043
## 1012 7.70 0.160 0.41 1.70 0.048
## 1013 8.30 0.160 0.48 1.70 0.057
## 1014 6.20 0.250 0.47 11.60 0.048
## 1016 7.60 0.390 0.22 2.80 0.036
## 1017 6.80 0.370 0.47 11.20 0.071
## 1018 7.60 0.160 0.44 1.40 0.043
## 1019 7.10 0.180 0.42 1.40 0.045
## 1020 8.30 0.140 0.26 1.50 0.049
## 1021 8.60 0.200 0.42 1.50 0.041
## 1022 8.60 0.200 0.42 1.50 0.041
## 1023 6.80 0.190 0.32 7.05 0.019
## 1024 7.60 0.190 0.38 10.60 0.060
## 1026 6.20 0.150 0.46 1.60 0.039
## 1027 6.60 0.140 0.44 1.60 0.042
## 1028 8.00 0.550 0.17 8.20 0.040
## 1029 7.00 0.240 0.35 1.50 0.052
## 1030 6.30 0.600 0.44 11.00 0.050
## 1031 7.10 0.200 0.41 2.10 0.054
## 1032 6.20 0.340 0.29 7.60 0.047
## 1033 7.10 0.300 0.36 6.80 0.055
## 1034 7.10 0.300 0.36 6.80 0.055
## 1036 8.80 0.170 0.38 1.80 0.040
## 1037 7.50 0.170 0.37 1.50 0.060
## 1038 7.10 0.470 0.24 6.00 0.044
## 1039 7.10 0.150 0.34 5.30 0.034
## 1040 7.50 0.170 0.34 1.40 0.035
## 1041 8.20 0.680 0.30 2.10 0.047
## 1042 7.70 0.275 0.30 1.00 0.039
## 1043 7.30 0.490 0.32 5.20 0.043
## 1044 7.50 0.330 0.48 19.45 0.048
## 1045 7.20 0.210 0.37 1.60 0.049
## 1046 7.30 0.150 0.40 2.00 0.050
## 1047 6.50 0.190 0.10 1.30 0.046
## 1048 7.00 0.310 0.52 1.70 0.029
## 1049 8.30 0.400 0.38 1.10 0.038
## 1050 6.10 0.370 0.36 4.70 0.035
## 1051 7.30 0.240 0.34 7.50 0.048
## 1053 7.60 0.290 0.42 1.30 0.035
## 1054 9.40 0.290 0.55 2.20 0.050
## 1055 7.00 0.310 0.52 1.70 0.029
## 1056 8.60 0.260 0.41 2.20 0.049
## 1057 7.50 0.210 0.34 1.20 0.060
## 1058 7.20 0.510 0.24 10.00 0.093
## 1059 7.50 0.210 0.34 1.20 0.060
## 1060 5.30 0.300 0.20 1.10 0.077
## 1061 8.00 0.260 0.36 2.00 0.054
## 1062 7.00 0.210 0.28 7.50 0.070
## 1063 6.70 0.260 0.26 4.00 0.079
## 1064 6.70 0.260 0.26 4.10 0.073
## 1065 8.10 0.260 0.37 1.90 0.072
## 1066 8.30 0.220 0.38 14.80 0.054
## 1067 6.40 0.300 0.51 5.50 0.048
## 1068 7.50 0.190 0.34 2.60 0.037
## 1069 8.80 0.330 0.44 6.35 0.024
## 1070 6.90 0.200 0.36 1.50 0.031
## 1071 8.00 0.370 0.32 1.60 0.040
## 1072 8.30 0.220 0.38 14.80 0.054
## 1073 8.20 0.290 0.33 9.10 0.036
## 1074 7.70 0.340 0.30 8.00 0.048
## 1075 6.20 0.550 0.45 12.00 0.049
## 1076 6.40 0.400 0.19 3.20 0.033
## 1077 7.50 0.280 0.33 7.70 0.048
## 1078 7.80 0.260 0.44 1.30 0.037
## 1079 6.50 0.260 0.34 16.30 0.051
## 1080 6.30 0.340 0.29 6.20 0.046
## 1081 6.80 0.150 0.33 4.70 0.059
## 1082 6.30 0.270 0.25 5.80 0.038
## 1083 6.30 0.270 0.25 5.80 0.038
## 1084 7.40 0.200 0.37 16.95 0.048
## 1085 6.30 0.230 0.21 5.10 0.035
## 1086 7.30 0.310 0.69 10.20 0.041
## 1087 5.20 0.240 0.45 3.80 0.027
## 1088 7.00 0.240 0.32 1.30 0.037
## 1089 7.40 0.200 0.37 16.95 0.048
## 1090 7.00 0.170 0.33 4.00 0.034
## 1091 8.30 0.210 0.58 17.10 0.049
## 1092 7.20 0.210 0.35 14.50 0.048
## 1093 7.10 0.210 0.40 1.20 0.069
## 1094 8.40 0.170 0.31 6.70 0.038
## 1095 7.40 0.240 0.31 8.40 0.045
## 1096 5.30 0.240 0.33 1.30 0.033
## 1097 6.50 0.280 0.26 8.80 0.040
## 1098 6.30 0.230 0.21 5.10 0.035
## 1099 6.50 0.290 0.25 10.60 0.039
## 1100 5.80 0.290 0.21 2.60 0.025
## 1101 6.30 0.270 0.25 5.80 0.038
## 1102 6.30 0.170 0.42 2.80 0.028
## 1103 6.30 0.160 0.40 1.60 0.033
## 1104 7.90 0.290 0.39 6.70 0.036
## 1105 7.30 0.310 0.69 10.20 0.041
## 1106 5.50 0.320 0.45 4.90 0.028
## 1107 5.20 0.240 0.45 3.80 0.027
## 1108 7.20 0.370 0.15 2.00 0.029
## 1109 6.10 0.290 0.27 1.70 0.024
## 1110 9.20 0.220 0.40 2.40 0.054
## 1111 7.20 0.370 0.15 2.00 0.029
## 1112 8.00 0.180 0.37 1.30 0.040
## 1113 6.50 0.220 0.34 12.00 0.053
## 1114 7.40 0.180 0.40 1.60 0.047
## 1115 6.50 0.520 0.17 1.40 0.047
## 1116 7.00 0.150 0.38 2.20 0.047
## 1117 5.90 0.415 0.13 1.40 0.040
## 1118 8.10 0.450 0.34 8.30 0.037
## 1119 5.80 0.415 0.13 1.40 0.040
## 1120 6.40 0.500 0.16 12.90 0.042
## 1121 6.70 0.105 0.32 12.40 0.051
## 1122 6.00 0.400 0.30 1.60 0.047
## 1123 6.60 0.250 0.39 1.45 0.040
## 1124 9.80 0.360 0.45 1.60 0.042
## 1125 9.60 0.230 0.40 1.50 0.044
## 1126 6.30 0.550 0.45 13.00 0.047
## 1128 6.40 0.125 0.29 5.85 0.042
## 1129 5.70 0.100 0.27 1.30 0.047
## 1130 7.90 0.250 0.29 5.30 0.031
## 1131 6.90 0.200 0.28 1.20 0.048
## 1132 6.90 0.230 0.34 4.00 0.047
## 1133 6.80 0.390 0.31 14.35 0.043
## 1134 8.70 0.220 0.42 2.30 0.053
## 1135 7.40 0.410 0.34 4.70 0.042
## 1136 6.70 0.250 0.34 12.85 0.048
## 1137 6.00 0.260 0.42 5.20 0.027
## 1138 6.10 0.310 0.37 8.40 0.031
## 1139 9.20 0.280 0.46 3.20 0.058
## 1140 9.00 0.310 0.49 6.90 0.034
## 1141 8.50 0.160 0.33 1.00 0.076
## 1142 9.30 0.340 0.49 7.30 0.052
## 1143 9.20 0.280 0.46 3.20 0.058
## 1144 7.20 0.240 0.30 1.60 0.048
## 1145 7.20 0.250 0.32 1.50 0.047
## 1146 6.80 0.320 0.18 7.50 0.041
## 1147 9.10 0.270 0.32 1.10 0.031
## 1148 8.90 0.340 0.32 1.30 0.041
## 1149 7.00 0.170 0.37 5.70 0.025
## 1150 6.70 0.250 0.23 7.20 0.038
## 1151 6.90 0.320 0.17 7.60 0.042
## 1152 6.80 0.320 0.18 7.50 0.041
## 1153 6.10 0.600 0.00 1.30 0.042
## 1154 5.30 0.395 0.07 1.30 0.035
## 1155 7.90 0.160 0.30 4.80 0.037
## 1156 7.60 0.330 0.36 2.10 0.034
## 1157 7.80 0.300 0.29 16.85 0.054
## 1158 7.80 0.300 0.29 16.85 0.054
## 1160 7.80 0.300 0.29 16.85 0.054
## 1161 7.50 0.140 0.34 1.30 0.055
## 1162 7.80 0.300 0.29 16.85 0.054
## 1163 6.60 0.250 0.41 7.40 0.043
## 1165 8.20 0.230 0.49 0.90 0.057
## 1166 6.00 0.240 0.32 6.30 0.030
## 1167 6.10 0.450 0.27 0.80 0.039
## 1168 7.40 0.230 0.43 1.40 0.044
## 1169 7.20 0.200 0.38 1.00 0.037
## 1170 7.50 0.140 0.34 1.30 0.055
## 1171 7.70 0.250 0.43 4.50 0.062
## 1172 8.20 0.610 0.45 5.40 0.030
## 1173 7.60 0.210 0.44 1.90 0.036
## 1174 7.40 0.220 0.33 2.00 0.045
## 1175 7.20 0.260 0.26 12.70 0.036
## 1176 6.40 0.250 0.41 8.60 0.042
## 1177 6.30 0.320 0.35 11.10 0.039
## 1178 6.80 0.250 0.29 2.00 0.042
## 1179 9.80 0.440 0.40 2.80 0.036
## 1180 7.20 0.200 0.25 4.50 0.044
## 1181 8.20 0.610 0.45 5.40 0.030
## 1182 7.50 0.420 0.45 9.10 0.029
## 1183 7.40 0.220 0.33 2.00 0.045
## 1184 6.40 0.260 0.30 2.20 0.025
## 1185 7.90 0.460 0.32 4.10 0.033
## 1186 6.50 0.410 0.64 11.80 0.065
## 1187 7.50 0.320 0.37 1.20 0.048
## 1188 6.60 0.210 0.38 2.20 0.026
## 1189 7.10 0.210 0.30 1.40 0.037
## 1190 7.60 0.260 0.47 1.60 0.068
## 1191 7.60 0.210 0.44 1.90 0.036
## 1192 6.90 0.250 0.26 5.20 0.024
## 1193 7.10 0.260 0.32 14.45 0.074
## 1194 7.30 0.220 0.40 14.75 0.042
## 1195 6.20 0.370 0.22 8.30 0.025
## 1196 7.90 0.220 0.45 14.20 0.038
## 1197 6.90 0.250 0.26 5.20 0.024
## 1198 7.30 0.220 0.40 14.75 0.042
## 1199 7.10 0.260 0.32 14.45 0.074
## 1200 7.40 0.250 0.37 6.90 0.020
## 1201 6.80 0.180 0.37 1.50 0.027
## 1202 7.00 0.170 0.37 1.50 0.028
## 1203 6.40 0.300 0.38 7.80 0.046
## 1204 5.00 0.330 0.16 1.50 0.049
## 1205 5.00 0.330 0.16 1.50 0.049
## 1207 7.00 0.260 0.46 15.55 0.037
## 1208 6.40 0.300 0.38 7.80 0.046
## 1209 6.30 0.210 0.40 1.70 0.031
## 1210 8.00 0.230 0.46 1.50 0.030
## 1211 9.20 0.280 0.41 1.00 0.042
## 1212 7.30 0.270 0.39 6.70 0.064
## 1213 7.60 0.320 0.36 1.60 0.040
## 1214 5.00 0.330 0.16 1.50 0.049
## 1215 9.70 0.240 0.45 1.20 0.033
## 1216 8.00 0.280 0.42 7.10 0.045
## 1217 8.20 0.370 0.36 1.00 0.034
## 1219 7.20 0.260 0.44 7.10 0.027
## 1220 8.20 0.370 0.36 1.00 0.034
## 1221 6.40 0.230 0.33 1.15 0.044
## 1222 5.90 0.400 0.32 6.00 0.034
## 1223 7.60 0.280 0.39 1.20 0.038
## 1224 8.00 0.280 0.42 7.10 0.045
## 1225 7.20 0.230 0.39 2.30 0.033
## 1226 6.80 0.320 0.37 3.40 0.023
## 1227 7.20 0.230 0.39 2.30 0.033
## 1228 6.90 0.180 0.38 6.50 0.039
## 1229 9.40 0.260 0.53 1.20 0.047
## 1230 8.30 0.330 0.42 1.15 0.033
## 1231 7.30 0.290 0.30 13.00 0.043
## 1232 7.90 0.410 0.37 4.50 0.030
## 1233 7.90 0.440 0.37 5.85 0.033
## 1234 7.70 0.390 0.30 5.20 0.037
## 1235 7.70 0.260 0.31 1.30 0.043
## 1236 7.80 0.320 0.31 1.70 0.036
## 1237 6.80 0.320 0.37 3.40 0.023
## 1238 7.30 0.240 0.39 3.60 0.024
## 1239 7.10 0.440 0.37 2.70 0.041
## 1240 10.30 0.250 0.48 2.20 0.042
## 1241 7.90 0.140 0.28 1.80 0.041
## 1242 7.40 0.180 0.42 2.10 0.036
## 1243 8.10 0.430 0.42 6.60 0.033
## 1244 7.10 0.440 0.37 2.70 0.041
## 1245 6.40 0.260 0.22 5.10 0.037
## 1247 8.00 0.200 0.40 5.20 0.055
## 1248 7.20 0.210 0.34 1.10 0.046
## 1249 7.20 0.180 0.31 1.10 0.045
## 1250 8.40 0.570 0.44 10.70 0.051
## 1251 5.30 0.260 0.23 5.15 0.034
## 1252 5.70 0.245 0.33 1.10 0.049
## 1253 5.60 0.245 0.32 1.10 0.047
## 1254 7.30 0.250 0.41 1.80 0.037
## 1256 6.40 0.220 0.34 1.80 0.057
## 1257 7.30 0.180 0.65 1.40 0.046
## 1258 6.40 0.170 0.27 6.70 0.036
## 1259 6.90 0.290 0.16 6.80 0.034
## 1260 6.20 0.210 0.38 6.80 0.036
## 1261 6.40 0.230 0.30 7.10 0.037
## 1262 7.30 0.190 0.68 1.50 0.050
## 1263 7.30 0.180 0.65 1.40 0.046
## 1265 7.20 0.140 0.35 1.20 0.036
## 1266 6.90 0.310 0.34 7.40 0.059
## 1267 7.50 0.280 0.34 4.20 0.028
## 1268 8.00 0.220 0.42 14.60 0.044
## 1269 7.60 0.310 0.29 10.50 0.040
## 1270 8.40 0.350 0.56 13.80 0.048
## 1271 8.00 0.220 0.42 14.60 0.044
## 1272 8.10 0.500 0.47 1.10 0.037
## 1273 7.00 0.390 0.31 5.30 0.169
## 1274 8.10 0.500 0.47 1.10 0.037
## 1275 8.40 0.350 0.56 13.80 0.048
## 1276 6.20 0.220 0.27 1.50 0.064
## 1277 8.00 0.220 0.42 14.60 0.044
## 1278 7.60 0.310 0.29 10.50 0.040
## 1279 7.00 0.240 0.36 4.90 0.083
## 1280 6.60 0.270 0.30 1.90 0.025
## 1281 7.80 0.160 0.41 1.70 0.026
## 1282 7.70 0.270 0.34 1.80 0.028
## 1283 7.40 0.310 0.74 10.70 0.039
## 1284 8.00 0.450 0.36 8.80 0.026
## 1285 7.70 0.270 0.34 1.80 0.028
## 1286 7.80 0.160 0.41 1.70 0.026
## 1287 6.60 0.160 0.29 1.80 0.050
## 1288 8.30 0.210 0.40 1.60 0.032
## 1289 7.20 0.320 0.33 1.40 0.029
## 1290 6.60 0.160 0.30 1.60 0.034
## 1291 8.40 0.160 0.33 1.50 0.033
## 1292 7.50 0.230 0.32 9.20 0.038
## 1293 6.20 0.170 0.30 1.10 0.037
## 1294 6.90 0.390 0.22 4.30 0.030
## 1295 6.90 0.410 0.22 4.20 0.031
## 1296 7.50 0.230 0.32 9.20 0.038
## 1297 7.50 0.380 0.33 5.00 0.045
## 1298 7.30 0.420 0.38 6.80 0.045
## 1299 7.30 0.340 0.39 5.20 0.040
## 1300 7.80 0.230 0.28 4.75 0.042
## 1301 9.00 0.245 0.38 5.90 0.045
## 1302 6.90 0.200 0.40 7.70 0.032
## 1303 7.40 0.190 0.42 6.40 0.067
## 1304 8.20 0.200 0.36 8.10 0.035
## 1306 7.90 0.140 0.45 1.80 0.050
## 1307 6.80 0.240 0.40 1.80 0.047
## 1308 9.70 0.140 0.59 1.50 0.049
## 1309 9.20 0.150 0.68 1.60 0.046
## 1310 9.40 0.170 0.55 1.60 0.049
## 1311 5.20 0.365 0.08 13.50 0.041
## 1312 6.30 0.230 0.22 3.75 0.039
## 1313 9.60 0.250 0.54 1.30 0.040
## 1314 9.20 0.320 0.42 1.30 0.046
## 1315 6.40 0.310 0.40 6.20 0.040
## 1316 8.10 0.200 0.36 9.70 0.044
## 1317 7.90 0.255 0.26 2.00 0.026
## 1318 7.00 0.150 0.34 1.40 0.039
## 1319 6.40 0.150 0.31 1.10 0.044
## 1320 6.40 0.250 0.53 6.60 0.038
## 1321 7.60 0.190 0.42 1.50 0.044
## 1322 7.30 0.430 0.37 4.60 0.028
## 1323 5.10 0.310 0.30 0.90 0.037
## 1324 6.20 0.200 0.26 1.70 0.093
## 1325 6.90 0.160 0.35 1.30 0.043
## 1326 7.70 0.320 0.48 2.30 0.040
## 1327 6.50 0.220 0.72 6.80 0.042
## 1328 6.80 0.260 0.33 1.50 0.047
## 1329 5.20 0.370 0.33 1.20 0.028
## 1330 8.40 0.190 0.43 2.10 0.052
## 1331 8.30 0.210 0.41 2.20 0.050
## 1332 6.80 0.150 0.32 8.80 0.058
## 1333 7.90 0.160 0.64 17.00 0.050
## 1334 7.80 0.210 0.39 1.80 0.034
## 1335 9.00 0.240 0.50 1.20 0.048
## 1336 5.70 0.210 0.24 2.30 0.047
## 1337 7.80 0.290 0.36 7.00 0.042
## 1338 6.70 0.180 0.30 6.40 0.048
## 1339 6.70 0.180 0.30 6.40 0.048
## 1340 8.40 0.580 0.27 12.15 0.033
## 1341 7.20 0.160 0.32 0.80 0.040
## 1342 7.60 0.540 0.23 2.00 0.029
## 1343 8.40 0.580 0.27 12.15 0.033
## 1344 6.60 0.250 0.31 12.40 0.059
## 1345 7.30 0.230 0.37 1.90 0.041
## 1346 7.30 0.390 0.37 1.10 0.043
## 1347 7.00 0.460 0.39 6.20 0.039
## 1348 8.20 0.350 0.40 6.30 0.039
## 1349 7.80 0.290 0.36 7.00 0.042
## 1350 9.20 0.350 0.39 0.90 0.042
## 1351 8.00 0.570 0.39 3.90 0.034
## 1352 6.50 0.370 0.33 3.90 0.027
## 1353 5.70 0.210 0.24 2.30 0.047
## 1354 6.70 0.180 0.30 6.40 0.048
## 1355 7.80 0.130 0.30 1.80 0.040
## 1356 7.60 0.190 0.41 1.10 0.040
## 1357 7.30 0.220 0.41 15.40 0.050
## 1358 6.30 0.290 0.40 6.50 0.039
## 1359 6.80 0.350 0.32 2.40 0.048
## 1360 6.50 0.190 0.32 1.40 0.040
## 1361 6.20 0.120 0.26 5.70 0.044
## 1362 6.00 0.130 0.28 5.70 0.038
## 1363 6.40 0.250 0.33 1.40 0.040
## 1364 6.90 0.320 0.16 1.40 0.051
## 1365 7.60 0.190 0.41 1.10 0.040
## 1366 6.70 0.130 0.28 1.20 0.046
## 1367 7.00 0.140 0.41 0.90 0.037
## 1368 7.60 0.270 0.24 3.80 0.058
## 1369 7.30 0.220 0.41 15.40 0.050
## 1371 7.60 0.280 0.39 1.90 0.052
## 1372 8.30 0.260 0.41 9.20 0.042
## 1373 10.70 0.220 0.56 8.20 0.044
## 1374 10.70 0.220 0.56 8.20 0.044
## 1375 6.90 0.230 0.34 2.70 0.032
## 1376 6.20 0.300 0.32 1.70 0.032
## 1377 6.90 0.270 0.41 1.70 0.047
## 1378 6.90 0.280 0.41 1.70 0.050
## 1379 6.90 0.280 0.30 1.60 0.047
## 1380 6.90 0.460 0.20 0.90 0.054
## 1381 6.90 0.380 0.32 8.50 0.044
## 1382 5.70 0.430 0.30 5.70 0.039
## 1383 6.60 0.560 0.16 3.10 0.045
## 1384 7.10 0.360 0.56 1.30 0.046
## 1385 6.80 0.230 0.40 1.60 0.047
## 1386 6.20 0.330 0.29 1.30 0.042
## 1388 6.60 0.420 0.33 2.80 0.034
## 1389 7.30 0.180 0.29 1.20 0.044
## 1390 8.10 0.190 0.40 0.90 0.037
## 1391 5.90 0.190 0.26 7.40 0.034
## 1392 6.20 0.160 0.47 1.40 0.029
## 1393 6.60 0.420 0.33 2.80 0.034
## 1394 5.70 0.135 0.30 4.60 0.042
## 1396 6.90 0.190 0.33 1.60 0.039
## 1397 7.30 0.180 0.29 1.20 0.044
## 1398 7.30 0.250 0.36 13.10 0.050
## 1399 7.30 0.250 0.36 13.10 0.050
## 1400 7.00 0.200 0.34 5.70 0.035
## 1401 7.30 0.250 0.36 13.10 0.050
## 1403 7.40 0.400 0.29 5.40 0.044
## 1404 7.10 0.260 0.31 2.20 0.044
## 1405 9.00 0.310 0.48 6.60 0.043
## 1406 6.30 0.390 0.24 6.90 0.069
## 1407 8.20 0.220 0.36 6.80 0.034
## 1408 7.10 0.190 0.28 3.60 0.033
## 1409 7.30 0.250 0.36 13.10 0.050
## 1410 7.90 0.200 0.34 1.20 0.040
## 1411 7.10 0.260 0.32 5.90 0.037
## 1412 7.00 0.200 0.34 5.70 0.035
## 1413 6.90 0.300 0.33 4.10 0.035
## 1414 8.10 0.290 0.49 7.10 0.042
## 1415 5.80 0.170 0.30 1.40 0.037
## 1416 5.90 0.415 0.02 0.80 0.038
## 1417 6.60 0.230 0.26 1.30 0.045
## 1420 7.60 0.140 0.74 1.60 0.040
## 1421 9.20 0.280 0.49 11.80 0.042
## 1422 6.20 0.180 0.49 4.50 0.047
## 1423 5.30 0.165 0.24 1.10 0.051
## 1424 9.80 0.250 0.74 10.00 0.056
## 1425 8.10 0.290 0.49 7.10 0.042
## 1426 6.80 0.220 0.49 0.90 0.052
## 1427 7.20 0.220 0.49 1.00 0.045
## 1428 7.40 0.250 0.49 1.10 0.042
## 1429 8.20 0.180 0.49 1.10 0.033
## 1430 6.10 0.220 0.49 1.50 0.051
## 1431 7.00 0.390 0.24 1.00 0.048
## 1432 6.10 0.220 0.49 1.50 0.051
## 1433 6.50 0.360 0.49 2.90 0.030
## 1434 7.10 0.290 0.49 1.20 0.031
## 1435 7.40 0.250 0.49 1.10 0.042
## 1436 6.90 0.230 0.24 14.20 0.053
## 1438 8.20 0.180 0.49 1.10 0.033
## 1439 6.30 0.230 0.49 7.10 0.050
## 1440 6.10 0.250 0.49 7.60 0.052
## 1441 7.20 0.260 0.74 13.60 0.050
## 1442 7.20 0.310 0.24 1.40 0.057
## 1443 8.00 0.250 0.49 1.20 0.061
## 1444 7.00 0.180 0.49 5.30 0.040
## 1445 7.80 0.430 0.49 13.00 0.033
## 1446 8.30 0.200 0.74 4.45 0.044
## 1447 6.30 0.270 0.49 1.20 0.063
## 1448 7.40 0.160 0.49 1.20 0.055
## 1449 7.40 0.160 0.49 1.20 0.055
## 1450 6.90 0.190 0.49 6.60 0.036
## 1451 7.80 0.430 0.49 13.00 0.033
## 1452 7.20 0.400 0.49 1.10 0.048
## 1453 7.80 0.430 0.49 13.00 0.033
## 1454 7.60 0.520 0.49 14.00 0.034
## 1455 8.30 0.210 0.49 19.80 0.054
## 1457 6.30 0.270 0.49 1.20 0.063
## 1458 8.30 0.200 0.74 4.45 0.044
## 1459 7.10 0.220 0.74 2.70 0.044
## 1460 7.90 0.110 0.49 4.50 0.048
## 1461 8.50 0.170 0.74 3.60 0.050
## 1462 6.40 0.145 0.49 5.40 0.048
## 1463 7.40 0.160 0.49 1.20 0.055
## 1464 8.30 0.190 0.49 1.20 0.051
## 1465 8.00 0.440 0.49 9.10 0.031
## 1467 6.90 0.190 0.49 6.60 0.036
## 1468 7.10 0.250 0.49 3.00 0.030
## 1469 6.50 0.240 0.24 1.60 0.046
## 1470 7.20 0.400 0.49 1.10 0.048
## 1471 7.60 0.520 0.49 14.00 0.034
## 1472 7.80 0.430 0.49 13.00 0.033
## 1473 7.80 0.210 0.49 1.35 0.052
## 1474 7.00 0.200 0.49 5.90 0.038
## 1475 6.90 0.250 0.24 3.60 0.057
## 1476 7.20 0.080 0.49 1.30 0.050
## 1478 7.60 0.510 0.24 1.20 0.040
## 1479 7.90 0.220 0.24 4.60 0.044
## 1480 7.70 0.160 0.49 2.00 0.056
## 1481 7.20 0.080 0.49 1.30 0.050
## 1482 6.60 0.250 0.24 1.70 0.048
## 1483 6.70 0.160 0.49 2.40 0.046
## 1484 6.90 0.250 0.24 3.60 0.057
## 1485 7.50 0.320 0.24 4.60 0.053
## 1486 7.40 0.280 0.49 1.50 0.034
## 1487 6.20 0.150 0.49 0.90 0.033
## 1489 6.50 0.260 0.74 13.30 0.044
## 1490 7.90 0.160 0.74 17.85 0.037
## 1491 5.60 0.185 0.49 1.10 0.030
## 1492 7.50 0.200 0.49 1.30 0.031
## 1493 8.00 0.300 0.49 9.40 0.046
## 1494 8.00 0.340 0.49 9.00 0.033
## 1495 7.70 0.350 0.49 8.65 0.033
## 1496 7.60 0.290 0.49 9.60 0.030
## 1497 6.70 0.620 0.24 1.10 0.039
## 1498 6.80 0.270 0.49 1.20 0.044
## 1499 7.70 0.270 0.49 1.80 0.041
## 1500 6.70 0.510 0.24 2.10 0.043
## 1501 7.40 0.190 0.49 9.30 0.030
## 1502 8.30 0.200 0.49 1.70 0.040
## 1503 6.60 0.300 0.24 1.20 0.034
## 1504 6.80 0.360 0.24 4.60 0.039
## 1506 9.20 0.180 0.49 1.50 0.041
## 1507 8.10 0.200 0.49 8.10 0.051
## 1508 7.80 0.260 0.74 7.50 0.044
## 1509 6.80 0.210 0.49 14.50 0.060
## 1510 7.90 0.200 0.49 1.60 0.053
## 1511 8.00 0.180 0.49 1.80 0.061
## 1512 8.80 0.230 0.74 3.20 0.042
## 1513 7.30 0.220 0.49 9.40 0.034
## 1514 7.30 0.220 0.49 9.90 0.031
## 1515 7.40 0.190 0.49 9.30 0.030
## 1516 7.30 0.155 0.49 1.30 0.039
## 1517 8.20 0.220 0.49 9.60 0.037
## 1518 8.20 0.240 0.49 9.30 0.038
## 1519 8.40 0.230 0.49 7.80 0.035
## 1520 8.30 0.200 0.49 1.70 0.040
## 1521 8.30 0.200 0.49 1.70 0.038
## 1522 6.60 0.300 0.24 1.20 0.034
## 1523 6.90 0.210 0.49 1.40 0.041
## 1524 8.00 0.250 0.49 9.00 0.044
## 1525 6.60 0.210 0.49 18.15 0.042
## 1526 7.20 0.270 0.74 12.50 0.037
## 1528 7.90 0.280 0.49 7.70 0.045
## 1529 7.40 0.270 0.49 1.10 0.037
## 1530 6.60 0.210 0.49 18.15 0.042
## 1531 7.20 0.270 0.74 12.50 0.037
## 1532 8.10 0.300 0.49 8.10 0.037
## 1533 7.50 0.230 0.49 7.70 0.049
## 1534 7.30 0.260 0.49 5.00 0.028
## 1536 8.50 0.150 0.49 1.50 0.031
## 1537 8.90 0.130 0.49 1.00 0.028
## 1538 8.10 0.280 0.49 1.00 0.040
## 1539 6.00 0.170 0.49 1.00 0.034
## 1540 7.30 0.260 0.49 5.00 0.028
## 1542 7.10 0.530 0.24 0.80 0.029
## 1543 7.20 0.160 0.49 1.30 0.037
## 1544 7.30 0.140 0.49 1.10 0.038
## 1545 8.90 0.130 0.49 1.00 0.028
## 1546 7.90 0.120 0.49 5.20 0.049
## 1547 6.70 0.290 0.49 4.70 0.034
## 1548 6.70 0.300 0.49 4.80 0.034
## 1549 7.10 0.360 0.24 1.80 0.025
## 1550 8.50 0.150 0.49 1.50 0.031
## 1551 7.90 0.180 0.49 5.20 0.051
## 1553 7.30 0.210 0.49 1.80 0.038
## 1554 6.90 0.300 0.49 7.60 0.057
## 1555 7.90 0.420 0.49 8.20 0.056
## 1556 6.90 0.240 0.49 1.30 0.032
## 1557 7.60 0.230 0.49 10.00 0.036
## 1558 7.90 0.180 0.49 5.20 0.051
## 1559 6.20 0.430 0.49 6.40 0.045
## 1560 8.80 0.350 0.49 1.00 0.036
## 1561 7.80 0.300 0.74 1.80 0.033
## 1562 9.10 0.280 0.49 2.00 0.059
## 1563 7.10 0.340 0.49 1.50 0.027
## 1564 7.80 0.300 0.74 1.80 0.033
## 1565 9.10 0.280 0.49 2.00 0.059
## 1566 8.50 0.190 0.49 3.50 0.044
## 1567 7.60 0.180 0.49 18.05 0.046
## 1568 7.50 0.190 0.49 1.80 0.055
## 1569 7.40 0.300 0.49 8.20 0.055
## 1570 6.70 0.300 0.74 5.00 0.038
## 1571 6.60 0.300 0.74 4.60 0.041
## 1572 7.40 0.300 0.49 8.20 0.055
## 1573 6.90 0.220 0.49 7.00 0.063
## 1574 7.80 0.260 0.49 3.10 0.045
## 1575 8.50 0.170 0.49 8.80 0.048
## 1577 6.20 0.270 0.49 1.40 0.050
## 1578 7.10 0.640 0.49 1.80 0.050
## 1580 7.60 0.310 0.49 13.40 0.062
## 1581 9.80 0.310 0.49 15.40 0.046
## 1582 9.00 0.300 0.49 7.20 0.039
## 1583 8.40 0.240 0.49 7.40 0.039
## 1585 6.40 0.250 0.74 7.80 0.045
## 1586 7.30 0.300 0.74 13.50 0.039
## 1587 9.30 0.310 0.49 1.30 0.042
## 1588 6.40 0.250 0.74 7.80 0.045
## 1589 7.30 0.300 0.74 13.50 0.039
## 1590 7.00 0.270 0.74 1.50 0.036
## 1591 7.90 0.140 0.74 1.20 0.028
## 1592 6.40 0.120 0.49 6.40 0.042
## 1593 6.80 0.210 0.74 1.20 0.047
## 1594 8.60 0.160 0.49 7.30 0.043
## 1595 7.00 0.290 0.49 3.80 0.047
## 1596 6.40 0.270 0.49 7.30 0.046
## 1597 6.60 0.550 0.01 2.70 0.034
## 1598 6.40 0.270 0.49 7.30 0.046
## 1601 7.00 0.290 0.49 3.80 0.047
## 1602 8.20 0.340 0.49 8.00 0.046
## 1603 5.60 0.390 0.24 4.70 0.034
## 1604 5.60 0.410 0.24 1.90 0.034
## 1605 6.70 0.410 0.01 2.80 0.048
## 1606 7.10 0.260 0.49 2.20 0.032
## 1607 7.50 0.320 0.49 1.70 0.031
## 1608 5.80 0.190 0.49 4.90 0.040
## 1609 6.90 0.270 0.49 23.50 0.057
## 1610 8.10 0.200 0.49 11.80 0.048
## 1611 7.50 0.320 0.49 1.70 0.031
## 1612 8.20 0.260 0.49 5.20 0.040
## 1613 7.80 0.260 0.49 3.20 0.027
## 1614 8.00 0.140 0.49 1.50 0.035
## 1615 8.00 0.290 0.49 11.70 0.035
## 1616 7.50 0.190 0.49 1.60 0.047
## 1617 6.90 0.340 0.49 7.30 0.045
## 1618 6.20 0.200 0.49 1.60 0.065
## 1619 6.40 0.370 0.49 13.30 0.045
## 1620 6.20 0.220 0.49 6.00 0.029
## 1621 7.80 0.260 0.49 3.20 0.027
## 1622 8.90 0.320 0.49 1.60 0.050
## 1623 6.50 0.440 0.49 7.70 0.045
## 1624 7.00 0.140 0.49 5.90 0.053
## 1625 9.00 0.170 0.49 1.00 0.039
## 1626 6.40 0.260 0.49 6.40 0.037
## 1627 9.00 0.220 0.49 10.40 0.048
## 1628 8.90 0.320 0.49 1.60 0.050
## 1629 8.20 0.200 0.49 3.50 0.057
## 1630 7.80 0.150 0.24 7.70 0.047
## 1631 6.90 0.250 0.24 1.80 0.053
## 1632 8.20 0.200 0.49 3.50 0.057
## 1633 7.10 0.280 0.49 6.50 0.041
## 1634 7.40 0.190 0.49 6.70 0.037
## 1635 8.30 0.250 0.49 16.80 0.048
## 1636 7.50 0.140 0.74 1.60 0.035
## 1637 7.80 0.490 0.49 7.00 0.043
## 1638 8.10 0.120 0.49 1.20 0.042
## 1640 7.90 0.220 0.49 3.80 0.042
## 1641 7.80 0.490 0.49 7.00 0.043
## 1642 6.40 0.220 0.49 7.50 0.054
## 1643 7.30 0.190 0.49 15.55 0.058
## 1644 8.10 0.300 0.49 12.30 0.049
## 1645 7.30 0.190 0.49 15.55 0.058
## 1646 7.50 0.240 0.49 9.40 0.048
## 1647 6.40 0.220 0.49 7.50 0.054
## 1648 7.80 0.210 0.49 1.20 0.036
## 1649 7.10 0.300 0.49 1.60 0.045
## 1650 6.90 0.260 0.49 1.60 0.058
## 1651 7.60 0.310 0.49 3.95 0.044
## 1653 8.20 0.290 0.49 1.00 0.044
## 1655 6.60 0.460 0.49 7.40 0.052
## 1656 7.80 0.280 0.49 1.30 0.046
## 1657 5.80 0.150 0.49 1.10 0.048
## 1658 7.80 0.400 0.49 7.80 0.060
## 1659 6.60 0.310 0.49 7.70 0.050
## 1660 6.60 0.325 0.49 7.70 0.049
## 1661 6.60 0.270 0.49 7.80 0.049
## 1662 6.70 0.260 0.49 8.30 0.047
## 1663 6.70 0.210 0.49 1.40 0.047
## 1665 8.10 0.280 0.46 15.40 0.059
## 1666 6.50 0.130 0.37 1.00 0.036
## 1667 7.80 0.445 0.56 1.00 0.040
## 1668 8.80 0.390 0.34 5.90 0.055
## 1669 7.90 0.180 0.33 1.20 0.033
## 1670 7.10 0.310 0.38 1.20 0.036
## 1671 7.80 0.240 0.18 6.70 0.046
## 1672 7.00 0.350 0.30 6.50 0.028
## 1673 6.60 0.260 0.31 4.80 0.138
## 1674 6.60 0.270 0.31 5.30 0.137
## 1675 6.80 0.220 0.29 8.90 0.046
## 1676 6.20 0.270 0.32 8.80 0.047
## 1677 7.00 0.350 0.30 6.50 0.028
## 1678 7.30 0.230 0.37 1.80 0.032
## 1679 6.20 0.300 0.20 6.60 0.045
## 1680 6.40 0.350 0.20 5.70 0.034
## 1681 7.60 0.320 0.34 18.35 0.054
## 1683 7.20 0.250 0.28 14.40 0.055
## 1684 7.20 0.250 0.28 14.40 0.055
## 1685 7.30 0.260 0.33 17.85 0.049
## 1686 7.20 0.250 0.28 14.40 0.055
## 1687 7.40 0.260 0.37 9.40 0.047
## 1688 7.30 0.260 0.33 17.85 0.049
## 1690 7.10 0.160 0.25 1.30 0.034
## 1691 9.00 0.430 0.30 1.50 0.050
## 1692 7.20 0.250 0.28 14.40 0.055
## 1693 7.00 0.240 0.30 4.20 0.040
## 1694 6.70 0.265 0.22 8.60 0.048
## 1695 7.70 0.120 0.32 1.40 0.060
## 1696 7.20 0.210 0.33 3.00 0.036
## 1697 8.50 0.320 0.36 14.90 0.041
## 1698 6.90 0.180 0.30 2.00 0.038
## 1699 7.00 0.240 0.30 4.20 0.040
## 1700 6.30 0.260 0.29 2.20 0.043
## 1701 6.70 0.260 0.30 1.80 0.043
## 1702 7.90 0.290 0.36 11.10 0.033
## 1703 6.50 0.270 0.19 4.20 0.046
## 1704 6.70 0.330 0.42 6.40 0.058
## 1705 6.70 0.310 0.42 6.40 0.057
## 1706 6.60 0.250 0.31 1.50 0.035
## 1707 6.40 0.240 0.22 1.50 0.038
## 1708 6.80 0.260 0.29 16.95 0.056
## 1709 7.00 0.610 0.26 1.70 0.051
## 1710 6.80 0.220 0.30 13.60 0.055
## 1711 8.10 0.310 0.24 1.60 0.032
## 1712 7.00 0.200 0.30 6.10 0.037
## 1713 7.90 0.180 0.37 3.00 0.061
## 1714 6.60 0.340 0.27 6.20 0.059
## 1715 6.80 0.300 0.24 6.60 0.123
## 1716 6.50 0.180 0.34 1.60 0.040
## 1717 7.00 0.210 0.31 6.00 0.046
## 1718 6.80 0.270 0.32 1.50 0.044
## 1719 9.30 0.200 0.33 1.70 0.050
## 1720 5.80 0.230 0.27 1.80 0.043
## 1721 7.60 0.200 0.39 2.60 0.044
## 1724 6.50 0.180 0.34 1.60 0.040
## 1725 7.00 0.130 0.30 5.00 0.056
## 1726 6.90 0.170 0.22 4.60 0.064
## 1727 7.00 0.300 0.32 6.40 0.034
## 1729 6.80 0.300 0.24 6.60 0.123
## 1730 7.50 0.220 0.33 6.70 0.036
## 1731 9.20 0.230 0.30 1.10 0.031
## 1733 6.60 0.545 0.04 2.50 0.031
## 1734 8.10 0.300 0.31 1.10 0.041
## 1735 6.90 0.160 0.30 9.60 0.057
## 1736 8.00 0.320 0.36 4.60 0.042
## 1737 6.10 0.220 0.23 3.10 0.052
## 1738 6.90 0.160 0.30 9.60 0.057
## 1739 7.50 0.150 0.38 1.80 0.054
## 1740 8.40 0.290 0.29 1.05 0.032
## 1741 6.60 0.370 0.47 6.50 0.061
## 1742 7.70 0.380 0.40 2.00 0.038
## 1743 6.30 0.250 0.23 14.90 0.039
## 1744 8.30 0.300 0.36 10.00 0.042
## 1746 6.10 0.340 0.31 12.00 0.053
## 1747 7.50 0.220 0.29 4.80 0.050
## 1748 8.30 0.300 0.36 10.00 0.042
## 1749 8.00 0.270 0.24 1.20 0.044
## 1750 6.10 0.170 0.27 1.50 0.056
## 1751 7.40 0.180 0.30 10.40 0.045
## 1752 6.70 0.160 0.28 2.50 0.046
## 1753 6.10 0.255 0.44 12.30 0.045
## 1754 7.40 0.230 0.25 1.40 0.049
## 1755 6.40 0.160 0.28 2.20 0.042
## 1756 6.30 0.250 0.23 14.90 0.039
## 1757 6.70 0.270 0.25 8.00 0.053
## 1758 6.90 0.290 0.23 8.60 0.056
## 1759 9.60 0.210 0.28 1.20 0.038
## 1760 6.60 0.620 0.20 8.70 0.046
## 1761 6.40 0.280 0.19 5.40 0.042
## 1762 8.00 0.300 0.28 5.70 0.044
## 1763 6.40 0.170 0.27 1.50 0.037
## 1764 7.30 0.210 0.30 10.90 0.037
## 1765 6.70 0.270 0.25 8.00 0.053
## 1766 6.90 0.290 0.23 8.60 0.056
## 1767 6.60 0.320 0.26 7.70 0.054
## 1768 7.40 0.320 0.22 1.70 0.051
## 1769 6.60 0.370 0.07 1.40 0.048
## 1770 7.70 0.430 0.28 4.50 0.046
## 1771 7.80 0.390 0.26 9.90 0.059
## 1772 6.50 0.180 0.26 1.40 0.041
## 1773 7.80 0.400 0.26 9.50 0.059
## 1774 7.80 0.390 0.26 9.90 0.059
## 1775 6.90 0.190 0.28 3.00 0.054
## 1777 6.60 0.250 0.35 14.00 0.069
## 1778 6.50 0.180 0.26 1.40 0.041
## 1779 6.40 0.150 0.36 1.80 0.034
## 1780 6.40 0.150 0.36 1.80 0.034
## 1781 8.40 0.170 0.31 5.40 0.052
## 1783 8.50 0.210 0.26 9.25 0.034
## 1784 8.70 0.450 0.40 1.50 0.067
## 1785 6.70 0.240 0.29 6.80 0.038
## 1786 8.50 0.210 0.26 9.25 0.034
## 1787 7.40 0.330 0.26 2.60 0.040
## 1788 7.20 0.260 0.30 2.10 0.033
## 1789 8.20 0.360 0.29 7.60 0.035
## 1790 7.80 0.200 0.24 1.60 0.026
## 1791 9.40 0.160 0.30 1.40 0.042
## 1792 6.40 0.330 0.24 1.60 0.054
## 1793 7.80 0.220 0.36 1.40 0.056
## 1794 7.40 0.350 0.31 17.95 0.062
## 1795 6.60 0.370 0.24 2.00 0.064
## 1796 6.70 0.370 0.41 6.30 0.061
## 1797 7.10 0.370 0.32 1.40 0.037
## 1798 6.90 0.250 0.27 9.05 0.039
## 1799 6.80 0.230 0.29 15.40 0.073
## 1800 6.40 0.260 0.21 7.10 0.040
## 1801 7.60 0.300 0.22 10.20 0.049
## 1802 9.40 0.160 0.23 1.60 0.042
## 1803 6.80 0.230 0.29 15.40 0.073
## 1804 6.40 0.260 0.21 7.10 0.040
## 1805 7.60 0.300 0.22 10.20 0.049
## 1806 7.50 0.330 0.39 12.40 0.065
## 1807 7.60 0.380 0.20 3.40 0.046
## 1808 8.80 0.200 0.43 15.00 0.053
## 1809 7.50 0.330 0.39 12.40 0.065
## 1810 8.80 0.200 0.43 15.00 0.053
## 1811 6.60 0.360 0.21 1.50 0.049
## 1812 7.60 0.380 0.20 3.40 0.046
## 1813 5.60 0.460 0.24 4.80 0.042
## 1814 7.20 0.150 0.38 1.20 0.038
## 1815 8.20 0.420 0.29 4.10 0.030
## 1816 6.80 0.300 0.35 2.80 0.038
## 1817 6.70 0.270 0.30 13.90 0.029
## 1818 7.20 0.500 0.00 0.80 0.034
## 1819 6.00 0.260 0.29 1.00 0.032
## 1820 6.80 0.330 0.28 1.20 0.032
## 1821 6.80 0.300 0.35 2.80 0.038
## 1822 7.40 0.290 0.31 1.70 0.035
## 1823 8.20 0.420 0.29 4.10 0.030
## 1824 7.30 0.190 0.24 6.30 0.054
## 1825 6.50 0.320 0.12 11.50 0.033
## 1826 7.10 0.320 0.40 1.50 0.034
## 1827 6.50 0.320 0.12 11.50 0.033
## 1828 7.30 0.190 0.24 6.30 0.054
## 1829 7.30 0.170 0.23 6.30 0.051
## 1830 7.70 0.440 0.24 11.20 0.031
## 1831 7.70 0.440 0.24 11.20 0.031
## 1832 7.40 0.490 0.24 15.10 0.030
## 1833 7.70 0.440 0.24 11.20 0.031
## 1834 7.40 0.490 0.24 15.10 0.030
## 1835 6.40 0.210 0.30 5.60 0.044
## 1837 7.00 0.190 0.23 5.70 0.123
## 1838 7.20 0.240 0.29 2.20 0.037
## 1839 6.50 0.340 0.36 11.00 0.052
## 1840 7.00 0.190 0.23 5.70 0.123
## 1841 6.90 0.180 0.33 1.00 0.054
## 1842 7.20 0.240 0.29 2.20 0.037
## 1843 8.20 0.180 0.31 11.80 0.039
## 1844 8.30 0.280 0.45 7.80 0.059
## 1845 6.10 0.340 0.46 4.70 0.029
## 1846 7.40 0.440 0.20 11.50 0.049
## 1847 7.60 0.260 0.58 7.90 0.041
## 1848 7.40 0.440 0.20 11.50 0.049
## 1850 7.00 0.240 0.25 1.70 0.042
## 1851 7.10 0.250 0.25 1.60 0.046
## 1852 6.10 0.340 0.46 4.70 0.029
## 1853 6.40 0.180 0.31 1.60 0.049
## 1854 8.30 0.270 0.39 2.40 0.058
## 1855 6.80 0.240 0.35 6.40 0.048
## 1856 8.00 0.220 0.28 14.00 0.053
## 1858 8.90 0.340 0.34 1.60 0.056
## 1859 8.90 0.330 0.34 1.40 0.056
## 1860 8.00 0.220 0.28 14.00 0.053
## 1861 6.70 0.180 0.19 4.70 0.046
## 1862 7.80 0.200 0.28 10.20 0.054
## 1863 7.30 0.130 0.31 2.30 0.054
## 1864 6.60 0.280 0.30 7.80 0.049
## 1865 7.10 0.250 0.30 2.40 0.042
## 1867 7.60 0.270 0.25 13.90 0.050
## 1868 6.90 0.370 0.28 13.80 0.031
## 1869 7.40 0.210 0.27 7.30 0.031
## 1870 8.20 0.180 0.28 8.50 0.035
## 1871 6.30 0.190 0.21 1.80 0.049
## 1872 7.00 0.210 0.22 5.10 0.048
## 1873 5.80 0.330 0.20 16.05 0.047
## 1874 5.80 0.330 0.20 16.05 0.047
## 1875 7.90 0.290 0.31 7.35 0.034
## 1876 6.60 0.310 0.38 16.05 0.058
## 1877 8.00 0.190 0.30 2.00 0.053
## 1878 8.00 0.200 0.36 1.20 0.032
## 1879 8.00 0.250 0.26 14.00 0.043
## 1880 7.20 0.200 0.61 16.20 0.043
## 1881 7.70 0.300 0.42 14.30 0.045
## 1882 7.20 0.200 0.61 16.20 0.043
## 1883 7.70 0.300 0.42 14.30 0.045
## 1884 7.70 0.300 0.42 14.30 0.045
## 1885 6.40 0.220 0.32 7.90 0.029
## 1886 7.20 0.200 0.61 16.20 0.043
## 1887 7.00 0.530 0.02 1.00 0.036
## 1888 7.30 0.240 0.41 13.60 0.050
## 1889 7.20 0.240 0.40 17.85 0.049
## 1890 7.60 0.150 0.40 1.30 0.036
## 1891 7.70 0.300 0.42 14.30 0.045
## 1892 7.60 0.330 0.41 13.70 0.045
## 1893 6.80 0.240 0.31 18.30 0.046
## 1894 6.80 0.240 0.31 18.30 0.046
## 1895 6.80 0.350 0.44 6.50 0.056
## 1896 7.90 0.260 0.33 10.30 0.039
## 1897 7.50 0.290 0.67 8.10 0.037
## 1898 7.50 0.290 0.67 8.10 0.037
## 1899 7.20 0.310 0.41 8.60 0.053
## 1900 6.70 0.440 0.31 1.90 0.030
## 1902 7.40 0.210 0.30 7.90 0.039
## 1903 8.80 0.230 0.35 10.70 0.040
## 1904 7.80 0.340 0.27 1.20 0.040
## 1905 7.90 0.260 0.33 10.30 0.039
## 1906 7.50 0.290 0.67 8.10 0.037
## 1907 6.00 0.280 0.35 1.90 0.037
## 1908 7.90 0.370 0.30 2.70 0.029
## 1909 7.20 0.360 0.36 5.70 0.038
## 1910 7.60 0.130 0.34 9.30 0.062
## 1911 6.60 0.250 0.36 8.10 0.045
## 1912 7.10 0.180 0.26 1.30 0.041
## 1913 7.90 0.300 0.27 8.50 0.036
## 1914 8.30 0.230 0.30 2.10 0.049
## 1915 6.80 0.430 0.30 3.50 0.033
## 1916 7.20 0.360 0.36 5.70 0.038
## 1917 6.60 0.250 0.36 8.10 0.045
## 1918 7.10 0.180 0.26 1.30 0.041
## 1919 6.60 0.350 0.29 14.40 0.044
## 1920 7.30 0.220 0.50 13.70 0.049
## 1921 8.10 0.260 0.33 11.10 0.052
## 1922 7.60 0.130 0.34 9.30 0.062
## 1923 7.00 0.120 0.19 4.90 0.055
## 1924 8.20 0.370 0.27 1.70 0.028
## 1925 7.60 0.260 0.36 1.60 0.032
## 1928 7.10 0.250 0.28 1.60 0.052
## 1929 7.00 0.270 0.32 6.80 0.047
## 1930 8.80 0.340 0.33 9.70 0.036
## 1931 9.20 0.270 0.34 10.50 0.043
## 1934 7.20 0.470 0.65 8.30 0.083
## 1935 6.80 0.280 0.36 1.60 0.040
## 1936 8.80 0.340 0.33 9.70 0.036
## 1937 9.20 0.270 0.34 10.50 0.043
## 1938 7.30 0.130 0.27 4.60 0.080
## 1939 7.20 0.160 0.35 1.20 0.031
## 1940 6.80 0.310 0.32 7.60 0.052
## 1941 8.30 0.360 0.57 15.00 0.052
## 1942 6.80 0.310 0.32 7.60 0.052
## 1943 8.30 0.360 0.57 15.00 0.052
## 1944 6.30 0.250 0.44 11.60 0.041
## 1946 8.10 0.260 0.30 7.80 0.049
## 1947 6.40 0.220 0.32 12.00 0.066
## 1949 7.20 0.190 0.31 1.40 0.046
## 1950 6.70 0.310 0.44 6.70 0.054
## 1951 8.00 0.250 0.13 17.20 0.036
## 1953 8.10 0.310 0.36 8.20 0.028
## 1954 8.10 0.240 0.38 4.30 0.044
## 1955 8.00 0.250 0.13 17.20 0.036
## 1956 6.40 0.290 0.28 11.10 0.063
## 1957 7.20 0.150 0.33 1.10 0.027
## 1958 7.00 0.120 0.32 7.20 0.058
## 1960 8.50 0.170 0.31 1.00 0.024
## 1961 8.50 0.170 0.31 1.00 0.024
## 1962 9.50 0.210 0.47 1.30 0.039
## 1963 8.20 0.210 0.48 1.40 0.041
## 1965 6.80 0.310 0.42 6.90 0.046
## 1966 6.80 0.270 0.28 13.30 0.076
## 1967 7.40 0.210 0.30 8.10 0.047
## 1968 8.00 0.230 0.35 9.20 0.044
## 1969 7.60 0.200 0.31 1.40 0.047
## 1970 6.30 0.410 0.30 3.20 0.030
## 1971 8.30 0.490 0.43 2.50 0.036
## 1972 6.30 0.410 0.30 3.20 0.030
## 1973 7.60 0.200 0.26 4.50 0.086
## 1974 7.50 0.260 0.26 18.35 0.084
## 1975 7.50 0.260 0.26 18.35 0.084
## 1976 6.80 0.270 0.35 7.80 0.048
## 1977 6.80 0.280 0.37 7.00 0.057
## 1978 8.40 0.200 0.27 6.30 0.048
## 1979 7.90 0.330 0.26 1.20 0.044
## 1980 7.50 0.380 0.50 12.80 0.042
## 1981 7.60 0.200 0.30 14.20 0.056
## 1982 7.60 0.200 0.30 14.20 0.056
## 1983 7.60 0.200 0.30 14.20 0.056
## 1984 7.60 0.200 0.30 14.20 0.056
## 1985 7.60 0.200 0.30 14.20 0.056
## 1986 8.10 0.190 0.58 16.65 0.049
## 1987 7.60 0.160 0.41 1.90 0.047
## 1988 8.10 0.220 0.28 7.70 0.043
## 1989 8.00 0.220 0.32 10.40 0.043
## 1990 7.10 0.330 0.30 3.30 0.034
## 1991 6.40 0.430 0.27 1.10 0.054
## 1992 7.60 0.200 0.30 14.20 0.056
## 1993 7.00 0.120 0.28 6.30 0.057
## 1994 7.40 0.300 0.22 5.25 0.053
## 1995 7.00 0.280 0.33 14.60 0.043
## 1996 8.40 0.200 0.38 11.80 0.055
## 1997 7.00 0.280 0.33 14.60 0.043
## 1998 8.40 0.200 0.38 11.80 0.055
## 1999 8.40 0.200 0.38 11.80 0.055
## 2000 7.30 0.180 0.31 17.30 0.055
## 2001 6.80 0.310 0.09 1.40 0.040
## 2002 6.70 0.310 0.08 1.30 0.038
## 2003 7.60 0.170 0.35 1.60 0.047
## 2004 7.40 0.300 0.22 5.25 0.053
## 2005 7.40 0.260 0.31 2.40 0.043
## 2006 7.00 0.280 0.33 14.60 0.043
## 2007 8.40 0.200 0.38 11.80 0.055
## 2008 5.60 0.180 0.31 1.50 0.038
## 2009 7.20 0.150 0.39 1.80 0.043
## 2010 8.00 0.400 0.33 7.70 0.034
## 2011 7.00 0.250 0.56 2.00 0.035
## 2012 7.20 0.150 0.39 1.80 0.043
## 2013 6.80 0.180 0.46 1.40 0.064
## 2014 6.60 0.320 0.22 16.70 0.046
## 2015 9.00 0.550 0.30 8.10 0.026
## 2016 6.90 0.190 0.39 8.00 0.028
## 2017 6.30 0.410 0.33 4.70 0.023
## 2018 9.00 0.550 0.30 8.10 0.026
## 2019 7.00 0.200 0.34 2.10 0.049
## 2020 6.60 0.320 0.22 16.70 0.046
## 2021 7.70 0.260 0.34 6.40 0.050
## 2022 6.30 0.210 0.28 1.50 0.051
## 2023 7.60 0.340 0.39 7.60 0.040
## 2024 6.30 0.210 0.28 1.50 0.051
## 2028 6.90 0.320 0.15 8.10 0.046
## 2029 8.90 0.210 0.34 7.10 0.037
## 2030 7.60 0.340 0.39 7.60 0.040
## 2031 9.50 0.420 0.41 2.30 0.034
## 2032 7.60 0.290 0.26 6.50 0.042
## 2033 6.50 0.250 0.20 1.40 0.024
## 2034 7.20 0.230 0.33 12.70 0.049
## 2035 7.90 0.350 0.36 1.60 0.038
## 2036 8.80 0.200 0.28 1.10 0.018
## 2038 7.60 0.290 0.26 6.50 0.042
## 2039 5.50 0.140 0.27 4.60 0.029
## 2040 8.70 0.240 0.35 0.60 0.042
## 2041 6.70 0.300 0.45 10.60 0.032
## 2042 5.50 0.140 0.27 4.60 0.029
## 2043 5.60 0.130 0.27 4.80 0.028
## 2044 7.40 0.180 0.34 2.70 0.030
## 2045 5.70 0.385 0.04 12.60 0.034
## 2046 8.70 0.240 0.35 0.60 0.042
## 2047 8.30 0.330 0.43 9.20 0.046
## 2048 6.80 0.340 0.44 6.60 0.052
## 2049 6.80 0.330 0.44 7.00 0.050
## 2050 6.30 0.280 0.24 8.45 0.031
## 2052 6.80 0.210 0.27 18.15 0.042
## 2053 6.80 0.210 0.27 18.15 0.042
## 2054 8.60 0.485 0.29 4.10 0.026
## 2055 8.60 0.485 0.29 4.10 0.026
## 2056 7.30 0.290 0.29 4.60 0.029
## 2057 6.80 0.210 0.27 18.15 0.042
## 2058 6.70 0.310 0.31 4.90 0.031
## 2059 7.30 0.290 0.37 8.30 0.044
## 2060 5.70 0.460 0.46 1.40 0.040
## 2061 6.80 0.280 0.44 11.50 0.040
## 2062 6.70 0.230 0.33 1.80 0.036
## 2063 6.90 0.170 0.25 1.60 0.047
## 2064 7.60 0.180 0.36 2.40 0.049
## 2065 6.60 0.220 0.28 4.90 0.042
## 2066 7.80 0.270 0.28 1.80 0.050
## 2067 7.70 0.280 0.29 4.30 0.051
## 2068 7.60 0.290 0.29 4.40 0.051
## 2069 5.70 0.320 0.18 1.40 0.029
## 2070 7.10 0.330 0.25 1.60 0.030
## 2071 7.30 0.340 0.30 1.30 0.057
## 2072 6.50 0.190 0.26 5.20 0.040
## 2073 6.60 0.230 0.27 5.60 0.043
## 2074 6.60 0.270 0.29 5.30 0.045
## 2075 6.60 0.220 0.28 4.90 0.042
## 2076 7.60 0.180 0.36 2.40 0.049
## 2077 6.80 0.360 0.32 1.60 0.039
## 2078 7.00 0.220 0.39 2.10 0.055
## 2079 5.90 0.170 0.30 1.40 0.042
## 2080 7.40 0.450 0.32 7.10 0.044
## 2081 6.80 0.360 0.32 1.60 0.039
## 2082 7.50 0.420 0.14 10.70 0.046
## 2083 7.50 0.330 0.32 11.10 0.036
## 2084 9.40 0.300 0.32 10.70 0.029
## 2085 7.90 0.170 0.32 1.60 0.053
## 2086 7.90 0.170 0.32 1.60 0.053
## 2087 8.20 0.170 0.32 1.50 0.050
## 2088 8.30 0.170 0.31 1.50 0.049
## 2089 8.70 0.150 0.30 1.60 0.046
## 2090 7.90 0.170 0.32 1.60 0.053
## 2091 7.20 0.250 0.19 8.00 0.044
## 2092 7.20 0.240 0.19 7.70 0.045
## 2093 5.30 0.760 0.03 2.70 0.043
## 2094 6.60 0.220 0.53 15.10 0.052
## 2095 6.60 0.220 0.53 15.10 0.052
## 2096 8.40 0.280 0.40 8.90 0.048
## 2097 6.80 0.320 0.34 6.00 0.050
## 2098 6.70 0.240 0.33 12.30 0.046
## 2099 7.40 0.180 0.36 13.10 0.056
## 2100 6.00 0.160 0.30 6.70 0.043
## 2101 6.70 0.240 0.33 12.30 0.046
## 2102 6.80 0.280 0.35 2.30 0.042
## 2103 6.20 0.340 0.30 11.10 0.047
## 2104 6.00 0.270 0.15 1.50 0.056
## 2105 6.00 0.160 0.30 6.70 0.043
## 2106 6.80 0.320 0.34 6.00 0.050
## 2107 8.50 0.240 0.47 15.20 0.057
## 2108 8.10 0.240 0.33 10.20 0.048
## 2109 7.40 0.180 0.36 13.10 0.056
## 2110 7.70 0.230 0.31 10.70 0.038
## 2111 6.50 0.220 0.25 17.10 0.050
## 2112 6.50 0.220 0.25 17.10 0.050
## 2113 6.50 0.220 0.25 17.10 0.050
## 2114 5.70 0.330 0.15 1.90 0.050
## 2115 7.70 0.230 0.31 10.70 0.038
## 2116 6.50 0.220 0.25 17.10 0.050
## 2117 6.80 0.200 0.27 1.20 0.034
## 2118 7.70 0.260 0.32 1.20 0.040
## 2119 6.40 0.200 0.32 3.10 0.041
## 2120 8.00 0.160 0.36 1.50 0.033
## 2121 6.80 0.250 0.27 10.70 0.076
## 2122 7.70 0.390 0.28 4.90 0.035
## 2123 6.90 0.260 0.33 12.60 0.051
## 2124 6.80 0.250 0.27 10.70 0.076
## 2125 7.70 0.390 0.28 4.90 0.035
## 2126 6.00 0.280 0.22 12.15 0.048
## 2127 6.50 0.430 0.28 12.00 0.056
## 2129 5.90 0.500 0.05 2.60 0.054
## 2130 6.80 0.280 0.39 1.40 0.036
## 2131 7.00 0.350 0.24 1.90 0.040
## 2132 7.10 0.220 0.32 16.90 0.056
## 2133 7.10 0.220 0.32 16.90 0.056
## 2134 8.30 0.240 0.27 2.10 0.030
## 2135 6.80 0.260 0.32 7.00 0.041
## 2136 7.20 0.160 0.26 7.10 0.054
## 2137 7.90 0.180 0.36 5.90 0.058
## 2138 7.20 0.160 0.26 7.10 0.054
## 2139 5.50 0.240 0.32 8.70 0.060
## 2140 7.10 0.330 0.64 13.20 0.056
## 2141 7.70 0.280 0.35 15.30 0.056
## 2142 7.70 0.280 0.35 15.30 0.056
## 2143 7.50 0.260 0.52 13.20 0.047
## 2144 6.50 0.140 0.32 2.70 0.037
## 2145 8.20 0.210 0.32 10.65 0.053
## 2146 7.20 0.200 0.31 10.00 0.054
## 2147 7.20 0.115 0.30 6.80 0.056
## 2148 6.40 0.290 0.20 15.60 0.040
## 2149 7.10 0.330 0.64 13.20 0.056
## 2150 6.80 0.240 0.34 5.10 0.038
## 2151 7.00 0.240 0.34 3.00 0.035
## 2152 7.70 0.280 0.35 15.30 0.056
## 2153 7.00 0.220 0.33 2.10 0.052
## 2154 7.50 0.180 0.39 1.90 0.054
## 2156 7.80 0.290 0.33 8.75 0.035
## 2157 7.90 0.280 0.32 3.60 0.038
## 2158 8.50 0.250 0.27 4.70 0.031
## 2159 7.40 0.180 0.27 1.30 0.048
## 2160 6.30 0.240 0.37 1.80 0.031
## 2161 6.00 0.330 0.38 9.70 0.040
## 2162 6.80 0.370 0.28 4.00 0.030
## 2163 9.90 0.490 0.23 2.40 0.087
## 2164 8.50 0.250 0.27 4.70 0.031
## 2166 7.00 0.350 0.31 1.80 0.069
## 2167 7.00 0.350 0.31 1.80 0.069
## 2168 7.40 0.190 0.30 12.80 0.053
## 2169 7.40 0.190 0.30 12.80 0.053
## 2170 7.40 0.190 0.30 12.80 0.053
## 2171 7.40 0.190 0.30 12.80 0.053
## 2172 7.40 0.190 0.30 12.80 0.053
## 2173 6.90 0.320 0.13 7.80 0.042
## 2174 7.60 0.320 0.58 16.75 0.050
## 2175 7.40 0.190 0.30 12.80 0.053
## 2176 7.40 0.190 0.30 12.80 0.053
## 2177 6.90 0.320 0.13 7.80 0.042
## 2178 6.00 0.340 0.24 5.40 0.060
## 2179 7.60 0.320 0.58 16.75 0.050
## 2180 7.70 0.240 0.31 1.30 0.047
## 2181 8.00 0.360 0.43 10.10 0.053
## 2182 7.40 0.290 0.25 3.80 0.044
## 2183 6.60 0.320 0.27 10.90 0.041
## 2184 6.30 0.300 0.24 6.60 0.040
## 2185 6.40 0.330 0.24 9.80 0.041
## 2186 7.50 0.180 0.31 11.70 0.051
## 2188 6.80 0.250 0.18 1.40 0.056
## 2189 6.40 0.180 0.32 9.60 0.052
## 2190 7.10 0.180 0.32 12.20 0.048
## 2191 7.60 0.270 0.42 2.60 0.044
## 2192 9.20 0.230 0.35 10.70 0.037
## 2193 7.90 0.280 0.41 4.90 0.058
## 2194 7.10 0.180 0.32 12.20 0.048
## 2195 6.40 0.180 0.32 9.60 0.052
## 2196 6.80 0.250 0.18 1.40 0.056
## 2197 7.00 0.220 0.26 1.10 0.037
## 2198 7.30 0.180 0.29 1.00 0.036
## 2199 7.10 0.260 0.19 8.20 0.051
## 2200 6.60 0.250 0.42 11.30 0.049
## 2201 6.40 0.240 0.23 7.30 0.069
## 2202 6.00 0.280 0.27 2.30 0.051
## 2203 7.10 0.260 0.19 8.20 0.051
## 2204 7.80 0.240 0.38 2.10 0.058
## 2205 7.60 0.270 0.33 2.00 0.059
## 2206 7.70 0.390 0.34 10.00 0.056
## 2208 6.60 0.230 0.24 3.90 0.045
## 2209 7.10 0.260 0.30 2.00 0.031
## 2210 7.00 0.320 0.35 1.50 0.039
## 2211 7.40 0.240 0.26 1.60 0.058
## 2212 6.90 0.210 0.33 1.40 0.056
## 2213 7.00 0.320 0.35 1.50 0.039
## 2214 7.40 0.170 0.29 1.40 0.047
## 2215 7.10 0.260 0.30 2.00 0.031
## 2216 8.50 0.280 0.34 13.80 0.041
## 2217 7.80 0.300 0.37 1.30 0.051
## 2218 8.10 0.250 0.38 3.80 0.051
## 2219 7.70 0.280 0.29 6.90 0.041
## 2220 6.50 0.240 0.36 2.20 0.027
## 2221 7.00 0.220 0.32 1.60 0.045
## 2222 8.50 0.280 0.34 13.80 0.041
## 2223 8.00 0.450 0.28 10.80 0.051
## 2224 6.90 0.230 0.33 12.80 0.056
## 2225 8.00 0.450 0.28 10.80 0.051
## 2226 7.60 0.230 0.26 15.30 0.067
## 2227 7.70 0.280 0.58 12.10 0.046
## 2228 7.70 0.270 0.61 12.00 0.046
## 2229 7.10 0.200 0.36 11.60 0.042
## 2230 6.90 0.250 0.35 9.20 0.034
## 2231 7.10 0.200 0.36 11.60 0.042
## 2232 6.90 0.250 0.35 9.20 0.034
## 2233 8.40 0.200 0.31 2.80 0.054
## 2234 6.50 0.390 0.35 1.60 0.049
## 2235 7.20 0.230 0.38 6.10 0.067
## 2236 6.90 0.440 0.42 8.50 0.048
## 2237 7.10 0.280 0.19 7.80 0.040
## 2238 6.40 0.340 0.20 14.90 0.060
## 2239 6.10 0.150 0.29 6.20 0.046
## 2240 6.90 0.440 0.42 8.50 0.048
## 2241 7.20 0.290 0.18 8.20 0.042
## 2242 7.10 0.280 0.19 7.80 0.040
## 2243 6.10 0.230 0.45 10.60 0.094
## 2244 6.70 0.230 0.42 11.20 0.047
## 2245 7.00 0.360 0.14 11.60 0.043
## 2246 7.50 0.310 0.24 7.10 0.031
## 2247 6.40 0.340 0.20 14.90 0.060
## 2248 6.10 0.150 0.29 6.20 0.046
## 2249 7.40 0.200 0.29 1.70 0.047
## 2250 6.30 0.270 0.18 7.70 0.048
## 2251 9.20 0.340 0.54 17.30 0.060
## 2252 7.40 0.180 0.29 1.40 0.042
## 2253 7.20 0.290 0.20 7.70 0.046
## 2254 6.30 0.270 0.18 7.70 0.048
## 2255 6.20 0.260 0.19 3.40 0.049
## 2256 7.30 0.210 0.21 1.60 0.046
## 2257 7.10 0.140 0.35 1.40 0.039
## 2258 7.20 0.390 0.54 1.40 0.157
## 2259 7.60 0.480 0.28 10.40 0.049
## 2260 7.20 0.390 0.54 1.40 0.157
## 2261 7.60 0.480 0.28 10.40 0.049
## 2262 6.50 0.360 0.31 4.10 0.061
## 2263 8.50 0.250 0.31 2.80 0.032
## 2264 6.90 0.300 0.21 15.70 0.056
## 2265 6.60 0.190 0.43 10.90 0.045
## 2266 6.90 0.300 0.21 15.70 0.056
## 2267 9.40 0.420 0.32 6.50 0.027
## 2268 6.60 0.190 0.43 10.90 0.045
## 2269 6.30 0.200 0.30 5.90 0.034
## 2270 8.50 0.190 0.56 17.30 0.055
## 2271 7.30 0.190 0.25 1.40 0.051
## 2272 6.70 0.250 0.26 13.50 0.060
## 2273 6.20 0.250 0.28 8.50 0.035
## 2274 6.10 0.460 0.32 6.20 0.053
## 2275 7.30 0.190 0.25 1.40 0.051
## 2276 7.50 0.290 0.26 14.95 0.067
## 2277 6.70 0.310 0.18 7.70 0.043
## 2278 7.40 0.140 0.30 1.30 0.033
## 2279 6.70 0.310 0.18 7.70 0.043
## 2280 7.10 0.400 0.52 1.30 0.148
## 2281 6.40 0.160 0.25 1.30 0.047
## 2282 6.30 0.160 0.22 1.30 0.046
## 2283 7.40 0.330 0.26 15.60 0.049
## 2284 7.40 0.330 0.26 15.60 0.049
## 2285 7.40 0.330 0.26 15.60 0.049
## 2286 7.40 0.330 0.26 15.60 0.049
## 2287 6.60 0.410 0.24 4.90 0.158
## 2288 6.70 0.430 0.23 5.00 0.157
## 2289 7.40 0.330 0.26 15.60 0.049
## 2290 7.30 0.400 0.28 6.50 0.037
## 2291 7.40 0.180 0.24 1.40 0.047
## 2292 8.60 0.170 0.28 2.70 0.047
## 2293 6.50 0.320 0.23 1.20 0.054
## 2294 7.30 0.400 0.28 6.50 0.037
## 2295 7.00 0.320 0.31 6.40 0.031
## 2296 7.50 0.420 0.19 6.90 0.041
## 2297 6.90 0.280 0.31 7.20 0.040
## 2298 6.50 0.290 0.42 10.60 0.042
## 2299 6.30 0.410 0.18 3.50 0.027
## 2300 7.00 0.320 0.31 6.40 0.031
## 2301 7.30 0.300 0.33 2.30 0.043
## 2302 6.60 0.220 0.28 12.05 0.058
## 2303 6.00 0.260 0.18 7.00 0.055
## 2304 6.90 0.440 0.18 11.80 0.051
## 2305 7.50 0.420 0.20 1.40 0.060
## 2306 7.00 0.360 0.30 5.00 0.040
## 2307 5.60 0.295 0.20 2.20 0.049
## 2308 6.80 0.210 0.55 14.60 0.053
## 2309 9.40 0.280 0.30 1.60 0.045
## 2310 8.10 0.280 0.34 1.30 0.035
## 2311 6.80 0.210 0.55 14.60 0.053
## 2312 7.00 0.220 0.26 2.80 0.036
## 2313 9.40 0.280 0.30 1.60 0.045
## 2314 6.80 0.320 0.30 3.30 0.029
## 2315 7.00 0.190 0.33 6.30 0.032
## 2316 7.70 0.420 0.38 8.10 0.061
## 2317 7.40 0.200 0.31 1.60 0.038
## 2318 7.50 0.240 0.62 10.60 0.045
## 2319 7.50 0.260 0.59 11.80 0.046
## 2320 6.60 0.400 0.32 1.70 0.035
## 2321 8.00 0.200 0.30 8.10 0.037
## 2323 6.10 0.410 0.04 1.30 0.036
## 2324 7.60 0.200 0.34 1.80 0.041
## 2325 6.90 0.300 0.21 7.20 0.045
## 2326 7.00 0.350 0.17 1.10 0.049
## 2327 6.90 0.350 0.55 11.95 0.038
## 2328 7.00 0.350 0.17 1.10 0.049
## 2329 6.90 0.350 0.55 11.95 0.038
## 2330 7.60 0.300 0.40 2.20 0.054
## 2331 7.50 0.380 0.29 12.70 0.050
## 2332 7.50 0.300 0.32 1.40 0.032
## 2333 6.30 0.400 0.32 10.60 0.049
## 2336 8.30 0.270 0.34 10.20 0.048
## 2338 6.50 0.280 0.35 9.80 0.067
## 2339 7.20 0.340 0.30 8.40 0.051
## 2340 7.00 0.230 0.26 7.20 0.041
## 2341 7.70 0.290 0.29 4.80 0.060
## 2342 7.20 0.340 0.30 8.40 0.051
## 2343 7.70 0.400 0.27 4.50 0.034
## 2344 6.70 0.170 0.27 1.40 0.032
## 2345 7.00 0.230 0.26 7.20 0.041
## 2346 8.10 0.240 0.26 11.00 0.043
## 2347 7.70 0.280 0.63 11.10 0.039
## 2348 7.50 0.230 0.29 2.60 0.031
## 2349 8.30 0.260 0.31 2.00 0.029
## 2351 7.90 0.310 0.22 13.30 0.048
## 2352 7.90 0.250 0.34 11.40 0.040
## 2353 6.10 0.280 0.16 1.30 0.060
## 2354 7.00 0.180 0.26 1.40 0.044
## 2355 6.50 0.210 0.28 1.40 0.046
## 2356 7.60 0.480 0.33 7.00 0.024
## 2357 7.10 0.340 0.32 2.00 0.051
## 2358 8.90 0.210 0.37 1.20 0.028
## 2359 7.40 0.320 0.27 12.90 0.040
## 2361 8.10 0.250 0.34 10.10 0.050
## 2362 8.20 0.250 0.46 3.75 0.050
## 2363 6.50 0.180 0.29 1.70 0.035
## 2364 6.70 0.240 0.26 12.60 0.053
## 2365 6.60 0.320 0.24 1.30 0.060
## 2366 7.60 0.320 0.35 1.60 0.092
## 2367 7.40 0.330 0.44 7.60 0.050
## 2368 7.20 0.300 0.30 8.10 0.050
## 2369 7.40 0.340 0.30 14.90 0.037
## 2370 6.10 0.160 0.29 6.00 0.030
## 2371 6.30 0.100 0.24 6.00 0.039
## 2373 6.00 0.330 0.18 3.00 0.036
## 2374 7.60 0.480 0.37 1.20 0.034
## 2375 7.20 0.200 0.30 2.00 0.039
## 2376 7.00 0.320 0.29 4.90 0.036
## 2377 7.20 0.200 0.30 2.00 0.039
## 2378 7.00 0.220 0.29 8.90 0.050
## 2380 6.40 0.270 0.19 2.00 0.084
## 2381 6.40 0.270 0.19 1.90 0.085
## 2382 7.00 0.230 0.42 5.10 0.042
## 2383 6.90 0.150 0.28 4.40 0.029
## 2384 6.70 0.260 0.29 5.80 0.025
## 2385 6.90 0.150 0.28 4.40 0.029
## 2386 7.60 0.200 0.68 12.90 0.042
## 2387 6.90 0.300 0.29 1.30 0.053
## 2388 6.90 0.300 0.30 1.30 0.053
## 2389 7.60 0.210 0.35 1.20 0.041
## 2390 6.80 0.460 0.26 2.70 0.042
## 2391 7.00 0.280 0.26 1.70 0.042
## 2392 6.50 0.240 0.29 8.20 0.043
## 2393 6.40 0.170 0.34 1.50 0.091
## 2394 6.40 0.170 0.34 1.50 0.093
## 2396 7.00 0.270 0.29 3.90 0.059
## 2398 6.50 0.190 0.27 4.90 0.037
## 2399 8.00 0.360 0.39 1.60 0.024
## 2400 6.10 0.160 0.24 1.40 0.046
## 2401 9.20 0.190 0.42 2.00 0.047
## 2402 9.20 0.160 0.49 2.00 0.044
## 2403 8.00 0.260 0.28 8.20 0.038
## 2405 9.80 0.160 0.46 1.80 0.046
## 2406 6.60 0.230 0.18 8.50 0.044
## 2407 7.90 0.440 0.26 4.45 0.033
## 2408 7.60 0.310 0.27 5.80 0.036
## 2410 7.10 0.210 0.28 2.70 0.034
## 2411 7.00 0.160 0.26 7.30 0.047
## 2412 8.00 0.270 0.25 19.10 0.045
## 2413 6.30 0.380 0.17 8.80 0.080
## 2414 7.10 0.210 0.28 2.70 0.034
## 2415 6.20 0.380 0.18 7.40 0.095
## 2416 8.20 0.240 0.30 2.30 0.050
## 2417 7.00 0.160 0.26 6.85 0.047
## 2419 6.30 0.410 0.16 0.90 0.032
## 2420 6.10 0.360 0.41 19.35 0.070
## 2421 8.10 0.400 0.32 7.90 0.031
## 2422 6.80 0.260 0.43 11.75 0.045
## 2423 6.20 0.440 0.18 7.70 0.096
## 2424 7.20 0.240 0.29 3.00 0.036
## 2425 6.20 0.440 0.18 7.70 0.096
## 2426 7.20 0.240 0.29 3.00 0.036
## 2427 7.30 0.220 0.26 1.50 0.040
## 2428 8.10 0.340 0.28 7.50 0.040
## 2429 7.30 0.220 0.26 1.50 0.040
## 2430 8.10 0.340 0.28 7.50 0.040
## 2431 6.40 0.280 0.17 8.30 0.042
## 2432 6.30 0.290 0.14 7.05 0.045
## 2433 6.40 0.270 0.17 8.40 0.044
## 2434 7.40 0.350 0.20 13.90 0.054
## 2435 8.30 0.280 0.27 17.50 0.045
## 2436 6.40 0.350 0.35 5.60 0.034
## 2437 6.90 0.430 0.28 9.40 0.056
## 2438 8.00 0.260 0.28 4.80 0.050
## 2439 6.90 0.430 0.28 9.40 0.056
## 2440 7.30 0.270 0.37 9.70 0.042
## 2441 6.80 0.460 0.26 6.30 0.147
## 2443 7.60 0.285 0.32 14.60 0.063
## 2444 6.60 0.320 0.33 2.50 0.052
## 2445 7.60 0.285 0.32 14.60 0.063
## 2446 6.60 0.340 0.34 2.60 0.051
## 2447 6.60 0.320 0.33 2.50 0.052
## 2448 6.50 0.270 0.26 8.20 0.042
## 2449 6.60 0.260 0.27 1.50 0.040
## 2450 6.70 0.270 0.26 2.30 0.043
## 2451 6.60 0.560 0.15 10.00 0.037
## 2452 6.60 0.560 0.15 10.00 0.037
## 2453 7.30 0.190 0.27 1.60 0.027
## 2454 6.30 0.200 0.26 1.60 0.027
## 2455 7.10 0.290 0.30 16.00 0.036
## 2456 7.80 0.320 0.33 10.40 0.031
## 2457 8.10 0.330 0.36 7.40 0.037
## 2458 8.10 0.330 0.36 7.40 0.037
## 2459 7.80 0.320 0.33 10.40 0.031
## 2460 6.60 0.330 0.24 16.05 0.045
## 2461 6.60 0.330 0.24 16.05 0.045
## 2462 8.20 0.260 0.33 2.60 0.053
## 2463 8.30 0.250 0.33 2.50 0.053
## 2464 7.00 0.260 0.26 10.80 0.039
## 2465 6.00 0.260 0.15 1.20 0.053
## 2468 7.00 0.280 0.32 1.70 0.038
## 2469 5.20 0.160 0.34 0.80 0.029
## 2470 6.80 0.340 0.10 1.40 0.049
## 2471 7.60 0.250 0.34 1.30 0.056
## 2472 5.60 0.350 0.40 6.30 0.022
## 2473 8.80 0.240 0.23 10.30 0.032
## 2474 6.00 0.290 0.21 15.55 0.043
## 2475 6.10 0.270 0.31 1.50 0.035
## 2476 7.40 0.560 0.09 1.50 0.071
## 2477 6.80 0.290 0.49 1.40 0.142
## 2478 6.10 0.270 0.31 1.50 0.035
## 2479 6.30 0.270 0.37 7.90 0.047
## 2480 6.60 0.240 0.30 13.00 0.052
## 2481 6.80 0.320 0.30 1.00 0.049
## 2482 6.40 0.370 0.37 4.85 0.041
## 2483 6.20 0.260 0.37 7.10 0.047
## 2484 6.30 0.270 0.37 7.90 0.047
## 2485 6.40 0.300 0.16 7.50 0.050
## 2486 8.00 0.280 0.32 7.60 0.045
## 2487 6.70 0.240 0.32 10.30 0.079
## 2488 7.90 0.270 0.27 1.70 0.034
## 2489 7.90 0.270 0.27 1.70 0.034
## 2490 6.10 0.280 0.24 19.95 0.074
## 2491 7.70 0.390 0.49 7.70 0.036
## 2492 6.00 0.200 0.24 5.30 0.075
## 2493 6.10 0.280 0.24 19.95 0.074
## 2494 7.60 0.310 0.23 12.70 0.054
## 2495 7.60 0.310 0.23 12.70 0.054
## 2496 6.30 0.180 0.22 1.50 0.043
## 2497 8.60 0.230 0.25 11.30 0.031
## 2498 6.80 0.210 0.36 18.10 0.046
## 2499 6.80 0.210 0.36 18.10 0.046
## 2500 6.90 0.260 0.31 7.00 0.039
## 2501 6.80 0.210 0.36 18.10 0.046
## 2502 6.40 0.310 0.40 6.40 0.039
## 2503 8.60 0.340 0.36 1.40 0.045
## 2504 8.60 0.340 0.36 1.40 0.045
## 2505 8.50 0.300 0.28 3.10 0.054
## 2506 7.40 0.400 0.41 14.10 0.053
## 2507 6.60 0.320 0.34 7.70 0.044
## 2508 7.10 0.340 0.31 5.20 0.032
## 2509 6.60 0.260 0.25 11.60 0.045
## 2510 8.00 0.270 0.57 10.40 0.053
## 2511 6.20 0.280 0.45 7.50 0.045
## 2512 6.20 0.300 0.49 11.20 0.058
## 2513 5.60 0.175 0.29 0.80 0.043
## 2514 6.90 0.340 0.36 1.40 0.032
## 2515 6.90 0.340 0.30 4.70 0.029
## 2516 7.10 0.120 0.30 3.10 0.018
## 2517 7.10 0.320 0.29 4.00 0.038
## 2518 7.30 0.510 0.29 11.30 0.034
## 2519 7.10 0.120 0.30 3.10 0.018
## 2520 6.30 0.240 0.55 8.10 0.040
## 2521 7.50 0.410 0.23 14.80 0.054
## 2522 6.50 0.180 0.33 1.40 0.029
## 2523 7.30 0.170 0.24 8.10 0.121
## 2524 8.20 0.200 0.38 3.50 0.053
## 2525 7.50 0.410 0.23 14.80 0.054
## 2526 7.30 0.170 0.24 8.10 0.121
## 2527 6.50 0.180 0.33 1.40 0.029
## 2528 7.30 0.160 0.35 1.50 0.036
## 2529 6.40 0.160 0.37 1.50 0.037
## 2530 6.60 0.420 0.13 12.80 0.044
## 2531 5.80 0.300 0.12 1.60 0.036
## 2532 6.70 0.540 0.27 7.10 0.049
## 2533 6.70 0.540 0.27 7.10 0.049
## 2534 6.40 0.220 0.30 11.20 0.046
## 2535 6.80 0.230 0.30 1.70 0.043
## 2536 9.00 0.260 0.34 6.70 0.029
## 2537 6.50 0.230 0.25 17.30 0.046
## 2538 5.90 0.280 0.14 8.60 0.032
## 2539 5.90 0.280 0.14 8.60 0.032
## 2540 6.20 0.270 0.18 1.50 0.028
## 2541 9.00 0.290 0.34 12.10 0.030
## 2542 9.00 0.260 0.34 6.70 0.029
## 2543 8.90 0.270 0.34 10.70 0.029
## 2544 6.50 0.230 0.25 17.30 0.046
## 2545 6.90 0.320 0.30 1.80 0.036
## 2546 7.20 0.220 0.24 1.40 0.041
## 2547 6.70 0.500 0.38 7.50 0.046
## 2548 6.20 0.330 0.14 4.80 0.052
## 2549 6.30 0.260 0.42 7.10 0.045
## 2550 7.50 0.200 0.47 16.90 0.052
## 2551 6.20 0.330 0.14 4.80 0.052
## 2552 6.30 0.260 0.42 7.10 0.045
## 2553 6.60 0.360 0.52 11.30 0.046
## 2554 6.30 0.130 0.42 1.10 0.043
## 2555 6.40 0.150 0.44 1.20 0.043
## 2556 6.30 0.130 0.42 1.10 0.043
## 2557 7.60 0.230 0.64 12.90 0.033
## 2558 6.40 0.150 0.44 1.20 0.043
## 2559 6.30 0.130 0.42 1.10 0.043
## 2561 6.90 0.320 0.26 2.30 0.030
## 2562 6.90 0.280 0.22 10.00 0.052
## 2563 6.90 0.320 0.26 2.30 0.030
## 2565 6.60 0.410 0.16 1.40 0.037
## 2566 7.30 0.370 0.16 14.90 0.048
## 2567 6.90 0.210 0.24 1.80 0.021
## 2568 6.60 0.240 0.28 1.80 0.028
## 2569 6.80 0.280 0.36 7.00 0.043
## 2570 6.60 0.240 0.24 8.60 0.034
## 2571 6.60 0.240 0.28 1.80 0.028
## 2572 7.00 0.160 0.32 1.10 0.032
## 2573 7.00 0.140 0.28 1.30 0.026
## 2574 6.30 0.340 0.36 4.90 0.035
## 2575 6.80 0.260 0.24 1.90 0.043
## 2576 6.70 0.170 0.42 10.40 0.038
## 2577 6.50 0.270 0.40 10.00 0.039
## 2578 6.70 0.250 0.36 8.60 0.037
## 2579 5.80 0.300 0.27 1.70 0.014
## 2581 7.70 0.300 0.26 18.95 0.053
## 2582 6.80 0.180 0.30 12.80 0.062
## 2583 6.80 0.180 0.30 12.80 0.062
## 2584 6.80 0.180 0.30 12.80 0.062
## 2585 6.80 0.180 0.30 12.80 0.062
## 2586 6.80 0.180 0.30 12.80 0.062
## 2587 6.80 0.180 0.30 12.80 0.062
## 2588 5.10 0.140 0.25 0.70 0.039
## 2589 6.80 0.180 0.30 12.80 0.062
## 2590 7.20 0.615 0.10 1.40 0.068
## 2591 6.90 0.130 0.28 13.30 0.050
## 2592 6.70 0.340 0.30 8.50 0.059
## 2593 7.30 0.320 0.29 1.50 0.038
## 2594 6.30 0.210 0.29 11.70 0.048
## 2596 8.20 0.520 0.34 1.20 0.042
## 2597 7.80 0.280 0.31 2.10 0.046
## 2598 6.40 0.220 0.34 1.40 0.023
## 2599 7.80 0.280 0.31 2.10 0.046
## 2600 6.90 0.320 0.27 16.00 0.034
## 2601 6.80 0.110 0.42 1.10 0.042
## 2602 6.20 0.260 0.32 15.30 0.031
## 2603 6.40 0.220 0.34 1.40 0.023
## 2604 6.70 0.300 0.29 2.80 0.025
## 2605 6.70 0.300 0.29 2.80 0.025
## 2606 7.10 0.200 0.30 0.90 0.019
## 2607 7.20 0.200 0.36 2.50 0.028
## 2608 8.90 0.260 0.33 8.10 0.024
## 2609 7.50 0.250 0.32 8.20 0.024
## 2610 7.10 0.200 0.30 0.90 0.019
## 2611 6.30 0.270 0.46 11.10 0.053
## 2612 6.50 0.300 0.39 7.80 0.038
## 2613 6.70 0.300 0.29 2.80 0.025
## 2614 6.60 0.360 0.52 10.10 0.050
## 2615 6.15 0.210 0.37 3.20 0.021
## 2616 6.50 0.180 0.41 14.20 0.039
## 2617 6.50 0.180 0.41 14.20 0.039
## 2618 6.50 0.180 0.41 14.20 0.039
## 2619 6.60 0.260 0.21 2.90 0.026
## 2620 6.60 0.350 0.35 6.00 0.063
## 2621 6.50 0.280 0.28 20.40 0.041
## 2622 6.60 0.360 0.52 10.10 0.050
## 2623 6.60 0.260 0.21 2.90 0.026
## 2624 6.50 0.180 0.41 14.20 0.039
## 2625 6.15 0.210 0.37 3.20 0.021
## 2627 8.00 0.240 0.26 1.70 0.033
## 2628 7.80 0.170 0.23 1.70 0.029
## 2629 7.00 0.240 0.24 9.00 0.030
## 2631 5.90 0.445 0.26 1.40 0.027
## 2632 6.70 0.280 0.28 2.40 0.012
## 2633 6.80 0.440 0.20 16.00 0.065
## 2634 7.20 0.240 0.27 11.40 0.034
## 2636 8.20 0.320 0.26 2.10 0.062
## 2637 7.20 0.240 0.27 11.40 0.034
## 2639 7.50 0.130 0.38 1.10 0.023
## 2640 9.20 0.140 0.37 1.10 0.034
## 2641 7.40 0.200 0.37 1.20 0.028
## 2642 6.10 0.150 0.35 15.80 0.042
## 2643 7.60 0.230 0.40 5.20 0.066
## 2644 8.10 0.330 0.22 5.20 0.047
## 2645 7.15 0.170 0.24 9.60 0.119
## 2646 6.70 0.120 0.30 5.20 0.048
## 2648 5.80 0.150 0.28 0.80 0.037
## 2649 6.60 0.230 0.29 14.45 0.057
## 2650 7.15 0.170 0.24 9.60 0.119
## 2651 7.00 0.340 0.39 6.90 0.066
## 2652 6.40 0.680 0.26 3.40 0.069
## 2653 7.30 0.220 0.31 2.30 0.018
## 2654 6.40 0.280 0.27 11.00 0.042
## 2656 6.80 0.190 0.23 5.10 0.034
## 2657 7.10 0.230 0.24 5.40 0.039
## 2658 6.45 0.140 0.42 1.20 0.050
## 2659 6.50 0.150 0.44 12.60 0.052
## 2660 7.10 0.150 0.34 1.00 0.033
## 2661 6.70 0.330 0.34 6.60 0.067
## 2662 7.20 0.300 0.26 1.50 0.041
## 2663 7.00 0.230 0.33 1.00 0.043
## 2664 8.00 0.130 0.25 1.10 0.033
## 2665 6.20 0.210 0.34 6.60 0.030
## 2666 8.30 0.400 0.41 8.20 0.050
## 2667 5.90 0.340 0.31 2.00 0.030
## 2668 6.60 0.120 0.25 1.40 0.039
## 2670 6.80 0.260 0.40 7.50 0.046
## 2671 5.90 0.340 0.31 2.00 0.030
## 2672 5.90 0.300 0.30 2.00 0.030
## 2673 7.00 0.150 0.30 13.30 0.049
## 2674 7.90 0.370 0.31 2.85 0.037
## 2675 7.20 0.350 0.25 5.60 0.032
## 2676 7.20 0.320 0.24 5.60 0.033
## 2677 7.60 0.100 0.33 1.00 0.031
## 2678 6.20 0.250 0.31 3.20 0.030
## 2679 7.10 0.310 0.17 1.00 0.042
## 2680 7.60 0.180 0.28 7.10 0.041
## 2681 8.00 0.170 0.29 2.40 0.029
## 2682 7.20 0.190 0.27 11.20 0.061
## 2683 7.60 0.320 0.25 9.50 0.030
## 2684 7.10 0.310 0.17 1.00 0.042
## 2685 6.60 0.210 0.29 1.80 0.026
## 2686 7.00 0.160 0.36 2.60 0.029
## 2687 8.00 0.170 0.29 2.40 0.029
## 2688 6.60 0.240 0.38 8.00 0.042
## 2689 7.20 0.190 0.27 11.20 0.061
## 2690 7.60 0.180 0.28 7.10 0.041
## 2691 6.90 0.300 0.25 3.30 0.041
## 2692 6.20 0.280 0.27 10.30 0.030
## 2693 6.90 0.310 0.32 1.20 0.024
## 2694 6.70 0.230 0.25 1.60 0.036
## 2695 6.20 0.280 0.27 10.30 0.030
## 2696 5.70 0.230 0.28 9.65 0.025
## 2697 6.50 0.220 0.50 16.40 0.048
## 2698 7.00 0.180 0.37 1.50 0.043
## 2699 6.90 0.310 0.32 1.20 0.024
## 2700 6.90 0.300 0.25 3.30 0.041
## 2701 6.50 0.460 0.31 5.00 0.027
## 2702 6.50 0.230 0.36 16.30 0.038
## 2703 6.50 0.230 0.36 16.30 0.038
## 2704 6.50 0.230 0.36 16.30 0.038
## 2707 7.50 0.280 0.39 10.20 0.045
## 2708 6.50 0.230 0.36 16.30 0.038
## 2709 6.80 0.230 0.42 7.40 0.044
## 2710 7.80 0.250 0.34 13.70 0.044
## 2711 7.80 0.250 0.34 13.70 0.044
## 2713 6.40 0.210 0.44 7.40 0.045
## 2714 6.80 0.230 0.42 7.40 0.044
## 2715 6.80 0.240 0.37 7.45 0.043
## 2716 7.80 0.250 0.28 7.20 0.040
## 2717 7.80 0.250 0.34 13.70 0.044
## 2718 6.80 0.160 0.29 10.40 0.046
## 2719 5.20 0.280 0.29 1.10 0.028
## 2720 7.50 0.180 0.31 6.50 0.029
## 2721 7.50 0.260 0.30 4.60 0.027
## 2723 7.60 0.400 0.27 5.20 0.030
## 2724 7.50 0.260 0.25 1.70 0.038
## 2725 7.50 0.180 0.31 6.50 0.029
## 2726 6.90 0.230 0.32 16.40 0.045
## 2727 5.30 0.200 0.31 3.60 0.036
## 2728 6.50 0.170 0.31 1.50 0.041
## 2729 6.50 0.350 0.28 12.40 0.051
## 2730 6.50 0.290 0.31 1.70 0.035
## 2732 7.90 0.510 0.36 6.20 0.051
## 2733 7.90 0.510 0.34 2.60 0.049
## 2734 6.50 0.290 0.31 1.70 0.035
## 2735 7.10 0.290 0.28 9.30 0.048
## 2736 6.50 0.350 0.28 12.40 0.051
## 2737 6.50 0.170 0.31 1.50 0.041
## 2738 7.40 0.200 0.28 9.10 0.047
## 2739 6.90 0.615 0.42 12.00 0.067
## 2740 6.80 0.320 0.28 4.80 0.034
## 2741 6.30 0.200 0.19 12.30 0.048
## 2742 6.90 0.615 0.42 12.00 0.067
## 2743 8.00 0.230 0.28 2.70 0.048
## 2744 6.70 0.270 0.33 3.60 0.034
## 2745 6.70 0.270 0.33 3.60 0.034
## 2746 6.70 0.440 0.22 4.30 0.032
## 2747 7.00 0.340 0.30 1.80 0.045
## 2748 7.30 0.260 0.33 11.80 0.057
## 2750 7.30 0.260 0.33 11.80 0.057
## 2752 6.80 0.170 0.36 1.40 0.036
## 2753 7.10 0.430 0.30 6.60 0.025
## 2754 5.80 0.315 0.27 1.55 0.026
## 2755 5.90 0.170 0.28 0.70 0.027
## 2756 6.60 0.340 0.18 6.40 0.082
## 2757 8.60 0.330 0.34 11.80 0.059
## 2758 5.60 0.120 0.26 4.30 0.038
## 2759 5.80 0.130 0.26 5.10 0.039
## 2760 7.70 0.180 0.35 5.80 0.055
## 2761 7.70 0.160 0.36 5.90 0.054
## 2762 6.00 0.260 0.15 1.30 0.060
## 2763 7.30 0.320 0.35 1.40 0.050
## 2764 7.70 0.300 0.34 1.20 0.048
## 2765 7.90 0.160 0.30 7.40 0.050
## 2766 6.40 0.270 0.29 10.80 0.028
## 2767 6.90 0.160 0.37 1.80 0.034
## 2768 7.90 0.160 0.30 7.40 0.050
## 2769 7.70 0.300 0.34 1.20 0.048
## 2770 7.30 0.320 0.35 1.40 0.050
## 2771 6.40 0.440 0.44 14.40 0.048
## 2773 6.20 0.290 0.32 3.60 0.026
## 2774 7.60 0.390 0.32 3.60 0.035
## 2775 7.00 0.360 0.32 10.05 0.045
## 2776 7.00 0.360 0.32 10.05 0.045
## 2777 7.00 0.360 0.32 10.50 0.045
## 2778 7.60 0.200 0.36 1.90 0.043
## 2779 7.60 0.390 0.32 3.60 0.035
## 2780 6.70 0.200 0.37 1.65 0.025
## 2781 6.20 0.235 0.34 1.90 0.036
## 2783 7.10 0.200 0.31 6.85 0.053
## 2784 7.10 0.200 0.31 7.40 0.053
## 2785 7.10 0.200 0.31 7.40 0.053
## 2786 6.40 0.240 0.25 20.20 0.083
## 2787 8.00 0.300 0.36 11.00 0.034
## 2788 6.40 0.240 0.25 20.20 0.083
## 2789 6.90 0.400 0.42 6.20 0.066
## 2790 6.90 0.400 0.43 6.20 0.065
## 2791 7.10 0.200 0.31 6.85 0.053
## 2792 6.60 0.250 0.51 8.00 0.047
## 2793 6.80 0.260 0.44 8.20 0.046
## 2794 6.50 0.370 0.30 2.20 0.033
## 2795 6.80 0.350 0.53 10.10 0.053
## 2796 6.40 0.220 0.32 7.20 0.028
## 2797 6.50 0.370 0.30 2.20 0.033
## 2798 6.80 0.350 0.53 10.10 0.053
## 2799 6.90 0.310 0.32 1.60 0.036
## 2800 6.70 0.160 0.37 1.30 0.036
## 2801 6.60 0.250 0.51 8.00 0.047
## 2802 6.80 0.260 0.44 8.20 0.046
## 2803 5.60 0.150 0.31 5.30 0.038
## 2804 5.50 0.150 0.32 14.00 0.031
## 2805 6.40 0.220 0.32 7.20 0.028
## 2806 7.30 0.200 0.26 1.60 0.040
## 2807 7.50 0.170 0.71 11.80 0.038
## 2808 7.50 0.180 0.72 9.60 0.039
## 2809 7.00 0.270 0.48 6.10 0.042
## 2810 5.80 0.320 0.31 2.70 0.049
## 2811 7.80 0.260 0.31 3.60 0.025
## 2812 7.40 0.300 0.32 1.70 0.030
## 2813 6.70 0.160 0.34 1.60 0.026
## 2814 5.80 0.320 0.31 2.70 0.049
## 2815 6.70 0.190 0.39 1.00 0.032
## 2816 6.60 0.360 0.24 0.90 0.038
## 2817 7.20 0.170 0.41 1.60 0.052
## 2818 6.70 0.190 0.39 1.00 0.032
## 2820 6.00 0.210 0.34 2.00 0.042
## 2822 6.60 0.400 0.46 6.20 0.056
## 2823 6.50 0.200 0.24 9.20 0.044
## 2824 7.60 0.270 0.34 5.00 0.040
## 2825 7.20 0.260 0.40 6.30 0.047
## 2826 6.30 0.250 0.22 3.30 0.048
## 2827 6.50 0.220 0.45 8.00 0.053
## 2828 6.40 0.140 0.31 1.20 0.034
## 2829 6.40 0.140 0.31 1.20 0.034
## 2830 7.10 0.260 0.32 16.20 0.044
## 2831 6.60 0.220 0.34 11.60 0.050
## 2832 6.60 0.450 0.43 7.20 0.064
## 2833 6.60 0.170 0.30 1.10 0.031
## 2834 7.20 0.440 0.28 3.40 0.048
## 2835 6.20 0.150 0.27 1.40 0.041
## 2836 6.30 0.250 0.22 3.30 0.048
## 2837 6.50 0.220 0.45 8.00 0.053
## 2838 7.30 0.260 0.30 9.30 0.050
## 2839 6.90 0.150 0.29 2.30 0.033
## 2840 5.80 0.220 0.29 0.90 0.034
## 2841 6.50 0.370 0.33 3.50 0.036
## 2842 5.50 0.375 0.38 1.70 0.036
## 2843 5.90 0.200 0.40 1.30 0.047
## 2844 5.90 0.220 0.38 1.30 0.046
## 2845 8.00 0.220 0.31 5.60 0.049
## 2846 6.50 0.220 0.29 7.40 0.028
## 2847 6.90 0.150 0.29 2.30 0.033
## 2848 5.80 0.200 0.34 1.00 0.035
## 2849 6.60 0.310 0.07 1.50 0.033
## 2851 6.70 0.240 0.29 14.90 0.053
## 2852 7.30 0.230 0.34 9.30 0.052
## 2853 7.90 0.200 0.39 1.00 0.041
## 2854 5.30 0.160 0.39 1.00 0.028
## 2855 6.40 0.210 0.28 5.90 0.047
## 2856 6.90 0.330 0.26 5.00 0.027
## 2857 5.60 0.180 0.58 1.25 0.034
## 2858 6.60 0.290 0.31 3.90 0.027
## 2859 6.90 0.330 0.26 5.00 0.027
## 2860 6.60 0.210 0.36 0.80 0.034
## 2861 7.30 0.210 0.33 1.00 0.037
## 2862 6.40 0.210 0.28 5.90 0.047
## 2863 5.10 0.110 0.32 1.60 0.028
## 2864 6.50 0.150 0.32 1.30 0.036
## 2865 5.30 0.160 0.39 1.00 0.028
## 2866 5.60 0.190 0.46 1.10 0.032
## 2867 5.60 0.180 0.58 1.25 0.034
## 2868 6.70 0.480 0.32 1.40 0.021
## 2869 6.20 0.230 0.23 1.20 0.018
## 2870 6.00 0.170 0.29 5.00 0.028
## 2871 6.70 0.480 0.32 1.40 0.021
## 2872 6.70 0.150 0.38 1.70 0.037
## 2874 5.80 0.210 0.32 1.60 0.045
## 2876 6.70 0.150 0.38 1.70 0.037
## 2877 6.40 0.220 0.31 13.90 0.040
## 2879 5.90 0.320 0.33 2.10 0.027
## 2880 5.70 0.370 0.30 1.10 0.029
## 2881 7.90 0.250 0.35 6.70 0.039
## 2882 7.20 0.210 0.28 2.70 0.033
## 2883 7.00 0.240 0.30 6.70 0.039
## 2884 6.80 0.475 0.33 3.95 0.047
## 2885 7.00 0.280 0.32 7.75 0.032
## 2886 6.90 0.400 0.30 10.60 0.033
## 2887 6.60 0.410 0.31 1.60 0.042
## 2888 6.40 0.200 0.28 2.50 0.032
## 2889 8.50 0.220 0.34 0.70 0.040
## 2890 8.40 0.360 0.36 11.10 0.032
## 2891 5.20 0.285 0.29 5.15 0.035
## 2892 6.90 0.200 0.30 4.70 0.041
## 2893 6.70 0.420 0.46 9.70 0.054
## 2895 6.40 0.125 0.36 1.40 0.044
## 2896 6.40 0.440 0.26 2.00 0.054
## 2897 7.00 0.310 0.39 7.50 0.055
## 2898 6.70 0.420 0.46 9.70 0.054
## 2899 8.60 0.180 0.28 0.80 0.032
## 2900 6.20 0.210 0.26 13.10 0.050
## 2901 6.10 0.160 0.37 1.10 0.031
## 2902 6.50 0.220 0.32 2.20 0.028
## 2903 6.20 0.360 0.14 8.90 0.036
## 2904 5.70 0.210 0.25 1.10 0.035
## 2905 6.40 0.250 0.32 0.90 0.034
## 2906 7.60 0.310 0.26 1.70 0.073
## 2907 6.60 0.260 0.46 6.90 0.047
## 2908 5.70 0.210 0.25 1.10 0.035
## 2909 6.20 0.200 0.31 1.00 0.031
## 2910 6.20 0.180 0.30 1.00 0.031
## 2911 6.10 0.370 0.20 7.60 0.031
## 2912 6.20 0.360 0.14 8.90 0.036
## 2913 6.50 0.220 0.32 2.20 0.028
## 2914 7.70 0.180 0.30 1.20 0.046
## 2915 6.90 0.140 0.38 1.00 0.041
## 2916 6.90 0.140 0.38 1.00 0.041
## 2917 6.00 0.440 0.26 3.10 0.053
## 2918 7.10 0.360 0.40 1.95 0.033
## 2919 5.70 0.280 0.28 2.20 0.019
## 2920 6.40 0.160 0.32 8.75 0.038
## 2921 7.40 0.280 0.40 11.90 0.032
## 2922 6.70 0.390 0.31 2.70 0.054
## 2923 6.50 0.440 0.47 5.45 0.014
## 2924 6.90 0.220 0.31 6.30 0.029
## 2925 6.60 0.220 0.29 14.40 0.046
## 2926 7.70 0.250 0.30 7.80 0.038
## 2927 5.20 0.155 0.33 1.60 0.028
## 2928 7.00 0.310 0.31 9.10 0.036
## 2929 7.00 0.310 0.31 9.10 0.036
## 2930 6.60 0.220 0.29 14.40 0.046
## 2932 5.20 0.155 0.33 1.60 0.028
## 2933 6.40 0.250 0.32 11.30 0.038
## 2934 6.90 0.220 0.31 6.30 0.029
## 2935 5.30 0.210 0.29 0.70 0.028
## 2936 7.10 0.270 0.28 1.25 0.023
## 2937 5.20 0.170 0.27 0.70 0.030
## 2938 7.70 0.250 0.30 7.80 0.038
## 2939 7.00 0.120 0.29 10.30 0.039
## 2940 7.00 0.120 0.29 10.30 0.039
## 2941 7.10 0.290 0.34 7.80 0.036
## 2942 7.20 0.300 0.30 8.70 0.022
## 2943 6.80 0.260 0.46 8.30 0.037
## 2944 7.00 0.120 0.29 10.30 0.039
## 2945 7.10 0.290 0.34 7.80 0.036
## 2946 4.90 0.330 0.31 1.20 0.016
## 2947 5.10 0.290 0.28 8.30 0.026
## 2948 5.10 0.290 0.28 8.30 0.026
## 2949 6.80 0.260 0.48 6.20 0.049
## 2950 6.00 0.280 0.52 5.00 0.078
## 2951 6.00 0.280 0.25 1.80 0.042
## 2952 7.20 0.200 0.22 1.60 0.044
## 2953 6.10 0.270 0.25 1.80 0.041
## 2954 6.00 0.280 0.25 1.80 0.042
## 2955 6.40 0.290 0.30 2.90 0.036
## 2956 7.40 0.350 0.24 6.00 0.042
## 2957 8.10 0.120 0.38 0.90 0.034
## 2958 6.40 0.120 0.30 1.10 0.031
## 2959 7.20 0.200 0.22 1.60 0.044
## 2960 7.30 0.400 0.26 5.45 0.016
## 2961 7.70 0.110 0.34 14.05 0.040
## 2962 6.90 0.230 0.41 8.00 0.030
## 2963 6.90 0.380 0.38 13.10 0.112
## 2964 7.50 0.380 0.29 4.90 0.021
## 2965 5.80 0.190 0.24 1.30 0.044
## 2966 5.50 0.340 0.26 2.20 0.021
## 2967 6.60 0.230 0.30 14.90 0.051
## 2968 6.60 0.230 0.30 14.90 0.051
## 2969 8.40 0.310 0.31 0.95 0.021
## 2970 6.70 0.200 0.30 1.40 0.025
## 2971 8.40 0.310 0.31 0.95 0.021
## 2972 7.30 0.260 0.24 1.70 0.050
## 2973 6.30 0.220 0.22 5.60 0.039
## 2974 6.60 0.230 0.30 14.90 0.051
## 2975 7.50 0.190 0.40 7.10 0.056
## 2976 8.00 0.140 0.33 1.20 0.045
## 2977 6.80 0.320 0.39 9.60 0.026
## 2978 6.60 0.230 0.20 11.40 0.044
## 2979 6.60 0.230 0.20 11.40 0.044
## 2980 6.70 0.360 0.26 7.90 0.034
## 2981 6.10 0.380 0.42 5.00 0.016
## 2982 8.50 0.230 0.28 11.10 0.033
## 2983 7.00 0.200 0.31 8.00 0.050
## 2984 6.00 0.260 0.32 3.80 0.029
## 2985 6.90 0.300 0.30 10.55 0.037
## 2986 6.70 0.180 0.28 10.20 0.039
## 2987 6.70 0.180 0.28 10.20 0.039
## 2988 6.80 0.180 0.28 9.80 0.039
## 2989 7.20 0.190 0.31 6.30 0.034
## 2990 6.20 0.160 0.32 1.10 0.036
## 2991 5.00 0.270 0.32 4.50 0.032
## 2992 6.30 0.370 0.28 6.30 0.034
## 2993 6.60 0.200 0.27 10.90 0.038
## 2994 6.80 0.180 0.28 9.80 0.039
## 2995 6.80 0.180 0.28 9.80 0.039
## 2996 6.60 0.280 0.34 0.80 0.037
## 2997 6.50 0.350 0.36 0.80 0.034
## 2998 6.90 0.250 0.33 1.20 0.035
## 2999 6.00 0.320 0.30 1.30 0.025
## 3000 6.80 0.180 0.28 9.80 0.039
## 3001 6.70 0.180 0.28 10.20 0.039
## 3002 6.60 0.200 0.27 10.90 0.038
## 3003 6.30 0.370 0.28 6.30 0.034
## 3004 7.20 0.190 0.31 6.30 0.034
## 3005 6.30 0.180 0.36 1.20 0.034
## 3006 6.90 0.300 0.36 0.90 0.037
## 3007 6.20 0.160 0.32 1.10 0.036
## 3008 5.00 0.270 0.32 4.50 0.032
## 3009 5.00 0.300 0.33 3.70 0.030
## 3010 6.50 0.200 0.50 18.10 0.054
## 3011 6.70 0.250 0.31 1.35 0.061
## 3012 6.60 0.220 0.36 5.50 0.029
## 3013 6.80 0.250 0.37 3.10 0.026
## 3014 7.00 0.130 0.37 12.85 0.042
## 3016 7.20 0.320 0.30 8.25 0.020
## 3017 7.00 0.130 0.37 12.85 0.042
## 3018 5.90 0.340 0.30 3.80 0.035
## 3019 6.80 0.220 0.31 6.90 0.037
## 3020 7.20 0.320 0.30 8.25 0.020
## 3021 8.40 0.320 0.35 11.70 0.029
## 3022 6.80 0.270 0.29 4.60 0.046
## 3023 8.00 0.740 0.21 4.00 0.050
## 3025 7.00 0.130 0.37 12.85 0.042
## 3027 8.40 0.220 0.30 8.90 0.024
## 3028 7.40 0.320 0.22 11.70 0.035
## 3029 7.50 0.180 0.37 6.20 0.050
## 3030 7.10 0.470 0.29 14.80 0.024
## 3031 7.10 0.470 0.29 14.80 0.024
## 3032 5.80 0.190 0.25 10.80 0.042
## 3033 6.70 0.140 0.46 1.60 0.036
## 3034 6.80 0.240 0.38 8.30 0.045
## 3035 6.90 0.250 0.47 8.40 0.042
## 3036 6.00 0.240 0.33 2.50 0.026
## 3037 6.80 0.290 0.34 3.50 0.054
## 3038 6.30 0.330 0.42 17.20 0.037
## 3039 6.50 0.230 0.45 2.10 0.027
## 3040 6.30 0.270 0.29 12.20 0.044
## 3041 6.30 0.200 0.37 11.80 0.045
## 3042 6.20 0.330 0.41 16.80 0.037
## 3043 6.30 0.330 0.42 17.20 0.037
## 3045 6.00 0.270 0.30 14.70 0.044
## 3046 5.70 0.120 0.26 5.50 0.034
## 3047 6.90 0.240 0.37 6.10 0.027
## 3048 7.70 0.180 0.53 1.20 0.041
## 3049 7.10 0.170 0.43 1.30 0.023
## 3050 7.50 0.330 0.38 8.70 0.126
## 3052 7.50 0.330 0.38 8.70 0.126
## 3054 7.60 0.170 0.36 4.50 0.042
## 3055 5.80 0.150 0.31 5.90 0.036
## 3056 6.30 0.250 0.44 1.70 0.024
## 3057 6.90 0.280 0.41 1.40 0.016
## 3058 7.20 0.270 0.37 5.40 0.026
## 3059 6.20 0.250 0.38 7.90 0.045
## 3060 8.50 0.190 0.48 1.10 0.026
## 3061 6.20 0.250 0.54 7.00 0.046
## 3062 6.20 0.250 0.54 7.00 0.046
## 3063 6.80 0.280 0.43 7.60 0.030
## 3064 6.20 0.250 0.54 7.00 0.046
## 3066 7.00 0.150 0.38 15.30 0.045
## 3068 7.30 0.280 0.42 1.20 0.033
## 3069 6.10 0.180 0.38 2.30 0.033
## 3070 7.00 0.530 0.43 6.10 0.029
## 3071 6.80 0.280 0.43 7.60 0.030
## 3072 6.50 0.360 0.38 10.20 0.028
## 3074 6.70 0.240 0.41 2.90 0.039
## 3075 6.60 0.250 0.33 8.50 0.042
## 3076 6.40 0.150 0.40 1.50 0.042
## 3077 6.30 0.280 0.30 3.10 0.039
## 3078 6.20 0.250 0.38 7.90 0.045
## 3079 7.10 0.280 0.35 3.50 0.028
## 3080 6.60 0.350 0.34 4.90 0.032
## 3081 8.50 0.190 0.48 1.10 0.026
## 3082 6.20 0.250 0.54 7.00 0.046
## 3083 6.00 0.350 0.51 1.20 0.029
## 3084 5.80 0.310 0.32 4.50 0.024
## 3085 6.60 0.170 0.35 2.60 0.030
## 3086 8.50 0.230 0.40 9.90 0.036
## 3087 5.80 0.310 0.32 4.50 0.024
## 3088 6.10 0.200 0.34 9.50 0.041
## 3089 6.30 0.370 0.37 1.50 0.024
## 3090 6.20 0.360 0.38 3.20 0.031
## 3091 6.60 0.170 0.35 2.60 0.030
## 3092 6.30 0.280 0.47 11.20 0.040
## 3093 7.60 0.270 0.52 3.20 0.043
## 3094 7.00 0.250 0.45 2.30 0.045
## 3097 6.80 0.130 0.39 1.40 0.034
## 3099 5.10 0.330 0.27 6.70 0.022
## 3100 6.70 0.340 0.40 2.10 0.033
## 3101 6.70 0.140 0.51 4.30 0.028
## 3102 7.00 0.260 0.34 10.90 0.038
## 3103 6.50 0.290 0.26 7.00 0.040
## 3104 7.00 0.250 0.45 2.30 0.045
## 3105 7.60 0.210 0.49 2.50 0.047
## 3106 7.70 0.260 0.51 2.60 0.045
## 3107 7.60 0.270 0.52 3.20 0.043
## 3108 7.70 0.250 0.49 2.50 0.047
## 3109 7.60 0.350 0.46 14.70 0.047
## 3110 6.90 0.300 0.36 4.50 0.054
## 3111 6.70 0.240 0.46 2.20 0.033
## 3112 6.50 0.230 0.39 1.90 0.036
## 3113 7.60 0.230 0.34 1.60 0.043
## 3114 6.50 0.240 0.39 17.30 0.052
## 3115 6.30 0.170 0.32 4.20 0.040
## 3116 6.30 0.170 0.32 4.20 0.040
## 3117 6.70 0.210 0.37 2.50 0.034
## 3118 6.50 0.230 0.39 1.90 0.036
## 3119 5.90 0.280 0.39 1.40 0.031
## 3120 5.90 0.190 0.37 0.80 0.027
## 3121 6.20 0.250 0.42 8.00 0.049
## 3122 7.60 0.230 0.34 1.60 0.043
## 3123 5.60 0.180 0.27 1.70 0.030
## 3124 5.50 0.180 0.22 5.50 0.037
## 3125 6.50 0.240 0.39 17.30 0.052
## 3126 7.40 0.230 0.38 8.60 0.052
## 3127 7.20 0.170 0.37 6.90 0.059
## 3128 7.60 0.300 0.38 2.10 0.043
## 3129 5.00 0.240 0.21 2.20 0.039
## 3130 6.10 0.210 0.38 1.50 0.039
## 3131 6.50 0.330 0.38 2.50 0.047
## 3132 6.30 0.350 0.26 17.60 0.061
## 3133 6.30 0.170 0.32 4.20 0.040
## 3134 6.60 0.250 0.35 2.90 0.034
## 3135 6.50 0.160 0.33 4.80 0.043
## 3136 6.60 0.390 0.39 11.90 0.057
## 3137 5.60 0.190 0.27 0.90 0.040
## 3138 6.20 0.250 0.39 1.30 0.051
## 3139 6.90 0.220 0.43 6.40 0.042
## 3140 6.20 0.190 0.29 4.30 0.045
## 3141 6.60 0.390 0.39 11.90 0.057
## 3142 5.90 0.330 0.32 8.10 0.038
## 3143 7.80 0.170 0.50 1.30 0.045
## 3144 5.50 0.190 0.27 0.90 0.040
## 3145 6.20 0.230 0.36 17.20 0.039
## 3146 6.20 0.230 0.36 17.20 0.039
## 3147 6.20 0.230 0.36 17.20 0.039
## 3148 7.20 0.320 0.40 8.70 0.038
## 3149 6.20 0.230 0.36 17.20 0.039
## 3150 7.20 0.320 0.40 8.70 0.038
## 3151 5.80 0.390 0.47 7.50 0.027
## 3152 6.20 0.230 0.36 17.20 0.039
## 3154 5.80 0.290 0.33 3.70 0.029
## 3155 7.20 0.400 0.38 2.20 0.030
## 3156 6.80 0.390 0.34 7.40 0.020
## 3157 6.10 0.170 0.42 15.10 0.033
## 3158 6.80 0.390 0.34 7.40 0.020
## 3159 7.10 0.360 0.37 4.80 0.019
## 3160 6.90 0.190 0.32 7.90 0.042
## 3161 6.50 0.340 0.46 1.00 0.023
## 3162 6.10 0.170 0.42 15.10 0.033
## 3163 6.80 0.390 0.34 7.40 0.020
## 3164 7.10 0.360 0.37 4.80 0.019
## 3165 7.80 0.300 0.36 4.60 0.024
## 3167 5.20 0.340 0.37 6.20 0.031
## 3168 5.60 0.280 0.40 6.10 0.034
## 3169 6.20 0.190 0.38 5.10 0.019
## 3170 5.70 0.160 0.26 6.30 0.043
## 3171 7.60 0.170 0.46 0.90 0.036
## 3172 7.30 0.200 0.39 2.30 0.048
## 3173 6.70 0.330 0.36 6.60 0.042
## 3174 6.70 0.330 0.34 7.50 0.036
## 3175 6.90 0.360 0.35 8.60 0.038
## 3176 7.80 0.210 0.34 11.90 0.039
## 3177 7.30 0.200 0.39 2.30 0.048
## 3178 5.60 0.410 0.22 7.10 0.050
## 3179 7.60 0.150 0.35 4.30 0.051
## 3180 8.50 0.200 0.40 1.10 0.046
## 3181 6.50 0.240 0.38 1.00 0.027
## 3182 8.30 0.160 0.37 7.90 0.025
## 3183 5.50 0.120 0.33 1.00 0.038
## 3184 6.50 0.240 0.38 1.00 0.027
## 3185 6.20 0.100 0.41 1.00 0.040
## 3186 6.50 0.210 0.40 7.30 0.041
## 3187 8.70 0.300 0.59 1.70 0.046
## 3188 6.70 0.180 0.37 1.30 0.027
## 3189 7.00 0.170 0.36 6.40 0.055
## 3190 6.60 0.190 0.33 1.80 0.035
## 3191 5.80 0.280 0.30 1.50 0.026
## 3192 7.60 0.240 0.44 3.80 0.037
## 3193 8.30 0.160 0.37 7.90 0.025
## 3194 5.50 0.120 0.33 1.00 0.038
## 3195 5.70 0.160 0.32 1.20 0.036
## 3196 7.00 0.210 0.42 5.30 0.037
## 3197 6.40 0.220 0.38 9.10 0.044
## 3198 7.90 0.340 0.44 6.50 0.027
## 3199 6.40 0.220 0.38 9.10 0.044
## 3200 6.80 0.210 0.40 6.30 0.032
## 3201 5.20 0.310 0.36 5.10 0.031
## 3202 7.90 0.340 0.44 6.50 0.027
## 3203 5.60 0.420 0.34 2.40 0.022
## 3204 6.40 0.220 0.38 9.10 0.044
## 3205 6.80 0.280 0.34 7.50 0.035
## 3206 6.80 0.450 0.36 5.00 0.033
## 3207 6.60 0.290 0.39 6.75 0.031
## 3208 6.80 0.210 0.42 1.20 0.045
## 3209 6.80 0.250 0.24 1.60 0.045
## 3210 6.40 0.210 0.34 16.05 0.040
## 3211 5.80 0.330 0.23 5.00 0.053
## 3212 8.20 0.300 0.44 12.40 0.043
## 3213 6.40 0.240 0.32 0.95 0.041
## 3214 7.50 0.180 0.45 4.60 0.041
## 3215 5.20 0.335 0.20 1.70 0.033
## 3216 7.10 0.140 0.33 1.00 0.104
## 3217 7.20 0.130 0.46 1.30 0.044
## 3218 5.80 0.330 0.23 5.00 0.053
## 3219 6.50 0.290 0.25 2.50 0.142
## 3220 6.20 0.350 0.31 2.60 0.036
## 3221 9.00 0.380 0.53 2.10 0.102
## 3222 6.60 0.240 0.38 12.75 0.034
## 3223 6.60 0.160 0.34 1.10 0.037
## 3224 8.20 0.300 0.44 12.40 0.043
## 3225 5.70 0.150 0.28 3.70 0.045
## 3226 6.60 0.330 0.40 2.65 0.041
## 3227 5.70 0.200 0.30 2.50 0.046
## 3228 6.80 0.270 0.37 8.20 0.055
## 3229 6.80 0.270 0.42 7.30 0.054
## 3230 6.20 0.200 0.26 1.10 0.047
## 3231 6.70 0.130 0.57 6.60 0.056
## 3232 6.80 0.210 0.37 7.00 0.038
## 3233 6.70 0.310 0.32 14.50 0.038
## 3234 6.20 0.200 0.29 11.80 0.035
## 3235 6.60 0.250 0.34 3.00 0.054
## 3236 5.70 0.150 0.28 3.70 0.045
## 3237 6.90 0.220 0.39 6.00 0.035
## 3238 6.40 0.230 0.35 4.60 0.039
## 3239 7.60 0.270 0.29 2.50 0.059
## 3240 6.60 0.340 0.24 3.30 0.034
## 3241 6.40 0.160 0.42 1.00 0.036
## 3242 5.80 0.300 0.42 1.10 0.036
## 3243 7.00 0.290 0.35 1.40 0.036
## 3244 6.60 0.340 0.24 3.30 0.034
## 3245 6.70 0.210 0.36 8.55 0.020
## 3246 7.60 0.270 0.29 2.50 0.059
## 3247 6.80 0.220 0.41 6.70 0.034
## 3248 7.70 0.270 0.49 3.80 0.037
## 3249 6.40 0.250 0.37 4.50 0.039
## 3250 6.40 0.230 0.35 4.60 0.039
## 3251 6.70 0.130 0.45 4.20 0.043
## 3252 6.70 0.240 0.37 11.30 0.043
## 3253 7.10 0.260 0.37 5.50 0.025
## 3254 5.30 0.300 0.16 4.20 0.029
## 3255 7.10 0.380 0.40 2.20 0.042
## 3256 7.40 0.190 0.31 14.50 0.045
## 3257 7.40 0.190 0.31 14.50 0.045
## 3258 7.40 0.190 0.31 14.50 0.045
## 3259 7.40 0.190 0.31 14.50 0.045
## 3260 7.40 0.190 0.31 14.50 0.045
## 3261 7.40 0.190 0.31 14.50 0.045
## 3262 6.30 0.320 0.32 1.50 0.030
## 3263 7.60 0.190 0.32 18.75 0.047
## 3264 6.50 0.260 0.31 3.60 0.030
## 3265 5.90 0.240 0.12 1.40 0.035
## 3267 8.10 0.240 0.32 10.50 0.030
## 3268 5.80 0.230 0.20 2.00 0.043
## 3269 7.50 0.330 0.36 2.60 0.051
## 3270 6.60 0.380 0.36 9.20 0.061
## 3271 6.40 0.150 0.29 1.80 0.044
## 3272 6.50 0.320 0.34 5.70 0.044
## 3273 7.50 0.220 0.32 2.40 0.045
## 3274 6.40 0.230 0.32 1.90 0.038
## 3275 6.10 0.220 0.31 1.40 0.039
## 3276 6.50 0.480 0.02 0.90 0.043
## 3277 6.60 0.230 0.30 4.60 0.060
## 3278 6.40 0.160 0.25 1.40 0.057
## 3279 6.60 0.380 0.36 9.20 0.061
## 3280 7.40 0.160 0.32 1.40 0.065
## 3281 6.40 0.150 0.29 1.80 0.044
## 3282 6.50 0.320 0.30 2.30 0.051
## 3283 6.70 0.120 0.36 2.30 0.039
## 3285 8.00 0.340 0.25 6.40 0.035
## 3286 6.80 0.210 0.31 2.90 0.046
## 3287 6.80 0.230 0.31 2.80 0.047
## 3288 6.80 0.210 0.31 2.90 0.046
## 3290 6.60 0.280 0.42 8.20 0.044
## 3291 7.80 0.250 0.37 1.00 0.043
## 3292 5.60 0.120 0.33 2.90 0.044
## 3293 6.60 0.280 0.41 7.00 0.046
## 3294 6.80 0.170 0.35 1.80 0.040
## 3295 7.30 0.250 0.28 1.50 0.043
## 3296 6.60 0.280 0.41 7.00 0.046
## 3297 6.60 0.280 0.42 8.20 0.044
## 3298 6.50 0.250 0.50 7.60 0.047
## 3299 6.30 0.240 0.35 2.30 0.039
## 3300 6.80 0.320 0.32 8.70 0.029
## 3301 7.80 0.250 0.37 1.00 0.043
## 3302 5.60 0.120 0.33 2.90 0.044
## 3303 6.60 0.240 0.28 6.70 0.032
## 3304 6.30 0.220 0.34 5.00 0.032
## 3305 6.00 0.320 0.30 1.90 0.033
## 3306 6.30 0.190 0.29 2.00 0.022
## 3307 6.00 0.320 0.30 1.90 0.033
## 3309 6.40 0.350 0.28 12.60 0.039
## 3310 6.70 0.460 0.27 5.20 0.039
## 3311 6.30 0.300 0.29 2.10 0.048
## 3312 6.00 0.190 0.29 1.10 0.047
## 3313 5.90 0.240 0.28 1.30 0.032
## 3314 7.30 0.145 0.33 1.10 0.042
## 3315 6.60 0.435 0.38 9.20 0.058
## 3316 5.80 0.180 0.37 1.20 0.036
## 3317 5.80 0.180 0.37 1.10 0.036
## 3318 5.60 0.320 0.32 8.30 0.043
## 3319 6.60 0.160 0.35 1.80 0.042
## 3320 5.10 0.210 0.28 1.40 0.047
## 3321 7.50 0.290 0.36 15.70 0.050
## 3322 6.00 0.260 0.33 4.35 0.040
## 3323 5.70 0.260 0.30 1.80 0.039
## 3324 7.10 0.170 0.31 1.60 0.037
## 3325 6.90 0.170 0.30 2.00 0.047
## 3326 6.80 0.250 0.28 5.00 0.035
## 3327 6.60 0.170 0.28 1.80 0.042
## 3328 5.80 0.170 0.36 1.30 0.036
## 3329 6.40 0.240 0.29 1.00 0.038
## 3330 6.70 0.210 0.34 1.40 0.049
## 3331 6.70 0.230 0.33 8.10 0.048
## 3332 6.80 0.230 0.32 8.60 0.046
## 3333 6.50 0.220 0.28 3.70 0.059
## 3334 5.10 0.165 0.22 5.70 0.047
## 3335 6.60 0.425 0.25 2.35 0.034
## 3336 6.90 0.380 0.29 13.65 0.048
## 3337 6.90 0.380 0.29 13.65 0.048
## 3338 6.90 0.380 0.29 13.65 0.048
## 3339 7.20 0.270 0.28 15.20 0.046
## 3340 7.60 0.170 0.27 4.60 0.050
## 3341 6.20 0.300 0.31 1.20 0.048
## 3342 7.60 0.170 0.27 4.60 0.050
## 3343 6.50 0.260 0.32 6.65 0.059
## 3344 6.90 0.360 0.28 13.55 0.048
## 3345 6.90 0.380 0.29 13.65 0.048
## 3346 6.80 0.180 0.24 9.80 0.058
## 3347 6.70 0.180 0.24 10.30 0.057
## 3348 6.60 0.160 0.21 6.70 0.055
## 3349 7.20 0.270 0.28 15.20 0.046
## 3350 6.40 0.170 0.27 9.90 0.047
## 3351 7.20 0.220 0.28 7.20 0.060
## 3352 6.00 0.220 0.28 1.10 0.034
## 3353 6.70 0.360 0.28 8.30 0.034
## 3354 6.50 0.430 0.28 11.25 0.032
## 3355 5.90 0.200 0.28 12.80 0.038
## 3356 5.30 0.320 0.23 9.65 0.026
## 3357 6.80 0.200 0.28 12.60 0.048
## 3358 6.00 0.220 0.33 12.20 0.033
## 3359 6.70 0.360 0.28 8.30 0.034
## 3360 6.50 0.430 0.28 11.25 0.032
## 3361 7.10 0.180 0.49 1.30 0.033
## 3362 6.40 0.170 0.27 9.90 0.047
## 3363 7.20 0.220 0.28 7.20 0.060
## 3364 6.00 0.220 0.28 1.10 0.034
## 3365 6.00 0.200 0.26 1.10 0.033
## 3366 7.60 0.200 0.26 4.80 0.033
## 3367 6.20 0.300 0.21 1.10 0.032
## 3368 6.00 0.290 0.25 1.40 0.033
## 3369 6.60 0.180 0.28 1.70 0.041
## 3370 7.00 0.220 0.28 10.60 0.039
## 3371 6.00 0.290 0.25 1.40 0.033
## 3372 6.20 0.300 0.21 1.10 0.032
## 3373 5.60 0.150 0.26 5.55 0.051
## 3374 6.90 0.280 0.24 2.10 0.034
## 3375 5.90 0.190 0.21 1.70 0.045
## 3376 7.80 0.220 0.26 9.00 0.047
## 3377 6.60 0.180 0.28 1.70 0.041
## 3378 7.00 0.400 0.25 1.80 0.050
## 3379 6.10 0.280 0.27 4.70 0.030
## 3380 7.60 0.360 0.49 11.30 0.046
## 3381 6.50 0.280 0.34 3.60 0.040
## 3382 6.90 0.190 0.35 6.90 0.045
## 3383 6.50 0.280 0.34 3.60 0.040
## 3384 6.40 0.220 0.32 4.90 0.046
## 3385 6.80 0.230 0.30 6.95 0.044
## 3386 6.40 0.320 0.31 1.90 0.037
## 3387 6.10 0.280 0.27 4.70 0.030
## 3388 7.60 0.360 0.49 11.30 0.046
## 3389 8.80 0.390 0.35 1.80 0.096
## 3390 6.60 0.240 0.30 11.30 0.026
## 3391 6.90 0.290 0.30 8.20 0.026
## 3392 6.90 0.280 0.30 8.30 0.026
## 3393 6.70 0.380 0.26 9.55 0.036
## 3394 8.00 0.280 0.30 8.40 0.030
## 3395 6.50 0.250 0.45 7.80 0.048
## 3396 6.60 0.260 0.46 7.80 0.047
## 3397 7.40 0.290 0.28 10.20 0.032
## 3398 6.30 0.190 0.29 5.50 0.042
## 3399 6.10 0.330 0.32 7.80 0.052
## 3400 5.60 0.320 0.33 7.40 0.037
## 3401 7.70 0.460 0.18 3.30 0.054
## 3402 8.80 0.190 0.30 5.00 0.028
## 3403 7.70 0.460 0.18 3.30 0.054
## 3404 8.80 0.270 0.25 5.00 0.024
## 3405 5.80 0.180 0.28 1.30 0.034
## 3406 5.80 0.150 0.32 1.20 0.037
## 3407 5.60 0.320 0.33 7.40 0.037
## 3408 6.10 0.330 0.32 7.80 0.052
## 3409 7.10 0.320 0.30 9.90 0.041
## 3410 6.20 0.230 0.35 0.70 0.051
## 3411 8.90 0.300 0.35 4.60 0.032
## 3412 6.00 0.140 0.17 5.60 0.036
## 3413 6.80 0.240 0.29 9.50 0.042
## 3414 6.70 0.210 0.48 14.80 0.050
## 3415 8.90 0.300 0.35 4.60 0.032
## 3416 6.10 0.300 0.30 2.10 0.031
## 3417 7.20 0.370 0.40 11.60 0.032
## 3418 6.70 0.640 0.30 1.20 0.030
## 3419 7.20 0.370 0.40 11.60 0.032
## 3420 6.10 0.300 0.30 2.10 0.031
## 3421 7.60 0.280 0.49 20.15 0.060
## 3422 6.30 0.290 0.28 4.70 0.059
## 3423 6.20 0.280 0.28 4.30 0.026
## 3424 7.10 0.180 0.39 14.50 0.051
## 3425 6.40 0.320 0.27 4.90 0.034
## 3426 7.10 0.170 0.40 14.55 0.047
## 3427 7.10 0.170 0.40 14.55 0.047
## 3428 5.80 0.240 0.26 10.05 0.039
## 3429 6.40 0.320 0.27 4.90 0.034
## 3430 7.10 0.180 0.39 14.50 0.051
## 3431 7.10 0.170 0.40 14.55 0.047
## 3432 7.10 0.180 0.39 15.25 0.047
## 3433 7.80 0.290 0.29 3.15 0.044
## 3434 6.20 0.255 0.27 1.30 0.037
## 3435 8.20 0.340 0.29 5.20 0.076
## 3436 6.50 0.240 0.28 1.10 0.034
## 3437 6.90 0.240 0.23 7.10 0.041
## 3438 6.70 0.400 0.22 8.80 0.052
## 3439 6.70 0.300 0.44 18.50 0.057
## 3440 6.70 0.400 0.22 8.80 0.052
## 3441 6.80 0.170 0.32 1.40 0.040
## 3442 7.10 0.250 0.28 1.20 0.040
## 3443 5.90 0.270 0.27 5.00 0.035
## 3444 6.00 0.160 0.22 1.60 0.042
## 3445 6.70 0.300 0.44 18.75 0.057
## 3446 6.60 0.150 0.32 6.00 0.033
## 3447 7.30 0.340 0.30 9.40 0.057
## 3448 6.00 0.170 0.29 9.70 0.044
## 3449 6.70 0.470 0.29 4.75 0.034
## 3450 6.60 0.150 0.32 6.00 0.033
## 3451 6.60 0.210 0.29 5.35 0.029
## 3452 6.60 0.210 0.29 5.35 0.029
## 3453 8.00 0.240 0.48 6.80 0.047
## 3454 5.60 0.340 0.30 6.90 0.038
## 3455 5.80 0.540 0.00 1.40 0.033
## 3456 7.30 0.230 0.24 0.90 0.031
## 3457 6.00 0.390 0.13 1.20 0.042
## 3458 6.10 0.105 0.31 1.30 0.037
## 3459 5.80 0.320 0.20 2.60 0.027
## 3460 7.60 0.220 0.28 12.00 0.056
## 3461 6.80 0.190 0.40 9.85 0.055
## 3463 6.80 0.170 0.34 2.00 0.040
## 3464 6.20 0.300 0.31 1.60 0.035
## 3465 6.90 0.290 0.41 7.80 0.046
## 3466 6.80 0.190 0.34 1.90 0.040
## 3467 6.80 0.170 0.34 2.00 0.040
## 3468 6.60 0.240 0.27 10.30 0.047
## 3469 6.60 0.160 0.36 1.10 0.031
## 3470 7.60 0.220 0.28 12.00 0.056
## 3472 6.80 0.190 0.40 9.85 0.055
## 3473 6.70 0.160 0.36 2.00 0.045
## 3474 6.50 0.300 0.27 4.00 0.038
## 3475 6.50 0.220 0.19 1.10 0.064
## 3476 6.20 0.360 0.45 10.40 0.060
## 3477 6.20 0.370 0.24 6.10 0.032
## 3478 7.60 0.310 0.24 1.80 0.037
## 3479 6.20 0.360 0.45 10.40 0.060
## 3480 5.90 0.320 0.28 4.70 0.039
## 3481 6.50 0.300 0.27 4.00 0.038
## 3482 5.80 0.220 0.30 1.10 0.047
## 3483 5.40 0.450 0.27 6.40 0.033
## 3484 6.10 0.360 0.26 8.15 0.035
## 3485 6.20 0.370 0.24 6.10 0.032
## 3486 7.50 0.210 0.32 4.80 0.056
## 3487 6.90 0.280 0.33 1.20 0.039
## 3488 6.50 0.220 0.19 1.10 0.064
## 3489 7.80 0.200 0.20 1.40 0.036
## 3490 6.70 0.280 0.31 7.40 0.041
## 3491 7.60 0.310 0.24 1.80 0.037
## 3492 8.00 0.200 0.44 1.00 0.057
## 3493 6.00 0.280 0.27 15.50 0.036
## 3494 6.00 0.280 0.27 15.50 0.036
## 3495 6.70 0.240 0.36 8.40 0.042
## 3496 6.30 0.220 0.28 2.40 0.042
## 3497 6.00 0.240 0.28 3.95 0.038
## 3499 6.40 0.300 0.36 2.00 0.052
## 3500 6.10 0.330 0.30 3.00 0.036
## 3501 6.00 0.280 0.27 15.50 0.036
## 3502 6.70 0.240 0.36 8.40 0.042
## 3503 6.70 0.290 0.45 14.30 0.054
## 3504 6.90 0.330 0.31 4.20 0.040
## 3505 6.50 0.160 0.34 1.40 0.029
## 3506 6.00 0.200 0.32 3.00 0.031
## 3507 7.50 0.330 0.28 4.90 0.042
## 3508 7.10 0.360 0.28 2.40 0.036
## 3509 6.70 0.290 0.45 14.30 0.054
## 3510 6.40 0.260 0.25 10.70 0.046
## 3511 7.00 0.220 0.24 11.00 0.041
## 3512 6.50 0.190 0.28 1.40 0.046
## 3513 6.30 0.210 0.31 1.20 0.043
## 3514 7.90 0.350 0.28 12.90 0.032
## 3515 7.70 0.380 0.23 10.80 0.030
## 3516 6.80 0.190 0.33 1.30 0.031
## 3517 7.20 0.330 0.34 2.00 0.044
## 3518 6.60 0.290 0.29 1.80 0.036
## 3519 7.50 0.200 0.41 1.20 0.050
## 3520 6.90 0.330 0.62 7.50 0.038
## 3522 5.90 0.230 0.24 3.80 0.038
## 3523 6.60 0.320 0.41 7.20 0.048
## 3525 5.30 0.360 0.27 6.30 0.028
## 3526 5.30 0.360 0.27 6.30 0.028
## 3527 8.90 0.270 0.28 0.80 0.024
## 3528 7.60 0.230 0.29 8.60 0.053
## 3529 6.90 0.750 0.13 6.30 0.036
## 3530 7.10 0.350 0.27 3.10 0.034
## 3531 7.20 0.310 0.35 7.20 0.046
## 3532 6.40 0.280 0.44 7.10 0.048
## 3533 7.20 0.230 0.46 6.40 0.036
## 3534 6.60 0.220 0.30 14.70 0.045
## 3535 7.20 0.310 0.35 7.20 0.046
## 3536 6.40 0.280 0.44 7.10 0.048
## 3537 7.20 0.240 0.28 1.90 0.032
## 3538 6.20 0.270 0.47 1.20 0.146
## 3539 6.50 0.280 0.25 4.80 0.029
## 3540 7.20 0.270 0.31 1.20 0.031
## 3541 7.80 0.280 0.25 3.40 0.024
## 3542 8.10 0.260 0.27 4.30 0.030
## 3543 6.60 0.230 0.37 8.50 0.036
## 3544 6.00 0.330 0.20 1.80 0.031
## 3545 6.00 0.330 0.20 1.80 0.031
## 3546 7.30 0.200 0.29 19.50 0.039
## 3547 6.60 0.230 0.37 8.50 0.036
## 3548 7.30 0.200 0.29 19.90 0.039
## 3549 6.20 0.470 0.19 8.30 0.029
## 3550 6.00 0.330 0.20 1.80 0.031
## 3551 7.20 0.140 0.32 1.10 0.022
## 3552 5.70 0.220 0.22 16.65 0.044
## 3553 5.70 0.220 0.22 16.65 0.044
## 3554 5.70 0.220 0.22 16.65 0.044
## 3555 8.10 0.200 0.28 0.90 0.023
## 3556 5.80 0.140 0.15 6.10 0.042
## 3557 4.80 0.210 0.21 10.20 0.037
## 3558 8.10 0.200 0.28 0.90 0.023
## 3559 5.70 0.220 0.22 16.65 0.044
## 3560 7.50 0.340 0.24 3.85 0.031
## 3561 6.60 0.640 0.28 4.40 0.032
## 3562 7.00 0.480 0.12 4.50 0.050
## 3563 7.60 0.370 0.34 3.20 0.028
## 3564 7.00 0.480 0.12 4.50 0.050
## 3565 6.60 0.640 0.28 4.40 0.032
## 3566 8.00 0.250 0.27 9.70 0.036
## 3567 7.60 0.380 0.28 4.20 0.029
## 3568 6.90 0.260 0.27 4.20 0.031
## 3569 7.80 0.150 0.34 1.10 0.035
## 3570 8.00 0.250 0.27 9.70 0.036
## 3571 6.90 0.260 0.27 4.20 0.031
## 3572 5.90 0.655 0.00 5.60 0.033
## 3573 7.60 0.380 0.28 4.20 0.029
## 3574 7.80 0.310 0.40 1.60 0.027
## 3575 8.10 0.170 0.21 1.60 0.036
## 3576 6.80 0.180 0.28 1.10 0.027
## 3577 7.40 0.280 0.36 14.60 0.048
## 3578 7.30 0.230 0.27 2.60 0.035
## 3579 6.70 0.220 0.22 1.20 0.038
## 3580 7.40 0.250 0.28 7.25 0.028
## 3581 7.50 0.300 0.21 6.55 0.026
## 3582 7.20 0.260 0.24 7.00 0.023
## 3583 6.30 0.320 0.32 1.50 0.037
## 3584 7.70 0.240 0.30 1.40 0.041
## 3585 7.40 0.250 0.28 7.25 0.028
## 3586 7.00 0.240 0.35 1.00 0.032
## 3587 5.80 0.280 0.28 4.20 0.044
## 3591 6.60 0.190 0.35 1.50 0.037
## 3592 6.40 0.280 0.36 1.30 0.053
## 3593 5.60 0.280 0.27 3.90 0.043
## 3594 5.60 0.280 0.28 4.20 0.044
## 3595 6.80 0.190 0.32 7.60 0.049
## 3596 7.20 0.160 0.29 1.00 0.031
## 3597 6.60 0.170 0.28 1.10 0.034
## 3598 6.60 0.190 0.28 11.80 0.042
## 3599 5.80 0.200 0.24 1.40 0.033
## 3600 6.60 0.390 0.38 9.70 0.053
## 3601 6.80 0.120 0.30 12.90 0.049
## 3602 6.60 0.295 0.24 1.60 0.039
## 3603 6.60 0.260 0.24 7.20 0.038
## 3604 7.00 0.320 0.27 7.10 0.027
## 3605 7.40 0.360 0.23 1.90 0.017
## 3606 6.70 0.350 0.48 8.80 0.056
## 3607 6.40 0.380 0.24 7.20 0.047
## 3608 6.80 0.140 0.18 1.40 0.047
## 3609 7.00 0.160 0.25 14.30 0.044
## 3610 7.00 0.160 0.25 14.30 0.044
## 3611 6.70 0.350 0.48 8.80 0.056
## 3612 6.80 0.140 0.18 1.40 0.047
## 3613 6.80 0.160 0.18 1.80 0.046
## 3614 7.00 0.160 0.25 14.30 0.044
## 3615 6.40 0.380 0.24 7.20 0.047
## 3616 7.20 0.240 0.30 1.20 0.037
## 3617 7.70 0.320 0.61 11.80 0.041
## 3618 7.00 0.290 0.33 0.90 0.041
## 3619 7.10 0.270 0.24 12.60 0.044
## 3622 7.10 0.270 0.24 12.60 0.044
## 3623 7.20 0.240 0.30 1.20 0.037
## 3625 6.60 0.360 0.28 6.10 0.029
## 3626 7.70 0.320 0.61 11.80 0.041
## 3627 7.00 0.290 0.33 0.90 0.041
## 3628 6.40 0.370 0.20 5.60 0.117
## 3629 6.40 0.380 0.20 5.30 0.117
## 3630 6.40 0.360 0.20 5.70 0.118
## 3631 6.60 0.300 0.25 8.00 0.036
## 3632 6.60 0.300 0.25 8.00 0.036
## 3633 6.50 0.210 0.51 17.60 0.045
## 3634 6.60 0.300 0.25 8.00 0.036
## 3635 7.60 0.310 0.27 8.80 0.021
## 3636 5.80 0.580 0.00 1.50 0.020
## 3637 6.50 0.260 0.39 1.40 0.020
## 3638 8.70 0.300 0.34 4.80 0.018
## 3639 6.40 0.290 0.32 2.40 0.014
## 3640 6.70 0.130 0.32 3.70 0.017
## 3641 6.80 0.190 0.33 4.90 0.047
## 3642 6.00 0.250 0.40 5.70 0.052
## 3643 6.00 0.250 0.40 5.70 0.052
## 3644 6.80 0.190 0.33 4.90 0.047
## 3645 6.40 0.240 0.23 2.00 0.046
## 3646 5.90 0.180 0.28 5.10 0.039
## 3647 7.20 0.330 0.22 4.50 0.031
## 3648 6.40 0.290 0.24 3.20 0.037
## 3649 7.30 0.310 0.25 6.65 0.032
## 3650 7.00 0.290 0.37 1.60 0.035
## 3651 6.90 0.190 0.60 4.00 0.037
## 3652 6.30 0.320 0.17 17.75 0.060
## 3653 6.60 0.085 0.33 1.40 0.036
## 3654 6.30 0.320 0.17 17.75 0.060
## 3655 6.80 0.180 0.32 7.20 0.047
## 3656 6.80 0.520 0.26 5.70 0.038
## 3657 7.10 0.280 0.28 8.50 0.030
## 3658 5.70 0.150 0.47 11.40 0.035
## 3659 5.80 0.275 0.30 5.40 0.043
## 3660 5.40 0.530 0.16 2.70 0.036
## 3661 5.80 0.320 0.28 4.30 0.032
## 3662 6.70 0.220 0.39 1.20 0.049
## 3663 6.10 0.600 0.12 1.80 0.050
## 3664 6.50 0.260 0.31 1.30 0.034
## 3665 5.00 0.290 0.54 5.70 0.035
## 3666 5.40 0.530 0.16 2.70 0.036
## 3667 6.80 0.210 0.26 11.70 0.038
## 3668 5.80 0.320 0.28 4.30 0.032
## 3669 6.50 0.270 0.26 11.00 0.030
## 3670 5.90 0.370 0.32 1.60 0.029
## 3671 6.20 0.210 0.18 11.60 0.044
## 3672 6.80 0.300 0.29 6.20 0.025
## 3673 7.30 0.410 0.29 1.80 0.032
## 3674 5.40 0.300 0.30 1.20 0.029
## 3675 6.60 0.340 0.20 1.00 0.053
## 3676 5.60 0.250 0.19 2.40 0.049
## 3677 5.30 0.300 0.30 1.20 0.029
## 3679 7.20 0.230 0.25 18.80 0.085
## 3680 7.10 0.200 0.27 9.60 0.037
## 3681 6.80 0.150 0.41 12.90 0.044
## 3682 7.00 0.220 0.26 9.20 0.027
## 3683 6.40 0.160 0.44 1.20 0.051
## 3684 6.80 0.150 0.41 12.90 0.044
## 3685 6.80 0.310 0.30 8.00 0.028
## 3686 6.80 0.150 0.41 12.90 0.044
## 3687 7.60 0.300 0.37 1.60 0.087
## 3688 6.00 0.160 0.27 12.00 0.030
## 3689 7.10 0.210 0.35 2.50 0.040
## 3690 7.00 0.220 0.26 9.20 0.027
## 3691 5.60 0.210 0.24 4.40 0.027
## 3692 7.40 0.220 0.26 8.80 0.027
## 3693 7.10 0.200 0.27 9.60 0.037
## 3694 6.80 0.310 0.30 8.00 0.028
## 3695 7.20 0.230 0.25 18.80 0.085
## 3696 6.40 0.150 0.40 1.30 0.053
## 3697 6.40 0.160 0.44 1.20 0.051
## 3698 6.80 0.150 0.41 12.90 0.044
## 3699 6.30 0.220 0.34 1.20 0.036
## 3700 7.60 0.300 0.37 1.60 0.087
## 3701 7.00 0.300 0.27 1.50 0.076
## 3702 6.60 0.260 0.22 18.15 0.050
## 3703 7.50 0.240 0.31 13.10 0.050
## 3704 7.50 0.240 0.31 13.10 0.050
## 3705 7.50 0.240 0.31 13.10 0.050
## 3706 7.50 0.240 0.31 13.10 0.050
## 3707 6.60 0.150 0.34 1.00 0.037
## 3708 6.70 0.340 0.43 1.60 0.041
## 3709 7.70 0.350 0.46 11.80 0.088
## 3710 6.70 0.310 0.09 1.40 0.039
## 3712 7.50 0.240 0.31 13.10 0.050
## 3713 6.30 0.200 0.18 10.60 0.045
## 3714 6.60 0.280 0.23 10.40 0.049
## 3715 8.50 0.180 0.30 1.10 0.028
## 3716 6.50 0.350 0.38 7.40 0.036
## 3717 6.80 0.220 0.26 1.20 0.041
## 3718 6.30 0.180 0.24 3.40 0.053
## 3719 6.60 0.260 0.22 18.15 0.050
## 3720 6.60 0.300 0.45 8.00 0.038
## 3721 6.30 0.340 0.27 2.50 0.024
## 3722 7.70 0.300 0.23 2.00 0.068
## 3723 7.70 0.310 0.23 2.00 0.069
## 3724 5.70 0.265 0.28 6.90 0.036
## 3725 5.40 0.255 0.33 1.20 0.051
## 3726 6.60 0.260 0.28 9.40 0.028
## 3727 4.80 0.170 0.28 2.90 0.030
## 3728 5.70 0.265 0.28 6.90 0.036
## 3729 6.20 0.200 0.33 5.40 0.028
## 3730 7.50 0.280 0.41 1.30 0.044
## 3731 6.20 0.220 0.20 20.80 0.035
## 3732 7.00 0.340 0.26 10.30 0.041
## 3733 7.50 0.280 0.41 1.30 0.044
## 3734 6.50 0.190 0.34 1.60 0.029
## 3735 6.00 0.210 0.29 13.10 0.042
## 3737 6.50 0.320 0.48 8.00 0.026
## 3739 5.60 0.260 0.18 1.40 0.034
## 3740 7.00 0.150 0.28 14.70 0.051
## 3741 7.00 0.150 0.28 14.70 0.051
## 3742 7.00 0.150 0.28 14.70 0.051
## 3743 7.00 0.150 0.28 14.70 0.051
## 3744 7.00 0.150 0.28 14.70 0.051
## 3745 7.00 0.150 0.28 14.70 0.051
## 3746 7.00 0.150 0.28 14.70 0.051
## 3747 7.40 0.270 0.28 1.80 0.040
## 3748 6.80 0.220 0.30 10.60 0.070
## 3749 6.20 0.240 0.25 12.50 0.055
## 3750 6.30 0.280 0.29 6.80 0.051
## 3751 7.00 0.150 0.28 14.70 0.051
## 3752 5.50 0.170 0.23 2.90 0.039
## 3753 6.50 0.260 0.34 1.40 0.040
## 3754 6.60 0.270 0.33 1.40 0.042
## 3755 5.40 0.460 0.15 2.10 0.026
## 3756 7.80 0.190 0.32 7.40 0.015
## 3757 5.50 0.170 0.23 2.90 0.039
## 3758 6.50 0.260 0.34 1.40 0.040
## 3759 6.60 0.270 0.33 1.40 0.042
## 3760 7.80 0.190 0.32 7.40 0.015
## 3761 7.80 0.200 0.32 5.00 0.016
## 3762 6.10 0.170 0.28 2.50 0.028
## 3763 7.40 0.200 0.35 6.10 0.025
## 3764 6.70 0.390 0.24 2.70 0.017
## 3765 5.40 0.460 0.15 2.10 0.026
## 3766 6.90 0.400 0.17 12.90 0.033
## 3767 6.90 0.400 0.17 12.90 0.033
## 3768 6.90 0.400 0.17 12.90 0.033
## 3769 6.30 0.240 0.29 13.70 0.035
## 3770 6.90 0.400 0.17 12.90 0.033
## 3771 7.40 0.270 0.31 2.40 0.014
## 3772 6.10 0.270 0.28 9.80 0.042
## 3773 6.30 0.240 0.29 13.70 0.035
## 3775 6.70 0.420 0.39 12.10 0.040
## 3776 6.50 0.330 0.28 6.10 0.018
## 3777 6.90 0.330 0.31 7.70 0.040
## 3778 6.50 0.330 0.28 6.10 0.018
## 3779 6.30 0.150 0.30 1.40 0.022
## 3780 6.50 0.320 0.45 7.70 0.022
## 3781 6.70 0.420 0.39 12.10 0.040
## 3782 7.40 0.250 0.29 6.80 0.020
## 3783 7.60 0.270 0.30 9.20 0.018
## 3784 6.40 0.270 0.45 8.30 0.050
## 3785 6.50 0.250 0.27 17.40 0.064
## 3786 5.60 0.190 0.31 2.70 0.027
## 3787 7.40 0.290 0.48 12.80 0.037
## 3788 6.40 0.340 0.44 8.20 0.043
## 3789 6.60 0.270 0.52 8.10 0.044
## 3790 6.60 0.260 0.52 8.20 0.047
## 3791 6.40 0.270 0.45 8.30 0.050
## 3792 6.50 0.260 0.50 8.00 0.051
## 3793 6.80 0.250 0.30 11.80 0.043
## 3794 6.30 0.320 0.26 12.00 0.049
## 3795 5.50 0.240 0.45 1.70 0.046
## 3796 6.50 0.250 0.27 17.40 0.064
## 3797 6.60 0.130 0.29 13.90 0.056
## 3798 7.00 0.390 0.21 10.70 0.098
## 3799 7.90 0.210 0.39 2.00 0.057
## 3800 7.00 0.300 0.28 2.20 0.042
## 3801 8.10 0.200 0.30 1.30 0.036
## 3802 8.30 0.180 0.30 1.10 0.033
## 3803 7.90 0.210 0.39 2.00 0.057
## 3804 7.20 0.170 0.34 6.40 0.042
## 3805 8.10 0.200 0.30 1.30 0.036
## 3806 8.30 0.180 0.30 1.10 0.033
## 3807 7.00 0.390 0.21 10.70 0.098
## 3808 6.80 0.210 0.62 6.40 0.041
## 3809 6.90 0.210 0.62 6.30 0.042
## 3810 7.20 0.170 0.34 6.40 0.042
## 3811 6.80 0.260 0.34 15.10 0.060
## 3812 7.20 0.280 0.38 2.00 0.052
## 3813 7.90 0.210 0.39 2.00 0.057
## 3814 7.00 0.300 0.28 2.20 0.042
## 3815 7.40 0.340 0.28 12.10 0.049
## 3816 6.30 0.430 0.32 8.80 0.042
## 3817 6.80 0.410 0.30 8.80 0.045
## 3818 6.30 0.400 0.24 5.10 0.036
## 3819 5.10 0.350 0.26 6.80 0.034
## 3820 5.10 0.350 0.26 6.80 0.034
## 3821 6.30 0.300 0.20 3.70 0.039
## 3822 6.90 0.280 0.28 12.20 0.042
## 3823 7.00 0.330 0.28 5.70 0.033
## 3824 6.70 0.260 0.49 8.10 0.052
## 3825 7.30 0.240 0.30 2.50 0.042
## 3826 6.70 0.460 0.21 4.00 0.034
## 3827 5.10 0.350 0.26 6.80 0.034
## 3828 5.10 0.230 0.18 1.00 0.053
## 3829 6.30 0.400 0.24 5.10 0.036
## 3830 7.10 0.440 0.23 5.80 0.035
## 3831 4.80 0.260 0.23 10.60 0.034
## 3832 6.80 0.310 0.19 3.50 0.086
## 3833 6.80 0.310 0.19 3.50 0.086
## 3834 7.00 0.150 0.29 16.40 0.058
## 3835 6.50 0.410 0.22 4.80 0.052
## 3836 6.20 0.310 0.23 3.30 0.052
## 3837 8.00 0.270 0.33 1.20 0.050
## 3838 8.00 0.270 0.33 1.20 0.050
## 3839 6.50 0.410 0.22 4.80 0.052
## 3840 6.20 0.310 0.23 3.30 0.052
## 3841 6.70 0.370 0.25 2.50 0.028
## 3842 6.60 0.210 0.50 8.70 0.036
## 3843 7.50 0.260 0.31 1.60 0.032
## 3844 7.50 0.340 0.28 4.00 0.028
## 3845 6.70 0.370 0.25 2.50 0.028
## 3846 6.40 0.320 0.23 16.20 0.055
## 3847 6.70 0.240 0.32 9.00 0.023
## 3848 6.40 0.320 0.23 16.20 0.055
## 3850 8.20 0.310 0.43 7.00 0.047
## 3851 6.70 0.240 0.32 9.00 0.023
## 3852 5.90 0.170 0.29 3.10 0.030
## 3853 5.90 0.200 0.23 1.50 0.037
## 3854 6.60 0.320 0.26 4.60 0.031
## 3855 5.90 0.120 0.27 4.80 0.030
## 3856 5.90 0.180 0.29 4.60 0.032
## 3857 5.90 0.200 0.23 1.50 0.037
## 3858 5.40 0.170 0.27 2.70 0.049
## 3859 6.10 0.210 0.30 6.30 0.039
## 3860 7.30 0.250 0.26 7.20 0.048
## 3861 7.30 0.250 0.26 7.20 0.048
## 3865 6.60 0.390 0.22 4.00 0.038
## 3866 6.00 0.310 0.38 4.80 0.040
## 3867 8.40 0.230 0.32 1.30 0.048
## 3868 7.30 0.250 0.26 7.20 0.048
## 3871 6.10 0.230 0.27 9.80 0.055
## 3873 7.30 0.360 0.54 13.30 0.054
## 3874 7.60 0.370 0.51 11.70 0.094
## 3875 6.70 0.260 0.51 8.00 0.062
## 3876 7.40 0.220 0.27 1.60 0.057
## 3877 6.10 0.220 0.28 16.55 0.059
## 3878 7.10 0.280 0.31 1.50 0.053
## 3879 6.50 0.350 0.31 10.20 0.069
## 3880 6.80 0.730 0.20 6.60 0.054
## 3881 6.00 0.280 0.24 17.80 0.047
## 3882 6.00 0.280 0.24 17.80 0.047
## 3883 7.10 0.200 0.37 1.50 0.049
## 3884 6.80 0.330 0.31 7.40 0.045
## 3885 6.00 0.280 0.24 17.80 0.047
## 3886 7.20 0.240 0.36 2.00 0.029
## 3887 6.80 0.330 0.31 7.40 0.045
## 3888 7.20 0.240 0.36 2.00 0.029
## 3889 6.00 0.280 0.24 17.80 0.047
## 3890 6.20 0.270 0.26 12.10 0.046
## 3891 6.40 0.380 0.26 8.20 0.043
## 3892 7.10 0.200 0.37 1.50 0.049
## 3893 6.00 0.210 0.30 8.70 0.036
## 3894 7.00 0.340 0.10 3.50 0.044
## 3895 5.90 0.435 0.16 6.40 0.031
## 3896 7.00 0.250 0.33 2.10 0.021
## 3897 6.70 0.260 0.29 7.70 0.038
## 3898 7.00 0.240 0.30 12.30 0.035
## 3899 8.50 0.230 0.34 1.30 0.035
## 3900 6.00 0.210 0.30 8.70 0.036
## 3901 7.00 0.340 0.10 3.50 0.044
## 3904 5.80 0.270 0.26 3.50 0.071
## 3906 6.50 0.330 0.30 3.80 0.036
## 3907 6.50 0.330 0.30 3.80 0.036
## 3908 6.70 0.310 0.30 2.40 0.038
## 3909 6.20 0.390 0.24 4.80 0.037
## 3910 6.20 0.390 0.24 4.80 0.037
## 3911 7.10 0.370 0.30 6.20 0.040
## 3913 6.50 0.330 0.30 3.80 0.036
## 3914 7.20 0.250 0.32 1.50 0.054
## 3915 6.20 0.390 0.24 4.80 0.037
## 3917 7.10 0.370 0.30 6.20 0.040
## 3918 6.20 0.280 0.51 7.90 0.056
## 3919 6.40 0.350 0.28 1.60 0.037
## 3920 6.60 0.310 0.28 1.40 0.035
## 3921 7.40 0.250 0.37 2.60 0.050
## 3922 7.30 0.360 0.34 14.80 0.057
## 3923 6.70 0.310 0.30 2.40 0.038
## 3924 8.60 0.310 0.30 0.90 0.045
## 3925 8.60 0.310 0.30 0.90 0.045
## 3926 8.60 0.220 0.33 1.20 0.031
## 3927 6.90 0.140 0.29 9.90 0.056
## 3928 6.50 0.220 0.31 3.90 0.046
## 3929 6.60 0.320 0.47 15.60 0.063
## 3930 6.60 0.320 0.47 15.60 0.063
## 3931 6.10 0.280 0.26 1.50 0.030
## 3932 6.20 0.300 0.28 1.60 0.036
## 3933 6.90 0.220 0.28 7.80 0.050
## 3934 8.70 0.310 0.21 5.60 0.039
## 3935 7.30 0.270 0.30 1.30 0.040
## 3936 7.00 0.460 0.20 16.70 0.046
## 3937 5.70 0.230 0.25 7.95 0.042
## 3939 8.20 0.180 0.38 1.10 0.040
## 3940 6.20 0.270 0.32 6.30 0.048
## 3941 6.90 0.400 0.37 8.90 0.053
## 3942 4.90 0.345 0.34 1.00 0.068
## 3943 7.20 0.230 0.39 1.50 0.053
## 3944 6.40 0.200 0.15 6.60 0.046
## 3945 6.10 0.270 0.32 6.20 0.048
## 3946 6.20 0.270 0.32 6.30 0.048
## 3947 6.00 0.300 0.33 2.10 0.042
## 3948 6.10 0.300 0.32 2.20 0.042
## 3949 5.70 0.140 0.30 5.40 0.045
## 3950 6.90 0.400 0.37 8.90 0.053
## 3951 4.90 0.345 0.34 1.00 0.068
## 3952 6.30 0.330 0.20 17.90 0.066
## 3953 7.00 0.160 0.30 2.60 0.043
## 3954 8.40 0.220 0.30 1.30 0.038
## 3955 6.30 0.330 0.20 17.90 0.066
## 3956 7.00 0.160 0.30 2.60 0.043
## 3957 5.40 0.240 0.18 2.30 0.050
## 3958 7.70 0.310 0.36 4.30 0.026
## 3959 5.60 0.185 0.19 7.10 0.048
## 3960 5.60 0.185 0.19 7.10 0.048
## 3961 6.60 0.430 0.24 11.90 0.040
## 3962 7.60 0.390 0.46 11.70 0.084
## 3963 7.20 0.580 0.27 5.80 0.032
## 3964 6.00 0.340 0.32 3.80 0.044
## 3965 7.50 0.350 0.48 12.40 0.056
## 3966 7.30 0.380 0.23 6.50 0.050
## 3967 5.40 0.185 0.19 7.10 0.048
## 3968 6.30 0.270 0.51 7.60 0.049
## 3969 6.50 0.290 0.52 7.90 0.049
## 3970 6.40 0.170 0.30 2.80 0.034
## 3971 6.70 0.180 0.31 10.60 0.035
## 3972 6.40 0.170 0.30 2.80 0.034
## 3974 6.30 0.270 0.51 7.60 0.049
## 3975 6.50 0.290 0.52 7.90 0.049
## 3976 6.10 0.240 0.26 1.70 0.033
## 3977 7.00 0.320 0.29 7.60 0.025
## 3978 6.90 0.270 0.25 7.50 0.030
## 3979 6.50 0.290 0.53 1.70 0.040
## 3980 6.50 0.290 0.52 1.70 0.034
## 3981 6.10 0.220 0.25 12.10 0.035
## 3983 6.10 0.240 0.26 1.70 0.033
## 3984 5.60 0.230 0.25 8.00 0.043
## 3985 7.00 0.320 0.29 7.60 0.025
## 3986 6.80 0.110 0.27 8.60 0.044
## 3987 6.80 0.110 0.27 8.60 0.044
## 3988 7.30 0.230 0.41 14.60 0.048
## 3989 6.10 0.200 0.17 1.60 0.048
## 3990 6.80 0.110 0.27 8.60 0.044
## 3991 7.30 0.230 0.41 14.60 0.048
## 3992 6.90 0.200 0.41 1.10 0.060
## 3993 6.70 0.190 0.32 3.70 0.041
## 3994 6.70 0.280 0.34 8.90 0.048
## 3995 6.70 0.280 0.34 8.90 0.048
## 3996 8.00 0.370 0.31 4.70 0.038
## 3997 6.70 0.280 0.34 8.90 0.048
## 3998 6.00 0.260 0.29 3.10 0.041
## 4002 6.40 0.250 0.57 1.00 0.062
## 4003 6.10 0.250 0.48 15.80 0.052
## 4004 6.80 0.140 0.35 1.50 0.047
## 4005 6.50 0.380 0.26 5.20 0.042
## 4006 6.80 0.140 0.35 1.50 0.047
## 4007 5.40 0.150 0.32 2.50 0.037
## 4008 6.40 0.250 0.57 1.00 0.062
## 4009 6.10 0.250 0.48 15.80 0.052
## 4010 6.80 0.220 0.32 5.90 0.054
## 4011 7.20 0.210 0.29 3.10 0.044
## 4012 6.00 0.260 0.29 3.10 0.041
## 4014 6.50 0.460 0.24 11.50 0.051
## 4015 6.50 0.180 0.48 18.00 0.054
## 4016 6.20 0.320 0.12 4.80 0.054
## 4017 7.20 0.400 0.24 8.50 0.055
## 4018 5.90 0.230 0.24 1.60 0.037
## 4019 6.40 0.180 0.48 18.00 0.054
## 4020 6.20 0.320 0.12 4.80 0.054
## 4021 6.40 0.370 0.12 5.90 0.056
## 4022 7.00 0.230 0.42 1.10 0.062
## 4023 7.20 0.400 0.24 8.50 0.055
## 4024 7.60 0.190 0.37 13.10 0.033
## 4025 6.00 0.280 0.27 4.10 0.046
## 4026 6.20 0.320 0.45 2.90 0.029
## 4027 7.60 0.190 0.37 13.10 0.033
## 4028 6.40 0.260 0.26 1.10 0.052
## 4029 5.90 0.250 0.27 1.50 0.029
## 4030 6.10 0.280 0.30 7.75 0.031
## 4031 6.90 0.190 0.38 1.15 0.023
## 4032 6.40 0.290 0.57 1.00 0.060
## 4033 6.80 0.270 0.22 17.80 0.034
## 4034 7.50 0.260 0.38 5.70 0.021
## 4035 6.80 0.270 0.22 17.80 0.034
## 4036 6.40 0.200 0.22 7.40 0.032
## 4037 7.30 0.330 0.22 1.40 0.041
## 4038 7.30 0.340 0.22 1.40 0.044
## 4039 6.40 0.290 0.57 1.00 0.060
## 4041 6.30 0.240 0.29 1.60 0.052
## 4042 6.20 0.240 0.22 7.90 0.053
## 4043 7.40 0.160 0.27 15.50 0.050
## 4044 7.40 0.160 0.27 15.50 0.050
## 4045 7.40 0.160 0.27 15.50 0.050
## 4046 7.40 0.160 0.27 15.50 0.050
## 4047 7.20 0.170 0.28 17.55 0.050
## 4048 6.90 0.190 0.35 13.50 0.038
## 4049 6.90 0.190 0.35 13.50 0.038
## 4050 6.80 0.160 0.36 1.30 0.034
## 4051 7.40 0.160 0.27 15.50 0.050
## 4052 6.80 0.300 0.27 11.60 0.028
## 4053 6.20 0.240 0.22 7.90 0.053
## 4054 7.40 0.160 0.27 15.50 0.050
## 4055 7.20 0.170 0.28 17.55 0.050
## 4056 6.80 0.300 0.27 11.60 0.028
## 4057 6.50 0.430 0.18 13.15 0.032
## 4058 6.60 0.170 0.36 1.90 0.036
## 4059 6.90 0.190 0.35 13.50 0.038
## 4060 6.80 0.160 0.36 1.30 0.034
## 4061 6.40 0.410 0.01 6.10 0.048
## 4062 6.40 0.410 0.01 6.10 0.048
## 4063 7.40 0.360 0.32 1.90 0.036
## 4064 6.10 0.170 0.21 1.90 0.090
## 4065 5.50 0.280 0.21 1.60 0.032
## 4067 7.10 0.440 0.27 8.40 0.057
## 4068 6.90 0.380 0.28 8.30 0.062
## 4069 7.10 0.440 0.27 8.40 0.057
## 4070 6.20 0.240 0.28 12.20 0.049
## 4071 6.10 0.280 0.27 8.00 0.048
## 4072 7.60 0.260 0.32 1.30 0.048
## 4073 7.50 0.160 0.38 12.70 0.043
## 4074 6.50 0.360 0.16 1.30 0.054
## 4075 6.60 0.350 0.19 10.50 0.060
## 4076 5.70 0.250 0.26 12.50 0.049
## 4077 7.40 0.370 0.26 9.60 0.050
## 4078 5.70 0.250 0.21 1.50 0.044
## 4079 5.80 0.230 0.21 1.50 0.044
## 4080 5.40 0.265 0.28 7.80 0.052
## 4081 5.70 0.250 0.27 10.80 0.050
## 4082 5.70 0.250 0.26 12.50 0.049
## 4083 5.90 0.230 0.28 8.60 0.046
## 4084 6.20 0.300 0.32 1.20 0.052
## 4085 6.50 0.330 0.24 14.50 0.048
## 4086 7.40 0.260 0.29 3.70 0.048
## 4087 7.00 0.200 0.40 1.10 0.058
## 4088 6.50 0.210 0.42 1.10 0.059
## 4089 7.30 0.250 0.27 3.80 0.047
## 4090 6.80 0.270 0.24 4.60 0.098
## 4091 6.70 0.240 0.30 10.20 0.070
## 4092 6.40 0.140 0.28 7.90 0.057
## 4093 6.40 0.500 0.20 2.40 0.059
## 4094 6.60 0.410 0.27 10.70 0.110
## 4095 6.40 0.250 0.28 4.90 0.030
## 4096 6.60 0.410 0.27 10.70 0.110
## 4097 8.00 0.250 0.35 1.10 0.054
## 4098 6.40 0.140 0.28 7.90 0.057
## 4099 6.60 0.210 0.34 5.60 0.046
## 4100 6.40 0.500 0.20 2.40 0.059
## 4101 6.30 0.290 0.23 14.20 0.037
## 4102 6.90 0.370 0.23 9.50 0.057
## 4103 6.90 0.370 0.23 9.50 0.057
## 4104 5.70 0.310 0.28 4.10 0.030
## 4105 6.90 0.450 0.27 4.70 0.035
## 4106 6.90 0.300 0.45 1.40 0.039
## 4107 5.30 0.230 0.56 0.90 0.041
## 4109 6.70 0.280 0.42 3.50 0.035
## 4110 5.00 0.255 0.22 2.70 0.043
## 4111 7.60 0.400 0.27 1.20 0.053
## 4112 5.50 0.210 0.25 1.20 0.040
## 4113 6.00 0.200 0.25 2.00 0.041
## 4114 6.10 0.170 0.29 1.10 0.041
## 4115 7.50 0.210 0.29 1.50 0.046
## 4116 7.30 0.260 0.32 1.20 0.041
## 4117 6.20 0.350 0.20 18.10 0.069
## 4118 6.20 0.350 0.20 18.10 0.069
## 4119 6.50 0.430 0.31 3.60 0.046
## 4120 6.50 0.400 0.31 3.50 0.046
## 4121 7.40 0.280 0.50 12.10 0.049
## 4122 6.30 0.230 0.22 17.45 0.054
## 4123 6.20 0.340 0.25 12.10 0.059
## 4124 6.60 0.440 0.32 3.00 0.095
## 4125 6.00 0.130 0.36 1.60 0.052
## 4126 6.30 0.170 0.23 5.70 0.048
## 4127 6.30 0.180 0.22 5.60 0.047
## 4128 6.70 0.310 0.34 6.80 0.059
## 4129 6.60 0.330 0.32 15.60 0.054
## 4130 6.30 0.340 0.31 6.00 0.020
## 4131 6.80 0.290 0.32 1.80 0.032
## 4132 7.40 0.310 0.26 8.60 0.048
## 4133 7.40 0.310 0.26 8.60 0.048
## 4134 5.70 0.250 0.27 11.50 0.040
## 4135 6.80 0.270 0.28 7.80 0.038
## 4136 5.90 0.260 0.24 2.40 0.046
## 4138 7.40 0.310 0.26 8.60 0.048
## 4139 6.60 0.230 0.32 1.50 0.041
## 4140 6.80 0.180 0.35 5.40 0.054
## 4141 6.80 0.280 0.29 11.90 0.052
## 4142 6.80 0.280 0.29 11.90 0.052
## 4143 5.90 0.270 0.27 9.00 0.051
## 4144 6.10 0.250 0.28 10.00 0.055
## 4145 6.80 0.280 0.29 11.90 0.052
## 4146 6.80 0.260 0.29 11.90 0.052
## 4147 7.10 0.130 0.29 15.50 0.064
## 4148 6.80 0.180 0.35 5.40 0.054
## 4149 6.20 0.200 0.25 15.00 0.055
## 4150 5.80 0.240 0.28 1.40 0.038
## 4151 7.60 0.480 0.31 9.40 0.046
## 4152 7.40 0.260 0.32 3.70 0.032
## 4153 6.20 0.200 0.25 15.00 0.055
## 4154 6.10 0.300 0.47 1.40 0.049
## 4155 6.20 0.320 0.50 6.50 0.048
## 4156 6.10 0.300 0.47 1.40 0.049
## 4157 6.30 0.340 0.52 6.30 0.047
## 4158 7.40 0.160 0.30 13.70 0.056
## 4159 7.40 0.160 0.30 13.70 0.056
## 4160 7.40 0.160 0.30 13.70 0.056
## 4161 7.40 0.160 0.30 13.70 0.056
## 4162 7.40 0.160 0.30 13.70 0.056
## 4163 7.40 0.160 0.30 13.70 0.056
## 4164 7.20 0.260 0.38 1.50 0.061
## 4165 7.00 0.310 0.35 1.60 0.063
## 4166 6.60 0.220 0.35 1.40 0.050
## 4167 5.80 0.230 0.31 3.50 0.044
## 4168 6.30 0.170 0.32 1.00 0.040
## 4169 6.00 0.190 0.26 1.40 0.039
## 4170 6.70 0.210 0.34 1.50 0.035
## 4171 7.40 0.160 0.30 13.70 0.056
## 4172 6.60 0.220 0.37 1.60 0.040
## 4173 6.80 0.340 0.27 5.20 0.060
## 4175 6.30 0.240 0.22 11.90 0.050
## 4176 6.90 0.350 0.39 2.40 0.048
## 4177 6.80 0.240 0.33 3.20 0.049
## 4178 6.40 0.250 0.33 1.70 0.037
## 4179 5.80 0.190 0.33 4.20 0.038
## 4180 6.90 0.240 0.40 15.40 0.052
## 4181 6.50 0.310 0.61 13.00 0.053
## 4182 6.60 0.250 0.32 5.60 0.039
## 4183 7.50 0.380 0.56 9.70 0.055
## 4184 6.20 0.300 0.30 2.50 0.041
## 4185 6.40 0.330 0.28 4.00 0.040
## 4186 6.90 0.240 0.40 15.40 0.052
## 4187 7.60 0.270 0.32 1.20 0.043
## 4188 5.90 0.240 0.34 2.00 0.037
## 4189 5.30 0.330 0.30 1.20 0.048
## 4190 6.40 0.210 0.21 5.10 0.097
## 4191 7.00 0.220 0.30 1.40 0.040
## 4192 7.80 0.270 0.35 1.20 0.050
## 4193 6.70 0.200 0.24 6.50 0.044
## 4194 8.10 0.270 0.33 1.30 0.045
## 4195 6.70 0.200 0.24 6.50 0.044
## 4196 7.10 0.450 0.24 2.70 0.040
## 4197 5.80 0.220 0.29 1.30 0.036
## 4198 6.30 0.300 0.48 7.40 0.053
## 4199 7.90 0.360 0.53 12.90 0.049
## 4200 8.10 0.270 0.33 1.30 0.045
## 4201 8.00 0.240 0.33 1.20 0.044
## 4202 6.70 0.410 0.27 2.60 0.033
## 4203 6.70 0.240 0.31 2.30 0.044
## 4204 6.20 0.300 0.32 1.30 0.054
## 4205 6.90 0.260 0.38 10.50 0.044
## 4206 6.70 0.410 0.27 2.60 0.033
## 4207 5.90 0.320 0.20 14.40 0.050
## 4208 6.10 0.250 0.30 1.20 0.036
## 4209 5.60 0.230 0.29 3.10 0.023
## 4210 6.60 0.230 0.32 1.70 0.024
## 4211 6.00 0.170 0.21 6.00 0.050
## 4212 7.10 0.380 0.42 11.80 0.041
## 4213 6.60 0.310 0.37 6.20 0.052
## 4214 6.50 0.380 0.53 1.40 0.142
## 4215 7.00 0.440 0.24 12.10 0.056
## 4216 7.00 0.440 0.24 12.10 0.056
## 4217 7.00 0.440 0.24 12.10 0.056
## 4218 6.10 0.380 0.14 3.90 0.060
## 4219 8.00 0.330 0.32 4.60 0.041
## 4220 7.00 0.440 0.24 12.10 0.056
## 4221 6.00 0.190 0.29 1.20 0.046
## 4222 6.30 0.280 0.34 8.10 0.038
## 4223 6.10 0.380 0.14 3.90 0.060
## 4224 5.30 0.430 0.11 1.10 0.029
## 4225 5.40 0.220 0.35 6.50 0.029
## 4226 6.20 0.345 0.27 10.10 0.056
## 4227 5.60 0.255 0.57 10.70 0.056
## 4228 5.20 0.200 0.27 3.20 0.047
## 4229 6.20 0.290 0.23 12.40 0.048
## 4230 6.30 0.260 0.25 5.20 0.046
## 4231 6.00 0.220 0.23 5.00 0.045
## 4232 7.50 0.350 0.37 2.50 0.066
## 4233 6.60 0.390 0.28 9.20 0.036
## 4234 6.30 0.230 0.33 6.90 0.052
## 4235 6.30 0.220 0.30 2.00 0.050
## 4236 6.40 0.290 0.18 15.00 0.040
## 4237 6.40 0.290 0.18 15.00 0.040
## 4238 7.50 0.230 0.30 1.20 0.030
## 4239 6.40 0.290 0.18 15.00 0.040
## 4241 6.50 0.260 0.24 10.80 0.042
## 4242 6.40 0.270 0.29 3.90 0.034
## 4243 5.90 0.220 0.29 4.20 0.037
## 4244 6.80 0.260 0.26 2.00 0.019
## 4245 7.60 0.360 0.48 13.50 0.038
## 4246 7.60 0.350 0.47 13.30 0.037
## 4247 5.70 0.180 0.26 2.20 0.023
## 4248 6.60 0.360 0.47 1.40 0.145
## 4249 5.90 0.140 0.20 1.60 0.040
## 4250 5.50 0.230 0.19 2.20 0.044
## 4251 6.70 0.110 0.26 14.80 0.053
## 4252 7.00 0.240 0.24 1.80 0.047
## 4253 6.70 0.110 0.26 14.80 0.053
## 4254 5.30 0.470 0.10 1.30 0.036
## 4255 7.50 0.290 0.24 9.90 0.058
## 4256 6.00 0.330 0.26 5.10 0.051
## 4257 6.00 0.330 0.26 5.10 0.051
## 4258 5.80 0.320 0.23 1.50 0.033
## 4259 5.80 0.300 0.23 1.50 0.034
## 4261 6.20 0.360 0.22 5.25 0.038
## 4262 6.00 0.310 0.27 2.30 0.042
## 4263 6.90 0.520 0.54 7.90 0.036
## 4264 7.00 0.550 0.05 8.00 0.036
## 4265 5.80 0.200 0.16 1.40 0.042
## 4266 6.20 0.360 0.22 5.25 0.038
## 4267 6.00 0.310 0.27 2.30 0.042
## 4268 6.00 0.290 0.27 2.30 0.044
## 4269 5.70 0.220 0.29 3.50 0.040
## 4270 7.10 0.460 0.23 13.70 0.045
## 4271 6.60 0.210 0.30 9.90 0.041
## 4272 6.90 0.420 0.20 15.40 0.043
## 4273 5.70 0.220 0.20 16.00 0.044
## 4274 5.70 0.220 0.20 16.00 0.044
## 4275 5.70 0.220 0.20 16.00 0.044
## 4276 5.70 0.220 0.20 16.00 0.044
## 4277 5.20 0.310 0.20 2.40 0.027
## 4278 7.20 0.220 0.35 5.50 0.054
## 4279 5.60 0.180 0.29 2.30 0.040
## 4280 6.20 0.240 0.27 16.80 0.040
## 4281 5.70 0.220 0.20 16.00 0.044
## 4282 5.70 0.260 0.24 17.80 0.059
## 4283 5.70 0.260 0.24 17.80 0.059
## 4284 6.00 0.200 0.26 6.80 0.049
## 4285 6.00 0.200 0.26 6.80 0.049
## 4286 6.00 0.200 0.26 6.80 0.049
## 4287 6.00 0.200 0.26 6.80 0.049
## 4288 7.60 0.280 0.17 1.60 0.046
## 4289 7.00 0.200 0.33 4.70 0.030
## 4290 6.60 0.260 0.27 11.80 0.048
## 4291 5.70 0.260 0.24 17.80 0.059
## 4292 7.20 0.210 0.36 15.70 0.045
## 4293 6.90 0.220 0.32 5.80 0.041
## 4294 7.20 0.210 0.36 15.70 0.045
## 4295 7.40 0.220 0.28 9.00 0.046
## 4296 7.20 0.210 0.36 15.70 0.045
## 4297 6.90 0.220 0.32 5.80 0.041
## 4298 7.00 0.200 0.35 8.80 0.037
## 4299 5.60 0.260 0.00 10.20 0.038
## 4302 7.20 0.340 0.23 8.90 0.105
## 4303 7.10 0.390 0.39 11.10 0.034
## 4304 6.90 0.260 0.29 4.20 0.043
## 4305 6.10 0.240 0.25 1.60 0.044
## 4306 5.90 0.250 0.24 7.40 0.044
## 4307 6.10 0.240 0.27 11.50 0.050
## 4308 6.50 0.220 0.27 1.60 0.039
## 4309 6.20 0.260 0.29 2.00 0.036
## 4310 6.60 0.340 0.25 4.80 0.038
## 4311 5.60 0.225 0.24 9.80 0.054
## 4312 7.10 0.230 0.28 1.90 0.046
## 4313 6.90 0.260 0.29 4.20 0.043
## 4314 6.40 0.270 0.30 1.60 0.040
## 4315 6.30 0.410 0.22 7.30 0.035
## 4316 6.70 0.410 0.24 5.40 0.035
## 4317 7.20 0.585 0.20 10.40 0.086
## 4318 6.70 0.340 0.26 1.90 0.038
## 4319 6.30 0.410 0.22 7.30 0.035
## 4320 6.70 0.410 0.24 5.40 0.035
## 4321 6.40 0.260 0.35 7.70 0.056
## 4322 6.30 0.280 0.22 11.50 0.036
## 4323 7.40 0.160 0.33 1.20 0.042
## 4324 8.40 0.270 0.30 2.20 0.037
## 4325 5.90 0.200 0.28 1.00 0.043
## 4326 6.40 0.240 0.26 8.20 0.054
## 4327 7.40 0.380 0.34 8.30 0.052
## 4328 6.40 0.240 0.26 8.20 0.054
## 4329 6.40 0.420 0.19 9.30 0.043
## 4330 6.40 0.230 0.26 8.10 0.054
## 4331 6.40 0.240 0.26 8.20 0.054
## 4332 7.40 0.380 0.34 8.30 0.052
## 4333 7.30 0.190 0.27 13.90 0.057
## 4334 7.30 0.190 0.27 13.90 0.057
## 4335 7.30 0.190 0.27 13.90 0.057
## 4336 7.30 0.190 0.27 13.90 0.057
## 4337 7.30 0.190 0.27 13.90 0.057
## 4338 7.30 0.190 0.27 13.90 0.057
## 4339 7.30 0.190 0.27 13.90 0.057
## 4340 6.80 0.240 0.29 2.00 0.044
## 4341 7.30 0.190 0.27 13.90 0.057
## 4342 7.40 0.270 0.52 15.70 0.054
## 4343 5.70 0.280 0.35 1.20 0.052
## 4344 5.80 0.220 0.25 1.50 0.024
## 4346 7.10 0.200 0.35 3.20 0.034
## 4348 7.10 0.230 0.30 2.60 0.034
## 4349 7.60 0.310 0.52 13.20 0.042
## 4350 7.20 0.340 0.28 10.40 0.108
## 4351 7.00 0.360 0.25 5.70 0.015
## 4352 6.40 0.310 0.28 2.50 0.039
## 4353 7.30 0.280 0.35 1.60 0.054
## 4354 7.40 0.160 0.30 1.40 0.064
## 4355 6.40 0.310 0.27 7.40 0.049
## 4356 6.40 0.310 0.28 2.50 0.039
## 4357 6.20 0.290 0.29 5.60 0.046
## 4358 5.90 0.280 0.34 3.60 0.040
## 4359 6.50 0.230 0.20 7.50 0.050
## 4360 7.20 0.340 0.20 5.80 0.062
## 4361 7.30 0.280 0.35 1.60 0.054
## 4362 6.50 0.200 0.33 1.50 0.039
## 4363 6.20 0.240 0.27 2.90 0.039
## 4364 7.10 0.310 0.25 11.20 0.048
## 4365 6.40 0.290 0.21 9.65 0.041
## 4366 6.30 0.190 0.33 10.10 0.063
## 4367 5.90 0.290 0.28 3.20 0.035
## 4368 7.10 0.310 0.25 11.20 0.048
## 4369 6.50 0.300 0.28 11.45 0.041
## 4370 6.40 0.290 0.21 9.65 0.041
## 4371 6.50 0.220 0.19 4.50 0.096
## 4372 7.00 0.230 0.28 2.70 0.053
## 4373 7.10 0.230 0.23 3.50 0.038
## 4374 6.10 0.260 0.28 1.70 0.043
## 4375 6.40 0.350 0.21 2.10 0.051
## 4376 6.00 0.320 0.32 4.80 0.041
## 4377 6.10 0.340 0.21 5.00 0.042
## 4378 6.50 0.130 0.27 2.60 0.035
## 4379 6.50 0.315 0.20 6.60 0.041
## 4380 6.10 0.340 0.21 5.00 0.042
## 4381 5.70 0.310 0.29 7.30 0.050
## 4382 6.40 0.300 0.27 5.00 0.058
## 4383 7.00 0.240 0.26 1.70 0.041
## 4384 6.50 0.130 0.27 2.60 0.035
## 4385 6.40 0.260 0.21 8.20 0.050
## 4386 6.40 0.260 0.21 8.20 0.050
## 4387 6.00 0.270 0.31 5.00 0.043
## 4388 7.10 0.210 0.33 1.20 0.039
## 4389 6.70 0.260 0.29 7.10 0.036
## 4390 6.30 0.280 0.22 9.50 0.040
## 4391 6.20 0.250 0.44 15.80 0.057
## 4392 7.30 0.220 0.37 15.50 0.048
## 4393 6.20 0.250 0.44 15.80 0.057
## 4394 6.40 0.180 0.28 17.05 0.047
## 4395 6.30 0.200 0.26 12.70 0.046
## 4396 6.60 0.240 0.22 12.30 0.051
## 4397 7.40 0.270 0.26 11.80 0.053
## 4398 7.40 0.270 0.26 11.80 0.053
## 4399 7.40 0.270 0.26 11.80 0.053
## 4400 6.60 0.240 0.22 12.30 0.051
## 4401 7.40 0.270 0.26 11.80 0.053
## 4403 6.80 0.430 0.26 5.20 0.043
## 4404 5.20 0.220 0.46 6.20 0.066
## 4405 5.90 0.290 0.16 7.90 0.044
## 4406 5.90 0.290 0.16 7.90 0.044
## 4407 6.30 0.290 0.29 3.30 0.037
## 4408 6.30 0.190 0.32 2.80 0.046
## 4409 5.70 0.290 0.16 7.90 0.044
## 4410 6.30 0.290 0.29 3.30 0.037
## 4411 5.70 0.240 0.47 6.30 0.069
## 4412 5.80 0.300 0.38 4.90 0.039
## 4413 7.10 0.270 0.27 10.40 0.041
## 4414 5.80 0.300 0.38 4.90 0.039
## 4415 7.10 0.270 0.27 10.40 0.041
## 4416 6.30 0.305 0.22 16.00 0.061
## 4417 5.70 0.240 0.47 6.30 0.069
## 4418 6.20 0.220 0.28 2.20 0.040
## 4419 6.60 0.220 0.23 17.30 0.047
## 4420 6.60 0.220 0.23 17.30 0.047
## 4421 6.60 0.220 0.23 17.30 0.047
## 4422 6.60 0.220 0.23 17.30 0.047
## 4423 6.20 0.220 0.28 2.20 0.040
## 4424 6.20 0.220 0.28 2.20 0.040
## 4425 6.60 0.220 0.23 17.30 0.047
## 4426 6.10 0.220 0.50 6.60 0.045
## 4427 6.20 0.210 0.52 6.50 0.047
## 4428 6.30 0.320 0.26 12.30 0.044
## 4429 6.90 0.440 0.27 5.00 0.038
## 4430 6.10 0.310 0.34 2.80 0.042
## 4431 8.10 0.360 0.59 13.60 0.051
## 4432 6.60 0.380 0.28 2.80 0.043
## 4433 6.70 0.240 0.26 5.40 0.030
## 4434 6.90 0.560 0.26 10.90 0.060
## 4435 7.20 0.240 0.24 1.70 0.045
## 4436 6.50 0.290 0.30 9.15 0.051
## 4437 6.70 0.280 0.28 4.50 0.051
## 4438 6.50 0.290 0.30 9.15 0.051
## 4439 6.10 0.210 0.19 1.40 0.046
## 4440 7.20 0.470 0.16 5.90 0.048
## 4441 6.70 0.340 0.31 16.40 0.051
## 4442 6.60 0.270 0.25 1.20 0.033
## 4443 6.70 0.340 0.31 16.40 0.051
## 4444 7.20 0.470 0.16 5.90 0.048
## 4445 5.00 0.350 0.25 7.80 0.031
## 4446 5.00 0.350 0.25 7.80 0.031
## 4447 4.40 0.460 0.10 2.80 0.024
## 4448 6.60 0.380 0.29 2.90 0.035
## 4449 7.30 0.300 0.25 2.50 0.045
## 4450 6.40 0.280 0.22 12.80 0.039
## 4451 6.90 0.290 0.25 12.20 0.040
## 4452 6.30 0.300 0.19 7.70 0.049
## 4453 6.30 0.390 0.22 2.80 0.048
## 4454 6.60 0.380 0.29 2.90 0.035
## 4455 6.60 0.180 0.26 17.30 0.051
## 4456 6.00 0.280 0.29 19.30 0.051
## 4457 6.00 0.280 0.29 19.30 0.051
## 4458 6.00 0.280 0.29 19.30 0.051
## 4459 6.60 0.350 0.26 2.70 0.045
## 4460 5.90 0.220 0.18 6.40 0.041
## 4461 6.60 0.180 0.26 17.30 0.051
## 4462 7.70 0.280 0.24 2.40 0.044
## 4463 7.10 0.420 0.20 2.80 0.038
## 4464 6.70 0.320 0.32 1.70 0.031
## 4465 6.60 0.260 0.56 15.40 0.053
## 4466 6.60 0.260 0.56 15.40 0.053
## 4467 6.20 0.320 0.24 4.10 0.051
## 4468 6.30 0.250 0.27 6.60 0.054
## 4469 6.20 0.210 0.24 1.20 0.051
## 4470 6.40 0.230 0.27 2.10 0.042
## 4471 4.70 0.145 0.29 1.00 0.042
## 4472 6.20 0.200 0.28 1.10 0.039
## 4473 7.00 0.280 0.28 1.40 0.039
## 4475 5.70 0.250 0.22 9.80 0.049
## 4476 5.70 0.220 0.33 1.90 0.036
## 4477 6.00 0.200 0.38 1.30 0.034
## 4478 6.40 0.320 0.26 7.90 0.050
## 4479 6.40 0.320 0.26 7.90 0.050
## 4480 6.00 0.555 0.26 4.50 0.053
## 4482 6.40 0.320 0.26 7.90 0.050
## 4483 6.20 0.300 0.33 3.50 0.037
## 4484 5.80 0.280 0.18 1.20 0.058
## 4485 5.80 0.555 0.26 4.50 0.053
## 4486 6.70 0.310 0.33 2.00 0.033
## 4487 6.40 0.150 0.25 7.80 0.050
## 4488 6.40 0.130 0.28 0.90 0.045
## 4489 6.70 0.480 0.49 2.90 0.030
## 4490 6.70 0.480 0.49 2.90 0.030
## 4491 5.80 0.300 0.33 3.50 0.033
## 4492 6.10 0.280 0.23 4.20 0.038
## 4493 6.00 0.190 0.37 9.70 0.032
## 4494 6.80 0.310 0.25 10.50 0.043
## 4495 7.50 0.240 0.29 1.10 0.046
## 4496 6.80 0.230 0.39 16.10 0.053
## 4497 7.50 0.240 0.29 1.10 0.046
## 4499 6.80 0.200 0.25 6.20 0.052
## 4500 5.20 0.380 0.26 7.70 0.053
## 4501 7.80 0.270 0.33 2.40 0.053
## 4502 6.60 0.540 0.21 16.30 0.055
## 4503 7.10 0.250 0.31 2.30 0.050
## 4505 6.50 0.320 0.23 8.50 0.051
## 4506 6.40 0.280 0.23 6.00 0.051
## 4507 6.60 0.190 0.28 1.10 0.044
## 4508 5.10 0.305 0.13 1.75 0.036
## 4509 5.80 0.260 0.30 2.60 0.034
## 4510 6.70 0.230 0.17 1.30 0.061
## 4511 6.80 0.330 0.30 2.10 0.047
## 4512 6.10 0.270 0.32 1.10 0.034
## 4513 6.10 0.270 0.32 1.10 0.034
## 4514 6.80 0.400 0.29 2.80 0.044
## 4515 6.10 0.400 0.18 9.00 0.051
## 4516 7.10 0.280 0.26 2.80 0.039
## 4517 6.20 0.320 0.32 2.20 0.036
## 4518 6.80 0.170 0.17 5.10 0.049
## 4519 9.00 0.200 0.33 3.50 0.049
## 4521 5.80 0.310 0.31 7.50 0.052
## 4522 6.30 0.360 0.20 2.00 0.048
## 4523 9.00 0.200 0.33 3.50 0.049
## 4524 6.70 0.180 0.25 14.30 0.048
## 4525 6.60 0.160 0.25 9.80 0.049
## 4527 5.80 0.270 0.22 12.70 0.058
## 4528 6.80 0.170 0.17 5.10 0.049
## 4529 6.40 0.370 0.19 3.50 0.068
## 4530 7.30 0.260 0.53 12.70 0.047
## 4531 7.30 0.280 0.54 12.90 0.049
## 4532 7.30 0.280 0.54 12.90 0.049
## 4533 5.80 0.120 0.21 1.30 0.056
## 4534 6.10 0.250 0.18 10.50 0.049
## 4535 6.40 0.240 0.27 1.50 0.040
## 4536 7.30 0.260 0.53 12.70 0.047
## 4537 7.30 0.280 0.54 12.90 0.049
## 4538 8.30 0.180 0.37 1.20 0.049
## 4539 7.10 0.090 0.30 6.20 0.032
## 4540 8.30 0.140 0.36 8.80 0.026
## 4541 5.80 0.280 0.30 3.90 0.026
## 4542 6.00 0.230 0.34 1.30 0.025
## 4543 6.90 0.280 0.37 9.10 0.037
## 4544 6.90 0.280 0.37 9.10 0.037
## 4545 5.80 0.280 0.30 3.90 0.026
## 4546 6.30 0.250 0.53 1.80 0.021
## 4547 6.50 0.200 0.31 2.10 0.033
## 4548 5.90 0.290 0.32 1.40 0.022
## 4549 6.40 0.460 0.22 14.70 0.047
## 4550 6.90 0.280 0.37 9.10 0.037
## 4551 6.80 0.230 0.33 1.90 0.047
## 4552 7.00 0.230 0.32 1.80 0.048
## 4553 6.40 0.550 0.26 9.60 0.027
## 4554 5.70 0.280 0.30 3.90 0.026
## 4555 6.00 0.230 0.34 1.30 0.025
## 4556 6.80 0.450 0.30 11.80 0.094
## 4557 6.10 0.200 0.40 1.90 0.028
## 4558 6.10 0.370 0.46 12.00 0.042
## 4559 5.90 0.210 0.23 7.90 0.033
## 4560 6.90 0.220 0.32 9.30 0.040
## 4561 5.40 0.270 0.22 4.60 0.022
## 4562 6.00 0.260 0.26 2.20 0.035
## 4563 5.60 0.180 0.30 10.20 0.028
## 4564 5.60 0.260 0.27 10.60 0.030
## 4565 7.00 0.230 0.35 1.40 0.036
## 4567 8.60 0.360 0.26 11.10 0.030
## 4569 6.40 0.300 0.27 4.40 0.055
## 4570 6.20 0.200 0.32 2.80 0.050
## 4571 5.80 0.290 0.15 1.10 0.029
## 4572 5.70 0.220 0.28 1.30 0.027
## 4573 5.60 0.220 0.32 1.20 0.024
## 4574 6.80 0.320 0.23 3.30 0.026
## 4575 6.20 0.200 0.26 9.70 0.030
## 4576 6.10 0.350 0.24 2.30 0.034
## 4577 5.90 0.300 0.29 1.10 0.036
## 4578 6.30 0.150 0.34 11.40 0.050
## 4579 4.80 0.130 0.32 1.20 0.042
## 4580 6.00 0.200 0.26 14.70 0.045
## 4582 6.00 0.270 0.26 1.30 0.038
## 4584 6.40 0.230 0.37 7.90 0.050
## 4585 5.90 0.340 0.25 2.00 0.042
## 4586 5.00 0.330 0.23 11.80 0.030
## 4587 5.40 0.290 0.38 1.20 0.029
## 4588 8.00 0.330 0.35 10.00 0.035
## 4589 6.40 0.300 0.33 5.20 0.050
## 4590 5.40 0.290 0.38 1.20 0.029
## 4591 6.40 0.330 0.30 7.20 0.041
## 4593 6.70 0.450 0.30 5.30 0.036
## 4594 6.50 0.360 0.31 13.55 0.053
## 4595 5.80 0.420 0.30 2.20 0.035
## 4596 7.10 0.390 0.30 9.90 0.037
## 4597 6.70 0.530 0.29 4.30 0.069
## 4599 6.50 0.360 0.31 13.55 0.053
## 4600 6.50 0.160 0.33 1.00 0.027
## 4601 8.30 0.220 0.34 1.10 0.043
## 4602 6.90 0.230 0.35 6.90 0.030
## 4603 6.40 0.170 0.34 13.40 0.044
## 4604 5.00 0.330 0.18 4.60 0.032
## 4605 6.80 0.380 0.29 9.90 0.037
## 4606 6.50 0.290 0.32 3.00 0.036
## 4607 6.90 0.290 0.32 5.80 0.040
## 4608 6.60 0.280 0.30 12.90 0.033
## 4609 6.20 0.360 0.27 3.20 0.032
## 4610 6.00 0.615 0.04 0.80 0.032
## 4611 5.90 0.440 0.36 2.50 0.030
## 4612 5.90 0.420 0.36 2.40 0.034
## 4613 5.80 0.340 0.21 7.20 0.041
## 4614 5.80 0.270 0.20 7.30 0.040
## 4615 7.10 0.330 0.18 6.30 0.094
## 4616 6.10 0.440 0.28 4.25 0.032
## 4617 7.30 0.280 0.37 1.20 0.039
## 4618 5.20 0.500 0.18 2.00 0.036
## 4619 6.10 0.440 0.28 4.25 0.032
## 4620 6.40 0.620 0.12 4.70 0.060
## 4621 6.40 0.380 0.19 4.50 0.038
## 4622 7.50 0.305 0.38 1.40 0.047
## 4623 6.50 0.500 0.22 4.10 0.036
## 4624 6.60 0.400 0.30 5.30 0.038
## 4625 6.40 0.400 0.25 4.20 0.032
## 4626 8.30 0.490 0.23 6.65 0.034
## 4628 6.10 0.190 0.37 2.60 0.041
## 4629 6.10 0.190 0.37 2.60 0.041
## 4630 5.60 0.240 0.34 2.00 0.041
## 4631 5.70 0.250 0.32 12.20 0.041
## 4632 6.60 0.210 0.39 2.30 0.041
## 4634 6.20 0.280 0.41 5.00 0.043
## 4635 5.80 0.290 0.38 10.70 0.038
## 4636 5.80 0.345 0.15 10.80 0.033
## 4637 6.50 0.510 0.25 1.70 0.048
## 4638 6.00 0.240 0.41 1.30 0.036
## 4639 6.50 0.510 0.25 1.70 0.048
## 4640 6.90 0.540 0.26 12.70 0.049
## 4641 6.00 0.240 0.41 1.30 0.036
## 4642 6.60 0.260 0.36 1.20 0.035
## 4643 5.70 0.240 0.30 1.30 0.030
## 4644 6.50 0.210 0.35 5.70 0.043
## 4645 6.80 0.290 0.22 3.40 0.035
## 4646 5.00 0.240 0.34 1.10 0.034
## 4647 5.90 0.180 0.28 1.00 0.037
## 4648 5.80 0.260 0.29 1.00 0.042
## 4650 5.70 0.695 0.06 6.80 0.042
## 4651 5.60 0.695 0.06 6.80 0.042
## 4652 5.70 0.390 0.25 4.90 0.033
## 4653 6.10 0.380 0.47 1.40 0.051
## 4654 6.30 0.360 0.28 2.50 0.035
## 4655 6.00 0.290 0.41 10.80 0.048
## 4656 6.00 0.290 0.41 10.80 0.048
## 4657 6.00 0.290 0.41 10.80 0.048
## 4658 6.00 0.290 0.41 10.80 0.048
## 4659 7.10 0.430 0.25 2.80 0.036
## 4660 6.60 0.250 0.25 1.30 0.040
## 4661 6.60 0.330 0.41 2.00 0.027
## 4662 8.00 0.230 0.41 1.10 0.048
## 4663 7.30 0.170 0.36 8.20 0.028
## 4664 6.00 0.170 0.33 6.00 0.036
## 4665 6.10 0.160 0.34 6.10 0.034
## 4666 7.30 0.170 0.36 8.20 0.028
## 4667 6.40 0.310 0.53 8.80 0.057
## 4668 6.10 0.160 0.34 6.10 0.034
## 4669 6.00 0.170 0.33 6.00 0.036
## 4670 5.90 0.440 0.33 1.20 0.049
## 4671 6.60 0.285 0.49 11.40 0.035
## 4672 4.90 0.335 0.14 1.30 0.036
## 4673 4.90 0.335 0.14 1.30 0.036
## 4674 6.00 0.280 0.52 6.20 0.028
## 4675 5.80 0.350 0.29 3.20 0.034
## 4676 5.70 0.210 0.37 4.50 0.040
## 4677 6.50 0.250 0.32 9.90 0.045
## 4678 6.00 0.280 0.52 6.20 0.028
## 4679 6.60 0.285 0.49 11.40 0.035
## 4680 4.70 0.335 0.14 1.30 0.036
## 4681 6.80 0.630 0.04 1.30 0.058
## 4682 5.60 0.270 0.37 0.90 0.025
## 4683 6.80 0.320 0.33 0.70 0.027
## 4684 6.50 0.330 0.32 1.00 0.041
## 4685 6.00 0.240 0.34 1.00 0.036
## 4686 7.20 0.260 0.32 10.40 0.062
## 4687 6.80 0.630 0.04 1.30 0.058
## 4688 6.70 0.160 0.32 12.50 0.035
## 4689 6.70 0.160 0.32 12.50 0.035
## 4690 6.70 0.160 0.32 12.50 0.035
## 4691 6.70 0.160 0.32 12.50 0.035
## 4692 6.90 0.190 0.31 19.25 0.043
## 4693 6.00 0.360 0.32 1.10 0.053
## 4694 6.70 0.160 0.32 12.50 0.035
## 4695 6.90 0.190 0.31 19.25 0.043
## 4696 6.70 0.350 0.32 9.00 0.032
## 4698 6.70 0.350 0.32 9.00 0.032
## 4700 6.80 0.300 0.33 12.80 0.041
## 4701 6.80 0.300 0.33 12.80 0.041
## 4702 6.40 0.690 0.09 7.60 0.044
## 4703 6.40 0.690 0.09 7.60 0.044
## 4704 5.90 0.120 0.28 1.40 0.037
## 4705 6.30 0.360 0.50 8.30 0.053
## 4706 5.70 0.270 0.16 9.00 0.053
## 4707 6.10 0.220 0.40 1.85 0.031
## 4708 5.60 0.205 0.16 12.55 0.051
## 4709 7.20 0.330 0.28 1.40 0.034
## 4710 5.90 0.210 0.31 1.80 0.033
## 4711 5.40 0.330 0.31 4.00 0.030
## 4712 5.40 0.205 0.16 12.55 0.051
## 4713 5.70 0.270 0.16 9.00 0.053
## 4714 6.40 0.280 0.28 3.00 0.040
## 4715 6.10 0.220 0.40 1.85 0.031
## 4716 6.70 0.150 0.32 7.90 0.034
## 4717 5.50 0.315 0.38 2.60 0.033
## 4718 4.80 0.225 0.38 1.20 0.074
## 4719 5.20 0.240 0.15 7.10 0.043
## 4720 6.70 0.150 0.32 7.90 0.034
## 4721 6.60 0.270 0.32 1.30 0.044
## 4722 6.10 0.320 0.33 10.70 0.036
## 4723 6.00 0.250 0.28 7.70 0.053
## 4724 6.40 0.420 0.46 8.40 0.050
## 4725 6.10 0.320 0.33 10.70 0.036
## 4726 6.90 0.310 0.33 12.70 0.038
## 4727 6.30 0.480 0.48 1.80 0.035
## 4728 6.00 0.250 0.28 7.70 0.053
## 4729 7.20 0.210 0.31 10.50 0.035
## 4730 6.80 0.320 0.43 1.60 0.050
## 4731 7.90 0.300 0.60 1.85 0.048
## 4732 5.30 0.310 0.38 10.50 0.031
## 4733 5.30 0.310 0.38 10.50 0.031
## 4734 5.20 0.185 0.22 1.00 0.030
## 4735 5.50 0.160 0.31 1.20 0.026
## 4736 6.00 0.170 0.36 1.70 0.042
## 4737 6.00 0.160 0.36 1.60 0.042
## 4738 6.10 0.240 0.32 9.00 0.031
## 4739 5.50 0.300 0.25 1.90 0.029
## 4740 5.50 0.160 0.31 1.20 0.026
## 4741 6.00 0.320 0.46 1.50 0.050
## 4742 6.10 0.270 0.31 3.90 0.034
## 4743 6.00 0.270 0.32 3.60 0.035
## 4744 6.00 0.140 0.37 1.20 0.032
## 4745 5.00 0.240 0.19 5.00 0.043
## 4747 6.30 0.230 0.50 10.40 0.043
## 4748 5.60 0.260 0.50 11.40 0.029
## 4749 6.10 0.340 0.24 18.35 0.050
## 4750 6.20 0.350 0.25 18.40 0.051
## 4751 6.00 0.140 0.37 1.20 0.032
## 4752 7.30 0.360 0.62 7.10 0.033
## 4753 5.10 0.250 0.36 1.30 0.035
## 4754 5.50 0.160 0.26 1.50 0.032
## 4755 6.40 0.190 0.35 10.20 0.043
## 4756 6.60 0.290 0.73 2.20 0.027
## 4757 6.00 0.380 0.26 3.50 0.035
## 4758 6.00 0.380 0.26 3.50 0.035
## 4759 6.50 0.200 0.35 3.90 0.040
## 4760 6.60 0.170 0.26 7.40 0.052
## 4761 6.60 0.170 0.26 7.40 0.052
## 4762 6.20 0.150 0.27 11.00 0.035
## 4763 5.90 0.480 0.30 1.50 0.037
## 4764 5.30 0.400 0.25 3.90 0.031
## 4765 5.90 0.260 0.29 5.40 0.046
## 4766 5.20 0.300 0.34 1.50 0.038
## 4767 6.40 0.320 0.25 5.00 0.055
## 4768 6.60 0.190 0.25 1.20 0.052
## 4769 6.80 0.270 0.30 13.00 0.047
## 4770 6.80 0.270 0.30 13.00 0.047
## 4771 6.80 0.270 0.30 13.00 0.047
## 4772 6.80 0.270 0.30 13.00 0.047
## 4773 6.40 0.280 0.45 8.60 0.057
## 4774 5.20 0.210 0.31 1.70 0.048
## 4775 7.10 0.240 0.34 1.20 0.045
## 4776 5.00 0.270 0.40 1.20 0.076
## 4777 5.80 0.270 0.40 1.20 0.076
## 4778 5.90 0.270 0.32 2.00 0.034
## 4779 5.80 0.315 0.19 19.40 0.031
## 4780 6.00 0.590 0.00 0.80 0.037
## 4781 5.80 0.300 0.09 6.30 0.042
## 4782 5.60 0.300 0.10 6.40 0.043
## 4783 6.70 0.300 0.50 12.10 0.045
## 4784 6.70 0.300 0.50 12.10 0.045
## 4785 6.40 0.310 0.31 12.90 0.045
## 4786 6.90 0.250 0.29 2.40 0.038
## 4787 4.40 0.320 0.39 4.30 0.030
## 4788 3.90 0.225 0.40 4.20 0.030
## 4789 6.40 0.310 0.31 12.90 0.045
## 4790 5.50 0.620 0.33 1.70 0.037
## 4791 6.20 0.300 0.42 2.20 0.036
## 4792 6.70 0.300 0.50 12.10 0.045
## 4796 6.40 0.105 0.29 1.10 0.035
## 4797 6.40 0.105 0.29 1.10 0.035
## 4798 5.70 0.330 0.32 1.40 0.043
## 4799 5.90 0.320 0.19 14.50 0.042
## 4800 6.20 0.260 0.20 8.00 0.047
## 4801 6.00 0.200 0.33 1.10 0.039
## 4802 6.40 0.105 0.29 1.10 0.035
## 4803 5.80 0.280 0.34 2.20 0.037
## 4804 6.40 0.310 0.50 5.80 0.038
## 4805 6.00 0.350 0.46 0.90 0.033
## 4806 5.10 0.260 0.34 6.40 0.034
## 4807 6.60 0.280 0.09 10.90 0.051
## 4808 6.00 0.170 0.30 7.30 0.039
## 4809 7.30 0.350 0.67 8.30 0.053
## 4810 6.00 0.260 0.24 1.30 0.053
## 4811 5.40 0.375 0.40 3.30 0.054
## 4812 7.00 0.170 0.42 1.00 0.075
## 4813 5.10 0.260 0.33 1.10 0.027
## 4815 5.70 0.400 0.35 5.10 0.026
## 4817 6.10 0.410 0.20 12.60 0.032
## 4818 5.80 0.385 0.25 3.70 0.031
## 4820 5.70 0.400 0.35 5.10 0.026
## 4822 7.00 0.240 0.47 1.30 0.043
## 4823 6.80 0.230 0.48 1.50 0.036
## 4824 6.50 0.280 0.34 4.60 0.054
## 4825 6.40 0.230 0.35 10.30 0.042
## 4826 6.00 0.340 0.29 6.10 0.046
## 4827 6.00 0.340 0.29 6.10 0.046
## 4828 6.70 0.220 0.33 1.20 0.036
## 4829 6.40 0.230 0.35 10.30 0.042
## 4830 6.00 0.320 0.33 9.90 0.032
## 4831 5.80 0.290 0.27 1.60 0.062
## 4832 5.80 0.380 0.26 1.10 0.058
## 4833 5.90 0.320 0.26 1.50 0.057
## 4834 5.60 0.330 0.28 1.20 0.031
## 4835 5.90 0.370 0.30 1.50 0.033
## 4836 5.60 0.295 0.26 1.10 0.035
## 4837 6.70 0.500 0.36 11.50 0.096
## 4838 6.50 0.280 0.38 7.80 0.031
## 4839 5.30 0.275 0.24 7.40 0.038
## 4840 5.20 0.405 0.15 1.45 0.038
## 4841 6.80 0.340 0.36 8.90 0.029
## 4843 6.20 0.280 0.57 1.00 0.043
## 4844 5.60 0.340 0.25 2.50 0.046
## 4845 4.80 0.290 0.23 1.10 0.044
## 4846 6.60 0.380 0.29 2.40 0.136
## 4847 5.10 0.300 0.30 2.30 0.048
## 4848 4.40 0.540 0.09 5.10 0.038
## 4849 7.00 0.360 0.35 2.50 0.048
## 4850 6.40 0.330 0.44 8.90 0.055
## 4851 7.00 0.360 0.35 2.50 0.048
## 4852 6.40 0.330 0.44 8.90 0.055
## 4853 6.20 0.230 0.38 1.60 0.044
## 4854 5.20 0.250 0.23 1.40 0.047
## 4855 6.20 0.350 0.29 3.90 0.041
## 4856 7.10 0.230 0.39 13.70 0.058
## 4857 7.10 0.230 0.39 13.70 0.058
## 4858 7.50 0.380 0.33 9.20 0.043
## 4859 6.40 0.350 0.51 7.80 0.055
## 4860 6.00 0.430 0.34 7.60 0.045
## 4861 6.00 0.520 0.33 7.70 0.046
## 4862 5.50 0.310 0.29 3.00 0.027
## 4863 5.90 0.220 0.30 1.30 0.052
## 4864 6.20 0.360 0.32 4.00 0.036
## 4865 6.00 0.410 0.23 1.10 0.066
## 4866 6.20 0.355 0.35 2.00 0.046
## 4867 5.70 0.410 0.21 1.90 0.048
## 4868 5.30 0.600 0.34 1.40 0.031
## 4869 5.80 0.230 0.31 4.50 0.046
## 4870 6.60 0.240 0.33 10.10 0.032
## 4871 6.10 0.320 0.28 6.60 0.021
## 4872 5.00 0.200 0.40 1.90 0.015
## 4873 6.00 0.420 0.41 12.40 0.032
## 4874 5.70 0.210 0.32 1.60 0.030
## 4875 5.60 0.200 0.36 2.50 0.048
## 4876 7.40 0.220 0.26 1.20 0.035
## 4877 6.20 0.380 0.42 2.50 0.038
## 4878 5.90 0.540 0.00 0.80 0.032
## 4879 6.20 0.530 0.02 0.90 0.035
## 4880 6.60 0.340 0.40 8.10 0.046
## 4881 6.60 0.340 0.40 8.10 0.046
## 4882 5.00 0.235 0.27 11.75 0.030
## 4883 5.50 0.320 0.13 1.30 0.037
## 4884 4.90 0.470 0.17 1.90 0.035
## 4885 6.50 0.330 0.38 8.30 0.048
## 4886 6.60 0.340 0.40 8.10 0.046
## 4888 6.20 0.410 0.22 1.90 0.023
## 4889 6.80 0.220 0.36 1.20 0.052
## 4890 4.90 0.235 0.27 11.75 0.030
## 4891 6.10 0.340 0.29 2.20 0.036
## 4892 5.70 0.210 0.32 0.90 0.038
## 4893 6.50 0.230 0.38 1.30 0.032
## 4894 6.20 0.210 0.29 1.60 0.039
## 4895 6.60 0.320 0.36 8.00 0.047
## 4896 6.50 0.240 0.19 1.20 0.041
## 4897 5.50 0.290 0.30 1.10 0.022
## 4898 6.00 0.210 0.38 0.80 0.020
## 4899 7.40 0.700 0.00 1.90 0.076
## 4900 7.80 0.880 0.00 2.60 0.098
## 4901 7.80 0.760 0.04 2.30 0.092
## 4902 11.20 0.280 0.56 1.90 0.075
## 4903 7.40 0.700 0.00 1.90 0.076
## 4904 7.40 0.660 0.00 1.80 0.075
## 4905 7.90 0.600 0.06 1.60 0.069
## 4906 7.30 0.650 0.00 1.20 0.065
## 4907 7.80 0.580 0.02 2.00 0.073
## 4908 7.50 0.500 0.36 6.10 0.071
## 4909 6.70 0.580 0.08 1.80 0.097
## 4910 7.50 0.500 0.36 6.10 0.071
## 4911 5.60 0.615 0.00 1.60 0.089
## 4915 8.50 0.280 0.56 1.80 0.092
## 4917 7.40 0.590 0.08 4.40 0.086
## 4919 8.90 0.220 0.48 1.80 0.077
## 4920 7.60 0.390 0.31 2.30 0.082
## 4921 7.90 0.430 0.21 1.60 0.106
## 4922 8.50 0.490 0.11 2.30 0.084
## 4923 6.90 0.400 0.14 2.40 0.085
## 4924 6.30 0.390 0.16 1.40 0.080
## 4925 7.60 0.410 0.24 1.80 0.080
## 4926 7.90 0.430 0.21 1.60 0.106
## 4927 7.10 0.710 0.00 1.90 0.080
## 4928 7.80 0.645 0.00 2.00 0.082
## 4929 6.70 0.675 0.07 2.40 0.089
## 4930 6.90 0.685 0.00 2.50 0.105
## 4931 8.30 0.655 0.12 2.30 0.083
## 4932 6.90 0.605 0.12 10.70 0.073
## 4933 5.20 0.320 0.25 1.80 0.103
## 4934 7.80 0.645 0.00 5.50 0.086
## 4935 7.80 0.600 0.14 2.40 0.086
## 4936 8.10 0.380 0.28 2.10 0.066
## 4938 7.30 0.450 0.36 5.90 0.074
## 4939 7.30 0.450 0.36 5.90 0.074
## 4940 8.80 0.610 0.30 2.80 0.088
## 4943 6.80 0.670 0.02 1.80 0.050
## 4946 8.70 0.290 0.52 1.60 0.113
## 4947 6.40 0.400 0.23 1.60 0.066
## 4948 5.60 0.310 0.37 1.40 0.074
## 4949 8.80 0.660 0.26 1.70 0.074
## 4950 6.60 0.520 0.04 2.20 0.069
## 4951 6.60 0.500 0.04 2.10 0.068
## 4952 8.60 0.380 0.36 3.00 0.081
## 4953 7.60 0.510 0.15 2.80 0.110
## 4954 7.70 0.620 0.04 3.80 0.084
## 4955 10.20 0.420 0.57 3.40 0.070
## 4956 7.50 0.630 0.12 5.10 0.111
## 4957 7.80 0.590 0.18 2.30 0.076
## 4958 7.30 0.390 0.31 2.40 0.074
## 4959 8.80 0.400 0.40 2.20 0.079
## 4960 7.70 0.690 0.49 1.80 0.115
## 4961 7.50 0.520 0.16 1.90 0.085
## 4962 7.00 0.735 0.05 2.00 0.081
## 4963 7.20 0.725 0.05 4.65 0.086
## 4964 7.20 0.725 0.05 4.65 0.086
## 4965 7.50 0.520 0.11 1.50 0.079
## 4966 6.60 0.705 0.07 1.60 0.076
## 4967 9.30 0.320 0.57 2.00 0.074
## 4968 8.00 0.705 0.05 1.90 0.074
## 4969 7.70 0.630 0.08 1.90 0.076
## 4970 7.70 0.670 0.23 2.10 0.088
## 4971 7.70 0.690 0.22 1.90 0.084
## 4972 8.30 0.675 0.26 2.10 0.084
## 4973 9.70 0.320 0.54 2.50 0.094
## 4974 8.80 0.410 0.64 2.20 0.093
## 4975 8.80 0.410 0.64 2.20 0.093
## 4976 6.80 0.785 0.00 2.40 0.104
## 4977 6.70 0.750 0.12 2.00 0.086
## 4979 6.20 0.450 0.20 1.60 0.069
## 4981 7.40 0.500 0.47 2.00 0.086
## 4983 6.30 0.300 0.48 1.80 0.069
## 4984 6.90 0.550 0.15 2.20 0.076
## 4986 7.70 0.490 0.26 1.90 0.062
## 4988 7.00 0.620 0.08 1.80 0.076
## 4989 7.90 0.520 0.26 1.90 0.079
## 4992 7.70 0.490 0.26 1.90 0.062
## 4995 6.80 0.775 0.00 3.00 0.102
## 4996 7.00 0.500 0.25 2.00 0.070
## 4997 7.60 0.900 0.06 2.50 0.079
## 4998 8.10 0.545 0.18 1.90 0.080
## 4999 8.30 0.610 0.30 2.10 0.084
## 5000 7.80 0.500 0.30 1.90 0.075
## 5001 8.10 0.545 0.18 1.90 0.080
## 5002 8.10 0.575 0.22 2.10 0.077
## 5003 7.20 0.490 0.24 2.20 0.070
## 5004 8.10 0.575 0.22 2.10 0.077
## 5006 6.20 0.630 0.31 1.70 0.088
## 5007 8.00 0.330 0.53 2.50 0.091
## 5009 7.80 0.560 0.19 1.80 0.104
## 5010 8.40 0.620 0.09 2.20 0.084
## 5011 8.40 0.600 0.10 2.20 0.085
## 5012 10.10 0.310 0.44 2.30 0.080
## 5013 7.80 0.560 0.19 1.80 0.104
## 5014 9.40 0.400 0.31 2.20 0.090
## 5015 8.30 0.540 0.28 1.90 0.077
## 5016 7.80 0.560 0.12 2.00 0.082
## 5017 8.80 0.550 0.04 2.20 0.119
## 5018 7.00 0.690 0.08 1.80 0.097
## 5020 8.80 0.550 0.04 2.20 0.119
## 5021 7.30 0.695 0.00 2.50 0.075
## 5022 8.00 0.710 0.00 2.60 0.080
## 5023 7.80 0.500 0.17 1.60 0.082
## 5024 9.00 0.620 0.04 1.90 0.146
## 5027 8.00 0.590 0.16 1.80 0.065
## 5028 6.10 0.380 0.15 1.80 0.072
## 5029 8.00 0.745 0.56 2.00 0.118
## 5032 6.60 0.500 0.01 1.50 0.060
## 5034 8.40 0.745 0.11 1.90 0.090
## 5035 8.30 0.715 0.15 1.80 0.089
## 5036 7.20 0.415 0.36 2.00 0.081
## 5037 7.80 0.560 0.19 2.10 0.081
## 5038 7.80 0.560 0.19 2.00 0.081
## 5039 8.40 0.745 0.11 1.90 0.090
## 5040 8.30 0.715 0.15 1.80 0.089
## 5042 6.30 0.390 0.08 1.70 0.066
## 5044 8.10 0.670 0.55 1.80 0.117
## 5045 5.80 0.680 0.02 1.80 0.087
## 5047 6.90 0.490 0.10 2.30 0.074
## 5048 8.20 0.400 0.44 2.80 0.089
## 5049 7.30 0.330 0.47 2.10 0.077
## 5051 7.50 0.600 0.03 1.80 0.095
## 5052 7.50 0.600 0.03 1.80 0.095
## 5053 7.10 0.430 0.42 5.50 0.070
## 5054 7.10 0.430 0.42 5.50 0.071
## 5055 7.10 0.430 0.42 5.50 0.070
## 5056 7.10 0.430 0.42 5.50 0.071
## 5057 7.10 0.680 0.00 2.20 0.073
## 5058 6.80 0.600 0.18 1.90 0.079
## 5059 7.60 0.950 0.03 2.00 0.090
## 5061 7.80 0.530 0.04 1.70 0.076
## 5062 7.40 0.600 0.26 7.30 0.070
## 5063 7.30 0.590 0.26 7.20 0.070
## 5064 7.80 0.630 0.48 1.70 0.100
## 5065 6.80 0.640 0.10 2.10 0.085
## 5066 7.30 0.550 0.03 1.60 0.072
## 5067 6.80 0.630 0.07 2.10 0.089
## 5070 8.00 0.420 0.17 2.00 0.073
## 5071 8.00 0.420 0.17 2.00 0.073
## 5072 7.40 0.620 0.05 1.90 0.068
## 5073 7.30 0.380 0.21 2.00 0.080
## 5074 6.90 0.500 0.04 1.50 0.085
## 5075 7.30 0.380 0.21 2.00 0.080
## 5076 7.50 0.520 0.42 2.30 0.087
## 5077 7.00 0.805 0.00 2.50 0.068
## 5078 8.80 0.610 0.14 2.40 0.067
## 5079 8.80 0.610 0.14 2.40 0.067
## 5081 7.20 0.730 0.02 2.50 0.076
## 5082 6.80 0.610 0.20 1.80 0.077
## 5083 6.70 0.620 0.21 1.90 0.079
## 5084 8.90 0.310 0.57 2.00 0.111
## 5085 7.40 0.390 0.48 2.00 0.082
## 5086 7.70 0.705 0.10 2.60 0.084
## 5087 7.90 0.500 0.33 2.00 0.084
## 5088 7.90 0.490 0.32 1.90 0.082
## 5089 8.20 0.500 0.35 2.90 0.077
## 5090 6.40 0.370 0.25 1.90 0.074
## 5091 6.80 0.630 0.12 3.80 0.099
## 5092 7.60 0.550 0.21 2.20 0.071
## 5093 7.60 0.550 0.21 2.20 0.071
## 5094 7.80 0.590 0.33 2.00 0.074
## 5095 7.30 0.580 0.30 2.40 0.074
## 5099 9.60 0.320 0.47 1.40 0.056
## 5100 8.80 0.370 0.48 2.10 0.097
## 5101 6.80 0.500 0.11 1.50 0.075
## 5102 7.00 0.420 0.35 1.60 0.088
## 5103 7.00 0.430 0.36 1.60 0.089
## 5106 7.80 0.570 0.31 1.80 0.069
## 5107 7.80 0.440 0.28 2.70 0.100
## 5108 11.00 0.300 0.58 2.10 0.054
## 5109 9.70 0.530 0.60 2.00 0.039
## 5110 8.00 0.725 0.24 2.80 0.083
## 5112 8.20 0.570 0.26 2.20 0.060
## 5113 7.80 0.735 0.08 2.40 0.092
## 5114 7.00 0.490 0.49 5.60 0.060
## 5115 8.70 0.625 0.16 2.00 0.101
## 5116 8.10 0.725 0.22 2.20 0.072
## 5117 7.50 0.490 0.19 1.90 0.076
## 5118 7.80 0.530 0.33 2.40 0.080
## 5119 7.80 0.340 0.37 2.00 0.082
## 5120 7.40 0.530 0.26 2.00 0.101
## 5121 6.80 0.610 0.04 1.50 0.057
## 5122 8.60 0.645 0.25 2.00 0.083
## 5123 8.40 0.635 0.36 2.00 0.089
## 5124 7.70 0.430 0.25 2.60 0.073
## 5126 9.00 0.820 0.14 2.60 0.089
## 5127 7.70 0.430 0.25 2.60 0.073
## 5128 6.90 0.520 0.25 2.60 0.081
## 5129 5.20 0.480 0.04 1.60 0.054
## 5130 8.00 0.380 0.06 1.80 0.078
## 5131 8.50 0.370 0.20 2.80 0.090
## 5132 6.90 0.520 0.25 2.60 0.081
## 5134 7.20 0.630 0.00 1.90 0.097
## 5135 7.20 0.630 0.00 1.90 0.097
## 5136 7.20 0.645 0.00 1.90 0.097
## 5137 7.20 0.630 0.00 1.90 0.097
## 5140 12.00 0.380 0.56 2.10 0.093
## 5141 7.70 0.580 0.10 1.80 0.102
## 5144 7.30 0.660 0.00 2.00 0.084
## 5145 7.10 0.680 0.07 1.90 0.075
## 5146 8.20 0.600 0.17 2.30 0.072
## 5147 7.70 0.530 0.06 1.70 0.074
## 5148 7.30 0.660 0.00 2.00 0.084
## 5149 10.80 0.320 0.44 1.60 0.063
## 5150 7.10 0.600 0.00 1.80 0.074
## 5151 11.10 0.350 0.48 3.10 0.090
## 5152 7.70 0.775 0.42 1.90 0.092
## 5153 7.10 0.600 0.00 1.80 0.074
## 5154 8.00 0.570 0.23 3.20 0.073
## 5155 9.40 0.340 0.37 2.20 0.075
## 5156 6.60 0.695 0.00 2.10 0.075
## 5158 10.00 0.310 0.47 2.60 0.085
## 5159 7.90 0.330 0.23 1.70 0.077
## 5161 8.00 0.520 0.03 1.70 0.070
## 5162 7.90 0.370 0.23 1.80 0.077
## 5165 8.10 0.870 0.00 3.30 0.096
## 5167 6.90 0.540 0.04 3.00 0.077
## 5169 7.90 0.545 0.06 4.00 0.087
## 5171 10.90 0.370 0.58 4.00 0.071
## 5172 8.40 0.715 0.20 2.40 0.076
## 5173 7.50 0.650 0.18 7.00 0.088
## 5174 7.90 0.545 0.06 4.00 0.087
## 5175 6.90 0.540 0.04 3.00 0.077
## 5177 10.30 0.320 0.45 6.40 0.073
## 5178 8.90 0.400 0.32 5.60 0.087
## 5181 7.60 0.520 0.12 3.00 0.067
## 5182 8.90 0.400 0.32 5.60 0.087
## 5183 9.90 0.590 0.07 3.40 0.102
## 5184 9.90 0.590 0.07 3.40 0.102
## 5185 12.00 0.450 0.55 2.00 0.073
## 5186 7.50 0.400 0.12 3.00 0.092
## 5187 8.70 0.520 0.09 2.50 0.091
## 5188 11.60 0.420 0.53 3.30 0.105
## 5189 8.70 0.520 0.09 2.50 0.091
## 5191 10.40 0.550 0.23 2.70 0.091
## 5192 6.90 0.360 0.25 2.40 0.098
## 5194 10.80 0.500 0.46 2.50 0.073
## 5195 10.60 0.830 0.37 2.60 0.086
## 5196 7.10 0.630 0.06 2.00 0.083
## 5197 7.20 0.650 0.02 2.30 0.094
## 5198 6.90 0.670 0.06 2.10 0.080
## 5199 7.50 0.530 0.06 2.60 0.086
## 5200 11.10 0.180 0.48 1.50 0.068
## 5201 8.30 0.705 0.12 2.60 0.092
## 5203 8.40 0.650 0.60 2.10 0.112
## 5204 10.30 0.530 0.48 2.50 0.063
## 5205 7.60 0.620 0.32 2.20 0.082
## 5208 7.40 0.290 0.38 1.70 0.062
## 5209 10.30 0.530 0.48 2.50 0.063
## 5210 7.90 0.530 0.24 2.00 0.072
## 5211 9.00 0.460 0.31 2.80 0.093
## 5212 8.60 0.470 0.30 3.00 0.076
## 5213 7.40 0.360 0.29 2.60 0.087
## 5214 7.10 0.350 0.29 2.50 0.096
## 5215 9.60 0.560 0.23 3.40 0.102
## 5216 9.60 0.770 0.12 2.90 0.082
## 5217 9.80 0.660 0.39 3.20 0.083
## 5218 9.60 0.770 0.12 2.90 0.082
## 5219 9.80 0.660 0.39 3.20 0.083
## 5220 9.30 0.610 0.26 3.40 0.090
## 5221 7.80 0.620 0.05 2.30 0.079
## 5222 10.30 0.590 0.42 2.80 0.090
## 5223 10.00 0.490 0.20 11.00 0.071
## 5224 10.00 0.490 0.20 11.00 0.071
## 5225 11.60 0.530 0.66 3.65 0.121
## 5226 10.30 0.440 0.50 4.50 0.107
## 5228 10.70 0.460 0.39 2.00 0.061
## 5231 8.00 0.580 0.28 3.20 0.066
## 5232 8.40 0.560 0.08 2.10 0.105
## 5233 7.90 0.650 0.01 2.50 0.078
## 5235 8.90 0.430 0.45 1.90 0.052
## 5236 7.80 0.430 0.32 2.80 0.080
## 5240 10.60 0.420 0.48 2.70 0.065
## 5241 10.90 0.390 0.47 1.80 0.118
## 5242 10.90 0.390 0.47 1.80 0.118
## 5243 11.90 0.570 0.50 2.60 0.082
## 5244 7.00 0.685 0.00 1.90 0.067
## 5245 6.60 0.815 0.02 2.70 0.072
## 5247 9.60 0.560 0.31 2.80 0.089
## 5248 9.10 0.785 0.00 2.60 0.093
## 5249 10.70 0.670 0.22 2.70 0.107
## 5250 9.10 0.795 0.00 2.60 0.096
## 5251 7.70 0.665 0.00 2.40 0.090
## 5253 6.10 0.210 0.40 1.40 0.066
## 5255 11.50 0.410 0.52 3.00 0.080
## 5256 10.50 0.420 0.66 2.95 0.116
## 5257 11.90 0.430 0.66 3.10 0.109
## 5259 8.20 0.700 0.23 2.00 0.099
## 5260 8.60 0.450 0.31 2.60 0.086
## 5264 10.00 0.420 0.50 3.40 0.107
## 5266 10.40 0.575 0.61 2.60 0.076
## 5267 10.30 0.340 0.52 2.80 0.159
## 5269 6.90 0.765 0.02 2.30 0.063
## 5270 7.90 0.240 0.40 1.60 0.056
## 5271 9.10 0.280 0.48 1.80 0.067
## 5272 7.40 0.550 0.22 2.20 0.106
## 5278 8.30 0.420 0.38 2.50 0.094
## 5279 8.30 0.260 0.42 2.00 0.080
## 5281 8.30 0.260 0.42 2.00 0.080
## 5282 8.30 0.260 0.42 2.00 0.080
## 5283 7.70 0.510 0.28 2.10 0.087
## 5284 7.40 0.630 0.07 2.40 0.090
## 5285 7.80 0.540 0.26 2.00 0.088
## 5286 8.30 0.660 0.15 1.90 0.079
## 5287 7.80 0.460 0.26 1.90 0.088
## 5288 9.60 0.380 0.31 2.50 0.096
## 5291 9.50 0.370 0.52 2.00 0.082
## 5292 8.40 0.665 0.61 2.00 0.112
## 5296 11.50 0.590 0.59 2.60 0.087
## 5297 11.50 0.590 0.59 2.60 0.087
## 5298 8.70 0.765 0.22 2.30 0.064
## 5300 7.70 0.260 0.30 1.70 0.059
## 5301 12.20 0.480 0.54 2.60 0.085
## 5302 11.40 0.600 0.49 2.70 0.085
## 5303 7.70 0.690 0.05 2.70 0.075
## 5304 8.70 0.310 0.46 1.40 0.059
## 5305 9.80 0.440 0.47 2.50 0.063
## 5306 12.00 0.390 0.66 3.00 0.093
## 5309 9.00 0.430 0.34 2.50 0.080
## 5310 9.10 0.450 0.35 2.40 0.080
## 5311 7.10 0.735 0.16 1.90 0.100
## 5312 9.90 0.400 0.53 6.70 0.097
## 5313 8.80 0.520 0.34 2.70 0.087
## 5315 10.60 0.480 0.64 2.20 0.111
## 5316 7.00 0.580 0.12 1.90 0.091
## 5317 11.90 0.380 0.51 2.00 0.121
## 5318 6.80 0.770 0.00 1.80 0.066
## 5319 9.50 0.560 0.33 2.40 0.089
## 5322 10.50 0.240 0.47 2.10 0.066
## 5325 6.40 0.670 0.08 2.10 0.045
## 5326 9.50 0.780 0.22 1.90 0.077
## 5327 9.10 0.520 0.33 1.30 0.070
## 5329 10.50 0.240 0.47 2.10 0.066
## 5330 7.80 0.550 0.35 2.20 0.074
## 5333 10.40 0.410 0.55 3.20 0.076
## 5335 8.00 0.670 0.30 2.00 0.060
## 5336 11.10 0.450 0.73 3.20 0.066
## 5337 10.40 0.410 0.55 3.20 0.076
## 5338 7.00 0.620 0.18 1.50 0.062
## 5340 11.90 0.400 0.65 2.15 0.068
## 5342 10.00 0.440 0.49 2.70 0.077
## 5343 5.30 0.570 0.01 1.70 0.054
## 5344 9.50 0.735 0.10 2.10 0.079
## 5345 12.50 0.380 0.60 2.60 0.081
## 5346 9.30 0.480 0.29 2.10 0.127
## 5347 8.60 0.530 0.22 2.00 0.100
## 5348 11.90 0.390 0.69 2.80 0.095
## 5349 11.90 0.390 0.69 2.80 0.095
## 5351 6.80 0.560 0.03 1.70 0.084
## 5353 7.00 0.230 0.40 1.60 0.063
## 5355 8.90 0.590 0.39 2.30 0.095
## 5356 9.20 0.630 0.21 2.70 0.097
## 5359 9.20 0.430 0.52 2.30 0.083
## 5360 8.30 0.615 0.22 2.60 0.087
## 5361 11.00 0.260 0.68 2.55 0.085
## 5363 11.50 0.315 0.54 2.10 0.084
## 5364 10.00 0.290 0.40 2.90 0.098
## 5365 10.30 0.500 0.42 2.00 0.069
## 5367 11.40 0.360 0.69 2.10 0.090
## 5370 9.60 0.540 0.42 2.40 0.081
## 5372 9.90 0.350 0.55 2.10 0.062
## 5373 10.50 0.280 0.51 1.70 0.080
## 5374 9.60 0.680 0.24 2.20 0.087
## 5375 9.30 0.270 0.41 2.00 0.091
## 5377 9.60 0.680 0.24 2.20 0.087
## 5378 9.40 0.685 0.11 2.70 0.077
## 5380 9.40 0.300 0.56 2.80 0.080
## 5384 10.20 0.670 0.39 1.90 0.054
## 5385 10.20 0.670 0.39 1.90 0.054
## 5386 10.20 0.645 0.36 1.80 0.053
## 5388 9.30 0.390 0.40 2.60 0.073
## 5389 9.30 0.775 0.27 2.80 0.078
## 5390 9.20 0.410 0.50 2.50 0.055
## 5391 8.90 0.400 0.51 2.60 0.052
## 5393 6.50 0.390 0.23 8.30 0.051
## 5394 10.70 0.350 0.53 2.60 0.070
## 5395 7.80 0.520 0.25 1.90 0.081
## 5396 7.20 0.340 0.32 2.50 0.090
## 5397 10.70 0.350 0.53 2.60 0.070
## 5399 7.80 0.520 0.25 1.90 0.081
## 5402 10.50 0.260 0.47 1.90 0.078
## 5404 10.20 0.490 0.63 2.90 0.072
## 5405 10.40 0.240 0.46 1.80 0.075
## 5406 11.20 0.670 0.55 2.30 0.084
## 5407 10.00 0.590 0.31 2.20 0.090
## 5410 10.00 0.590 0.31 2.20 0.090
## 5411 10.70 0.400 0.48 2.10 0.125
## 5412 10.50 0.510 0.64 2.40 0.107
## 5413 10.50 0.510 0.64 2.40 0.107
## 5417 10.90 0.210 0.49 2.80 0.088
## 5418 7.30 0.365 0.49 2.50 0.088
## 5419 9.80 0.250 0.49 2.70 0.088
## 5420 7.60 0.410 0.49 2.00 0.088
## 5421 8.20 0.390 0.49 2.30 0.099
## 5422 9.30 0.400 0.49 2.50 0.085
## 5423 9.20 0.430 0.49 2.40 0.086
## 5424 10.40 0.640 0.24 2.80 0.105
## 5425 7.30 0.365 0.49 2.50 0.088
## 5426 7.00 0.380 0.49 2.50 0.097
## 5427 8.20 0.420 0.49 2.60 0.084
## 5428 9.90 0.630 0.24 2.40 0.077
## 5429 9.10 0.220 0.24 2.10 0.078
## 5430 11.90 0.380 0.49 2.70 0.098
## 5431 11.90 0.380 0.49 2.70 0.098
## 5433 10.00 0.480 0.24 2.70 0.102
## 5434 9.10 0.220 0.24 2.10 0.078
## 5435 9.90 0.630 0.24 2.40 0.077
## 5436 8.10 0.825 0.24 2.10 0.084
## 5439 9.20 0.590 0.24 3.30 0.101
## 5440 9.50 0.460 0.49 6.30 0.064
## 5441 9.30 0.715 0.24 2.10 0.070
## 5442 11.20 0.660 0.24 2.50 0.085
## 5444 9.10 0.470 0.49 2.60 0.094
## 5445 7.50 0.550 0.24 2.00 0.078
## 5446 10.60 0.310 0.49 2.50 0.067
## 5447 12.40 0.350 0.49 2.60 0.079
## 5448 9.00 0.530 0.49 1.90 0.171
## 5449 6.80 0.510 0.01 2.10 0.074
## 5450 9.40 0.430 0.24 2.80 0.092
## 5451 9.50 0.460 0.24 2.70 0.092
## 5460 9.00 0.440 0.49 2.40 0.078
## 5461 9.00 0.540 0.49 2.90 0.094
## 5462 7.60 0.290 0.49 2.70 0.092
## 5468 6.20 0.360 0.24 2.20 0.095
## 5469 11.50 0.350 0.49 3.30 0.070
## 5470 6.20 0.360 0.24 2.20 0.095
## 5471 10.20 0.240 0.49 2.40 0.075
## 5472 10.50 0.590 0.49 2.10 0.070
## 5473 10.60 0.340 0.49 3.20 0.078
## 5475 9.90 0.500 0.24 2.30 0.103
## 5476 8.80 0.440 0.49 2.80 0.083
## 5477 8.80 0.470 0.49 2.90 0.085
## 5478 10.60 0.310 0.49 2.20 0.063
## 5481 11.70 0.490 0.49 2.20 0.083
## 5482 12.00 0.280 0.49 1.90 0.074
## 5484 7.60 0.510 0.24 2.40 0.091
## 5485 11.10 0.310 0.49 2.70 0.094
## 5486 7.30 0.730 0.24 1.90 0.108
## 5488 10.20 0.290 0.49 2.60 0.059
## 5489 9.00 0.450 0.49 2.60 0.084
## 5490 6.60 0.390 0.49 1.70 0.070
## 5491 9.00 0.450 0.49 2.60 0.084
## 5492 9.90 0.490 0.58 3.50 0.094
## 5493 7.90 0.720 0.17 2.60 0.096
## 5494 8.90 0.595 0.41 7.90 0.086
## 5497 8.50 0.585 0.18 2.10 0.078
## 5499 8.20 0.915 0.27 2.10 0.088
## 5501 7.70 0.835 0.00 2.60 0.081
## 5503 8.30 0.580 0.13 2.90 0.096
## 5504 8.30 0.600 0.13 2.60 0.085
## 5505 9.40 0.410 0.48 4.60 0.072
## 5506 8.80 0.480 0.41 3.30 0.092
## 5509 8.80 0.240 0.54 2.50 0.083
## 5511 7.50 0.640 0.00 2.40 0.077
## 5512 8.20 0.390 0.38 1.50 0.058
## 5514 9.60 0.600 0.50 2.30 0.079
## 5515 9.60 0.600 0.50 2.30 0.079
## 5516 11.50 0.310 0.51 2.20 0.079
## 5517 11.40 0.460 0.50 2.70 0.122
## 5518 11.30 0.370 0.41 2.30 0.088
## 5519 8.30 0.540 0.24 3.40 0.076
## 5520 8.20 0.560 0.23 3.40 0.078
## 5521 10.00 0.580 0.22 1.90 0.080
## 5522 7.90 0.510 0.25 2.90 0.077
## 5523 6.80 0.690 0.00 5.60 0.124
## 5524 6.80 0.690 0.00 5.60 0.124
## 5525 8.80 0.600 0.29 2.20 0.098
## 5526 8.80 0.600 0.29 2.20 0.098
## 5527 8.70 0.540 0.26 2.50 0.097
## 5528 7.60 0.685 0.23 2.30 0.111
## 5529 8.70 0.540 0.26 2.50 0.097
## 5530 10.40 0.280 0.54 2.70 0.105
## 5531 7.60 0.410 0.14 3.00 0.087
## 5533 7.90 0.350 0.21 1.90 0.073
## 5537 7.70 0.915 0.12 2.20 0.143
## 5539 9.90 0.540 0.45 2.30 0.071
## 5540 9.50 0.590 0.44 2.30 0.071
## 5541 9.90 0.540 0.45 2.30 0.071
## 5542 9.50 0.590 0.44 2.30 0.071
## 5543 9.90 0.540 0.45 2.30 0.071
## 5544 7.80 0.640 0.10 6.00 0.115
## 5545 7.30 0.670 0.05 3.60 0.107
## 5546 8.30 0.845 0.01 2.20 0.070
## 5547 8.70 0.480 0.30 2.80 0.066
## 5548 6.70 0.420 0.27 8.60 0.068
## 5549 10.70 0.430 0.39 2.20 0.106
## 5553 8.60 0.470 0.47 2.40 0.074
## 5554 9.70 0.550 0.17 2.90 0.087
## 5555 10.70 0.430 0.39 2.20 0.106
## 5556 12.00 0.500 0.59 1.40 0.073
## 5557 7.20 0.520 0.07 1.40 0.074
## 5558 7.10 0.840 0.02 4.40 0.096
## 5559 7.20 0.520 0.07 1.40 0.074
## 5560 7.50 0.420 0.31 1.60 0.080
## 5561 7.20 0.570 0.06 1.60 0.076
## 5562 10.10 0.280 0.46 1.80 0.050
## 5563 12.10 0.400 0.52 2.00 0.092
## 5564 9.40 0.590 0.14 2.00 0.084
## 5566 11.30 0.340 0.45 2.00 0.082
## 5567 10.00 0.730 0.43 2.30 0.059
## 5568 11.30 0.340 0.45 2.00 0.082
## 5569 6.90 0.400 0.24 2.50 0.083
## 5570 8.20 0.730 0.21 1.70 0.074
## 5572 8.20 0.730 0.21 1.70 0.074
## 5573 10.80 0.400 0.41 2.20 0.084
## 5574 9.30 0.410 0.39 2.20 0.064
## 5575 10.80 0.400 0.41 2.20 0.084
## 5576 8.60 0.800 0.11 2.30 0.084
## 5577 8.30 0.780 0.10 2.60 0.081
## 5578 10.80 0.260 0.45 3.30 0.060
## 5580 8.00 0.450 0.23 2.20 0.094
## 5581 8.50 0.460 0.31 2.25 0.078
## 5582 8.10 0.780 0.23 2.60 0.059
## 5584 8.10 0.780 0.23 2.60 0.059
## 5585 7.10 0.650 0.18 1.80 0.070
## 5586 9.10 0.640 0.23 3.10 0.095
## 5587 7.70 0.660 0.04 1.60 0.039
## 5592 9.00 0.480 0.32 2.80 0.084
## 5593 9.00 0.470 0.31 2.70 0.084
## 5595 7.00 0.650 0.02 2.10 0.066
## 5596 7.00 0.650 0.02 2.10 0.066
## 5597 9.40 0.615 0.28 3.20 0.087
## 5598 11.80 0.380 0.55 2.10 0.071
## 5600 7.00 0.650 0.02 2.10 0.066
## 5601 7.00 0.640 0.02 2.10 0.067
## 5602 7.50 0.380 0.48 2.60 0.073
## 5603 9.10 0.765 0.04 1.60 0.078
## 5605 7.00 0.780 0.08 2.00 0.093
## 5606 7.40 0.490 0.19 3.00 0.077
## 5607 7.80 0.545 0.12 2.50 0.068
## 5608 9.70 0.310 0.47 1.60 0.062
## 5610 8.90 0.565 0.34 3.00 0.093
## 5611 8.70 0.690 0.00 3.20 0.084
## 5612 8.00 0.430 0.36 2.30 0.075
## 5613 9.90 0.740 0.28 2.60 0.078
## 5614 7.20 0.490 0.18 2.70 0.069
## 5615 8.00 0.430 0.36 2.30 0.075
## 5616 7.60 0.460 0.11 2.60 0.079
## 5617 8.40 0.560 0.04 2.00 0.082
## 5618 7.10 0.660 0.00 3.90 0.086
## 5619 8.40 0.560 0.04 2.00 0.082
## 5620 8.90 0.480 0.24 2.85 0.094
## 5621 7.60 0.420 0.08 2.70 0.084
## 5624 9.00 0.660 0.17 3.00 0.077
## 5626 6.40 0.570 0.02 1.80 0.067
## 5627 6.40 0.570 0.02 1.80 0.067
## 5631 7.30 0.835 0.03 2.10 0.092
## 5632 7.00 0.450 0.34 2.70 0.082
## 5633 7.70 0.560 0.20 2.00 0.075
## 5634 7.70 0.965 0.10 2.10 0.112
## 5635 7.70 0.965 0.10 2.10 0.112
## 5636 8.20 0.590 0.00 2.50 0.093
## 5637 9.00 0.460 0.23 2.80 0.092
## 5638 9.00 0.690 0.00 2.40 0.088
## 5639 8.30 0.760 0.29 4.20 0.075
## 5640 9.20 0.530 0.24 2.60 0.078
## 5641 6.50 0.615 0.00 1.90 0.065
## 5642 11.60 0.410 0.58 2.80 0.096
## 5643 11.10 0.390 0.54 2.70 0.095
## 5644 7.30 0.510 0.18 2.10 0.070
## 5645 8.20 0.340 0.38 2.50 0.080
## 5646 8.60 0.330 0.40 2.60 0.083
## 5647 7.20 0.500 0.18 2.10 0.071
## 5648 7.30 0.510 0.18 2.10 0.070
## 5649 8.30 0.650 0.10 2.90 0.089
## 5650 8.30 0.650 0.10 2.90 0.089
## 5651 7.60 0.540 0.13 2.50 0.097
## 5652 8.30 0.650 0.10 2.90 0.089
## 5656 8.10 0.870 0.00 2.20 0.084
## 5657 8.10 0.870 0.00 2.20 0.084
## 5658 8.80 0.420 0.21 2.50 0.092
## 5659 9.00 0.580 0.25 2.80 0.075
## 5660 9.30 0.655 0.26 2.00 0.096
## 5661 8.80 0.700 0.00 1.70 0.069
## 5662 9.30 0.655 0.26 2.00 0.096
## 5663 9.10 0.680 0.11 2.80 0.093
## 5664 9.20 0.670 0.10 3.00 0.091
## 5665 8.80 0.590 0.18 2.90 0.089
## 5666 7.50 0.600 0.32 2.70 0.103
## 5667 7.10 0.590 0.02 2.30 0.082
## 5668 7.90 0.720 0.01 1.90 0.076
## 5669 7.10 0.590 0.02 2.30 0.082
## 5670 9.40 0.685 0.26 2.40 0.082
## 5671 9.50 0.570 0.27 2.30 0.082
## 5672 7.90 0.400 0.29 1.80 0.157
## 5673 7.90 0.400 0.30 1.80 0.157
## 5677 8.30 0.430 0.30 3.40 0.079
## 5678 7.10 0.520 0.03 2.60 0.076
## 5680 6.50 0.460 0.14 2.40 0.114
## 5681 9.00 0.820 0.05 2.40 0.081
## 5682 6.50 0.460 0.14 2.40 0.114
## 5683 7.10 0.590 0.01 2.50 0.077
## 5684 9.90 0.350 0.41 2.30 0.083
## 5685 9.90 0.350 0.41 2.30 0.083
## 5686 10.00 0.560 0.24 2.20 0.079
## 5687 10.00 0.560 0.24 2.20 0.079
## 5688 8.60 0.630 0.17 2.90 0.099
## 5689 7.40 0.370 0.43 2.60 0.082
## 5690 8.80 0.640 0.17 2.90 0.084
## 5691 7.10 0.610 0.02 2.50 0.081
## 5692 7.70 0.600 0.00 2.60 0.055
## 5693 10.10 0.270 0.54 2.30 0.065
## 5695 8.70 0.460 0.31 2.50 0.126
## 5696 9.30 0.370 0.44 1.60 0.038
## 5697 9.40 0.500 0.34 3.60 0.082
## 5698 9.40 0.500 0.34 3.60 0.082
## 5699 7.20 0.610 0.08 4.00 0.082
## 5700 8.60 0.550 0.09 3.30 0.068
## 5702 7.70 0.560 0.08 2.50 0.114
## 5703 8.40 0.520 0.22 2.70 0.084
## 5704 8.20 0.280 0.40 2.40 0.052
## 5705 8.40 0.250 0.39 2.00 0.041
## 5706 8.20 0.280 0.40 2.40 0.052
## 5707 7.40 0.530 0.12 1.90 0.165
## 5708 7.60 0.480 0.31 2.80 0.070
## 5709 7.30 0.490 0.10 2.60 0.068
## 5711 10.80 0.450 0.33 2.50 0.099
## 5712 6.90 0.390 0.24 2.10 0.102
## 5714 10.80 0.450 0.33 2.50 0.099
## 5715 9.80 0.510 0.19 3.20 0.081
## 5716 10.80 0.290 0.42 1.60 0.084
## 5717 7.10 0.715 0.00 2.35 0.071
## 5718 9.10 0.660 0.15 3.20 0.097
## 5719 7.00 0.685 0.00 1.90 0.099
## 5721 6.70 0.540 0.13 2.00 0.076
## 5722 6.70 0.540 0.13 2.00 0.076
## 5723 7.10 0.480 0.28 2.80 0.068
## 5724 7.10 0.460 0.14 2.80 0.076
## 5725 7.50 0.270 0.34 2.30 0.050
## 5726 7.10 0.460 0.14 2.80 0.076
## 5727 7.80 0.570 0.09 2.30 0.065
## 5728 5.90 0.610 0.08 2.10 0.071
## 5729 7.50 0.685 0.07 2.50 0.058
## 5730 5.90 0.610 0.08 2.10 0.071
## 5731 10.40 0.440 0.42 1.50 0.145
## 5733 8.80 0.685 0.26 1.60 0.088
## 5734 7.60 0.665 0.10 1.50 0.066
## 5735 6.70 0.280 0.28 2.40 0.012
## 5736 6.70 0.280 0.28 2.40 0.012
## 5737 10.10 0.310 0.35 1.60 0.075
## 5738 6.00 0.500 0.04 2.20 0.092
## 5739 11.10 0.420 0.47 2.65 0.085
## 5740 6.60 0.660 0.00 3.00 0.115
## 5741 10.60 0.500 0.45 2.60 0.119
## 5742 7.10 0.685 0.35 2.00 0.088
## 5743 9.90 0.250 0.46 1.70 0.062
## 5744 6.40 0.640 0.21 1.80 0.081
## 5745 6.40 0.640 0.21 1.80 0.081
## 5746 7.40 0.680 0.16 1.80 0.078
## 5747 6.40 0.640 0.21 1.80 0.081
## 5748 6.40 0.630 0.21 1.60 0.080
## 5749 9.30 0.430 0.44 1.90 0.085
## 5750 9.30 0.430 0.44 1.90 0.085
## 5751 8.00 0.420 0.32 2.50 0.080
## 5752 9.30 0.360 0.39 1.50 0.080
## 5753 9.30 0.360 0.39 1.50 0.080
## 5754 7.60 0.735 0.02 2.50 0.071
## 5755 9.30 0.360 0.39 1.50 0.080
## 5756 8.20 0.260 0.34 2.50 0.073
## 5757 11.70 0.280 0.47 1.70 0.054
## 5758 6.80 0.560 0.22 1.80 0.074
## 5759 7.20 0.620 0.06 2.70 0.077
## 5761 7.50 0.420 0.32 2.70 0.067
## 5762 7.20 0.620 0.06 2.50 0.078
## 5763 7.20 0.620 0.06 2.70 0.077
## 5764 7.20 0.635 0.07 2.60 0.077
## 5765 6.80 0.490 0.22 2.30 0.071
## 5766 6.90 0.510 0.23 2.00 0.072
## 5767 6.80 0.560 0.22 1.80 0.074
## 5768 7.60 0.630 0.03 2.00 0.080
## 5769 7.70 0.715 0.01 2.10 0.064
## 5770 6.90 0.560 0.03 1.50 0.086
## 5771 7.30 0.350 0.24 2.00 0.067
## 5772 9.10 0.210 0.37 1.60 0.067
## 5773 10.40 0.380 0.46 2.10 0.104
## 5774 8.80 0.310 0.40 2.80 0.109
## 5775 7.10 0.470 0.00 2.20 0.067
## 5776 7.70 0.715 0.01 2.10 0.064
## 5777 8.80 0.610 0.19 4.00 0.094
## 5778 7.20 0.600 0.04 2.50 0.076
## 5779 9.20 0.560 0.18 1.60 0.078
## 5780 7.60 0.715 0.00 2.10 0.068
## 5782 7.20 0.600 0.04 2.50 0.076
## 5783 8.80 0.610 0.19 4.00 0.094
## 5784 8.90 0.750 0.14 2.50 0.086
## 5785 9.00 0.800 0.12 2.40 0.083
## 5786 10.70 0.520 0.38 2.60 0.066
## 5787 6.80 0.570 0.00 2.50 0.072
## 5789 7.20 0.340 0.24 2.00 0.071
## 5790 7.20 0.660 0.03 2.30 0.078
## 5791 10.10 0.450 0.23 1.90 0.082
## 5792 7.20 0.660 0.03 2.30 0.078
## 5793 7.20 0.630 0.03 2.20 0.080
## 5794 7.10 0.590 0.01 2.30 0.080
## 5795 8.30 0.310 0.39 2.40 0.078
## 5796 7.10 0.590 0.01 2.30 0.080
## 5797 8.30 0.310 0.39 2.40 0.078
## 5799 8.90 0.310 0.36 2.60 0.056
## 5800 7.40 0.635 0.10 2.40 0.080
## 5801 7.40 0.635 0.10 2.40 0.080
## 5802 6.80 0.590 0.06 6.00 0.060
## 5803 6.80 0.590 0.06 6.00 0.060
## 5804 9.20 0.580 0.20 3.00 0.081
## 5805 7.20 0.540 0.27 2.60 0.084
## 5806 6.10 0.560 0.00 2.20 0.079
## 5807 7.40 0.520 0.13 2.40 0.078
## 5808 7.30 0.305 0.39 1.20 0.059
## 5810 9.10 0.280 0.46 9.00 0.114
## 5811 10.00 0.460 0.44 2.90 0.065
## 5812 9.40 0.395 0.46 4.60 0.094
## 5813 7.30 0.305 0.39 1.20 0.059
## 5814 8.60 0.315 0.40 2.20 0.079
## 5816 6.80 0.410 0.31 8.80 0.084
## 5817 8.40 0.360 0.32 2.20 0.081
## 5818 8.40 0.620 0.12 1.80 0.072
## 5819 9.60 0.410 0.37 2.30 0.091
## 5820 8.40 0.360 0.32 2.20 0.081
## 5821 8.40 0.620 0.12 1.80 0.072
## 5822 6.80 0.410 0.31 8.80 0.084
## 5823 8.60 0.470 0.27 2.30 0.055
## 5824 8.60 0.220 0.36 1.90 0.064
## 5826 8.40 0.670 0.19 2.20 0.093
## 5827 8.60 0.470 0.27 2.30 0.055
## 5828 8.70 0.330 0.38 3.30 0.063
## 5829 6.60 0.610 0.01 1.90 0.080
## 5830 7.40 0.610 0.01 2.00 0.074
## 5831 7.60 0.400 0.29 1.90 0.078
## 5832 7.40 0.610 0.01 2.00 0.074
## 5833 6.60 0.610 0.01 1.90 0.080
## 5834 8.80 0.300 0.38 2.30 0.060
## 5835 8.80 0.300 0.38 2.30 0.060
## 5836 12.00 0.630 0.50 1.40 0.071
## 5837 7.20 0.380 0.38 2.80 0.068
## 5838 6.20 0.460 0.17 1.60 0.073
## 5839 9.60 0.330 0.52 2.20 0.074
## 5840 9.90 0.270 0.49 5.00 0.082
## 5841 10.10 0.430 0.40 2.60 0.092
## 5842 9.80 0.500 0.34 2.30 0.094
## 5843 8.30 0.300 0.49 3.80 0.090
## 5844 10.20 0.440 0.42 2.00 0.071
## 5845 10.20 0.440 0.58 4.10 0.092
## 5846 8.30 0.280 0.48 2.10 0.093
## 5847 8.90 0.120 0.45 1.80 0.075
## 5848 8.90 0.120 0.45 1.80 0.075
## 5849 8.90 0.120 0.45 1.80 0.075
## 5850 8.30 0.280 0.48 2.10 0.093
## 5851 8.20 0.310 0.40 2.20 0.058
## 5852 10.20 0.340 0.48 2.10 0.052
## 5853 7.60 0.430 0.40 2.70 0.082
## 5854 8.50 0.210 0.52 1.90 0.090
## 5855 9.00 0.360 0.52 2.10 0.111
## 5856 9.50 0.370 0.52 2.00 0.088
## 5857 6.40 0.570 0.12 2.30 0.120
## 5858 8.00 0.590 0.05 2.00 0.089
## 5859 8.50 0.470 0.27 1.90 0.058
## 5860 7.10 0.560 0.14 1.60 0.078
## 5861 6.60 0.570 0.02 2.10 0.115
## 5862 8.80 0.270 0.39 2.00 0.100
## 5863 8.50 0.470 0.27 1.90 0.058
## 5864 8.30 0.340 0.40 2.40 0.065
## 5865 9.00 0.380 0.41 2.40 0.103
## 5866 8.50 0.660 0.20 2.10 0.097
## 5867 9.00 0.400 0.43 2.40 0.068
## 5868 6.70 0.560 0.09 2.90 0.079
## 5869 10.40 0.260 0.48 1.90 0.066
## 5870 10.40 0.260 0.48 1.90 0.066
## 5871 10.10 0.380 0.50 2.40 0.104
## 5872 8.50 0.340 0.44 1.70 0.079
## 5873 8.80 0.330 0.41 5.90 0.073
## 5874 7.20 0.410 0.30 2.10 0.083
## 5875 7.20 0.410 0.30 2.10 0.083
## 5876 8.40 0.590 0.29 2.60 0.109
## 5877 7.00 0.400 0.32 3.60 0.061
## 5879 9.10 0.500 0.30 1.90 0.065
## 5880 9.50 0.860 0.26 1.90 0.079
## 5882 9.10 0.500 0.30 1.90 0.065
## 5884 7.40 0.580 0.00 2.00 0.064
## 5885 9.80 0.340 0.39 1.40 0.066
## 5886 7.10 0.360 0.30 1.60 0.080
## 5887 7.70 0.390 0.12 1.70 0.097
## 5888 9.70 0.295 0.40 1.50 0.073
## 5889 7.70 0.390 0.12 1.70 0.097
## 5890 7.10 0.340 0.28 2.00 0.082
## 5891 6.50 0.400 0.10 2.00 0.076
## 5892 7.10 0.340 0.28 2.00 0.082
## 5893 10.00 0.350 0.45 2.50 0.092
## 5894 7.70 0.600 0.06 2.00 0.079
## 5895 5.60 0.660 0.00 2.20 0.087
## 5896 5.60 0.660 0.00 2.20 0.087
## 5898 6.40 0.690 0.00 1.65 0.055
## 5899 7.50 0.430 0.30 2.20 0.062
## 5900 9.90 0.350 0.38 1.50 0.058
## 5901 9.10 0.290 0.33 2.05 0.063
## 5902 6.80 0.360 0.32 1.80 0.067
## 5903 8.20 0.430 0.29 1.60 0.081
## 5904 6.80 0.360 0.32 1.80 0.067
## 5905 9.10 0.290 0.33 2.05 0.063
## 5906 9.10 0.300 0.34 2.00 0.064
## 5907 8.90 0.350 0.40 3.60 0.110
## 5908 9.60 0.500 0.36 2.80 0.116
## 5909 8.90 0.280 0.45 1.70 0.067
## 5910 8.90 0.320 0.31 2.00 0.088
## 5912 7.50 0.710 0.00 1.60 0.092
## 5913 8.00 0.580 0.16 2.00 0.120
## 5914 10.50 0.390 0.46 2.20 0.075
## 5915 8.90 0.380 0.40 2.20 0.068
## 5916 8.00 0.180 0.37 0.90 0.049
## 5917 8.00 0.180 0.37 0.90 0.049
## 5918 7.00 0.500 0.14 1.80 0.078
## 5921 7.00 0.510 0.09 2.10 0.062
## 5922 8.20 0.320 0.42 2.30 0.098
## 5923 7.70 0.580 0.01 1.80 0.088
## 5924 8.60 0.830 0.00 2.80 0.095
## 5925 7.90 0.310 0.32 1.90 0.066
## 5926 6.40 0.795 0.00 2.20 0.065
## 5927 7.20 0.340 0.21 2.50 0.075
## 5928 7.70 0.580 0.01 1.80 0.088
## 5929 7.10 0.590 0.00 2.10 0.091
## 5930 7.30 0.550 0.01 1.80 0.093
## 5931 8.10 0.820 0.00 4.10 0.095
## 5932 7.50 0.570 0.08 2.60 0.089
## 5933 8.90 0.745 0.18 2.50 0.077
## 5934 10.10 0.370 0.34 2.40 0.085
## 5935 7.60 0.310 0.34 2.50 0.082
## 5936 7.30 0.910 0.10 1.80 0.074
## 5937 8.70 0.410 0.41 6.20 0.078
## 5938 8.90 0.500 0.21 2.20 0.088
## 5939 7.40 0.965 0.00 2.20 0.088
## 5940 6.90 0.490 0.19 1.70 0.079
## 5941 8.90 0.500 0.21 2.20 0.088
## 5942 9.50 0.390 0.41 8.90 0.069
## 5943 6.40 0.390 0.33 3.30 0.046
## 5944 6.90 0.440 0.00 1.40 0.070
## 5945 7.60 0.780 0.00 1.70 0.076
## 5946 7.10 0.430 0.17 1.80 0.082
## 5947 9.30 0.490 0.36 1.70 0.081
## 5948 9.30 0.500 0.36 1.80 0.084
## 5949 7.10 0.430 0.17 1.80 0.082
## 5951 5.60 0.605 0.05 2.40 0.073
## 5952 8.30 0.330 0.42 2.30 0.070
## 5953 8.20 0.640 0.27 2.00 0.095
## 5954 8.20 0.640 0.27 2.00 0.095
## 5955 8.90 0.480 0.53 4.00 0.101
## 5956 7.60 0.420 0.25 3.90 0.104
## 5957 9.90 0.530 0.57 2.40 0.093
## 5958 8.90 0.480 0.53 4.00 0.101
## 5959 11.60 0.230 0.57 1.80 0.074
## 5960 9.10 0.400 0.50 1.80 0.071
## 5961 8.00 0.380 0.44 1.90 0.098
## 5962 10.20 0.290 0.65 2.40 0.075
## 5963 8.20 0.740 0.09 2.00 0.067
## 5964 7.70 0.610 0.18 2.40 0.083
## 5965 6.60 0.520 0.08 2.40 0.070
## 5966 11.10 0.310 0.53 2.20 0.060
## 5967 11.10 0.310 0.53 2.20 0.060
## 5968 8.00 0.620 0.35 2.80 0.086
## 5969 9.30 0.330 0.45 1.50 0.057
## 5970 7.50 0.770 0.20 8.10 0.098
## 5971 7.20 0.350 0.26 1.80 0.083
## 5972 8.00 0.620 0.33 2.70 0.088
## 5973 7.50 0.770 0.20 8.10 0.098
## 5974 9.10 0.250 0.34 2.00 0.071
## 5975 9.90 0.320 0.56 2.00 0.073
## 5976 8.60 0.370 0.65 6.40 0.080
## 5977 8.60 0.370 0.65 6.40 0.080
## 5979 10.30 0.270 0.56 1.40 0.047
## 5981 7.20 0.380 0.30 1.80 0.073
## 5982 8.70 0.420 0.45 2.40 0.072
## 5983 7.20 0.380 0.30 1.80 0.073
## 5984 6.80 0.480 0.08 1.80 0.074
## 5985 8.50 0.340 0.40 4.70 0.055
## 5986 7.90 0.190 0.42 1.60 0.057
## 5987 11.60 0.410 0.54 1.50 0.095
## 5988 11.60 0.410 0.54 1.50 0.095
## 5989 10.00 0.260 0.54 1.90 0.083
## 5990 7.90 0.340 0.42 2.00 0.086
## 5991 7.00 0.540 0.09 2.00 0.081
## 5992 9.20 0.310 0.36 2.20 0.079
## 5993 6.60 0.725 0.09 5.50 0.117
## 5994 9.40 0.400 0.47 2.50 0.087
## 5995 6.60 0.725 0.09 5.50 0.117
## 5996 8.60 0.520 0.38 1.50 0.096
## 5998 8.60 0.520 0.38 1.50 0.096
## 5999 8.40 0.340 0.42 2.10 0.072
## 6000 7.40 0.490 0.27 2.10 0.071
## 6001 6.10 0.480 0.09 1.70 0.078
## 6002 7.40 0.490 0.27 2.10 0.071
## 6003 8.00 0.480 0.34 2.20 0.073
## 6004 6.30 0.570 0.28 2.10 0.048
## 6005 8.20 0.230 0.42 1.90 0.069
## 6006 9.10 0.300 0.41 2.00 0.068
## 6007 8.10 0.780 0.10 3.30 0.090
## 6008 10.80 0.470 0.43 2.10 0.171
## 6009 8.30 0.530 0.00 1.40 0.070
## 6011 7.90 0.330 0.41 1.50 0.056
## 6012 8.90 0.240 0.39 1.60 0.074
## 6013 5.00 0.400 0.50 4.30 0.046
## 6014 7.00 0.690 0.07 2.50 0.091
## 6015 7.00 0.690 0.07 2.50 0.091
## 6016 7.00 0.690 0.07 2.50 0.091
## 6017 7.10 0.390 0.12 2.10 0.065
## 6018 5.60 0.660 0.00 2.50 0.066
## 6019 7.90 0.540 0.34 2.50 0.076
## 6020 6.60 0.500 0.00 1.80 0.062
## 6021 6.30 0.470 0.00 1.40 0.055
## 6022 10.70 0.400 0.37 1.90 0.081
## 6023 6.50 0.580 0.00 2.20 0.096
## 6024 8.80 0.240 0.35 1.70 0.055
## 6025 5.80 0.290 0.26 1.70 0.063
## 6026 6.30 0.760 0.00 2.90 0.072
## 6027 10.00 0.430 0.33 2.70 0.095
## 6028 10.50 0.430 0.35 3.30 0.092
## 6029 9.10 0.600 0.00 1.90 0.058
## 6030 5.90 0.190 0.21 1.70 0.045
## 6031 7.40 0.360 0.34 1.80 0.075
## 6032 7.20 0.480 0.07 5.50 0.089
## 6033 8.50 0.280 0.35 1.70 0.061
## 6034 8.00 0.250 0.43 1.70 0.067
## 6035 10.40 0.520 0.45 2.00 0.080
## 6036 10.40 0.520 0.45 2.00 0.080
## 6037 7.50 0.410 0.15 3.70 0.104
## 6038 8.20 0.510 0.24 2.00 0.079
## 6039 7.30 0.400 0.30 1.70 0.080
## 6040 8.20 0.380 0.32 2.50 0.080
## 6041 6.90 0.450 0.11 2.40 0.043
## 6042 7.00 0.220 0.30 1.80 0.065
## 6043 7.30 0.320 0.23 2.30 0.066
## 6044 8.20 0.200 0.43 2.50 0.076
## 6046 10.00 0.410 0.45 6.20 0.071
## 6047 7.80 0.390 0.42 2.00 0.086
## 6048 10.00 0.350 0.47 2.00 0.061
## 6049 8.20 0.330 0.32 2.80 0.067
## 6050 6.10 0.580 0.23 2.50 0.044
## 6051 8.30 0.600 0.25 2.20 0.118
## 6052 9.60 0.420 0.35 2.10 0.083
## 6053 6.60 0.580 0.00 2.20 0.100
## 6054 8.30 0.600 0.25 2.20 0.118
## 6055 8.50 0.180 0.51 1.75 0.071
## 6058 10.20 0.410 0.43 2.20 0.110
## 6059 10.60 0.360 0.57 2.30 0.087
## 6060 8.80 0.450 0.43 1.40 0.076
## 6061 8.50 0.320 0.42 2.30 0.075
## 6062 9.00 0.785 0.24 1.70 0.078
## 6063 9.00 0.785 0.24 1.70 0.078
## 6065 9.90 0.540 0.26 2.00 0.111
## 6066 8.20 0.330 0.39 2.50 0.074
## 6067 6.50 0.340 0.27 2.80 0.067
## 6068 7.60 0.500 0.29 2.30 0.086
## 6069 9.20 0.360 0.34 1.60 0.062
## 6070 7.10 0.590 0.00 2.20 0.078
## 6071 9.70 0.420 0.46 2.10 0.074
## 6072 7.60 0.360 0.31 1.70 0.079
## 6073 7.60 0.360 0.31 1.70 0.079
## 6074 6.50 0.610 0.00 2.20 0.095
## 6075 6.50 0.880 0.03 5.60 0.079
## 6076 7.10 0.660 0.00 2.40 0.052
## 6078 8.20 0.350 0.33 2.40 0.076
## 6079 8.20 0.350 0.33 2.40 0.076
## 6080 9.80 0.390 0.43 1.65 0.068
## 6081 10.20 0.400 0.40 2.50 0.068
## 6082 6.80 0.660 0.07 1.60 0.070
## 6083 6.70 0.640 0.23 2.10 0.080
## 6084 7.00 0.430 0.30 2.00 0.085
## 6085 6.60 0.800 0.03 7.80 0.079
## 6086 7.00 0.430 0.30 2.00 0.085
## 6087 6.70 0.640 0.23 2.10 0.080
## 6089 9.10 0.400 0.57 4.60 0.080
## 6091 7.20 0.250 0.37 2.50 0.063
## 6093 7.00 0.745 0.12 1.80 0.114
## 6094 6.20 0.430 0.22 1.80 0.078
## 6095 7.90 0.580 0.23 2.30 0.076
## 6096 7.70 0.570 0.21 1.50 0.069
## 6097 7.70 0.260 0.26 2.00 0.052
## 6098 7.90 0.580 0.23 2.30 0.076
## 6099 7.70 0.570 0.21 1.50 0.069
## 6100 7.90 0.340 0.36 1.90 0.065
## 6101 8.60 0.420 0.39 1.80 0.068
## 6102 9.90 0.740 0.19 5.80 0.111
## 6103 7.20 0.360 0.46 2.10 0.074
## 6104 7.20 0.360 0.46 2.10 0.074
## 6105 7.20 0.360 0.46 2.10 0.074
## 6107 7.20 0.360 0.46 2.10 0.074
## 6108 6.20 0.390 0.43 2.00 0.071
## 6109 6.80 0.650 0.02 2.10 0.078
## 6110 6.60 0.440 0.15 2.10 0.076
## 6111 6.80 0.650 0.02 2.10 0.078
## 6112 9.60 0.380 0.42 1.90 0.071
## 6113 10.20 0.330 0.46 1.90 0.081
## 6114 8.80 0.270 0.46 2.10 0.095
## 6115 7.90 0.570 0.31 2.00 0.079
## 6116 8.20 0.340 0.37 1.90 0.057
## 6117 8.20 0.400 0.31 1.90 0.082
## 6118 9.00 0.390 0.40 1.30 0.044
## 6119 10.90 0.320 0.52 1.80 0.132
## 6120 10.90 0.320 0.52 1.80 0.132
## 6121 8.10 0.530 0.22 2.20 0.078
## 6122 10.50 0.360 0.47 2.20 0.074
## 6124 9.20 0.460 0.23 2.60 0.091
## 6125 7.50 0.580 0.03 4.10 0.080
## 6126 9.00 0.580 0.25 2.00 0.104
## 6128 7.60 0.430 0.29 2.10 0.075
## 6129 7.70 0.180 0.34 2.70 0.066
## 6130 7.80 0.815 0.01 2.60 0.074
## 6131 7.60 0.430 0.29 2.10 0.075
## 6132 10.20 0.230 0.37 2.20 0.057
## 6133 7.10 0.750 0.01 2.20 0.059
## 6134 6.00 0.330 0.32 12.90 0.054
## 6135 7.80 0.550 0.00 1.70 0.070
## 6136 7.10 0.750 0.01 2.20 0.059
## 6137 8.10 0.730 0.00 2.50 0.081
## 6138 6.50 0.670 0.00 4.30 0.057
## 6139 7.50 0.610 0.20 1.70 0.076
## 6140 9.80 0.370 0.39 2.50 0.079
## 6141 9.00 0.400 0.41 2.00 0.058
## 6142 8.30 0.560 0.22 2.40 0.082
## 6143 5.90 0.290 0.25 13.40 0.067
## 6144 7.40 0.550 0.19 1.80 0.082
## 6145 7.40 0.740 0.07 1.70 0.086
## 6146 7.40 0.550 0.19 1.80 0.082
## 6147 6.90 0.410 0.33 2.20 0.081
## 6148 7.10 0.600 0.01 2.30 0.079
## 6149 7.10 0.600 0.01 2.30 0.079
## 6150 7.50 0.580 0.14 2.20 0.077
## 6151 7.10 0.720 0.00 1.80 0.123
## 6152 7.90 0.660 0.00 1.40 0.096
## 6153 7.80 0.700 0.06 1.90 0.079
## 6154 6.10 0.640 0.02 2.40 0.069
## 6155 7.50 0.590 0.22 1.80 0.082
## 6156 7.00 0.580 0.28 4.80 0.085
## 6157 6.80 0.640 0.00 2.70 0.123
## 6158 6.80 0.640 0.00 2.70 0.123
## 6161 9.80 0.450 0.38 2.50 0.081
## 6162 8.20 0.780 0.00 2.20 0.089
## 6163 8.50 0.370 0.32 1.80 0.066
## 6164 7.20 0.570 0.05 2.30 0.081
## 6165 7.20 0.570 0.05 2.30 0.081
## 6166 10.40 0.430 0.50 2.30 0.068
## 6167 6.90 0.410 0.31 2.00 0.079
## 6170 7.30 0.440 0.20 1.60 0.049
## 6171 5.90 0.460 0.00 1.90 0.077
## 6172 7.50 0.580 0.20 2.00 0.073
## 6173 7.80 0.580 0.13 2.10 0.102
## 6174 8.00 0.715 0.22 2.30 0.075
## 6175 8.50 0.400 0.40 6.30 0.050
## 6176 7.00 0.690 0.00 1.90 0.114
## 6177 8.00 0.715 0.22 2.30 0.075
## 6178 9.80 0.300 0.39 1.70 0.062
## 6179 7.10 0.460 0.20 1.90 0.077
## 6180 7.10 0.460 0.20 1.90 0.077
## 6181 7.90 0.765 0.00 2.00 0.084
## 6182 8.70 0.630 0.28 2.70 0.096
## 6183 7.00 0.420 0.19 2.30 0.071
## 6184 11.30 0.370 0.50 1.80 0.090
## 6185 7.10 0.160 0.44 2.50 0.068
## 6186 8.00 0.600 0.08 2.60 0.056
## 6189 7.60 0.740 0.00 1.90 0.100
## 6190 8.20 0.635 0.10 2.10 0.073
## 6191 5.90 0.395 0.13 2.40 0.056
## 6192 7.50 0.755 0.00 1.90 0.084
## 6193 8.20 0.635 0.10 2.10 0.073
## 6194 6.60 0.630 0.00 4.30 0.093
## 6195 6.60 0.630 0.00 4.30 0.093
## 6196 7.20 0.530 0.14 2.10 0.064
## 6197 5.70 0.600 0.00 1.40 0.063
## 6200 6.70 0.860 0.07 2.00 0.100
## 6201 9.10 0.370 0.32 2.10 0.064
## 6202 8.00 0.280 0.44 1.80 0.081
## 6203 7.60 0.790 0.21 2.30 0.087
## 6204 7.50 0.610 0.26 1.90 0.073
## 6205 9.70 0.690 0.32 2.50 0.088
## 6206 6.80 0.680 0.09 3.90 0.068
## 6207 9.70 0.690 0.32 2.50 0.088
## 6208 7.00 0.620 0.10 1.40 0.071
## 6209 7.50 0.610 0.26 1.90 0.073
## 6210 6.50 0.510 0.15 3.00 0.064
## 6212 7.00 0.360 0.21 2.30 0.086
## 6213 7.00 0.360 0.21 2.40 0.086
## 6214 7.50 0.630 0.27 2.00 0.083
## 6216 9.90 0.440 0.46 2.20 0.091
## 6217 7.50 0.630 0.27 2.00 0.083
## 6219 9.70 0.660 0.34 2.60 0.094
## 6221 9.10 0.340 0.42 1.80 0.058
## 6222 9.10 0.360 0.39 1.80 0.060
## 6223 6.70 0.460 0.24 1.70 0.077
## 6224 6.70 0.460 0.24 1.70 0.077
## 6225 6.70 0.460 0.24 1.70 0.077
## 6226 6.70 0.460 0.24 1.70 0.077
## 6227 6.50 0.520 0.11 1.80 0.073
## 6228 7.40 0.600 0.26 2.10 0.083
## 6229 7.40 0.600 0.26 2.10 0.083
## 6230 7.80 0.870 0.26 3.80 0.107
## 6231 8.40 0.390 0.10 1.70 0.075
## 6232 9.10 0.775 0.22 2.20 0.079
## 6234 6.60 0.580 0.02 2.40 0.069
## 6235 6.00 0.500 0.00 1.40 0.057
## 6236 6.00 0.500 0.00 1.40 0.057
## 6237 6.00 0.500 0.00 1.40 0.057
## 6238 7.50 0.510 0.02 1.70 0.084
## 6239 7.50 0.510 0.02 1.70 0.084
## 6240 7.50 0.510 0.02 1.70 0.084
## 6241 7.60 0.540 0.02 1.70 0.085
## 6242 7.50 0.510 0.02 1.70 0.084
## 6243 11.50 0.420 0.48 2.60 0.077
## 6244 8.20 0.440 0.24 2.30 0.063
## 6245 6.10 0.590 0.01 2.10 0.056
## 6246 7.20 0.655 0.03 1.80 0.078
## 6247 7.20 0.655 0.03 1.80 0.078
## 6248 6.90 0.570 0.00 2.80 0.081
## 6249 9.00 0.600 0.29 2.00 0.069
## 6250 7.20 0.620 0.01 2.30 0.065
## 6251 7.60 0.645 0.03 1.90 0.086
## 6252 7.60 0.645 0.03 1.90 0.086
## 6253 7.20 0.580 0.03 2.30 0.077
## 6254 6.10 0.320 0.25 1.80 0.086
## 6255 6.10 0.340 0.25 1.80 0.084
## 6256 7.30 0.430 0.24 2.50 0.078
## 6257 7.40 0.640 0.17 5.40 0.168
## 6258 11.60 0.475 0.40 1.40 0.091
## 6259 9.20 0.540 0.31 2.30 0.112
## 6260 8.30 0.850 0.14 2.50 0.093
## 6261 11.60 0.475 0.40 1.40 0.091
## 6262 8.00 0.830 0.27 2.00 0.080
## 6263 7.20 0.605 0.02 1.90 0.096
## 6264 7.80 0.500 0.09 2.20 0.115
## 6265 7.30 0.740 0.08 1.70 0.094
## 6267 8.00 0.770 0.32 2.10 0.079
## 6268 6.60 0.610 0.00 1.60 0.069
## 6272 7.70 0.750 0.27 3.80 0.110
## 6274 7.20 0.560 0.26 2.00 0.083
## 6275 8.20 0.885 0.20 1.40 0.086
## 6277 7.20 0.450 0.15 2.00 0.078
## 6278 7.50 0.570 0.02 2.60 0.077
## 6279 7.50 0.570 0.02 2.60 0.077
## 6280 6.80 0.830 0.09 1.80 0.074
## 6281 8.00 0.600 0.22 2.10 0.080
## 6282 8.00 0.600 0.22 2.10 0.080
## 6283 7.10 0.755 0.15 1.80 0.107
## 6284 8.00 0.810 0.25 3.40 0.076
## 6285 7.40 0.640 0.07 1.80 0.100
## 6286 7.40 0.640 0.07 1.80 0.100
## 6287 6.60 0.640 0.31 6.10 0.083
## 6288 6.70 0.480 0.02 2.20 0.080
## 6289 6.00 0.490 0.00 2.30 0.068
## 6290 8.00 0.640 0.22 2.40 0.094
## 6291 7.10 0.620 0.06 1.30 0.070
## 6292 8.00 0.520 0.25 2.00 0.078
## 6293 6.40 0.570 0.14 3.90 0.070
## 6294 8.60 0.685 0.10 1.60 0.092
## 6295 8.70 0.675 0.10 1.60 0.090
## 6296 7.30 0.590 0.26 2.00 0.080
## 6297 7.00 0.600 0.12 2.20 0.083
## 6298 7.20 0.670 0.00 2.20 0.068
## 6299 7.90 0.690 0.21 2.10 0.080
## 6300 7.90 0.690 0.21 2.10 0.080
## 6301 7.60 0.300 0.42 2.00 0.052
## 6303 8.00 0.500 0.39 2.60 0.082
## 6304 7.70 0.280 0.30 2.00 0.062
## 6305 8.20 0.240 0.34 5.10 0.062
## 6306 6.00 0.510 0.00 2.10 0.064
## 6308 6.00 0.510 0.00 2.10 0.064
## 6310 6.40 0.470 0.40 2.40 0.071
## 6311 8.20 0.240 0.34 5.10 0.062
## 6312 9.90 0.570 0.25 2.00 0.104
## 6313 10.00 0.320 0.59 2.20 0.077
## 6314 6.20 0.580 0.00 1.60 0.065
## 6315 10.00 0.320 0.59 2.20 0.077
## 6316 7.30 0.340 0.33 2.50 0.064
## 6317 7.80 0.530 0.01 1.60 0.077
## 6318 7.70 0.640 0.21 2.20 0.077
## 6319 7.80 0.530 0.01 1.60 0.077
## 6320 7.50 0.400 0.18 1.60 0.079
## 6321 7.00 0.540 0.00 2.10 0.079
## 6322 6.40 0.530 0.09 3.90 0.123
## 6323 8.30 0.260 0.37 1.40 0.076
## 6324 8.30 0.260 0.37 1.40 0.076
## 6326 7.60 0.410 0.33 2.50 0.078
## 6327 7.80 0.640 0.00 1.90 0.072
## 6328 7.90 0.180 0.40 2.20 0.049
## 6329 7.40 0.410 0.24 1.80 0.066
## 6330 7.60 0.430 0.31 2.10 0.069
## 6331 5.90 0.440 0.00 1.60 0.042
## 6332 6.10 0.400 0.16 1.80 0.069
## 6335 10.00 0.380 0.38 1.60 0.169
## 6337 7.00 0.590 0.00 1.70 0.052
## 6338 7.30 0.670 0.02 2.20 0.072
## 6339 7.20 0.370 0.32 2.00 0.062
## 6340 7.40 0.785 0.19 5.20 0.094
## 6341 6.90 0.630 0.02 1.90 0.078
## 6342 6.90 0.580 0.20 1.75 0.058
## 6343 7.30 0.670 0.02 2.20 0.072
## 6344 7.40 0.785 0.19 5.20 0.094
## 6345 6.90 0.630 0.02 1.90 0.078
## 6346 6.80 0.670 0.00 1.90 0.080
## 6347 6.90 0.580 0.01 1.90 0.080
## 6348 7.20 0.380 0.31 2.00 0.056
## 6349 7.20 0.370 0.32 2.00 0.062
## 6350 7.80 0.320 0.44 2.70 0.104
## 6351 6.60 0.580 0.02 2.00 0.062
## 6352 7.60 0.490 0.33 1.90 0.074
## 6353 11.70 0.450 0.63 2.20 0.073
## 6354 6.50 0.900 0.00 1.60 0.052
## 6355 6.00 0.540 0.06 1.80 0.050
## 6356 7.60 0.490 0.33 1.90 0.074
## 6357 8.40 0.290 0.40 1.70 0.067
## 6358 7.90 0.200 0.35 1.70 0.054
## 6360 6.20 0.785 0.00 2.10 0.060
## 6361 6.80 0.640 0.03 2.30 0.075
## 6362 6.90 0.630 0.01 2.40 0.076
## 6363 6.80 0.590 0.10 1.70 0.063
## 6364 6.80 0.590 0.10 1.70 0.063
## 6365 7.30 0.480 0.32 2.10 0.062
## 6367 7.30 0.480 0.32 2.10 0.062
## 6369 10.00 0.690 0.11 1.40 0.084
## 6370 6.70 0.700 0.08 3.75 0.067
## 6371 7.60 0.350 0.60 2.60 0.073
## 6372 6.10 0.600 0.08 1.80 0.071
## 6377 7.10 0.875 0.05 5.70 0.082
## 6378 8.20 0.280 0.60 3.00 0.104
## 6379 5.60 0.620 0.03 1.50 0.080
## 6380 8.20 0.280 0.60 3.00 0.104
## 6382 8.10 0.330 0.44 1.50 0.042
## 6383 6.80 0.910 0.06 2.00 0.060
## 6384 7.00 0.655 0.16 2.10 0.074
## 6385 6.80 0.680 0.21 2.10 0.070
## 6386 6.00 0.640 0.05 1.90 0.066
## 6387 5.60 0.540 0.04 1.70 0.049
## 6388 6.20 0.570 0.10 2.10 0.048
## 6389 7.10 0.220 0.49 1.80 0.039
## 6390 5.60 0.540 0.04 1.70 0.049
## 6391 6.20 0.650 0.06 1.60 0.050
## 6392 7.70 0.540 0.26 1.90 0.089
## 6393 6.40 0.310 0.09 1.40 0.066
## 6394 7.00 0.430 0.02 1.90 0.080
## 6395 7.70 0.540 0.26 1.90 0.089
## 6396 6.90 0.740 0.03 2.30 0.054
## 6397 6.60 0.895 0.04 2.30 0.068
## 6398 6.90 0.740 0.03 2.30 0.054
## 6399 7.50 0.725 0.04 1.50 0.076
## 6400 7.80 0.820 0.29 4.30 0.083
## 6401 7.30 0.585 0.18 2.40 0.078
## 6402 6.20 0.440 0.39 2.50 0.077
## 6403 7.50 0.380 0.57 2.30 0.106
## 6404 6.70 0.760 0.02 1.80 0.078
## 6405 6.80 0.810 0.05 2.00 0.070
## 6406 7.50 0.380 0.57 2.30 0.106
## 6408 7.90 0.180 0.40 1.80 0.062
## 6409 6.40 0.360 0.21 2.20 0.047
## 6410 7.10 0.690 0.04 2.10 0.068
## 6411 6.40 0.790 0.04 2.20 0.061
## 6412 6.40 0.560 0.15 1.80 0.078
## 6413 6.90 0.840 0.21 4.10 0.074
## 6414 6.90 0.840 0.21 4.10 0.074
## 6416 6.50 0.530 0.06 2.00 0.063
## 6417 7.40 0.470 0.46 2.20 0.114
## 6418 6.60 0.700 0.08 2.60 0.106
## 6419 6.50 0.530 0.06 2.00 0.063
## 6420 6.90 0.480 0.20 1.90 0.082
## 6422 6.80 0.480 0.25 2.00 0.076
## 6423 6.00 0.420 0.19 2.00 0.075
## 6424 6.70 0.480 0.08 2.10 0.064
## 6425 6.80 0.470 0.08 2.20 0.064
## 6426 7.10 0.530 0.07 1.70 0.071
## 6427 7.90 0.290 0.49 2.20 0.096
## 6428 7.10 0.690 0.08 2.10 0.063
## 6429 6.60 0.440 0.09 2.20 0.063
## 6430 6.10 0.705 0.10 2.80 0.081
## 6431 7.20 0.530 0.13 2.00 0.058
## 6432 8.00 0.390 0.30 1.90 0.074
## 6433 6.60 0.560 0.14 2.40 0.064
## 6434 7.00 0.550 0.13 2.20 0.075
## 6435 6.10 0.530 0.08 1.90 0.077
## 6436 5.40 0.580 0.08 1.90 0.059
## 6437 6.20 0.640 0.09 2.50 0.081
## 6438 7.20 0.390 0.32 1.80 0.065
## 6439 6.20 0.520 0.08 4.40 0.071
## 6440 7.40 0.250 0.29 2.20 0.054
## 6441 6.70 0.855 0.02 1.90 0.064
## 6442 11.10 0.440 0.42 2.20 0.064
## 6443 8.40 0.370 0.43 2.30 0.063
## 6444 6.50 0.630 0.33 1.80 0.059
## 6445 7.00 0.570 0.02 2.00 0.072
## 6446 6.30 0.600 0.10 1.60 0.048
## 6447 11.20 0.400 0.50 2.00 0.099
## 6448 7.40 0.360 0.30 1.80 0.074
## 6449 7.10 0.680 0.00 2.30 0.087
## 6450 7.10 0.670 0.00 2.30 0.083
## 6451 6.30 0.680 0.01 3.70 0.103
## 6452 7.30 0.735 0.00 2.20 0.080
## 6453 6.60 0.855 0.02 2.40 0.062
## 6454 7.00 0.560 0.17 1.70 0.065
## 6455 6.60 0.880 0.04 2.20 0.066
## 6456 6.60 0.855 0.02 2.40 0.062
## 6458 7.80 0.600 0.26 2.00 0.080
## 6459 7.80 0.600 0.26 2.00 0.080
## 6460 7.80 0.600 0.26 2.00 0.080
## 6461 7.20 0.695 0.13 2.00 0.076
## 6462 7.20 0.695 0.13 2.00 0.076
## 6463 7.20 0.695 0.13 2.00 0.076
## 6464 6.70 0.670 0.02 1.90 0.061
## 6466 7.20 0.695 0.13 2.00 0.076
## 6467 7.00 0.560 0.13 1.60 0.077
## 6468 6.20 0.510 0.14 1.90 0.056
## 6470 6.40 0.380 0.14 2.20 0.038
## 6471 7.30 0.690 0.32 2.20 0.069
## 6472 6.00 0.580 0.20 2.40 0.075
## 6474 7.50 0.520 0.40 2.20 0.060
## 6475 8.00 0.300 0.63 1.60 0.081
## 6476 6.20 0.700 0.15 5.10 0.076
## 6477 6.80 0.670 0.15 1.80 0.118
## 6478 6.20 0.560 0.09 1.70 0.053
## 6479 7.40 0.350 0.33 2.40 0.068
## 6480 6.20 0.560 0.09 1.70 0.053
## 6481 6.10 0.715 0.10 2.60 0.053
## 6482 6.20 0.460 0.29 2.10 0.074
## 6483 6.70 0.320 0.44 2.40 0.061
## 6484 7.20 0.390 0.44 2.60 0.066
## 6485 7.50 0.310 0.41 2.40 0.065
## 6486 5.80 0.610 0.11 1.80 0.066
## 6487 7.20 0.660 0.33 2.50 0.068
## 6488 6.60 0.725 0.20 7.80 0.073
## 6489 6.30 0.550 0.15 1.80 0.077
## 6490 5.40 0.740 0.09 1.70 0.089
## 6491 6.30 0.510 0.13 2.30 0.076
## 6492 6.80 0.620 0.08 1.90 0.068
## 6493 6.20 0.600 0.08 2.00 0.090
## 6494 5.90 0.550 0.10 2.20 0.062
## 6495 6.30 0.510 0.13 2.30 0.076
## 6496 5.90 0.645 0.12 2.00 0.075
## 6497 6.00 0.310 0.47 3.60 0.067
## free.sulfur.dioxide total.sulfur.dioxide pH sulphates alcohol
## 1 45.0 170.0 3.00 0.45 8.800000
## 2 14.0 132.0 3.30 0.49 9.500000
## 3 30.0 97.0 3.26 0.44 10.100000
## 4 47.0 186.0 3.19 0.40 9.900000
## 5 47.0 186.0 3.19 0.40 9.900000
## 6 30.0 97.0 3.26 0.44 10.100000
## 7 30.0 136.0 3.18 0.47 9.600000
## 8 45.0 170.0 3.00 0.45 8.800000
## 9 14.0 132.0 3.30 0.49 9.500000
## 10 28.0 129.0 3.22 0.45 11.000000
## 11 11.0 63.0 2.99 0.56 12.000000
## 12 17.0 109.0 3.14 0.53 9.700000
## 13 16.0 75.0 3.18 0.63 10.800000
## 14 48.0 143.0 3.54 0.52 12.400000
## 15 41.0 172.0 2.98 0.67 9.700000
## 16 28.0 112.0 3.25 0.55 11.400000
## 17 30.0 99.0 3.24 0.36 9.600000
## 19 17.0 171.0 3.12 0.53 11.300000
## 20 34.0 133.0 3.22 0.50 9.500000
## 22 19.0 102.0 3.17 0.35 11.000000
## 23 41.0 122.0 3.47 0.48 10.500000
## 24 25.0 168.0 3.05 0.51 9.300000
## 25 16.0 142.0 3.42 0.47 10.000000
## 26 56.0 245.0 3.25 0.50 10.400000
## 27 35.0 146.0 3.45 0.44 10.000000
## 28 32.0 141.0 3.38 0.53 10.500000
## 29 17.0 132.0 3.19 0.49 11.600000
## 30 37.0 114.0 3.10 0.71 12.300000
## 31 20.0 142.0 3.20 0.53 10.000000
## 33 31.0 100.0 3.19 0.44 10.800000
## 34 43.0 117.0 3.42 0.51 9.000000
## 35 22.0 179.0 3.37 0.37 10.200000
## 36 21.0 123.0 3.19 0.42 12.800000
## 37 25.0 149.0 3.24 0.35 10.000000
## 38 38.0 138.0 3.13 0.28 11.200000
## 39 45.0 149.0 3.21 0.36 8.600000
## 40 45.0 149.0 3.21 0.36 8.600000
## 43 28.0 160.0 3.13 0.46 9.800000
## 44 33.0 152.0 3.22 0.56 9.500000
## 45 33.0 154.0 3.24 0.56 9.500000
## 46 38.0 167.0 3.16 0.53 10.000000
## 47 63.0 206.0 3.27 0.52 9.800000
## 48 62.0 207.0 3.25 0.52 9.800000
## 49 28.0 160.0 3.13 0.46 9.800000
## 50 32.0 150.0 3.36 0.48 9.800000
## 51 31.0 173.0 3.35 0.44 11.700000
## 52 39.0 124.0 3.34 0.58 11.000000
## 53 21.0 82.0 3.32 0.46 10.900000
## 54 39.0 108.0 3.31 0.35 10.900000
## 56 29.0 191.0 3.13 0.52 11.000000
## 57 37.0 213.0 3.09 0.50 9.600000
## 58 50.0 147.0 3.30 0.36 8.900000
## 59 25.0 78.0 3.11 0.38 10.200000
## 60 44.0 111.0 3.36 0.34 9.900000
## 61 30.0 123.0 3.03 0.46 8.600000
## 62 50.0 147.0 3.30 0.36 8.900000
## 63 17.0 151.0 3.02 0.34 10.500000
## 64 25.0 78.0 3.11 0.38 10.200000
## 65 31.0 122.0 3.15 0.46 10.300000
## 66 29.0 120.0 3.22 0.54 9.100000
## 67 27.0 124.0 3.22 0.49 12.600000
## 68 81.0 174.0 3.14 0.42 9.800000
## 69 30.0 96.0 3.33 0.64 10.700000
## 70 21.0 105.0 3.13 0.35 9.500000
## 71 48.0 244.0 3.10 0.51 9.000000
## 72 50.5 238.5 3.32 0.60 9.500000
## 73 31.0 201.0 3.69 0.71 10.000000
## 74 9.0 72.0 2.95 0.49 9.100000
## 75 30.0 96.0 3.33 0.64 10.700000
## 76 21.0 105.0 3.13 0.35 9.500000
## 77 31.0 87.0 3.26 0.37 12.700000
## 78 20.0 69.0 3.31 0.65 12.000000
## 79 26.0 103.0 2.94 0.56 9.300000
## 80 21.0 105.0 3.27 0.37 9.000000
## 81 34.0 114.0 3.39 0.77 10.600000
## 82 51.0 166.0 3.21 0.60 9.200000
## 83 47.0 164.0 3.17 0.42 10.000000
## 84 42.0 207.0 3.33 0.46 9.500000
## 85 54.0 155.0 3.11 0.45 8.700000
## 86 52.0 152.0 3.12 0.46 8.700000
## 87 55.0 156.0 3.09 0.44 8.700000
## 88 69.0 202.0 3.22 0.48 9.700000
## 89 54.0 155.0 3.11 0.45 8.700000
## 90 52.0 152.0 3.12 0.46 8.700000
## 91 55.0 156.0 3.09 0.44 8.700000
## 92 65.0 243.0 3.12 0.47 9.000000
## 93 47.0 136.0 3.26 0.40 12.600000
## 94 48.0 136.0 3.25 0.41 12.600000
## 95 51.0 148.0 3.21 0.44 11.500000
## 96 62.0 240.0 3.04 0.42 9.200000
## 98 15.0 80.0 2.95 0.36 11.400000
## 101 52.0 192.0 3.00 0.44 9.100000
## 102 64.0 162.0 3.40 0.41 9.400000
## 103 55.0 164.0 3.34 0.39 9.400000
## 104 44.0 170.0 2.99 0.46 9.000000
## 105 52.0 192.0 3.00 0.44 9.100000
## 106 34.0 109.0 3.20 0.35 9.200000
## 107 64.0 162.0 3.40 0.41 9.400000
## 108 60.0 171.0 3.16 0.59 9.100000
## 109 60.0 171.0 3.16 0.59 9.100000
## 110 37.0 187.0 3.27 0.60 10.300000
## 111 64.0 163.0 2.89 0.39 8.800000
## 112 45.0 255.0 3.04 0.52 8.900000
## 113 68.0 195.0 3.01 0.47 9.200000
## 114 29.0 150.0 3.22 0.51 9.100000
## 115 29.0 150.0 3.22 0.51 9.100000
## 116 8.0 103.0 3.63 0.40 9.700000
## 117 25.0 143.0 3.31 0.44 11.300000
## 118 16.0 85.0 3.19 0.42 11.800000
## 119 68.0 195.0 3.01 0.47 9.200000
## 120 57.0 196.0 3.04 0.50 9.200000
## 121 21.0 87.0 3.22 0.51 10.200000
## 122 42.0 138.0 3.01 0.54 8.800000
## 123 31.0 131.0 3.29 0.34 9.700000
## 124 14.0 146.0 3.29 0.36 9.100000
## 125 40.0 158.0 3.21 0.36 9.800000
## 126 63.0 143.0 3.27 0.48 11.000000
## 127 29.0 126.0 3.14 0.42 10.500000
## 128 48.0 203.0 3.45 0.54 9.700000
## 129 47.0 179.0 3.30 0.57 10.900000
## 130 46.0 184.0 3.31 0.57 10.900000
## 131 7.0 57.0 3.39 0.37 10.600000
## 132 48.0 203.0 3.45 0.54 9.700000
## 133 59.0 241.0 3.23 0.57 9.000000
## 134 46.0 188.0 3.24 0.51 9.200000
## 135 55.0 203.0 3.19 0.52 8.900000
## 136 44.0 179.0 3.26 0.56 9.600000
## 137 36.0 121.0 3.12 0.38 10.700000
## 138 49.0 155.0 3.16 0.44 8.700000
## 139 30.0 96.0 3.15 0.54 10.800000
## 140 18.0 79.0 3.23 0.52 11.800000
## 141 20.0 77.0 3.30 0.43 10.200000
## 142 49.0 155.0 3.16 0.44 8.700000
## 143 38.0 107.0 3.21 0.54 10.800000
## 144 24.0 99.0 3.18 0.53 9.700000
## 145 19.0 87.0 3.12 0.54 11.200000
## 146 37.0 114.0 3.00 0.39 10.900000
## 147 53.0 168.0 3.28 0.37 10.100000
## 148 15.0 97.0 3.38 0.36 9.000000
## 149 19.0 80.0 3.38 0.58 12.000000
## 150 23.0 116.0 2.99 0.38 9.400000
## 151 46.0 152.0 3.12 0.32 11.500000
## 152 58.0 135.0 3.14 0.43 9.900000
## 153 23.0 116.0 2.99 0.38 9.400000
## 154 41.0 97.0 3.14 0.45 10.400000
## 155 12.0 76.0 3.06 0.84 9.700000
## 156 48.0 198.0 2.89 0.42 8.900000
## 157 48.0 198.0 2.89 0.42 8.900000
## 158 38.0 124.0 3.29 0.42 12.400000
## 159 43.0 119.0 3.36 0.33 12.100000
## 160 43.0 119.0 3.36 0.33 12.100000
## 161 38.0 124.0 3.29 0.42 12.400000
## 162 27.0 159.0 2.98 0.40 9.100000
## 163 14.0 85.0 3.28 0.39 10.600000
## 164 48.0 198.0 2.89 0.42 8.900000
## 165 64.0 205.0 3.15 0.50 9.500000
## 166 72.0 177.0 3.16 0.49 9.800000
## 167 39.0 197.0 3.14 0.59 9.600000
## 168 25.0 98.0 3.08 0.44 12.600000
## 169 20.0 151.0 3.08 0.54 9.300000
## 171 29.0 133.0 3.12 0.54 12.700000
## 172 17.0 96.0 3.13 0.39 11.000000
## 173 4.0 100.0 3.03 0.39 11.400000
## 174 31.0 130.0 3.35 0.33 11.500000
## 175 33.0 173.0 3.09 0.64 10.200000
## 176 50.0 151.0 3.11 0.27 11.400000
## 177 19.0 65.0 3.03 0.41 12.600000
## 178 57.0 170.0 3.28 0.39 9.400000
## 179 9.0 108.0 3.11 0.35 8.700000
## 180 41.0 176.0 3.19 0.68 9.200000
## 181 42.0 173.0 3.19 0.66 9.300000
## 182 61.0 183.0 3.09 0.43 9.200000
## 183 48.0 167.0 2.93 0.50 8.700000
## 184 64.0 227.0 3.18 0.58 9.600000
## 185 64.0 226.0 3.02 0.63 9.300000
## 186 66.0 230.0 3.02 0.63 9.300000
## 187 49.0 166.0 3.12 0.61 9.900000
## 188 42.0 119.0 3.15 0.50 11.000000
## 189 26.0 109.0 3.26 0.57 12.700000
## 190 54.0 210.0 3.09 0.54 8.900000
## 191 55.0 211.0 3.09 0.55 8.900000
## 192 48.0 167.0 2.93 0.50 8.700000
## 193 28.0 123.0 3.02 0.37 11.400000
## 194 34.0 125.0 3.36 0.42 9.600000
## 198 54.0 214.0 3.13 0.47 8.900000
## 199 52.0 204.0 3.10 0.49 8.800000
## 200 54.0 214.0 3.13 0.47 8.900000
## 201 55.0 196.0 3.15 0.50 9.300000
## 202 52.0 204.0 3.10 0.49 8.800000
## 203 53.0 236.0 3.20 0.50 9.600000
## 204 39.0 134.0 3.33 0.53 12.000000
## 205 36.0 114.0 3.28 0.50 10.200000
## 206 45.0 153.0 3.15 0.43 8.800000
## 207 38.0 126.0 3.21 0.34 9.200000
## 209 15.0 77.0 3.32 0.74 10.200000
## 210 23.0 170.0 3.22 0.77 9.500000
## 211 12.0 68.0 3.31 0.34 10.500000
## 212 35.0 111.0 3.32 0.59 11.200000
## 213 38.0 126.0 3.21 0.34 9.200000
## 214 31.0 122.0 3.44 0.37 9.700000
## 215 35.0 105.0 3.30 0.44 11.100000
## 216 55.0 152.0 3.31 0.38 9.400000
## 217 45.0 164.0 3.03 0.33 11.000000
## 218 55.0 152.0 3.31 0.38 9.400000
## 219 60.0 167.0 3.31 0.44 9.400000
## 220 43.0 161.0 3.04 0.32 11.000000
## 221 45.0 164.0 3.03 0.33 11.000000
## 222 33.0 172.0 3.00 0.55 9.100000
## 223 35.0 105.0 3.30 0.44 11.100000
## 224 33.0 144.0 3.42 0.39 9.100000
## 225 31.0 140.0 3.39 0.54 10.400000
## 226 39.0 145.0 3.32 0.39 8.700000
## 227 41.0 200.0 3.50 0.50 9.700000
## 228 66.0 272.0 3.17 0.52 9.100000
## 229 41.0 200.0 3.50 0.50 9.700000
## 230 39.0 145.0 3.32 0.39 8.700000
## 231 26.0 142.0 3.37 0.46 8.900000
## 232 38.0 194.0 3.34 0.51 9.600000
## 233 49.0 208.0 3.31 0.51 9.500000
## 234 55.0 194.0 3.09 0.44 9.000000
## 235 55.0 194.0 3.09 0.44 9.000000
## 236 55.0 194.0 3.09 0.44 9.000000
## 237 55.0 194.0 3.09 0.44 9.000000
## 238 54.0 221.0 3.27 0.50 9.600000
## 239 40.0 120.0 3.34 0.41 11.100000
## 240 28.0 159.0 3.48 0.64 9.600000
## 241 49.0 197.0 3.20 0.46 8.700000
## 242 23.0 90.0 3.13 0.50 10.400000
## 243 23.0 100.0 3.15 0.38 11.400000
## 244 64.5 218.5 3.30 0.58 9.700000
## 245 40.0 142.0 3.14 0.46 8.700000
## 247 26.0 139.0 3.16 0.61 12.600000
## 248 12.0 77.0 3.25 0.36 10.900000
## 249 12.0 76.0 3.25 0.37 10.900000
## 250 18.0 119.0 3.38 0.45 10.000000
## 251 40.0 199.0 3.72 0.70 10.000000
## 252 41.0 197.0 3.02 0.50 9.800000
## 253 40.0 142.0 3.14 0.46 8.700000
## 254 5.0 109.0 3.53 0.43 11.700000
## 255 37.0 158.0 3.21 0.52 9.300000
## 256 45.0 147.0 3.32 0.58 9.600000
## 257 8.0 97.0 3.27 0.41 11.000000
## 258 8.0 97.0 3.27 0.41 11.000000
## 259 23.0 118.0 3.32 0.50 11.800000
## 260 3.0 75.0 3.28 0.34 11.400000
## 261 36.0 108.0 3.32 0.42 10.200000
## 262 36.0 156.0 2.93 0.47 8.900000
## 263 15.0 95.0 3.17 0.33 10.200000
## 264 66.0 231.0 3.08 0.59 9.600000
## 265 22.0 167.0 3.10 0.48 10.600000
## 266 36.0 156.0 2.93 0.47 8.900000
## 267 32.0 180.0 3.25 0.51 9.200000
## 268 34.0 149.0 3.34 0.57 9.700000
## 269 34.0 145.0 3.34 0.57 9.700000
## 270 36.0 147.0 3.34 0.57 9.700000
## 271 32.0 180.0 3.25 0.51 9.200000
## 272 33.0 147.0 3.33 0.58 9.700000
## 273 44.0 148.0 3.29 0.38 9.300000
## 274 30.0 123.0 3.24 0.38 9.000000
## 275 59.0 234.0 3.05 0.61 9.500000
## 276 51.0 169.0 3.14 0.57 9.800000
## 277 50.0 166.0 3.14 0.58 9.800000
## 278 9.0 60.0 2.89 0.50 10.600000
## 279 14.0 67.0 3.05 0.47 10.600000
## 280 17.0 105.0 3.26 0.68 12.400000
## 281 22.0 112.0 3.19 0.38 12.600000
## 282 36.0 114.0 3.30 0.60 12.300000
## 283 46.0 201.0 3.08 0.65 10.500000
## 284 51.0 196.0 3.19 0.49 9.300000
## 285 46.0 198.0 3.12 0.49 8.800000
## 286 47.0 180.0 3.08 0.47 8.800000
## 287 51.0 190.0 3.22 0.51 9.700000
## 288 49.0 192.0 2.98 0.48 9.000000
## 289 49.0 192.0 2.98 0.48 9.000000
## 290 49.0 192.0 2.98 0.48 9.000000
## 291 49.0 192.0 2.98 0.48 9.000000
## 292 53.0 155.0 3.52 0.46 10.500000
## 293 53.0 195.0 2.96 0.44 9.100000
## 294 26.0 157.0 3.44 0.64 9.800000
## 295 34.0 182.0 3.23 0.38 8.500000
## 296 34.0 175.0 3.37 0.54 9.400000
## 297 33.0 169.0 3.09 0.57 9.400000
## 298 82.0 187.0 3.19 0.60 11.200000
## 299 65.0 146.0 3.17 0.45 10.000000
## 300 27.0 122.0 3.15 0.45 10.300000
## 301 36.0 87.0 3.27 0.67 10.800000
## 302 12.0 74.0 3.13 0.38 10.500000
## 303 36.0 87.0 3.27 0.67 10.800000
## 304 42.0 168.0 3.32 0.43 11.100000
## 305 41.0 163.0 3.20 0.41 9.900000
## 306 41.0 163.0 3.20 0.41 9.900000
## 307 40.0 163.0 3.20 0.41 9.900000
## 308 41.0 166.0 3.20 0.41 9.900000
## 309 30.0 134.0 3.20 0.42 10.400000
## 310 36.0 148.0 3.21 0.41 10.400000
## 311 16.0 100.0 3.40 0.71 11.500000
## 312 35.0 164.0 3.53 0.51 12.500000
## 313 37.0 149.0 3.36 0.45 10.000000
## 314 51.0 166.0 3.29 0.63 10.000000
## 315 50.0 167.0 3.29 0.62 10.000000
## 316 42.0 127.0 3.09 0.44 9.100000
## 317 34.0 134.0 3.21 0.38 10.600000
## 318 36.0 135.0 3.19 0.37 10.500000
## 319 19.0 133.0 3.52 0.43 11.500000
## 320 10.0 69.0 3.54 0.59 10.100000
## 321 15.0 65.0 3.61 0.61 10.300000
## 322 36.0 135.0 3.19 0.37 10.500000
## 323 34.0 134.0 3.21 0.38 10.600000
## 324 35.0 137.0 3.16 0.36 10.400000
## 327 38.0 216.0 2.96 0.60 10.000000
## 328 37.0 143.0 3.19 0.65 10.000000
## 329 55.0 195.0 3.23 0.50 9.600000
## 330 33.0 85.0 3.17 0.51 10.400000
## 331 34.0 101.0 3.36 0.60 12.500000
## 332 37.0 135.0 3.20 0.39 10.600000
## 333 16.0 91.0 3.28 0.40 11.800000
## 334 30.0 133.0 3.11 0.44 9.800000
## 335 12.0 80.0 3.25 0.38 10.800000
## 336 16.0 91.0 3.28 0.40 11.800000
## 337 15.0 105.0 3.32 0.42 11.200000
## 338 55.0 170.0 3.28 0.42 9.300000
## 339 12.0 139.0 3.45 0.53 10.400000
## 340 49.0 141.0 3.43 0.85 10.200000
## 341 27.0 153.0 3.19 0.55 9.000000
## 342 17.0 129.0 3.20 0.54 10.000000
## 343 30.0 140.0 3.18 0.47 9.100000
## 344 46.0 144.0 3.29 0.76 10.000000
## 345 47.0 145.0 3.29 0.75 10.000000
## 346 33.0 131.0 3.28 0.40 9.600000
## 347 20.0 68.0 3.36 0.51 11.200000
## 348 75.0 155.0 3.20 0.44 8.800000
## 349 38.0 118.0 3.15 0.50 10.000000
## 350 56.0 137.0 3.15 0.47 10.000000
## 351 47.0 146.0 3.27 0.74 11.400000
## 352 32.0 138.0 3.03 0.30 11.900000
## 353 27.0 128.0 3.14 0.51 9.600000
## 354 32.0 138.0 3.03 0.30 11.900000
## 355 38.5 245.0 3.25 0.57 9.600000
## 356 48.0 191.0 2.89 0.38 9.000000
## 357 48.0 191.0 2.89 0.38 9.000000
## 358 24.0 169.0 3.15 0.78 9.500000
## 359 19.0 152.0 3.00 0.42 10.400000
## 360 43.0 161.0 3.20 0.59 10.600000
## 361 54.0 162.0 3.28 0.50 10.200000
## 362 24.0 84.0 3.15 0.43 8.900000
## 363 40.0 127.0 3.40 0.39 9.700000
## 364 48.0 191.0 2.89 0.38 9.000000
## 365 18.0 102.0 3.49 0.42 11.400000
## 366 29.0 113.0 3.40 0.71 12.300000
## 367 40.0 143.0 3.49 0.62 10.800000
## 368 39.0 148.0 3.12 0.45 9.400000
## 369 36.0 178.0 3.17 0.64 10.600000
## 370 26.0 72.0 3.17 0.29 11.600000
## 371 39.0 148.0 3.12 0.45 9.400000
## 372 36.0 178.0 3.17 0.64 10.600000
## 374 30.0 149.0 3.10 0.51 9.200000
## 375 18.0 89.0 3.51 0.38 12.500000
## 376 18.0 89.0 3.51 0.38 12.500000
## 377 12.0 119.0 3.32 0.51 10.400000
## 378 21.0 98.0 3.15 0.46 10.000000
## 379 17.0 155.0 3.22 0.64 10.000000
## 380 12.0 119.0 3.32 0.51 10.400000
## 381 21.0 98.0 3.15 0.46 10.000000
## 382 48.0 179.0 3.10 0.52 9.000000
## 383 26.0 157.0 3.12 0.53 9.200000
## 384 30.0 149.0 3.10 0.51 9.200000
## 385 20.0 125.0 3.38 0.39 11.300000
## 386 18.0 89.0 3.51 0.38 12.500000
## 387 24.0 115.0 3.48 0.39 10.800000
## 388 82.5 260.0 3.12 0.66 10.100000
## 389 29.0 140.0 3.39 0.46 9.700000
## 390 60.0 181.0 3.18 0.61 9.300000
## 391 60.0 181.0 3.18 0.61 9.300000
## 392 13.0 66.0 3.10 0.46 10.600000
## 393 19.0 125.0 3.36 0.47 10.200000
## 394 20.0 69.0 3.08 0.56 12.200000
## 395 62.0 163.0 3.19 0.44 8.800000
## 397 30.0 93.0 3.09 0.39 11.400000
## 398 35.0 107.0 3.46 0.50 11.400000
## 399 52.0 168.0 3.35 0.44 9.400000
## 400 32.0 83.0 3.30 0.41 11.700000
## 401 35.0 107.0 3.46 0.50 11.400000
## 402 62.0 163.0 3.19 0.44 8.800000
## 403 22.0 108.0 3.23 0.52 9.200000
## 404 55.0 252.0 3.07 0.56 8.700000
## 405 33.0 170.0 3.24 0.66 12.600000
## 407 40.0 99.0 3.39 0.39 12.800000
## 408 13.0 125.0 3.17 0.51 9.400000
## 409 26.0 116.0 3.26 0.53 10.300000
## 410 30.0 93.0 3.09 0.39 11.400000
## 411 42.0 155.0 2.97 0.47 9.000000
## 412 38.0 140.0 3.30 0.79 9.600000
## 413 32.0 85.0 3.16 0.50 10.500000
## 414 32.0 85.0 3.16 0.50 10.500000
## 415 42.0 155.0 2.97 0.47 9.000000
## 416 38.0 140.0 3.30 0.79 9.600000
## 417 27.0 99.0 3.19 0.33 9.800000
## 418 57.0 210.0 3.10 0.47 9.000000
## 419 27.0 99.0 3.19 0.33 9.800000
## 420 33.0 137.0 3.31 0.56 10.500000
## 421 41.0 136.0 3.16 0.37 12.700000
## 422 37.0 222.0 3.25 0.54 10.400000
## 423 37.0 221.0 3.25 0.54 10.400000
## 424 37.0 221.0 3.25 0.54 10.400000
## 425 47.0 162.0 3.34 0.52 10.500000
## 426 37.0 222.0 3.25 0.54 10.400000
## 427 37.0 221.0 3.25 0.54 10.400000
## 428 48.0 194.0 3.09 0.45 9.400000
## 429 20.0 89.0 3.06 0.46 9.100000
## 430 54.0 197.0 3.10 0.49 9.300000
## 431 48.0 194.0 3.09 0.45 9.400000
## 432 19.0 84.0 3.21 0.38 9.800000
## 433 73.5 214.0 3.18 0.61 9.900000
## 434 16.0 151.0 3.07 0.57 9.200000
## 435 31.0 104.0 3.35 0.47 12.100000
## 436 24.0 97.0 3.38 0.49 12.200000
## 437 23.0 218.5 3.27 0.60 9.800000
## 438 49.0 186.0 3.35 0.64 12.400000
## 439 73.5 214.0 3.18 0.61 9.900000
## 440 23.0 108.0 3.26 0.54 9.200000
## 441 24.0 102.0 3.29 0.59 11.600000
## 442 25.0 137.0 3.30 0.69 10.400000
## 443 54.0 126.0 3.43 0.65 12.900000
## 444 54.0 245.0 3.26 0.54 9.300000
## 445 40.0 139.0 3.20 0.33 11.000000
## 446 16.0 66.0 3.24 0.40 11.500000
## 447 30.0 156.0 3.53 0.42 12.400000
## 448 24.0 113.0 3.44 0.53 9.800000
## 449 24.0 113.0 3.44 0.53 9.800000
## 450 34.0 127.0 3.48 0.56 10.500000
## 451 21.0 174.0 3.03 0.54 9.100000
## 452 34.0 128.0 3.24 0.44 10.100000
## 453 27.0 160.0 3.46 0.51 10.600000
## 454 32.0 113.0 3.41 0.51 10.500000
## 455 34.0 127.0 3.48 0.56 10.500000
## 456 24.0 113.0 3.44 0.53 9.800000
## 457 11.0 82.0 3.30 0.40 12.900000
## 458 26.0 111.0 2.95 0.52 9.500000
## 459 31.0 218.5 3.29 0.72 9.800000
## 460 83.0 249.0 3.37 0.50 8.500000
## 461 26.0 111.0 2.95 0.52 9.500000
## 462 40.0 171.0 3.22 0.45 9.300000
## 463 50.0 162.0 3.35 0.38 9.500000
## 464 15.0 68.0 3.17 0.39 9.400000
## 465 66.0 178.0 3.16 0.50 8.700000
## 466 34.0 126.0 2.95 0.46 8.900000
## 467 54.0 141.0 3.22 0.43 9.400000
## 468 15.0 68.0 3.17 0.39 9.400000
## 469 66.0 178.0 3.16 0.50 8.700000
## 470 59.0 182.0 3.09 0.52 9.600000
## 471 21.0 158.0 3.00 0.73 9.300000
## 472 34.0 200.0 3.14 0.76 10.000000
## 473 19.0 86.0 3.25 0.45 12.500000
## 474 34.0 132.0 3.36 0.48 9.600000
## 475 30.0 102.0 3.24 0.36 9.400000
## 476 55.0 227.0 3.03 0.61 9.500000
## 477 42.0 105.0 2.99 0.39 12.400000
## 478 29.0 115.0 3.11 0.55 10.500000
## 479 21.0 165.0 2.97 0.58 9.200000
## 480 67.0 164.0 3.32 0.56 10.400000
## 481 31.0 172.0 3.22 0.60 9.200000
## 482 45.0 104.0 3.33 0.51 10.600000
## 483 41.0 137.0 3.34 0.42 9.500000
## 484 31.0 172.0 3.22 0.60 9.200000
## 486 36.0 117.0 3.47 0.54 9.700000
## 487 43.0 117.0 3.46 0.51 9.700000
## 488 32.0 90.0 3.10 0.42 10.700000
## 489 53.0 180.0 3.34 0.68 10.500000
## 490 52.0 177.0 3.13 0.45 8.900000
## 491 8.0 70.0 3.09 0.46 12.100000
## 492 12.0 65.0 3.25 0.40 12.700000
## 493 42.0 182.0 3.18 0.46 9.900000
## 494 28.0 158.0 3.20 0.64 11.400000
## 495 27.0 103.0 3.37 0.58 10.700000
## 496 28.0 173.0 3.33 0.48 12.500000
## 497 70.0 189.0 3.08 0.49 8.600000
## 498 43.0 147.0 3.29 0.54 12.500000
## 499 13.0 174.0 3.27 0.66 10.000000
## 500 70.0 189.0 3.08 0.49 8.600000
## 501 54.0 200.0 3.08 0.49 9.500000
## 502 51.0 164.0 3.12 0.48 9.600000
## 505 46.0 140.0 3.06 0.53 8.900000
## 506 46.0 140.0 3.06 0.53 8.900000
## 507 7.0 135.0 3.01 0.52 8.800000
## 508 40.0 170.0 3.64 0.54 10.000000
## 509 55.0 152.0 3.44 0.44 12.000000
## 510 40.0 170.0 3.64 0.54 10.000000
## 511 62.0 138.0 3.21 0.42 10.000000
## 512 8.0 167.0 3.11 0.41 12.100000
## 513 31.0 141.0 3.16 0.59 11.000000
## 514 27.0 55.0 3.21 0.33 11.200000
## 515 34.0 115.0 3.17 0.39 10.300000
## 516 28.0 167.0 3.37 0.47 10.400000
## 517 47.0 154.0 3.08 0.45 9.100000
## 518 49.0 154.0 3.00 0.60 10.400000
## 519 20.0 78.0 3.43 0.64 10.800000
## 520 7.0 41.0 3.19 0.40 11.700000
## 521 8.0 143.0 3.05 0.74 9.800000
## 522 8.0 143.0 3.05 0.74 9.800000
## 523 22.0 101.0 3.03 0.39 11.400000
## 524 22.0 96.0 3.03 0.38 11.200000
## 525 6.0 72.0 3.37 0.34 11.400000
## 526 24.0 140.0 3.09 0.45 9.200000
## 527 3.0 29.0 3.04 0.53 12.500000
## 528 32.0 116.0 3.36 0.44 12.600000
## 529 24.0 104.0 3.44 0.35 12.200000
## 530 19.0 112.0 3.56 0.45 11.200000
## 531 31.0 103.0 3.43 0.79 9.700000
## 533 53.0 178.0 3.01 0.48 9.000000
## 534 53.0 178.0 3.01 0.48 9.000000
## 535 53.0 178.0 3.01 0.48 9.000000
## 536 54.0 171.0 3.09 0.51 9.100000
## 537 54.0 171.0 3.09 0.51 9.100000
## 538 53.0 178.0 3.01 0.48 9.000000
## 539 22.0 61.0 3.31 0.54 10.400000
## 540 41.0 211.0 3.37 0.67 9.500000
## 541 10.0 175.0 3.46 0.55 11.400000
## 543 14.0 167.0 3.34 0.68 9.900000
## 544 29.0 148.0 3.22 0.62 9.900000
## 545 49.0 162.0 3.21 0.51 9.000000
## 546 41.0 149.0 3.49 0.58 10.000000
## 547 38.0 172.0 3.49 0.64 9.700000
## 548 10.0 87.0 3.30 0.49 11.800000
## 549 30.0 127.0 3.49 0.50 10.200000
## 551 40.0 168.0 3.07 0.52 9.600000
## 552 31.0 93.0 2.93 0.37 11.300000
## 553 32.0 118.0 3.00 0.38 12.100000
## 554 40.0 168.0 3.07 0.52 9.600000
## 555 32.0 118.0 3.00 0.38 12.100000
## 556 31.0 93.0 2.93 0.37 11.300000
## 557 22.0 160.0 2.98 0.65 9.400000
## 558 16.0 137.0 3.32 0.50 10.400000
## 559 53.0 165.0 3.25 0.39 9.500000
## 560 51.0 144.0 3.01 0.76 12.300000
## 561 31.0 150.0 3.12 0.74 9.900000
## 562 39.0 128.0 3.24 0.48 10.100000
## 563 39.0 184.0 3.09 0.63 9.200000
## 564 16.0 135.0 3.08 0.77 10.400000
## 565 38.0 165.0 3.20 0.42 9.100000
## 566 28.0 99.0 3.12 0.47 10.000000
## 567 6.0 37.0 3.13 0.39 11.500000
## 568 59.0 153.0 3.08 0.61 9.800000
## 569 61.0 154.0 3.08 0.60 9.800000
## 570 44.0 179.0 3.19 0.69 9.400000
## 572 26.0 107.0 3.32 0.41 11.600000
## 573 44.0 181.0 3.04 0.56 8.800000
## 574 49.0 151.0 3.16 0.39 12.700000
## 575 39.0 138.0 3.17 0.44 11.700000
## 576 47.0 185.0 3.13 0.50 10.200000
## 577 47.0 187.0 3.13 0.50 10.200000
## 578 48.0 153.0 3.15 0.38 12.700000
## 579 26.0 107.0 3.32 0.41 11.600000
## 580 42.0 134.0 3.38 0.38 12.300000
## 582 25.0 111.0 3.35 0.39 9.400000
## 583 44.0 168.0 3.13 0.35 10.100000
## 584 26.0 81.0 2.86 0.36 9.700000
## 585 32.0 134.0 3.42 0.51 10.100000
## 586 26.0 81.0 2.86 0.36 9.700000
## 587 38.0 157.0 3.13 0.48 8.900000
## 588 37.0 136.0 3.47 0.50 10.800000
## 589 42.0 121.0 3.42 0.49 10.800000
## 590 25.0 136.0 3.19 0.58 9.500000
## 591 6.0 148.0 2.94 0.44 9.100000
## 592 48.0 119.0 3.32 0.49 10.900000
## 593 28.0 152.0 3.20 0.52 9.400000
## 594 10.0 131.0 2.97 0.28 10.800000
## 595 9.0 131.0 2.97 0.29 10.800000
## 596 7.0 140.0 3.45 0.50 10.500000
## 597 28.0 152.0 3.20 0.52 9.400000
## 598 26.0 127.0 3.17 0.44 10.800000
## 599 31.0 115.0 3.35 0.48 10.500000
## 600 14.0 55.0 3.08 0.68 11.500000
## 602 31.0 106.0 2.88 0.38 10.800000
## 603 10.0 131.0 2.97 0.28 10.800000
## 604 9.0 131.0 2.97 0.29 10.800000
## 605 34.0 134.0 2.99 0.61 9.800000
## 606 34.0 134.0 2.99 0.61 9.800000
## 607 38.0 158.0 3.43 0.38 9.600000
## 608 38.0 158.0 3.43 0.38 9.600000
## 609 48.0 161.0 3.34 0.48 9.500000
## 610 12.0 94.0 3.48 0.69 10.700000
## 611 29.0 119.0 3.25 0.65 12.400000
## 612 9.0 95.0 3.09 0.39 11.100000
## 613 37.0 133.0 2.99 0.38 8.800000
## 614 38.0 133.0 3.00 0.36 8.700000
## 615 38.0 133.0 3.00 0.36 8.700000
## 616 37.0 133.0 2.99 0.38 8.800000
## 617 18.0 101.0 3.21 0.65 11.700000
## 618 52.0 195.0 3.23 0.50 10.900000
## 619 52.0 190.0 3.23 0.50 10.800000
## 620 33.0 135.0 3.12 0.50 9.600000
## 621 59.0 222.0 3.18 0.58 9.000000
## 622 50.0 171.0 2.85 0.50 9.000000
## 623 22.0 141.0 3.36 0.60 10.400000
## 624 3.0 64.0 3.23 0.51 11.400000
## 625 27.0 128.0 3.26 0.55 9.300000
## 626 49.0 130.0 3.33 0.46 11.000000
## 627 22.0 177.0 3.32 0.45 9.100000
## 628 31.0 228.0 3.23 0.62 9.400000
## 629 31.0 228.0 3.23 0.62 9.400000
## 630 23.0 99.0 3.18 0.60 10.500000
## 631 35.0 144.0 3.22 0.42 8.800000
## 632 35.0 144.0 3.22 0.42 8.800000
## 633 16.0 131.0 3.26 0.64 10.700000
## 634 45.0 187.0 3.33 0.42 9.500000
## 635 46.0 150.0 3.43 0.49 10.900000
## 636 34.0 140.0 3.49 0.51 10.800000
## 637 39.0 133.0 3.41 0.46 10.800000
## 638 25.0 148.0 3.10 0.62 9.200000
## 639 48.0 198.0 3.30 0.71 10.300000
## 640 49.0 197.0 3.30 0.71 10.300000
## 641 33.0 127.0 3.34 0.50 11.000000
## 642 34.0 189.0 3.25 0.43 9.000000
## 643 68.0 179.0 3.36 0.50 10.400000
## 644 34.0 163.0 3.31 0.45 9.500000
## 645 32.0 166.0 3.31 0.45 9.500000
## 646 44.0 166.0 3.24 0.41 9.000000
## 648 57.0 146.0 3.16 0.37 9.000000
## 649 34.0 190.0 3.16 0.72 10.000000
## 650 35.0 189.0 3.07 0.53 9.100000
## 651 35.0 189.0 3.07 0.53 9.100000
## 652 35.0 189.0 3.07 0.53 9.100000
## 653 35.0 189.0 3.07 0.53 9.100000
## 654 34.0 134.0 3.34 0.45 9.500000
## 655 70.0 138.0 3.33 0.75 11.400000
## 656 30.0 117.0 3.11 0.42 12.200000
## 657 27.0 95.0 3.04 0.40 11.300000
## 658 14.0 136.0 3.25 0.44 10.200000
## 659 41.0 188.0 3.24 0.40 11.300000
## 661 12.0 86.0 3.15 0.38 9.400000
## 662 47.0 133.0 3.37 0.50 12.200000
## 663 23.0 188.0 3.40 0.47 9.200000
## 664 12.0 86.0 3.15 0.38 9.400000
## 665 49.0 182.0 3.35 0.52 9.600000
## 666 24.0 130.0 3.28 0.48 9.500000
## 667 38.0 195.0 3.35 0.72 12.500000
## 668 49.0 182.0 3.35 0.52 9.600000
## 669 37.0 173.0 3.35 0.46 10.000000
## 670 60.0 211.0 3.18 0.57 9.300000
## 671 34.0 199.0 3.14 0.55 9.300000
## 672 22.0 101.0 3.29 0.57 11.600000
## 673 46.0 150.0 3.38 0.50 12.500000
## 674 18.0 130.0 3.36 0.63 10.600000
## 675 57.0 206.0 3.08 0.60 9.400000
## 676 44.0 201.0 3.19 0.40 9.100000
## 677 48.0 224.0 3.23 0.41 9.000000
## 678 23.0 94.0 3.42 0.42 11.800000
## 679 23.0 94.0 3.42 0.42 11.800000
## 680 23.0 94.0 3.42 0.42 11.800000
## 681 64.0 159.0 3.17 0.39 10.000000
## 683 30.0 165.0 3.24 0.44 9.500000
## 685 50.0 183.0 3.03 0.42 11.200000
## 686 54.0 201.0 3.25 0.46 9.000000
## 687 21.0 114.0 3.30 0.53 10.700000
## 689 61.0 222.0 3.14 0.50 9.100000
## 690 34.0 125.0 3.26 0.60 10.800000
## 691 25.0 136.0 3.31 0.60 10.100000
## 692 36.0 198.0 3.17 0.62 9.900000
## 693 36.0 191.0 3.17 0.62 9.800000
## 694 34.0 185.0 3.17 0.63 9.800000
## 695 51.0 225.0 3.16 0.66 9.500000
## 696 49.0 198.0 3.23 0.46 9.500000
## 697 22.0 94.0 3.23 0.57 11.100000
## 698 62.0 204.0 3.06 0.60 9.500000
## 699 62.0 204.0 3.06 0.60 9.500000
## 700 62.0 204.0 3.06 0.59 9.400000
## 701 29.0 197.0 3.06 0.64 9.700000
## 702 19.0 135.0 3.41 0.78 13.900000
## 703 20.0 84.0 3.22 0.45 10.100000
## 704 30.0 110.0 3.12 0.42 10.500000
## 705 18.0 115.0 3.42 0.50 12.600000
## 706 13.0 41.0 2.89 0.34 10.900000
## 707 50.0 218.0 3.15 0.60 10.000000
## 708 57.0 166.0 3.13 0.62 11.200000
## 709 44.0 130.0 3.11 0.48 10.000000
## 710 13.0 98.0 3.14 0.46 9.200000
## 711 51.0 172.0 3.35 0.45 9.500000
## 712 31.0 128.0 3.10 0.50 12.300000
## 713 31.0 128.0 3.10 0.50 12.300000
## 714 57.0 213.0 3.32 0.43 10.000000
## 715 39.0 187.0 3.41 0.50 10.800000
## 716 41.0 150.0 3.49 0.71 10.500000
## 717 22.0 221.0 3.06 0.61 9.200000
## 718 34.0 157.0 2.96 0.50 9.100000
## 719 41.0 150.0 3.49 0.71 10.500000
## 720 35.0 127.0 3.45 0.50 10.200000
## 721 62.0 178.0 3.02 0.45 8.900000
## 722 15.0 182.0 3.50 0.52 10.400000
## 723 23.0 128.0 3.37 0.47 11.700000
## 724 29.0 89.0 3.26 0.44 12.400000
## 725 23.0 122.0 3.14 0.39 10.900000
## 726 35.0 136.0 3.15 0.46 10.200000
## 727 41.0 114.0 3.37 0.66 11.700000
## 728 19.0 101.0 2.99 0.59 9.400000
## 729 42.0 157.0 3.35 0.47 10.500000
## 731 25.0 139.0 3.35 0.56 10.400000
## 732 78.0 240.0 3.25 0.47 9.500000
## 733 14.0 49.0 3.01 0.33 11.100000
## 734 40.0 183.0 3.02 0.50 9.100000
## 735 28.0 191.0 3.28 0.61 9.200000
## 736 15.0 129.0 3.14 0.49 9.600000
## 737 40.0 183.0 3.02 0.50 9.100000
## 738 28.0 191.0 3.28 0.61 9.200000
## 739 40.0 142.0 3.17 0.39 10.800000
## 740 15.0 129.0 3.14 0.49 9.600000
## 741 5.0 19.0 3.31 0.37 12.600000
## 742 21.0 57.0 3.44 0.55 11.000000
## 743 26.0 136.0 3.28 0.61 10.200000
## 744 38.0 152.0 3.33 0.43 9.400000
## 745 24.0 160.0 3.17 0.43 10.000000
## 747 31.0 253.0 3.22 0.56 10.500000
## 748 56.0 177.0 3.04 0.32 11.500000
## 749 44.0 176.0 3.30 0.54 9.800000
## 750 51.0 175.0 3.04 0.32 11.400000
## 751 56.0 177.0 3.04 0.32 11.500000
## 752 78.0 167.0 3.15 0.55 10.200000
## 753 83.0 160.0 3.16 0.50 9.400000
## 754 31.0 253.0 3.22 0.56 10.500000
## 755 14.0 138.0 3.09 0.50 9.100000
## 756 32.0 107.0 3.25 0.48 12.200000
## 757 45.0 175.0 3.42 0.43 9.500000
## 758 68.0 178.0 3.40 0.85 9.300000
## 761 44.0 176.0 3.30 0.54 9.800000
## 762 42.0 173.0 3.30 0.54 9.800000
## 763 55.0 247.0 3.00 0.56 8.700000
## 764 38.0 128.0 3.37 0.57 10.200000
## 765 36.0 168.0 3.22 0.69 9.500000
## 766 35.0 135.0 2.94 0.46 11.000000
## 768 7.0 46.0 3.21 0.60 10.900000
## 769 41.0 113.0 3.42 0.40 9.300000
## 770 41.0 113.0 3.42 0.40 9.300000
## 771 29.0 120.0 3.41 0.46 9.800000
## 774 49.0 172.0 3.40 0.45 9.400000
## 775 28.0 124.0 3.20 0.46 10.400000
## 776 29.0 104.0 3.24 0.58 12.100000
## 777 18.0 98.0 3.02 0.56 11.000000
## 778 47.0 197.0 3.12 0.53 9.000000
## 779 59.0 178.0 3.37 0.82 9.500000
## 780 43.0 145.0 3.28 0.75 8.800000
## 781 7.0 55.0 3.37 0.38 11.200000
## 782 44.0 213.0 3.08 0.61 9.300000
## 783 59.0 178.0 3.37 0.82 9.500000
## 784 43.0 145.0 3.28 0.75 8.800000
## 785 47.0 197.0 3.12 0.53 9.000000
## 786 31.0 119.0 3.27 0.30 9.300000
## 787 31.0 117.0 3.27 0.29 9.200000
## 788 31.0 117.0 3.27 0.29 9.200000
## 789 26.0 116.0 3.46 0.45 10.000000
## 790 31.0 119.0 3.27 0.30 9.300000
## 791 31.0 117.0 3.27 0.29 9.200000
## 792 28.0 92.0 3.39 0.69 10.900000
## 793 34.0 144.0 3.10 0.56 10.000000
## 794 28.0 92.0 3.39 0.69 10.900000
## 795 38.0 173.0 3.03 0.52 9.300000
## 796 37.0 157.0 3.09 0.43 9.000000
## 797 42.0 215.0 3.02 0.58 9.200000
## 798 47.0 153.0 3.28 0.77 9.600000
## 799 30.0 113.0 3.42 0.40 9.400000
## 800 14.0 75.0 3.34 0.58 11.100000
## 801 44.0 161.0 3.06 0.41 8.900000
## 802 61.0 222.0 3.19 0.47 9.300000
## 803 57.0 220.0 3.07 0.53 9.300000
## 804 46.0 165.0 3.41 0.44 9.800000
## 805 24.0 112.0 3.22 0.46 9.800000
## 806 44.0 161.0 3.06 0.41 8.900000
## 807 57.0 205.0 3.17 0.41 9.600000
## 808 55.0 204.0 3.16 0.41 9.600000
## 809 65.0 246.0 3.15 0.38 9.000000
## 810 57.0 206.0 3.17 0.43 9.500000
## 811 61.0 222.0 3.19 0.47 9.300000
## 812 17.0 120.0 3.21 0.56 9.200000
## 813 9.0 160.0 3.42 0.50 9.100000
## 814 44.0 166.0 3.38 0.46 9.500000
## 815 44.0 229.0 3.03 0.59 10.500000
## 816 24.0 125.0 3.01 0.46 9.000000
## 817 7.0 77.0 3.16 0.52 11.700000
## 818 27.0 133.0 3.20 0.51 9.100000
## 819 24.0 125.0 3.01 0.46 9.000000
## 820 27.0 133.0 3.20 0.51 9.100000
## 821 24.0 85.0 3.41 0.61 12.400000
## 822 28.0 212.0 2.96 0.58 9.200000
## 823 34.0 104.0 3.30 0.43 9.400000
## 824 36.0 117.0 3.34 0.43 9.600000
## 825 7.0 77.0 3.16 0.52 11.700000
## 826 36.0 167.0 3.26 0.56 9.800000
## 827 24.0 155.0 3.33 0.59 10.200000
## 828 27.0 139.0 3.28 0.48 12.500000
## 829 20.0 90.0 3.16 0.44 10.900000
## 830 21.0 90.0 3.16 0.42 11.000000
## 831 34.0 110.0 3.72 0.69 10.500000
## 832 34.0 161.0 3.05 0.62 11.500000
## 833 34.0 108.0 3.36 0.53 12.800000
## 834 27.0 82.0 3.18 0.44 12.200000
## 835 34.0 110.0 3.72 0.69 10.500000
## 836 34.0 108.0 3.14 0.45 12.800000
## 837 30.0 177.0 3.25 0.40 11.900000
## 838 30.0 177.0 3.25 0.40 11.900000
## 839 30.0 177.0 3.25 0.40 11.900000
## 840 12.0 126.0 3.16 0.39 12.000000
## 841 12.0 126.0 3.16 0.39 12.000000
## 842 35.0 169.0 3.12 0.47 8.800000
## 843 35.0 169.0 3.12 0.47 8.800000
## 844 33.0 101.0 3.21 0.54 10.800000
## 845 29.0 118.0 3.30 0.50 11.000000
## 846 29.0 118.0 3.30 0.50 11.000000
## 847 62.0 153.0 3.02 0.40 9.300000
## 848 17.0 73.0 3.08 0.39 10.800000
## 849 35.0 169.0 3.12 0.47 8.800000
## 850 30.0 105.0 3.31 0.47 11.500000
## 851 33.0 101.0 3.21 0.54 10.800000
## 852 58.0 166.0 3.10 0.54 9.400000
## 854 41.0 151.0 3.06 0.49 8.600000
## 856 30.0 116.0 3.49 0.77 10.300000
## 857 58.0 166.0 3.10 0.54 9.400000
## 858 59.0 169.0 3.10 0.52 9.400000
## 859 60.0 149.0 3.17 0.54 10.000000
## 861 38.0 103.0 3.22 0.63 10.400000
## 862 57.0 182.0 3.29 0.75 9.100000
## 863 33.0 163.0 3.36 0.61 9.900000
## 864 24.0 111.0 3.24 0.50 12.100000
## 865 34.0 163.0 3.35 0.61 9.900000
## 866 26.0 117.0 3.12 0.30 12.500000
## 868 41.0 143.0 3.24 0.76 8.500000
## 869 49.0 173.0 3.28 0.82 9.000000
## 870 37.0 97.0 3.19 0.70 10.100000
## 872 41.0 151.0 3.06 0.49 8.600000
## 873 24.0 125.0 3.06 0.34 10.700000
## 875 10.0 64.0 3.35 0.39 10.100000
## 876 28.0 141.0 3.20 0.57 10.000000
## 877 57.0 119.0 3.28 0.36 12.700000
## 878 33.0 104.0 3.19 0.38 10.200000
## 879 37.0 110.0 3.23 0.37 8.900000
## 880 18.0 111.0 3.41 0.82 11.900000
## 881 28.0 141.0 3.20 0.57 10.000000
## 882 9.0 121.0 3.19 0.48 9.900000
## 883 22.0 125.0 3.13 0.55 11.500000
## 884 22.0 125.0 3.13 0.55 11.500000
## 885 38.0 236.0 3.35 0.52 9.800000
## 886 20.0 105.0 3.40 0.67 12.200000
## 887 39.0 173.0 3.19 0.51 11.400000
## 888 34.0 90.0 3.37 0.68 11.000000
## 889 39.0 173.0 3.19 0.51 11.400000
## 890 34.0 90.0 3.37 0.68 11.000000
## 891 43.0 166.0 3.30 0.63 9.900000
## 892 40.0 114.0 3.42 0.40 11.000000
## 893 38.0 114.0 3.58 0.48 9.400000
## 894 33.0 128.0 3.12 0.36 12.200000
## 895 40.0 114.0 3.42 0.40 11.000000
## 896 17.0 67.0 3.23 0.53 10.300000
## 897 52.0 242.0 3.22 0.53 10.500000
## 898 12.0 87.0 3.08 0.46 10.500000
## 899 13.0 67.0 3.05 0.49 10.900000
## 900 52.0 242.0 3.22 0.53 10.500000
## 901 30.0 145.0 3.32 0.56 11.000000
## 902 26.0 113.0 3.25 0.37 9.700000
## 903 63.0 229.0 3.08 0.40 8.900000
## 904 60.0 206.0 3.20 0.39 9.600000
## 905 49.0 159.0 3.02 0.47 8.800000
## 906 9.0 101.0 3.06 0.65 11.100000
## 907 8.0 72.0 3.08 0.61 10.300000
## 908 30.0 124.0 3.28 0.43 12.200000
## 909 23.0 159.0 3.32 0.47 9.800000
## 910 46.0 217.0 3.08 0.53 8.800000
## 911 24.0 144.0 3.15 0.63 9.900000
## 912 22.0 143.0 3.15 0.63 9.900000
## 913 22.0 145.0 3.15 0.63 9.900000
## 914 11.0 30.0 3.36 0.35 9.200000
## 915 11.5 88.0 3.24 0.37 9.500000
## 916 11.0 30.0 3.36 0.35 9.200000
## 917 36.0 137.0 3.36 0.56 10.300000
## 918 23.0 124.0 2.93 0.33 11.000000
## 919 27.0 107.0 3.06 0.39 11.900000
## 920 20.0 107.0 2.94 0.32 10.200000
## 921 59.0 144.0 3.55 0.44 9.400000
## 922 56.0 153.0 3.13 0.44 8.900000
## 923 56.0 153.0 3.13 0.44 8.900000
## 924 69.0 215.0 3.17 0.43 10.000000
## 925 50.0 152.0 3.45 0.49 10.700000
## 926 13.0 100.0 3.28 0.43 9.800000
## 927 26.0 80.0 3.36 0.38 9.300000
## 928 52.0 173.0 3.02 0.48 9.500000
## 929 47.0 179.0 3.58 0.47 10.000000
## 930 42.0 115.0 3.15 0.51 9.000000
## 931 21.0 84.0 3.14 0.40 11.900000
## 932 64.0 230.0 3.08 0.38 8.900000
## 933 80.0 225.0 3.18 0.41 10.000000
## 934 58.0 205.0 3.26 0.41 9.600000
## 935 64.0 233.0 3.08 0.38 8.900000
## 936 61.0 230.0 3.12 0.40 8.900000
## 937 10.0 67.0 3.08 0.41 11.400000
## 938 42.0 115.0 3.15 0.51 9.000000
## 939 56.0 244.0 3.36 0.55 10.000000
## 940 39.0 194.0 3.06 0.47 9.600000
## 941 40.0 197.0 3.14 0.60 9.700000
## 942 61.0 212.0 3.25 0.53 9.500000
## 943 27.0 88.0 3.54 0.41 10.000000
## 944 31.0 135.0 3.14 0.38 12.200000
## 945 16.0 131.0 3.28 0.44 8.700000
## 946 28.0 105.0 3.52 0.44 10.200000
## 948 24.0 147.0 2.96 0.36 10.000000
## 949 10.0 57.0 3.36 0.52 9.500000
## 950 8.0 84.0 3.18 0.46 11.500000
## 951 15.0 134.0 3.08 0.38 9.500000
## 952 26.0 143.0 3.08 0.49 9.800000
## 953 14.0 99.0 3.23 0.55 10.100000
## 954 39.0 117.0 2.99 0.36 10.000000
## 955 26.0 143.0 3.08 0.49 9.800000
## 956 15.0 134.0 3.08 0.38 9.500000
## 957 13.0 133.0 3.07 0.38 9.500000
## 958 25.0 79.0 3.39 0.54 10.200000
## 959 25.0 78.0 3.39 0.54 10.200000
## 960 38.0 174.0 3.03 0.42 9.000000
## 961 38.0 174.0 3.03 0.42 9.000000
## 962 34.0 101.0 3.13 0.57 12.300000
## 963 38.0 174.0 3.03 0.42 9.000000
## 964 23.0 112.0 3.37 0.51 11.600000
## 965 36.0 152.0 3.28 0.43 9.500000
## 966 14.0 101.0 3.15 0.36 11.500000
## 967 43.0 188.0 3.13 0.37 9.600000
## 968 38.0 153.0 3.24 0.42 9.000000
## 969 23.0 93.0 3.34 0.70 12.000000
## 970 18.0 68.0 3.33 0.51 11.400000
## 971 25.0 102.0 3.38 0.36 12.300000
## 972 24.0 110.0 3.32 0.47 12.600000
## 973 38.0 153.0 3.24 0.42 9.000000
## 974 23.0 93.0 3.34 0.70 12.000000
## 975 14.0 114.0 3.32 0.90 11.700000
## 976 22.0 111.0 3.12 0.49 9.200000
## 977 47.0 131.0 3.51 0.45 10.300000
## 978 53.0 189.0 3.25 0.49 8.600000
## 979 32.0 155.0 3.39 0.62 10.700000
## 982 32.0 155.0 3.39 0.62 10.700000
## 983 15.0 72.0 3.50 0.45 12.500000
## 984 21.0 77.0 3.41 0.45 11.900000
## 985 63.0 149.0 3.44 0.52 10.800000
## 986 29.0 122.0 3.42 0.52 10.500000
## 987 44.0 161.0 3.12 0.48 10.300000
## 988 45.0 163.0 3.12 0.45 10.300000
## 989 63.0 149.0 3.44 0.52 10.800000
## 990 8.0 117.0 3.06 0.38 12.000000
## 991 41.0 143.0 2.95 0.39 10.200000
## 992 7.0 69.0 3.14 0.62 10.200000
## 993 75.0 217.0 3.19 0.39 9.900000
## 994 9.0 62.0 3.38 0.47 10.100000
## 995 24.0 187.0 3.25 0.55 9.500000
## 996 27.0 154.0 3.05 0.45 10.500000
## 997 6.0 29.0 3.29 0.63 10.400000
## 998 33.0 152.0 3.31 0.47 9.500000
## 999 43.0 184.0 3.05 0.50 9.200000
## 1000 47.0 165.0 3.05 0.54 10.100000
## 1001 16.0 84.0 3.15 0.45 9.800000
## 1002 61.0 216.0 3.09 0.46 9.400000
## 1003 60.0 221.0 3.09 0.45 9.400000
## 1004 18.0 136.0 3.31 0.48 10.400000
## 1005 40.0 153.0 3.34 0.55 11.300000
## 1006 18.0 91.0 3.42 0.64 10.800000
## 1007 40.0 153.0 3.34 0.55 11.300000
## 1008 30.0 79.0 3.32 0.43 9.300000
## 1009 45.0 199.0 3.37 0.55 10.300000
## 1010 32.0 146.0 3.08 0.39 10.500000
## 1011 25.0 109.0 3.11 0.75 10.300000
## 1012 60.0 173.0 3.24 0.66 11.200000
## 1013 31.0 98.0 3.15 0.41 10.300000
## 1014 62.0 210.0 3.19 0.50 9.500000
## 1016 19.0 113.0 3.03 0.29 10.200000
## 1017 44.0 136.0 2.98 0.88 9.200000
## 1018 25.0 109.0 3.11 0.75 10.300000
## 1019 47.0 157.0 2.95 0.31 10.500000
## 1020 56.0 189.0 3.21 0.62 9.500000
## 1021 35.0 125.0 3.11 0.49 11.400000
## 1022 35.0 125.0 3.11 0.49 11.400000
## 1023 54.0 188.0 3.25 0.37 11.100000
## 1024 48.0 174.0 3.13 0.38 10.500000
## 1026 38.0 123.0 3.38 0.51 9.700000
## 1027 47.0 140.0 3.32 0.51 10.200000
## 1028 13.0 60.0 3.09 0.30 9.500000
## 1029 51.0 128.0 3.41 0.59 10.400000
## 1030 50.0 245.0 3.19 0.57 9.300000
## 1031 24.0 166.0 3.48 0.62 10.500000
## 1032 45.0 232.0 3.35 0.62 10.000000
## 1033 44.5 234.0 3.49 0.64 10.200000
## 1034 44.5 234.0 3.49 0.64 10.200000
## 1036 39.0 148.0 3.16 0.67 10.200000
## 1037 18.0 75.0 3.54 0.88 10.700000
## 1038 11.0 77.0 3.21 0.56 9.700000
## 1039 33.0 104.0 3.37 0.52 9.300000
## 1040 13.0 102.0 3.05 0.74 11.000000
## 1041 17.0 138.0 3.22 0.71 10.800000
## 1042 19.0 75.0 3.01 0.56 10.700000
## 1043 18.0 104.0 3.24 0.45 10.700000
## 1044 55.0 243.0 2.95 0.40 8.800000
## 1045 23.0 94.0 3.16 0.48 10.900000
## 1046 24.0 92.0 3.14 0.45 10.500000
## 1047 23.0 107.0 3.29 0.45 10.000000
## 1048 5.0 61.0 3.07 0.43 10.400000
## 1049 15.0 75.0 3.03 0.43 9.200000
## 1050 36.0 116.0 3.31 0.62 12.600000
## 1051 29.0 152.0 3.10 0.54 9.000000
## 1053 18.0 86.0 2.99 0.39 11.300000
## 1054 17.0 119.0 3.12 0.69 10.300000
## 1055 5.0 61.0 3.07 0.43 10.400000
## 1056 29.0 111.0 2.96 0.44 10.000000
## 1057 26.0 111.0 3.51 0.47 10.700000
## 1058 35.0 197.0 3.41 0.47 9.000000
## 1059 26.0 111.0 3.51 0.47 10.700000
## 1060 48.0 166.0 3.30 0.54 8.700000
## 1061 30.0 121.0 3.09 0.72 11.600000
## 1062 45.0 185.0 3.34 0.55 9.400000
## 1063 35.5 216.0 3.31 0.68 9.500000
## 1064 36.0 202.0 3.30 0.67 9.500000
## 1065 48.0 159.0 3.37 0.70 10.900000
## 1066 32.0 126.0 3.22 0.50 9.700000
## 1067 62.0 172.0 3.08 0.45 9.100000
## 1068 33.0 125.0 3.10 0.49 11.100000
## 1069 9.0 87.0 2.96 0.40 12.600000
## 1070 38.0 147.0 3.35 0.56 11.000000
## 1071 32.0 166.0 3.00 0.55 11.300000
## 1072 32.0 126.0 3.22 0.50 9.700000
## 1073 28.0 118.0 2.96 0.40 10.900000
## 1074 25.0 192.0 2.97 0.47 10.900000
## 1075 27.0 186.0 3.17 0.50 9.300000
## 1076 28.0 124.0 3.22 0.54 12.700000
## 1077 42.0 180.0 3.37 0.59 10.100000
## 1078 43.0 132.0 3.18 0.65 10.000000
## 1079 56.0 197.0 3.49 0.42 9.800000
## 1080 29.0 227.0 3.29 0.53 10.100000
## 1081 31.0 118.0 3.43 0.39 9.000000
## 1082 52.0 155.0 3.28 0.38 9.400000
## 1083 52.0 155.0 3.28 0.38 9.400000
## 1084 43.0 190.0 3.03 0.42 9.200000
## 1085 29.0 142.0 3.36 0.33 10.100000
## 1086 58.0 160.0 3.06 0.45 8.600000
## 1087 21.0 128.0 3.55 0.49 11.200000
## 1088 39.0 123.0 3.17 0.42 11.200000
## 1089 43.0 190.0 3.03 0.42 9.200000
## 1090 17.0 127.0 3.19 0.39 10.600000
## 1091 62.0 213.0 3.01 0.51 9.300000
## 1092 35.0 178.0 3.05 0.47 8.900000
## 1093 24.0 156.0 3.42 0.43 10.600000
## 1094 29.0 132.0 3.10 0.32 10.600000
## 1095 52.0 183.0 3.09 0.32 8.800000
## 1096 25.0 97.0 3.59 0.38 11.000000
## 1097 44.0 139.0 3.32 0.37 10.200000
## 1098 29.0 142.0 3.36 0.33 10.100000
## 1099 32.0 120.0 3.31 0.34 10.100000
## 1100 12.0 120.0 3.39 0.79 14.000000
## 1101 52.0 155.0 3.28 0.38 9.400000
## 1102 45.0 107.0 3.27 0.43 11.800000
## 1103 59.0 148.0 3.44 0.53 11.400000
## 1104 6.0 117.0 3.12 0.42 10.700000
## 1105 58.0 160.0 3.06 0.45 8.600000
## 1106 25.0 191.0 3.51 0.49 11.500000
## 1107 21.0 128.0 3.55 0.49 11.200000
## 1108 27.0 87.0 3.30 0.59 12.600000
## 1109 13.0 76.0 3.21 0.51 12.600000
## 1110 18.0 151.0 3.04 0.46 9.300000
## 1111 27.0 87.0 3.30 0.59 12.600000
## 1112 15.0 96.0 3.06 0.61 12.100000
## 1113 55.0 177.0 3.52 0.44 9.900000
## 1114 22.0 102.0 3.28 0.44 10.700000
## 1115 5.0 26.0 3.26 0.32 10.000000
## 1116 33.0 96.0 3.13 0.39 10.400000
## 1117 11.0 64.0 3.29 0.52 10.500000
## 1118 33.0 216.0 3.31 0.64 9.700000
## 1119 11.0 64.0 3.29 0.52 10.500000
## 1120 26.0 138.0 3.28 0.33 9.000000
## 1121 34.0 106.0 3.54 0.45 9.200000
## 1122 30.0 117.0 3.17 0.48 10.100000
## 1123 40.0 89.0 3.35 0.40 11.400000
## 1124 11.0 124.0 2.93 0.46 10.800000
## 1125 19.0 135.0 2.96 0.49 10.900000
## 1126 33.0 182.0 3.20 0.46 9.200000
## 1128 24.0 99.0 3.23 0.32 12.000000
## 1129 21.0 100.0 3.27 0.46 9.500000
## 1130 33.0 117.0 3.06 0.32 11.800000
## 1131 36.0 159.0 3.19 0.43 9.100000
## 1132 24.0 128.0 3.20 0.52 9.700000
## 1133 28.0 162.0 3.17 0.54 9.100000
## 1134 27.0 114.0 2.99 0.43 10.000000
## 1135 19.0 127.0 3.25 0.42 10.400000
## 1136 30.0 161.0 3.44 0.47 9.500000
## 1137 70.0 178.0 3.40 0.40 12.300000
## 1138 70.0 170.0 3.42 0.40 11.700000
## 1139 39.0 133.0 3.14 0.58 9.500000
## 1140 26.0 91.0 2.99 0.34 11.500000
## 1141 17.0 57.0 3.14 0.46 10.600000
## 1142 30.0 146.0 3.17 0.61 10.200000
## 1143 39.0 133.0 3.14 0.58 9.500000
## 1144 27.0 131.0 3.25 0.45 10.500000
## 1145 27.0 132.0 3.26 0.44 10.500000
## 1146 71.0 223.0 3.14 0.41 8.900000
## 1147 15.0 151.0 3.03 0.41 10.600000
## 1148 12.0 188.0 3.17 0.49 9.500000
## 1149 29.0 111.0 3.20 0.49 10.800000
## 1150 61.0 220.0 3.14 0.35 9.500000
## 1151 69.0 219.0 3.13 0.40 8.900000
## 1152 71.0 223.0 3.14 0.41 8.900000
## 1153 24.0 79.0 3.31 0.38 9.400000
## 1154 26.0 102.0 3.50 0.35 10.600000
## 1155 37.0 171.0 3.47 0.44 9.000000
## 1156 26.0 172.0 3.42 0.48 10.500000
## 1157 23.0 135.0 3.16 0.38 9.000000
## 1158 23.0 135.0 3.16 0.38 9.000000
## 1160 23.0 135.0 3.16 0.38 9.000000
## 1161 50.0 153.0 3.29 0.80 9.600000
## 1162 23.0 135.0 3.16 0.38 9.000000
## 1163 29.0 151.0 3.15 0.60 10.200000
## 1165 15.0 73.0 3.07 0.38 10.400000
## 1166 34.0 129.0 3.52 0.41 10.400000
## 1167 13.0 82.0 3.23 0.32 9.500000
## 1168 22.0 113.0 3.22 0.62 10.600000
## 1169 21.0 74.0 3.21 0.37 11.000000
## 1170 50.0 153.0 3.29 0.80 9.600000
## 1171 20.0 115.0 3.38 0.50 9.900000
## 1172 15.0 118.0 3.14 0.34 9.600000
## 1173 10.0 119.0 3.01 0.70 12.800000
## 1174 31.0 101.0 3.42 0.55 11.400000
## 1175 49.0 214.0 3.41 0.50 10.000000
## 1176 57.0 173.0 3.00 0.44 9.100000
## 1177 29.0 198.0 3.36 0.50 9.400000
## 1178 19.0 189.0 3.46 0.54 10.200000
## 1179 35.0 167.0 2.97 0.39 9.200000
## 1180 31.0 109.0 3.23 0.36 9.400000
## 1181 15.0 118.0 3.14 0.34 9.600000
## 1182 20.0 125.0 3.12 0.36 10.100000
## 1183 31.0 101.0 3.42 0.55 11.400000
## 1184 33.0 134.0 3.21 0.47 10.600000
## 1185 40.0 138.0 3.18 0.44 12.800000
## 1186 65.0 225.0 3.12 0.51 8.900000
## 1187 22.0 184.0 3.09 0.43 9.300000
## 1188 40.0 104.0 3.25 0.40 11.100000
## 1189 45.0 143.0 3.13 0.33 9.900000
## 1190 5.0 55.0 3.10 0.45 9.600000
## 1191 10.0 119.0 3.01 0.70 12.800000
## 1192 36.0 135.0 3.16 0.72 10.700000
## 1193 29.0 107.0 2.96 0.42 9.200000
## 1194 44.5 129.5 3.36 0.41 9.100000
## 1195 36.0 216.0 3.33 0.60 9.600000
## 1196 53.0 141.0 3.03 0.46 9.200000
## 1197 36.0 135.0 3.16 0.72 10.700000
## 1198 44.5 129.5 3.36 0.41 9.100000
## 1199 29.0 107.0 2.96 0.42 9.200000
## 1200 14.0 93.0 3.00 0.48 10.700000
## 1201 37.0 93.0 3.30 0.45 10.800000
## 1202 26.0 75.0 3.30 0.46 10.800000
## 1203 35.0 192.0 3.10 0.37 9.000000
## 1204 10.0 97.0 3.48 0.44 10.700000
## 1205 10.0 97.0 3.48 0.44 10.700000
## 1207 61.0 171.0 2.94 0.35 8.800000
## 1208 35.0 192.0 3.10 0.37 9.000000
## 1209 48.0 134.0 3.42 0.49 11.500000
## 1210 30.0 125.0 3.23 0.47 12.500000
## 1211 14.0 59.0 2.96 0.25 10.500000
## 1212 28.0 188.0 3.29 0.30 9.700000
## 1213 32.0 155.0 3.23 0.52 11.300000
## 1214 10.0 97.0 3.48 0.44 10.700000
## 1215 11.0 59.0 2.74 0.47 10.800000
## 1216 41.0 169.0 3.17 0.43 10.600000
## 1217 17.0 93.0 3.04 0.32 11.700000
## 1219 25.0 126.0 3.02 0.34 11.100000
## 1220 17.0 93.0 3.04 0.32 11.700000
## 1221 15.5 217.5 3.33 0.44 11.000000
## 1222 50.0 127.0 3.51 0.58 12.500000
## 1223 21.0 115.0 3.16 0.67 10.000000
## 1224 41.0 169.0 3.17 0.43 10.600000
## 1225 29.0 102.0 3.26 0.54 12.300000
## 1226 19.0 87.0 3.14 0.53 12.700000
## 1227 29.0 102.0 3.26 0.54 12.300000
## 1228 20.0 110.0 3.10 0.42 10.500000
## 1229 25.0 109.0 3.23 0.28 12.500000
## 1230 18.0 96.0 3.20 0.32 12.400000
## 1231 46.0 238.0 3.06 0.41 8.700000
## 1232 40.0 114.0 3.17 0.54 12.400000
## 1233 27.0 93.0 3.16 0.54 12.600000
## 1234 29.0 131.0 3.38 0.44 11.000000
## 1235 47.0 155.0 3.42 0.50 10.100000
## 1236 46.0 195.0 3.03 0.48 10.500000
## 1237 19.0 87.0 3.14 0.53 12.700000
## 1238 35.0 116.0 3.17 0.51 10.900000
## 1239 35.0 128.0 3.07 0.43 13.500000
## 1240 28.0 164.0 3.19 0.59 9.700000
## 1241 44.0 178.0 3.45 0.43 9.200000
## 1242 33.0 187.0 3.40 0.41 10.600000
## 1243 36.0 141.0 2.98 0.39 13.300000
## 1244 35.0 128.0 3.07 0.43 13.500000
## 1245 23.0 131.0 3.29 0.32 10.100000
## 1247 41.0 167.0 3.18 0.40 10.600000
## 1248 25.0 80.0 3.25 0.40 11.300000
## 1249 20.0 73.0 3.32 0.40 10.800000
## 1250 46.0 195.0 3.15 0.51 10.400000
## 1251 48.0 160.0 3.82 0.51 10.500000
## 1252 28.0 150.0 3.13 0.42 9.300000
## 1253 24.0 152.0 3.12 0.42 9.300000
## 1254 52.0 165.0 3.29 0.39 12.200000
## 1256 29.0 104.0 3.81 0.57 10.300000
## 1257 28.0 157.0 3.33 0.62 9.400000
## 1258 88.0 223.0 3.28 0.35 10.200000
## 1259 65.0 212.0 3.08 0.39 9.000000
## 1260 64.0 245.0 3.06 0.36 9.300000
## 1261 63.0 236.0 3.06 0.34 9.200000
## 1262 31.0 156.0 3.32 0.64 9.400000
## 1263 28.0 157.0 3.33 0.62 9.400000
## 1265 15.0 73.0 3.46 0.39 9.900000
## 1266 36.0 174.0 3.46 0.62 11.100000
## 1267 36.0 116.0 2.99 0.41 12.300000
## 1268 45.0 163.0 3.21 0.69 8.600000
## 1269 21.0 145.0 3.04 0.35 9.400000
## 1270 55.0 190.0 3.07 0.58 9.400000
## 1271 45.0 163.0 3.21 0.69 8.600000
## 1272 23.0 126.0 3.21 0.42 10.900000
## 1273 32.0 162.0 3.20 0.48 9.400000
## 1274 23.0 126.0 3.21 0.42 10.900000
## 1275 55.0 190.0 3.07 0.58 9.400000
## 1276 20.0 132.0 3.22 0.46 9.200000
## 1277 45.0 163.0 3.21 0.69 8.600000
## 1278 21.0 145.0 3.04 0.35 9.400000
## 1279 10.0 133.0 3.33 0.37 10.800000
## 1280 14.0 153.0 3.29 0.62 10.500000
## 1281 29.0 140.0 3.02 0.78 12.500000
## 1282 26.0 168.0 2.99 0.48 12.100000
## 1283 51.0 147.0 3.02 0.43 8.700000
## 1284 50.0 151.0 3.07 0.25 12.700000
## 1285 26.0 168.0 2.99 0.48 12.100000
## 1286 29.0 140.0 3.02 0.78 12.500000
## 1287 40.0 147.0 3.06 0.44 11.400000
## 1288 35.0 110.0 3.02 0.60 12.900000
## 1289 29.0 109.0 3.15 0.51 12.800000
## 1290 15.0 78.0 3.38 0.44 11.200000
## 1291 16.0 98.0 3.14 0.42 9.700000
## 1292 54.0 191.0 3.04 0.56 9.700000
## 1293 14.0 79.0 3.50 0.54 10.300000
## 1294 10.0 102.0 3.00 0.87 11.600000
## 1295 10.0 102.0 3.00 0.86 11.600000
## 1296 54.0 191.0 3.04 0.56 9.700000
## 1297 30.0 131.0 3.32 0.44 10.900000
## 1298 29.0 122.0 3.19 0.37 12.600000
## 1299 45.0 163.0 3.30 0.47 12.400000
## 1300 45.0 166.0 2.96 0.40 11.500000
## 1301 52.0 159.0 2.93 0.35 10.200000
## 1302 51.0 176.0 3.22 0.27 11.400000
## 1303 39.0 212.0 3.30 0.33 9.600000
## 1304 60.0 163.0 3.05 0.30 10.300000
## 1306 17.0 114.0 3.33 0.49 10.700000
## 1307 34.0 105.0 3.13 0.49 12.800000
## 1308 23.0 142.0 2.98 0.62 9.500000
## 1309 22.0 130.0 3.02 0.45 10.400000
## 1310 14.0 94.0 3.02 0.61 10.300000
## 1311 37.0 142.0 3.46 0.39 9.900000
## 1312 37.0 116.0 3.23 0.50 10.700000
## 1313 16.0 160.0 2.94 0.43 10.500000
## 1314 14.0 186.0 3.08 0.48 9.600000
## 1315 46.0 169.0 3.15 0.46 9.300000
## 1316 63.0 162.0 3.10 0.46 10.000000
## 1317 40.0 190.0 3.04 0.39 11.200000
## 1318 21.0 177.0 3.32 0.62 10.800000
## 1319 25.0 96.0 3.54 0.51 10.300000
## 1320 59.0 234.0 3.03 0.42 8.800000
## 1321 6.0 114.0 3.04 0.74 12.800000
## 1322 17.0 114.0 3.23 0.43 13.200000
## 1323 28.0 152.0 3.54 0.56 10.100000
## 1324 40.0 161.0 3.44 0.66 11.000000
## 1325 21.0 182.0 3.25 0.62 10.800000
## 1326 28.0 114.0 3.20 0.52 12.800000
## 1327 33.0 168.0 3.12 0.36 9.200000
## 1328 44.0 167.0 3.12 0.44 10.500000
## 1329 13.0 81.0 3.37 0.38 11.700000
## 1330 20.0 104.0 2.85 0.46 9.500000
## 1331 24.0 108.0 2.85 0.45 9.500000
## 1332 24.0 110.0 3.40 0.40 8.800000
## 1333 69.0 210.0 3.15 0.51 9.300000
## 1334 62.0 180.0 3.09 0.75 12.600000
## 1335 26.0 107.0 3.21 0.34 12.400000
## 1336 60.0 189.0 3.65 0.72 10.100000
## 1337 38.0 161.0 3.26 0.37 11.200000
## 1338 40.0 251.0 3.29 0.52 10.000000
## 1339 40.0 251.0 3.29 0.52 10.000000
## 1340 37.0 116.0 2.99 0.39 10.800000
## 1341 50.0 121.0 3.27 0.33 10.000000
## 1342 13.0 151.0 3.04 0.33 10.400000
## 1343 37.0 116.0 2.99 0.39 10.800000
## 1344 52.0 181.0 3.51 0.47 9.800000
## 1345 51.0 165.0 3.26 0.40 12.200000
## 1346 36.0 113.0 3.39 0.48 12.700000
## 1347 46.0 163.0 3.21 0.35 12.200000
## 1348 35.0 162.0 3.15 0.34 11.900000
## 1349 38.0 161.0 3.26 0.37 11.200000
## 1350 15.0 61.0 2.96 0.28 10.400000
## 1351 22.0 122.0 3.29 0.67 12.800000
## 1352 40.0 130.0 3.28 0.39 12.700000
## 1353 60.0 189.0 3.65 0.72 10.100000
## 1354 40.0 251.0 3.29 0.52 10.000000
## 1355 43.0 179.0 3.43 0.41 9.000000
## 1356 38.0 143.0 2.92 0.42 11.400000
## 1357 55.0 191.0 3.32 0.59 8.900000
## 1358 43.0 167.0 3.15 0.44 9.300000
## 1359 35.0 103.0 3.28 0.46 12.000000
## 1360 31.0 132.0 3.36 0.54 10.800000
## 1361 56.0 158.0 3.52 0.37 10.500000
## 1362 56.0 189.5 3.59 0.43 10.600000
## 1363 42.0 115.0 3.19 0.48 11.300000
## 1364 15.0 96.0 3.22 0.38 9.500000
## 1365 38.0 143.0 2.92 0.42 11.400000
## 1366 35.0 140.0 3.33 0.33 10.100000
## 1367 22.0 95.0 3.25 0.43 10.900000
## 1368 19.0 115.0 3.15 0.45 8.900000
## 1369 55.0 191.0 3.32 0.59 8.900000
## 1371 23.0 116.0 3.25 0.40 10.400000
## 1372 41.0 162.0 3.10 0.38 12.000000
## 1373 37.0 181.0 2.87 0.68 9.500000
## 1374 37.0 181.0 2.87 0.68 9.500000
## 1375 24.0 121.0 3.14 0.38 12.400000
## 1376 30.0 130.0 3.28 0.41 11.200000
## 1377 6.0 134.0 3.15 0.69 11.400000
## 1378 10.0 136.0 3.16 0.71 11.400000
## 1379 46.0 132.0 3.35 0.38 11.100000
## 1380 5.0 126.0 3.10 0.42 10.400000
## 1381 36.0 152.0 3.38 0.35 12.000000
## 1382 24.0 98.0 3.54 0.61 12.300000
## 1383 28.0 92.0 3.12 0.35 9.100000
## 1384 25.0 102.0 3.24 0.33 10.500000
## 1385 5.0 133.0 3.23 0.70 11.400000
## 1386 26.0 138.0 3.77 0.64 9.500000
## 1388 15.0 85.0 3.28 0.51 13.400000
## 1389 12.0 143.0 3.20 0.48 11.300000
## 1390 73.0 180.0 3.06 0.34 10.000000
## 1391 33.0 123.0 3.49 0.42 10.100000
## 1392 23.0 81.0 3.26 0.42 12.200000
## 1393 15.0 85.0 3.28 0.51 13.400000
## 1394 19.0 101.0 3.31 0.42 9.300000
## 1396 27.0 98.0 3.09 0.46 12.300000
## 1397 12.0 143.0 3.20 0.48 11.300000
## 1398 35.0 200.0 3.04 0.46 8.900000
## 1399 35.0 200.0 3.04 0.46 8.900000
## 1400 32.0 83.0 3.19 0.46 11.500000
## 1401 35.0 200.0 3.04 0.46 8.900000
## 1403 31.0 122.0 3.30 0.50 11.100000
## 1404 29.0 128.0 3.34 0.64 10.900000
## 1405 11.0 73.0 2.90 0.38 11.600000
## 1406 9.0 117.0 3.15 0.35 10.200000
## 1407 12.0 90.0 3.01 0.38 10.500000
## 1408 16.0 78.0 2.91 0.78 11.400000
## 1409 35.0 200.0 3.04 0.46 8.900000
## 1410 29.0 118.0 3.14 0.41 10.600000
## 1411 39.0 97.0 3.31 0.40 11.600000
## 1412 32.0 83.0 3.19 0.46 11.500000
## 1413 26.0 155.0 3.25 0.79 12.300000
## 1414 22.0 124.0 3.14 0.41 10.800000
## 1415 55.0 130.0 3.29 0.38 11.300000
## 1416 22.0 63.0 3.36 0.36 9.300000
## 1417 16.0 128.0 3.36 0.60 10.000000
## 1420 27.0 103.0 3.07 0.40 10.800000
## 1421 29.0 137.0 3.10 0.34 10.100000
## 1422 17.0 90.0 3.27 0.37 11.600000
## 1423 25.0 105.0 3.32 0.47 9.100000
## 1424 36.0 225.0 3.06 0.43 10.000000
## 1425 22.0 124.0 3.14 0.41 10.800000
## 1426 26.0 128.0 3.25 0.35 11.400000
## 1427 34.0 140.0 3.05 0.34 12.700000
## 1428 35.0 156.0 3.13 0.55 11.300000
## 1429 28.0 81.0 3.00 0.68 10.400000
## 1430 18.0 87.0 3.30 0.46 9.600000
## 1431 8.0 119.0 3.00 0.31 10.100000
## 1432 18.0 87.0 3.30 0.46 9.600000
## 1433 16.0 94.0 3.10 0.49 12.100000
## 1434 32.0 99.0 3.07 0.33 12.200000
## 1435 35.0 156.0 3.13 0.55 11.300000
## 1436 19.0 94.0 3.17 0.50 9.600000
## 1438 28.0 81.0 3.00 0.68 10.400000
## 1439 67.0 210.0 3.23 0.34 9.500000
## 1440 67.0 226.0 3.16 0.47 8.900000
## 1441 56.0 162.0 3.03 0.44 8.800000
## 1442 17.0 117.0 3.16 0.35 10.500000
## 1443 27.0 117.0 3.08 0.34 9.400000
## 1444 34.0 125.0 3.24 0.40 12.200000
## 1445 37.0 158.0 3.14 0.35 11.300000
## 1446 33.0 130.0 3.25 0.42 12.200000
## 1447 35.0 92.0 3.38 0.42 12.200000
## 1448 18.0 150.0 3.23 0.47 11.200000
## 1449 18.0 150.0 3.23 0.47 11.200000
## 1450 49.0 172.0 3.20 0.27 11.500000
## 1451 37.0 158.0 3.14 0.35 11.300000
## 1452 11.0 138.0 3.01 0.42 9.300000
## 1453 37.0 158.0 3.14 0.35 11.300000
## 1454 37.0 156.0 3.14 0.38 11.800000
## 1455 50.0 231.0 2.99 0.54 9.200000
## 1457 35.0 92.0 3.38 0.42 12.200000
## 1458 33.0 130.0 3.25 0.42 12.200000
## 1459 42.0 144.0 3.31 0.41 12.200000
## 1460 27.0 133.0 3.24 0.42 10.600000
## 1461 29.0 128.0 3.28 0.40 12.400000
## 1462 54.0 164.0 3.56 0.44 10.800000
## 1463 18.0 150.0 3.23 0.47 11.200000
## 1464 11.0 137.0 3.06 0.46 11.000000
## 1465 46.0 151.0 3.16 0.27 12.700000
## 1467 49.0 172.0 3.20 0.27 11.500000
## 1468 30.0 96.0 3.13 0.39 12.300000
## 1469 15.0 60.0 3.19 0.39 9.800000
## 1470 11.0 138.0 3.01 0.42 9.300000
## 1471 37.0 156.0 3.14 0.38 11.800000
## 1472 37.0 158.0 3.14 0.35 11.300000
## 1473 6.0 48.0 3.15 0.28 11.400000
## 1474 39.0 128.0 3.21 0.48 10.800000
## 1475 13.0 85.0 2.99 0.48 9.500000
## 1476 18.0 148.0 3.46 0.44 10.200000
## 1478 10.0 104.0 3.05 0.29 10.800000
## 1479 39.0 159.0 2.99 0.28 11.500000
## 1480 20.0 124.0 3.32 0.49 10.700000
## 1481 18.0 148.0 3.46 0.44 10.200000
## 1482 26.0 124.0 3.37 0.60 10.100000
## 1483 57.0 187.0 3.62 0.81 10.400000
## 1484 13.0 85.0 2.99 0.48 9.500000
## 1485 8.0 134.0 3.14 0.50 9.100000
## 1486 20.0 126.0 2.98 0.39 10.600000
## 1487 17.0 51.0 3.30 0.70 9.400000
## 1489 68.0 224.0 3.18 0.54 9.500000
## 1490 52.0 187.0 2.99 0.41 9.300000
## 1491 28.0 117.0 3.55 0.45 10.300000
## 1492 8.0 97.0 3.06 0.62 11.100000
## 1493 47.0 188.0 3.14 0.48 10.000000
## 1494 39.0 180.0 3.13 0.38 12.300000
## 1495 42.0 186.0 3.14 0.38 12.400000
## 1496 45.0 197.0 3.13 0.38 12.300000
## 1497 6.0 62.0 3.41 0.32 10.400000
## 1498 35.0 126.0 3.13 0.48 12.100000
## 1499 23.0 86.0 3.16 0.42 12.500000
## 1500 14.0 155.0 3.22 0.60 13.000000
## 1501 26.0 132.0 2.99 0.32 11.000000
## 1502 34.0 169.0 3.05 0.37 10.100000
## 1503 17.0 121.0 3.13 0.36 9.200000
## 1504 24.0 124.0 3.27 0.34 12.600000
## 1506 39.0 130.0 3.04 0.49 9.800000
## 1507 51.0 205.0 3.10 0.52 11.000000
## 1508 59.0 160.0 3.22 0.64 10.000000
## 1509 50.0 170.0 3.55 0.44 9.800000
## 1510 15.0 144.0 3.16 0.47 10.500000
## 1511 10.0 145.0 3.23 0.48 10.000000
## 1512 15.0 126.0 3.02 0.51 11.200000
## 1513 29.0 134.0 2.99 0.32 11.000000
## 1514 48.0 161.0 3.01 0.28 11.200000
## 1515 26.0 132.0 2.99 0.32 11.000000
## 1516 34.0 136.0 3.14 0.77 10.500000
## 1517 53.0 154.0 3.02 0.33 10.600000
## 1518 52.0 163.0 3.02 0.33 10.600000
## 1519 22.0 95.0 3.04 0.34 12.000000
## 1520 34.0 169.0 3.05 0.37 10.100000
## 1521 38.0 167.0 3.05 0.37 10.100000
## 1522 17.0 121.0 3.13 0.36 9.200000
## 1523 15.0 164.0 3.25 0.63 11.000000
## 1524 31.0 185.0 3.34 0.49 10.000000
## 1525 41.0 158.0 3.28 0.39 8.700000
## 1526 47.0 156.0 3.04 0.44 8.700000
## 1528 48.0 195.0 3.04 0.55 11.000000
## 1529 33.0 156.0 3.15 0.54 11.100000
## 1530 41.0 158.0 3.28 0.39 8.700000
## 1531 47.0 156.0 3.04 0.44 8.700000
## 1532 26.0 174.0 3.10 0.30 11.200000
## 1533 61.0 209.0 3.14 0.30 11.100000
## 1534 32.0 107.0 3.24 0.54 10.800000
## 1536 17.0 122.0 3.03 0.40 10.300000
## 1537 6.0 24.0 2.91 0.32 9.900000
## 1538 32.0 148.0 3.13 0.41 10.000000
## 1539 26.0 106.0 3.21 0.42 9.800000
## 1540 32.0 107.0 3.24 0.54 10.800000
## 1542 29.0 86.0 3.16 0.32 9.100000
## 1543 27.0 104.0 3.23 0.57 10.600000
## 1544 28.0 99.0 3.20 0.72 10.600000
## 1545 6.0 24.0 2.91 0.32 9.900000
## 1546 33.0 152.0 3.18 0.47 10.600000
## 1547 35.0 156.0 3.13 0.45 9.900000
## 1548 36.0 158.0 3.12 0.45 9.900000
## 1549 32.0 102.0 3.34 0.59 12.800000
## 1550 17.0 122.0 3.03 0.40 10.300000
## 1551 36.0 157.0 3.18 0.48 10.600000
## 1553 44.0 152.0 3.32 0.44 12.600000
## 1554 25.0 156.0 3.43 0.63 11.000000
## 1555 32.0 164.0 3.29 0.60 11.200000
## 1556 35.0 148.0 3.45 0.57 10.700000
## 1557 45.0 182.0 3.08 0.58 9.600000
## 1558 36.0 157.0 3.18 0.48 10.600000
## 1559 12.0 115.0 3.27 0.57 9.000000
## 1560 14.0 56.0 2.96 0.33 10.500000
## 1561 33.0 156.0 3.29 0.52 12.800000
## 1562 10.0 112.0 3.15 0.46 10.100000
## 1563 26.0 126.0 3.30 0.33 12.200000
## 1564 33.0 156.0 3.29 0.52 12.800000
## 1565 10.0 112.0 3.15 0.46 10.100000
## 1566 29.0 117.0 3.14 0.51 10.100000
## 1567 36.0 158.0 3.06 0.41 9.200000
## 1568 19.0 110.0 3.33 0.44 9.900000
## 1569 49.0 188.0 3.52 0.58 9.700000
## 1570 35.0 157.0 3.21 0.46 9.900000
## 1571 36.0 159.0 3.21 0.45 9.900000
## 1572 49.0 188.0 3.52 0.58 9.700000
## 1573 50.0 168.0 3.54 0.50 10.300000
## 1574 21.0 116.0 3.16 0.35 10.300000
## 1575 23.0 108.0 2.88 0.34 10.500000
## 1577 20.0 74.0 3.32 0.44 9.800000
## 1578 17.0 128.0 3.31 0.58 10.600000
## 1580 50.0 191.0 3.22 0.53 9.000000
## 1581 13.0 119.0 3.18 0.45 9.500000
## 1582 32.0 84.0 2.94 0.32 11.500000
## 1583 46.0 108.0 3.03 0.33 11.900000
## 1585 52.0 209.0 3.21 0.42 9.200000
## 1586 46.0 165.0 3.02 0.40 8.700000
## 1587 34.0 147.0 3.11 0.46 9.800000
## 1588 52.0 209.0 3.21 0.42 9.200000
## 1589 46.0 165.0 3.02 0.40 8.700000
## 1590 27.0 122.0 3.35 0.48 11.200000
## 1591 30.0 165.0 3.08 0.82 12.300000
## 1592 49.0 161.0 3.34 0.44 10.400000
## 1593 25.0 111.0 3.13 0.41 10.700000
## 1594 9.0 63.0 3.13 0.59 10.500000
## 1595 37.0 136.0 2.95 0.40 9.400000
## 1596 53.0 206.0 3.24 0.43 9.200000
## 1597 56.0 122.0 3.15 0.30 11.900000
## 1598 53.0 206.0 3.24 0.43 9.200000
## 1601 37.0 136.0 2.95 0.40 9.400000
## 1602 55.0 223.0 3.08 0.52 10.700000
## 1603 27.0 77.0 3.28 0.36 12.700000
## 1604 10.0 53.0 3.32 0.50 13.500000
## 1605 39.0 137.0 3.24 0.35 9.500000
## 1606 31.0 113.0 3.37 0.42 12.900000
## 1607 44.0 109.0 3.07 0.46 12.500000
## 1608 44.0 118.0 3.34 0.38 9.500000
## 1609 59.0 235.0 2.98 0.47 8.600000
## 1610 46.0 212.0 3.09 0.46 10.000000
## 1611 44.0 109.0 3.07 0.46 12.500000
## 1612 19.0 100.0 3.12 0.34 10.100000
## 1613 28.0 87.0 3.03 0.32 11.300000
## 1614 42.0 120.0 3.26 0.40 10.600000
## 1615 40.0 131.0 3.14 0.34 10.800000
## 1616 42.0 140.0 3.40 0.47 10.700000
## 1617 61.0 206.0 3.09 0.40 9.000000
## 1618 17.0 143.0 3.22 0.52 9.200000
## 1619 53.0 243.0 3.14 0.48 8.500000
## 1620 31.0 128.0 3.41 0.36 11.300000
## 1621 28.0 87.0 3.03 0.32 11.300000
## 1622 17.0 131.0 3.13 0.34 9.400000
## 1623 16.0 169.0 3.11 0.37 8.700000
## 1624 22.0 118.0 3.36 0.36 9.400000
## 1625 46.0 131.0 3.09 0.51 10.500000
## 1626 37.0 161.0 3.38 0.53 9.700000
## 1627 52.0 195.0 3.31 0.44 10.200000
## 1628 17.0 131.0 3.13 0.34 9.400000
## 1629 14.0 108.0 3.19 0.35 11.500000
## 1630 21.0 98.0 2.94 0.31 9.600000
## 1631 6.0 121.0 3.23 0.70 11.400000
## 1632 14.0 108.0 3.19 0.35 11.500000
## 1633 28.0 111.0 3.41 0.58 12.200000
## 1634 15.0 110.0 3.20 0.38 11.000000
## 1635 50.0 228.0 3.03 0.52 9.200000
## 1636 21.0 126.0 3.26 0.45 10.200000
## 1637 29.0 149.0 3.21 0.33 10.000000
## 1638 43.0 160.0 3.13 0.48 9.700000
## 1640 26.0 105.0 3.10 0.39 10.500000
## 1641 29.0 149.0 3.21 0.33 10.000000
## 1642 42.0 151.0 3.27 0.52 10.100000
## 1643 50.0 134.0 3.42 0.36 9.100000
## 1644 50.0 144.0 3.09 0.57 10.200000
## 1645 50.0 134.0 3.42 0.36 9.100000
## 1646 50.0 149.0 3.17 0.59 10.500000
## 1647 42.0 151.0 3.27 0.52 10.100000
## 1648 20.0 99.0 3.05 0.28 12.100000
## 1649 31.0 100.0 3.40 0.59 10.200000
## 1650 39.0 166.0 3.65 0.52 9.400000
## 1651 27.0 131.0 3.08 0.67 12.800000
## 1653 29.0 118.0 3.24 0.36 10.900000
## 1655 19.0 184.0 3.11 0.38 9.000000
## 1656 27.0 142.0 3.09 0.59 10.200000
## 1657 21.0 98.0 3.19 0.48 9.200000
## 1658 34.0 162.0 3.26 0.58 11.300000
## 1659 52.0 220.0 3.12 0.45 8.800000
## 1660 53.0 217.0 3.16 0.40 9.300000
## 1661 62.0 217.0 3.17 0.45 9.400000
## 1662 54.0 191.0 3.23 0.40 10.300000
## 1663 30.0 114.0 2.92 0.42 10.800000
## 1665 32.0 177.0 3.27 0.58 9.000000
## 1666 48.0 114.0 3.41 0.51 11.500000
## 1667 8.0 84.0 3.25 0.43 10.800000
## 1668 33.0 128.0 2.95 0.51 11.800000
## 1669 20.0 72.0 3.12 0.38 10.500000
## 1670 10.0 124.0 3.14 0.44 9.900000
## 1671 33.0 160.0 3.20 0.56 9.800000
## 1672 27.0 87.0 3.40 0.42 11.400000
## 1673 41.0 168.0 3.20 0.38 9.300000
## 1674 35.0 163.0 3.20 0.38 9.300000
## 1675 82.0 188.0 3.30 0.44 10.300000
## 1676 65.0 224.0 3.17 0.47 8.900000
## 1677 27.0 87.0 3.40 0.42 11.400000
## 1678 60.0 156.0 3.11 0.35 11.100000
## 1679 42.0 170.0 3.36 0.45 10.400000
## 1680 18.0 117.0 3.33 0.43 10.100000
## 1681 44.0 197.0 3.22 0.55 9.000000
## 1683 55.0 205.0 3.12 0.38 9.000000
## 1684 55.0 205.0 3.12 0.38 9.000000
## 1685 41.5 195.0 3.06 0.44 9.100000
## 1686 55.0 205.0 3.12 0.38 9.000000
## 1687 42.0 147.0 3.46 0.72 10.000000
## 1688 41.5 195.0 3.06 0.44 9.100000
## 1690 28.0 123.0 3.27 0.55 11.400000
## 1691 7.0 175.0 3.11 0.45 9.700000
## 1692 55.0 205.0 3.12 0.38 9.000000
## 1693 41.0 213.0 3.28 0.49 11.800000
## 1694 54.0 198.0 3.25 0.41 10.200000
## 1695 47.0 150.0 3.37 0.42 9.200000
## 1696 35.0 132.0 3.25 0.40 11.000000
## 1697 47.0 190.0 3.08 0.31 10.000000
## 1698 39.0 190.0 3.32 0.37 12.200000
## 1699 41.0 213.0 3.28 0.49 11.800000
## 1700 35.0 175.0 3.38 0.43 11.600000
## 1701 25.0 121.0 3.44 0.61 10.200000
## 1702 43.0 208.0 3.14 0.46 10.300000
## 1703 6.0 114.0 3.25 0.35 8.600000
## 1704 27.0 151.0 3.16 0.44 9.600000
## 1705 25.0 148.0 3.16 0.45 9.600000
## 1706 32.0 127.0 3.41 0.47 11.300000
## 1707 38.0 157.0 3.41 0.55 9.900000
## 1708 48.0 179.0 3.45 0.40 9.600000
## 1709 25.0 161.0 3.36 0.60 10.600000
## 1710 50.0 180.0 3.44 0.39 9.800000
## 1711 10.0 67.0 3.08 0.47 10.500000
## 1712 31.0 120.0 3.24 0.51 10.800000
## 1713 25.0 178.0 3.22 0.51 10.000000
## 1714 23.0 136.0 3.30 0.49 10.100000
## 1715 35.0 116.0 3.07 0.48 9.400000
## 1716 43.0 148.0 3.32 0.59 11.500000
## 1717 29.0 108.0 3.26 0.50 10.800000
## 1718 19.0 142.0 3.10 0.43 9.900000
## 1719 28.0 178.0 3.16 0.43 9.000000
## 1720 24.0 69.0 3.38 0.31 9.400000
## 1721 30.0 180.0 3.46 0.44 10.800000
## 1724 43.0 148.0 3.32 0.59 11.500000
## 1725 31.0 122.0 3.47 0.42 10.500000
## 1726 55.0 152.0 3.29 0.37 9.300000
## 1727 28.0 97.0 3.23 0.44 11.800000
## 1729 35.0 116.0 3.07 0.48 9.400000
## 1730 45.0 138.0 3.20 0.68 11.400000
## 1731 40.0 99.0 2.94 0.30 10.400000
## 1733 48.0 111.0 3.14 0.32 11.900000
## 1734 49.0 123.0 2.99 0.45 11.100000
## 1735 50.0 185.0 3.39 0.38 9.600000
## 1736 56.0 178.0 3.29 0.47 12.000000
## 1737 15.0 104.0 3.14 0.42 8.700000
## 1738 50.0 185.0 3.39 0.38 9.600000
## 1739 19.0 101.0 3.24 0.44 10.000000
## 1740 4.0 55.0 2.91 0.32 11.400000
## 1741 23.0 150.0 3.14 0.45 9.600000
## 1742 28.0 152.0 3.18 0.32 12.900000
## 1743 47.0 142.0 3.14 0.35 9.700000
## 1744 33.0 169.0 3.23 0.51 9.300000
## 1746 46.0 238.0 3.16 0.48 8.600000
## 1747 33.0 87.0 3.14 0.42 9.900000
## 1748 33.0 169.0 3.23 0.51 9.300000
## 1749 20.0 102.0 3.28 0.42 10.900000
## 1750 45.0 135.0 3.20 0.43 10.200000
## 1751 44.0 174.0 3.11 0.57 9.700000
## 1752 40.0 153.0 3.38 0.51 11.400000
## 1753 53.0 197.0 3.24 0.54 9.500000
## 1754 43.0 141.0 3.42 0.54 10.200000
## 1755 33.0 93.0 3.31 0.43 11.100000
## 1756 47.0 142.0 3.14 0.35 9.700000
## 1757 54.0 202.0 3.22 0.43 9.300000
## 1758 56.0 215.0 3.17 0.44 8.800000
## 1759 12.0 53.0 2.80 0.46 10.600000
## 1760 81.0 224.0 3.17 0.44 9.300000
## 1761 67.0 181.0 3.31 0.35 10.200000
## 1762 31.0 124.0 3.16 0.51 10.200000
## 1763 20.0 98.0 3.46 0.42 11.000000
## 1764 18.0 112.0 3.40 0.50 9.600000
## 1765 54.0 202.0 3.22 0.43 9.300000
## 1766 56.0 215.0 3.17 0.44 8.800000
## 1767 56.0 209.0 3.17 0.45 8.800000
## 1768 50.0 179.0 3.28 0.69 8.900000
## 1769 58.0 144.0 3.17 0.38 10.000000
## 1770 33.0 102.0 3.16 0.56 12.200000
## 1771 33.0 181.0 3.04 0.42 10.900000
## 1772 40.0 141.0 3.34 0.72 9.500000
## 1773 32.0 178.0 3.04 0.43 10.900000
## 1774 33.0 181.0 3.04 0.42 10.900000
## 1775 33.0 99.0 3.16 0.40 10.800000
## 1777 42.0 163.0 3.56 0.47 9.800000
## 1778 40.0 141.0 3.34 0.72 9.500000
## 1779 43.0 150.0 3.42 0.69 11.000000
## 1780 43.0 150.0 3.42 0.69 11.000000
## 1781 47.0 150.0 3.24 0.38 9.800000
## 1783 73.0 142.0 3.05 0.37 11.400000
## 1784 17.0 100.0 3.27 0.57 10.100000
## 1785 54.0 127.0 3.33 0.46 11.600000
## 1786 73.0 142.0 3.05 0.37 11.400000
## 1787 29.0 115.0 3.07 0.52 11.800000
## 1788 50.0 158.0 3.33 0.43 12.100000
## 1789 37.0 122.0 3.16 0.34 12.000000
## 1790 26.0 189.0 3.08 0.74 12.100000
## 1791 26.0 176.0 3.15 0.46 9.100000
## 1792 25.0 117.0 3.36 0.50 9.300000
## 1793 21.0 153.0 3.20 0.53 10.400000
## 1794 42.0 187.0 3.27 0.64 9.100000
## 1795 23.0 120.0 3.32 0.54 9.400000
## 1796 22.0 149.0 3.16 0.47 9.600000
## 1797 27.0 126.0 3.19 0.62 12.000000
## 1798 37.0 128.0 3.27 0.34 11.300000
## 1799 56.0 173.0 3.06 0.41 8.700000
## 1800 35.0 162.0 3.39 0.58 9.900000
## 1801 57.0 191.0 3.08 0.40 9.300000
## 1802 14.0 67.0 3.07 0.32 9.500000
## 1803 56.0 173.0 3.06 0.41 8.700000
## 1804 35.0 162.0 3.39 0.58 9.900000
## 1805 57.0 191.0 3.08 0.40 9.300000
## 1806 29.0 119.0 3.16 0.39 9.400000
## 1807 9.0 116.0 3.15 0.41 9.400000
## 1808 60.0 184.0 3.28 0.79 8.800000
## 1809 29.0 119.0 3.16 0.39 9.400000
## 1810 60.0 184.0 3.28 0.79 8.800000
## 1811 39.0 184.0 3.18 0.41 9.900000
## 1812 9.0 116.0 3.15 0.41 9.400000
## 1813 24.0 72.0 3.29 0.37 12.600000
## 1814 18.0 110.0 3.19 0.43 11.100000
## 1815 31.0 100.0 3.00 0.32 12.800000
## 1816 10.0 164.0 3.09 0.53 12.000000
## 1817 34.0 131.0 3.36 0.50 12.000000
## 1818 46.0 114.0 3.19 0.34 9.200000
## 1819 27.0 96.0 3.38 0.44 12.300000
## 1820 38.0 131.0 3.19 0.41 13.000000
## 1821 10.0 164.0 3.09 0.53 12.000000
## 1822 23.0 110.0 3.07 0.38 10.900000
## 1823 31.0 100.0 3.00 0.32 12.800000
## 1824 34.0 231.0 3.36 0.54 10.000000
## 1825 35.0 165.0 3.22 0.32 9.000000
## 1826 13.0 84.0 3.42 0.60 10.400000
## 1827 35.0 165.0 3.22 0.32 9.000000
## 1828 34.0 231.0 3.36 0.54 10.000000
## 1829 35.0 240.0 3.36 0.54 10.000000
## 1830 41.0 167.0 3.12 0.43 11.300000
## 1831 41.0 167.0 3.12 0.43 11.300000
## 1832 34.0 153.0 3.13 0.51 12.000000
## 1833 41.0 167.0 3.12 0.43 11.300000
## 1834 34.0 153.0 3.13 0.51 12.000000
## 1835 43.0 160.0 3.60 0.41 10.600000
## 1837 27.0 104.0 3.04 0.54 9.400000
## 1838 37.0 102.0 3.27 0.64 11.000000
## 1839 53.0 247.0 3.44 0.55 9.300000
## 1840 27.0 104.0 3.04 0.54 9.400000
## 1841 24.0 164.0 3.42 0.51 10.500000
## 1842 37.0 102.0 3.27 0.64 11.000000
## 1843 96.0 249.0 3.07 0.52 9.500000
## 1844 32.0 139.0 3.33 0.77 11.200000
## 1845 21.0 94.0 3.29 0.62 12.300000
## 1846 44.0 157.0 3.27 0.44 9.000000
## 1847 62.0 180.0 3.07 0.38 9.000000
## 1848 44.0 157.0 3.27 0.44 9.000000
## 1850 48.0 189.0 3.25 0.42 11.400000
## 1851 50.0 181.0 3.20 0.42 11.000000
## 1852 21.0 94.0 3.29 0.62 12.300000
## 1853 36.0 127.0 3.60 0.67 10.400000
## 1854 16.0 107.0 3.28 0.59 10.300000
## 1855 44.0 172.0 3.29 0.55 10.500000
## 1856 83.0 197.0 3.14 0.45 9.800000
## 1858 13.0 176.0 3.14 0.47 9.700000
## 1859 14.0 171.0 3.13 0.47 9.700000
## 1860 83.0 197.0 3.14 0.45 9.800000
## 1861 57.0 161.0 3.32 0.66 10.500000
## 1862 78.0 186.0 3.14 0.46 10.000000
## 1863 22.0 104.0 3.24 0.92 11.500000
## 1864 57.0 202.0 3.24 0.39 9.500000
## 1865 25.0 122.0 3.43 0.61 10.500000
## 1867 45.0 199.0 3.34 0.50 9.800000
## 1868 34.0 137.0 3.10 0.37 11.600000
## 1869 41.0 144.0 3.15 0.38 11.800000
## 1870 41.0 140.0 3.04 0.37 10.100000
## 1871 35.0 163.0 3.31 0.50 10.300000
## 1872 38.0 168.0 3.34 0.49 10.400000
## 1873 26.0 166.0 3.09 0.46 8.900000
## 1874 26.0 166.0 3.09 0.46 8.900000
## 1875 37.0 154.0 3.06 0.31 10.800000
## 1876 16.0 165.0 3.38 0.60 9.200000
## 1877 48.0 140.0 3.18 0.49 9.600000
## 1878 21.0 78.0 3.08 0.37 10.400000
## 1879 41.0 248.0 3.03 0.57 8.700000
## 1880 14.0 103.0 3.06 0.36 9.200000
## 1881 45.0 213.0 3.18 0.63 9.200000
## 1882 14.0 103.0 3.06 0.36 9.200000
## 1883 45.0 213.0 3.18 0.63 9.200000
## 1884 45.0 213.0 3.18 0.63 9.200000
## 1885 34.0 124.0 3.40 0.39 10.200000
## 1886 14.0 103.0 3.06 0.36 9.200000
## 1887 39.0 107.0 3.20 0.32 9.000000
## 1888 41.0 178.0 3.37 0.43 9.700000
## 1889 50.0 185.0 3.34 0.42 9.600000
## 1890 24.0 112.0 3.14 0.76 10.000000
## 1891 45.0 213.0 3.18 0.63 9.200000
## 1892 44.0 197.0 3.18 0.64 9.100000
## 1893 40.0 142.0 3.30 0.41 8.700000
## 1894 40.0 142.0 3.30 0.41 8.700000
## 1895 31.0 161.0 3.14 0.44 9.500000
## 1896 73.0 212.0 2.93 0.49 9.500000
## 1897 53.0 166.0 2.90 0.41 8.900000
## 1898 53.0 166.0 2.90 0.41 8.900000
## 1899 15.0 89.0 3.29 0.64 9.900000
## 1900 41.0 104.0 3.29 0.62 12.600000
## 1902 14.0 118.0 2.96 0.34 10.400000
## 1903 26.0 183.0 2.93 0.49 9.100000
## 1904 25.0 106.0 3.01 0.55 10.400000
## 1905 73.0 212.0 2.93 0.49 9.500000
## 1906 53.0 166.0 2.90 0.41 8.900000
## 1907 16.0 120.0 3.16 0.69 10.600000
## 1908 64.0 158.0 3.12 0.59 12.000000
## 1909 26.0 98.0 2.93 0.59 12.500000
## 1910 40.0 126.0 3.21 0.39 9.600000
## 1911 54.0 180.0 3.08 0.42 9.200000
## 1912 20.0 71.0 3.04 0.74 9.900000
## 1913 20.0 112.0 2.96 0.46 11.700000
## 1914 21.0 153.0 3.09 0.50 9.600000
## 1915 27.0 135.0 3.00 0.37 12.000000
## 1916 26.0 98.0 2.93 0.59 12.500000
## 1917 54.0 180.0 3.08 0.42 9.200000
## 1918 20.0 71.0 3.04 0.74 9.900000
## 1919 54.0 177.0 3.17 0.58 8.900000
## 1920 56.0 189.0 3.24 0.66 9.000000
## 1921 52.5 158.0 3.03 0.49 10.200000
## 1922 40.0 126.0 3.21 0.39 9.600000
## 1923 27.0 127.0 3.29 0.41 9.400000
## 1924 10.0 59.0 2.97 0.48 10.400000
## 1925 6.0 106.0 3.15 0.40 10.400000
## 1928 46.0 169.0 3.05 0.41 10.500000
## 1929 47.0 193.0 3.23 0.39 11.400000
## 1930 46.0 172.0 3.08 0.40 10.200000
## 1931 49.0 228.0 3.04 0.41 10.400000
## 1934 27.0 182.0 3.00 0.35 9.200000
## 1935 25.0 87.0 3.23 0.66 10.300000
## 1936 46.0 172.0 3.08 0.40 10.200000
## 1937 49.0 228.0 3.04 0.41 10.400000
## 1938 34.0 172.0 3.23 0.39 11.100000
## 1939 27.0 84.0 3.33 0.34 9.900000
## 1940 35.0 143.0 3.14 0.38 9.000000
## 1941 35.0 256.0 2.93 0.64 8.600000
## 1942 35.0 143.0 3.14 0.38 9.000000
## 1943 35.0 256.0 2.93 0.64 8.600000
## 1944 48.0 195.0 3.18 0.52 9.500000
## 1946 39.0 152.0 2.99 0.58 10.000000
## 1947 57.0 158.0 3.60 0.43 9.000000
## 1949 37.0 135.0 3.34 0.57 10.200000
## 1950 29.0 160.0 3.04 0.44 9.600000
## 1951 49.0 219.0 2.96 0.46 9.700000
## 1953 29.0 142.0 3.01 0.34 13.000000
## 1954 49.0 172.0 3.37 0.74 10.800000
## 1955 49.0 219.0 2.96 0.46 9.700000
## 1956 66.0 169.0 2.89 0.57 9.000000
## 1957 16.0 63.0 3.37 0.40 9.900000
## 1958 22.0 89.0 3.29 0.38 9.200000
## 1960 13.0 91.0 2.79 0.37 10.100000
## 1961 13.0 91.0 2.79 0.37 10.100000
## 1962 21.0 123.0 2.90 0.64 9.500000
## 1963 11.0 99.0 3.17 0.57 9.900000
## 1965 50.0 173.0 3.19 0.46 9.000000
## 1966 50.0 163.0 3.03 0.38 8.600000
## 1967 13.0 114.0 3.12 0.35 10.500000
## 1968 53.0 186.0 3.09 0.56 9.500000
## 1969 41.0 142.0 3.43 0.53 10.100000
## 1970 49.0 164.0 3.53 0.79 11.700000
## 1971 32.0 116.0 3.23 0.47 10.700000
## 1972 49.0 164.0 3.53 0.79 11.700000
## 1973 37.0 133.0 3.15 0.42 9.200000
## 1974 33.0 139.0 3.17 0.39 8.800000
## 1975 33.0 139.0 3.17 0.39 8.800000
## 1976 76.0 197.0 3.24 0.43 9.500000
## 1977 35.0 208.0 3.57 0.55 10.200000
## 1978 30.0 143.0 3.25 0.50 9.100000
## 1979 23.0 103.0 3.19 0.54 10.500000
## 1980 57.0 184.0 3.09 0.46 9.000000
## 1981 53.0 212.5 3.14 0.46 8.900000
## 1982 53.0 212.5 3.14 0.46 8.900000
## 1983 53.0 212.5 3.14 0.46 8.900000
## 1984 53.0 212.5 3.14 0.46 8.900000
## 1985 53.0 212.5 3.14 0.46 8.900000
## 1986 48.0 181.0 3.20 0.62 9.100000
## 1987 27.0 151.0 3.20 0.53 10.100000
## 1988 57.0 176.0 3.12 0.55 10.000000
## 1989 63.0 201.0 3.11 0.53 9.500000
## 1990 30.0 102.0 3.08 0.31 12.300000
## 1991 5.0 110.0 3.24 0.52 9.100000
## 1992 53.0 212.5 3.14 0.46 8.900000
## 1993 17.0 103.0 3.50 0.44 9.600000
## 1994 33.0 180.0 3.13 0.45 11.600000
## 1995 47.0 168.0 3.34 0.67 8.800000
## 1996 51.0 170.0 3.34 0.82 8.900000
## 1997 47.0 168.0 3.34 0.67 8.800000
## 1998 51.0 170.0 3.34 0.82 8.900000
## 1999 51.0 170.0 3.34 0.82 8.900000
## 2000 32.0 197.0 3.13 0.46 9.000000
## 2001 56.0 145.0 3.19 0.46 10.000000
## 2002 58.0 147.0 3.18 0.46 10.000000
## 2003 43.0 154.0 3.36 0.69 11.100000
## 2004 33.0 180.0 3.13 0.45 11.600000
## 2005 58.0 178.0 3.42 0.68 10.600000
## 2006 47.0 168.0 3.34 0.67 8.800000
## 2007 51.0 170.0 3.34 0.82 8.900000
## 2008 16.0 84.0 3.34 0.58 10.100000
## 2009 21.0 159.0 3.52 0.47 10.000000
## 2010 27.0 98.0 3.18 0.41 12.200000
## 2011 20.0 95.0 3.23 0.53 11.000000
## 2012 21.0 159.0 3.52 0.47 10.000000
## 2013 37.0 160.0 3.37 0.45 11.100000
## 2014 38.0 133.0 3.22 0.67 10.400000
## 2015 14.0 71.0 2.94 0.36 11.800000
## 2016 22.0 84.0 3.11 0.66 10.800000
## 2017 28.0 110.0 3.30 0.38 12.500000
## 2018 14.0 71.0 2.94 0.36 11.800000
## 2019 12.0 136.0 3.25 0.46 11.600000
## 2020 38.0 133.0 3.22 0.67 10.400000
## 2021 36.0 163.0 3.19 0.70 11.500000
## 2022 46.0 142.0 3.23 0.42 10.100000
## 2023 45.0 215.0 3.11 0.53 9.200000
## 2024 46.0 142.0 3.23 0.42 10.100000
## 2028 51.0 180.0 3.13 0.45 8.900000
## 2029 33.0 150.0 3.10 0.45 9.700000
## 2030 45.0 215.0 3.11 0.53 9.200000
## 2031 22.0 145.0 3.06 0.52 11.000000
## 2032 32.0 160.0 3.14 0.47 10.700000
## 2033 29.0 101.0 3.24 0.54 10.800000
## 2034 50.0 183.0 3.41 0.40 9.800000
## 2035 11.0 124.0 3.25 0.48 11.000000
## 2036 18.0 72.0 2.97 0.35 10.400000
## 2038 32.0 160.0 3.14 0.47 10.700000
## 2039 22.0 104.0 3.34 0.44 9.000000
## 2040 11.0 71.0 3.08 0.38 10.600000
## 2041 56.0 212.0 3.22 0.59 9.500000
## 2042 22.0 104.0 3.34 0.44 9.000000
## 2043 22.0 104.0 3.34 0.45 9.200000
## 2044 30.0 107.0 2.97 0.53 11.000000
## 2045 22.0 115.0 3.28 0.63 9.900000
## 2046 11.0 71.0 3.08 0.38 10.600000
## 2047 22.0 126.0 3.38 0.47 9.300000
## 2048 28.0 156.0 3.14 0.41 9.600000
## 2049 29.0 155.0 3.14 0.42 9.500000
## 2050 32.0 172.0 3.39 0.57 9.700000
## 2052 41.0 146.0 3.30 0.36 8.700000
## 2053 41.0 146.0 3.30 0.36 8.700000
## 2054 19.0 101.0 3.01 0.38 12.400000
## 2055 19.0 101.0 3.01 0.38 12.400000
## 2056 27.0 155.0 3.07 0.26 10.600000
## 2057 41.0 146.0 3.30 0.36 8.700000
## 2058 20.0 151.0 3.36 0.82 12.000000
## 2059 45.0 227.0 3.12 0.47 9.000000
## 2060 31.0 169.0 3.13 0.47 8.800000
## 2061 58.0 223.0 3.22 0.56 9.500000
## 2062 23.0 96.0 3.32 0.40 10.800000
## 2063 34.0 132.0 3.16 0.48 11.400000
## 2064 38.0 123.0 3.60 0.46 10.300000
## 2065 51.0 180.0 3.30 0.75 9.500000
## 2066 21.0 127.0 3.15 0.44 9.900000
## 2067 25.0 142.0 3.16 0.39 10.200000
## 2068 26.0 146.0 3.16 0.39 10.200000
## 2069 26.0 104.0 3.44 0.37 11.000000
## 2070 25.0 126.0 3.22 0.34 12.100000
## 2071 25.0 173.0 3.26 0.51 9.100000
## 2072 31.0 140.0 3.26 0.68 9.500000
## 2073 43.0 164.0 3.27 0.76 9.500000
## 2074 57.0 189.0 3.31 0.79 9.800000
## 2075 51.0 180.0 3.30 0.75 9.500000
## 2076 38.0 123.0 3.60 0.46 10.300000
## 2077 10.0 124.0 3.30 0.67 9.600000
## 2078 39.0 198.0 3.52 0.54 10.200000
## 2079 25.0 119.0 3.68 0.72 10.500000
## 2080 17.0 117.0 3.32 0.41 10.400000
## 2081 10.0 124.0 3.30 0.67 9.600000
## 2082 18.0 95.0 3.22 0.33 10.700000
## 2083 25.0 119.0 3.15 0.34 10.500000
## 2084 14.0 111.0 2.85 0.42 10.600000
## 2085 47.0 150.0 3.29 0.76 9.600000
## 2086 47.0 150.0 3.29 0.76 9.600000
## 2087 17.0 101.0 3.14 0.58 9.500000
## 2088 48.0 153.0 3.12 0.58 9.400000
## 2089 29.0 130.0 3.22 0.38 9.800000
## 2090 47.0 150.0 3.29 0.76 9.600000
## 2091 51.0 172.0 3.16 0.44 9.200000
## 2092 53.0 176.0 3.17 0.38 9.500000
## 2093 27.0 93.0 3.34 0.38 9.200000
## 2094 22.0 136.0 2.94 0.35 9.400000
## 2095 22.0 136.0 2.94 0.35 9.400000
## 2096 33.0 146.0 3.40 0.46 9.300000
## 2097 5.0 129.0 3.19 0.40 9.100000
## 2098 31.0 145.0 3.36 0.40 9.500000
## 2099 72.0 163.0 3.42 0.35 9.100000
## 2100 43.0 153.0 3.63 0.46 10.600000
## 2101 31.0 145.0 3.36 0.40 9.500000
## 2102 16.0 85.0 3.19 0.56 12.400000
## 2103 28.0 237.0 3.18 0.49 8.700000
## 2104 35.0 128.0 3.12 0.45 8.800000
## 2105 43.0 153.0 3.63 0.46 10.600000
## 2106 5.0 129.0 3.19 0.40 9.100000
## 2107 40.0 234.0 3.02 0.66 9.000000
## 2108 46.0 141.0 3.16 0.48 10.300000
## 2109 72.0 163.0 3.42 0.35 9.100000
## 2110 59.0 186.0 3.12 0.55 9.500000
## 2111 44.0 138.0 3.30 0.37 8.800000
## 2112 44.0 138.0 3.30 0.37 8.800000
## 2113 44.0 138.0 3.30 0.37 8.800000
## 2114 20.0 93.0 3.38 0.62 9.900000
## 2115 59.0 186.0 3.12 0.55 9.500000
## 2116 44.0 138.0 3.30 0.37 8.800000
## 2117 19.0 68.0 3.14 0.37 11.700000
## 2118 26.0 117.0 3.21 0.56 10.800000
## 2119 18.0 126.0 3.43 0.42 12.000000
## 2120 14.0 122.0 3.20 0.39 10.300000
## 2121 47.0 154.0 3.05 0.38 9.000000
## 2122 36.0 109.0 3.19 0.58 12.200000
## 2123 59.0 173.0 3.39 0.38 9.900000
## 2124 47.0 154.0 3.05 0.38 9.000000
## 2125 36.0 109.0 3.19 0.58 12.200000
## 2126 42.0 163.0 3.20 0.46 10.100000
## 2127 23.0 174.0 3.31 0.55 9.300000
## 2129 36.0 146.0 3.43 0.50 9.200000
## 2130 15.0 115.0 3.27 0.72 11.700000
## 2131 21.0 144.0 3.35 0.38 11.000000
## 2132 49.0 158.0 3.37 0.38 9.600000
## 2133 49.0 158.0 3.37 0.38 9.600000
## 2134 22.0 162.0 2.99 0.68 11.900000
## 2135 38.0 118.0 3.25 0.52 10.800000
## 2136 41.0 224.0 3.38 0.55 10.100000
## 2137 31.0 132.0 3.25 0.52 10.900000
## 2138 41.0 224.0 3.38 0.55 10.100000
## 2139 19.0 102.0 3.27 0.31 10.400000
## 2140 12.0 105.0 3.05 0.39 9.200000
## 2141 31.0 117.0 3.27 0.50 9.600000
## 2142 31.0 117.0 3.27 0.50 9.600000
## 2143 64.0 179.0 3.10 0.46 9.000000
## 2144 18.0 89.0 3.40 0.74 11.500000
## 2145 53.0 145.0 3.17 0.48 10.200000
## 2146 49.0 165.0 3.40 0.42 9.900000
## 2147 26.0 105.0 3.44 0.40 9.600000
## 2148 20.0 142.0 3.10 0.54 10.600000
## 2149 12.0 105.0 3.05 0.39 9.200000
## 2150 31.0 99.0 3.24 0.46 11.800000
## 2151 36.0 102.0 3.18 0.43 12.200000
## 2152 31.0 117.0 3.27 0.50 9.600000
## 2153 15.0 76.0 3.20 0.41 10.600000
## 2154 23.0 91.0 3.27 0.45 10.300000
## 2156 33.0 181.0 3.11 0.46 10.700000
## 2157 9.0 76.0 3.05 0.31 11.700000
## 2158 31.0 92.0 3.01 0.33 12.000000
## 2159 26.0 105.0 3.52 0.66 10.600000
## 2160 6.0 61.0 3.30 0.34 12.200000
## 2161 29.0 124.0 3.47 0.48 11.000000
## 2162 29.0 79.0 3.23 0.46 12.400000
## 2163 19.0 115.0 2.77 0.44 9.400000
## 2164 31.0 92.0 3.01 0.33 12.000000
## 2166 15.0 162.0 3.18 0.47 9.400000
## 2167 15.0 162.0 3.18 0.47 9.400000
## 2168 48.5 229.0 3.14 0.49 9.100000
## 2169 48.5 229.0 3.14 0.49 9.100000
## 2170 48.5 229.0 3.14 0.49 9.100000
## 2171 48.5 229.0 3.14 0.49 9.100000
## 2172 48.5 229.0 3.14 0.49 9.100000
## 2173 11.0 117.0 3.23 0.37 9.200000
## 2174 43.0 163.0 3.15 0.54 9.200000
## 2175 48.5 229.0 3.14 0.49 9.100000
## 2176 48.5 212.0 3.14 0.49 9.100000
## 2177 11.0 117.0 3.23 0.37 9.200000
## 2178 23.0 126.0 3.25 0.44 9.000000
## 2179 43.0 163.0 3.15 0.54 9.200000
## 2180 33.0 106.0 3.22 0.55 10.800000
## 2181 29.0 146.0 3.40 0.46 9.500000
## 2182 30.0 114.0 3.11 0.40 11.000000
## 2183 37.0 146.0 3.24 0.47 10.000000
## 2184 38.0 141.0 3.22 0.47 9.500000
## 2185 29.0 109.0 3.29 0.47 10.100000
## 2186 24.0 94.0 3.19 0.44 9.500000
## 2188 13.0 137.0 3.11 0.42 9.500000
## 2189 24.0 90.0 3.35 0.49 9.400000
## 2190 36.0 125.0 2.92 0.54 9.400000
## 2191 29.0 110.0 3.31 0.51 12.700000
## 2192 34.0 145.0 3.09 0.32 9.700000
## 2193 31.0 153.0 3.27 0.51 9.700000
## 2194 36.0 125.0 2.92 0.54 9.400000
## 2195 24.0 90.0 3.35 0.49 9.400000
## 2196 13.0 137.0 3.11 0.42 9.500000
## 2197 20.0 71.0 3.10 0.38 11.700000
## 2198 26.0 101.0 3.09 0.37 11.700000
## 2199 53.0 187.0 3.16 0.52 9.700000
## 2200 77.0 231.0 3.24 0.52 9.500000
## 2201 31.0 157.0 3.25 0.53 9.100000
## 2202 23.0 147.0 3.23 0.67 10.300000
## 2203 53.0 187.0 3.16 0.52 9.700000
## 2204 14.0 167.0 3.21 0.55 9.900000
## 2205 19.0 175.0 3.22 0.56 9.900000
## 2206 35.0 178.0 3.26 0.60 10.200000
## 2208 36.0 138.0 3.15 0.64 11.300000
## 2209 13.0 128.0 3.19 0.49 11.400000
## 2210 24.0 125.0 3.17 0.64 12.200000
## 2211 53.0 150.0 3.18 0.50 9.900000
## 2212 35.0 136.0 3.63 0.78 10.300000
## 2213 24.0 125.0 3.17 0.64 12.200000
## 2214 23.0 107.0 3.52 0.65 10.400000
## 2215 13.0 128.0 3.19 0.49 11.400000
## 2216 32.0 161.0 3.13 0.40 9.900000
## 2217 16.0 96.0 3.32 0.62 10.000000
## 2218 18.0 129.0 3.21 0.38 11.500000
## 2219 29.0 163.0 3.44 0.60 10.500000
## 2220 36.0 134.0 3.28 0.36 12.500000
## 2221 40.0 120.0 2.98 0.44 10.500000
## 2222 32.0 161.0 3.13 0.40 9.900000
## 2223 25.0 157.0 3.06 0.47 11.400000
## 2224 44.0 169.0 3.42 0.42 9.800000
## 2225 25.0 157.0 3.06 0.47 11.400000
## 2226 32.0 166.0 3.03 0.44 9.200000
## 2227 60.0 177.0 3.08 0.46 8.900000
## 2228 64.0 179.0 3.07 0.46 8.900000
## 2229 45.0 124.0 2.92 0.59 9.500000
## 2230 42.0 150.0 3.21 0.36 11.500000
## 2231 45.0 124.0 2.92 0.59 9.500000
## 2232 42.0 150.0 3.21 0.36 11.500000
## 2233 16.0 89.0 2.96 0.45 9.500000
## 2234 10.0 164.0 3.35 0.51 9.700000
## 2235 20.0 90.0 3.17 0.79 9.700000
## 2236 10.0 147.0 3.32 0.46 9.500000
## 2237 48.0 184.0 3.16 0.50 9.400000
## 2238 37.0 162.0 3.13 0.45 9.000000
## 2239 39.0 151.0 3.60 0.44 10.600000
## 2240 10.0 147.0 3.32 0.46 9.500000
## 2241 41.0 180.0 3.16 0.49 9.100000
## 2242 48.0 184.0 3.16 0.50 9.400000
## 2243 49.0 169.0 3.05 0.54 8.800000
## 2244 52.0 171.0 3.54 0.74 10.400000
## 2245 35.0 228.0 3.13 0.51 8.900000
## 2246 28.0 141.0 3.16 0.38 10.600000
## 2247 37.0 162.0 3.13 0.45 9.000000
## 2248 39.0 151.0 3.60 0.44 10.600000
## 2249 16.0 100.0 3.28 0.45 10.600000
## 2250 45.0 186.0 3.23 0.47 9.000000
## 2251 46.0 235.0 3.08 0.61 8.800000
## 2252 34.0 101.0 3.54 0.60 10.500000
## 2253 51.0 174.0 3.16 0.52 9.500000
## 2254 45.0 186.0 3.23 0.47 9.000000
## 2255 47.0 172.0 3.14 0.43 10.400000
## 2256 35.0 133.0 3.38 0.46 10.000000
## 2257 24.0 128.0 2.97 0.68 10.400000
## 2258 34.0 132.0 3.11 0.53 9.000000
## 2259 57.0 205.0 3.24 0.45 9.300000
## 2260 34.0 132.0 3.11 0.53 9.000000
## 2261 57.0 205.0 3.24 0.45 9.300000
## 2262 20.0 134.0 3.18 0.45 9.000000
## 2263 11.0 61.0 3.06 0.44 11.500000
## 2264 49.0 159.0 3.11 0.48 9.000000
## 2265 53.0 154.0 3.52 0.77 10.400000
## 2266 49.0 159.0 3.11 0.48 9.000000
## 2267 20.0 167.0 3.08 0.43 10.600000
## 2268 53.0 154.0 3.52 0.77 10.400000
## 2269 35.0 152.0 3.47 0.40 8.500000
## 2270 47.0 169.0 3.07 0.67 9.300000
## 2271 41.0 107.0 3.53 0.66 10.500000
## 2272 50.0 156.0 3.39 0.46 9.900000
## 2273 28.0 108.0 3.40 0.42 10.400000
## 2274 10.0 94.0 3.35 0.47 10.100000
## 2275 41.0 107.0 3.53 0.66 10.500000
## 2276 47.0 178.0 3.04 0.49 9.200000
## 2277 57.0 200.0 3.17 0.44 9.400000
## 2278 25.0 91.0 3.53 0.39 10.600000
## 2279 57.0 200.0 3.17 0.44 9.400000
## 2280 45.0 149.0 3.08 0.56 8.700000
## 2281 20.0 77.0 3.61 0.54 10.200000
## 2282 18.0 66.0 3.61 0.55 10.300000
## 2283 67.0 210.0 3.06 0.68 9.500000
## 2284 67.0 210.0 3.06 0.68 9.500000
## 2285 67.0 210.0 3.06 0.68 9.500000
## 2286 67.0 210.0 3.06 0.68 9.500000
## 2287 47.0 144.0 3.17 0.49 9.400000
## 2288 49.0 145.0 3.17 0.49 9.400000
## 2289 67.0 210.0 3.06 0.68 9.500000
## 2290 26.0 97.0 3.16 0.58 12.600000
## 2291 21.0 106.0 3.52 0.64 10.500000
## 2292 38.0 150.0 3.10 0.56 10.800000
## 2293 39.0 208.0 3.18 0.46 9.900000
## 2294 26.0 97.0 3.16 0.58 12.600000
## 2295 38.0 115.0 3.38 0.58 12.200000
## 2296 62.0 150.0 3.23 0.37 10.000000
## 2297 47.0 168.0 3.29 0.57 10.600000
## 2298 66.0 202.0 3.24 0.53 9.500000
## 2299 23.0 109.0 3.34 0.54 12.800000
## 2300 38.0 115.0 3.38 0.58 12.200000
## 2301 28.0 125.0 3.34 0.44 12.600000
## 2302 25.0 125.0 3.45 0.45 9.400000
## 2303 50.0 194.0 3.21 0.43 9.000000
## 2304 26.0 126.0 3.23 0.48 9.100000
## 2305 15.0 168.0 3.06 0.40 9.400000
## 2306 40.0 143.0 3.33 0.42 12.200000
## 2307 18.0 134.0 3.21 0.68 10.000000
## 2308 34.0 159.0 2.93 0.44 9.200000
## 2309 36.0 139.0 3.11 0.49 9.300000
## 2310 11.0 126.0 3.14 0.50 9.800000
## 2311 34.0 159.0 2.93 0.44 9.200000
## 2312 44.0 132.0 3.34 0.41 12.000000
## 2313 36.0 139.0 3.11 0.49 9.300000
## 2314 15.0 80.0 3.33 0.63 12.600000
## 2315 42.0 127.0 3.31 0.38 12.200000
## 2316 49.0 144.0 3.40 0.58 11.000000
## 2317 34.0 116.0 3.25 0.39 12.000000
## 2318 51.0 153.0 3.16 0.44 8.800000
## 2319 58.0 164.0 3.17 0.46 8.900000
## 2320 39.0 84.0 3.59 0.48 12.700000
## 2321 42.0 130.0 3.10 0.67 11.800000
## 2323 23.0 121.0 3.24 0.61 9.900000
## 2324 42.0 148.0 3.35 0.66 11.100000
## 2325 54.0 190.0 3.22 0.48 9.400000
## 2326 7.0 119.0 3.13 0.36 9.700000
## 2327 22.0 111.0 3.11 0.29 9.700000
## 2328 7.0 119.0 3.13 0.36 9.700000
## 2329 22.0 111.0 3.11 0.29 9.700000
## 2330 29.0 175.0 3.19 0.53 9.800000
## 2331 25.0 209.0 3.25 0.59 9.300000
## 2332 31.0 161.0 2.95 0.42 10.500000
## 2333 38.0 209.0 3.47 0.59 9.300000
## 2336 50.0 118.0 3.18 0.51 10.300000
## 2338 61.0 180.0 3.15 0.57 9.000000
## 2339 40.0 167.0 3.48 0.62 9.700000
## 2340 21.0 90.0 3.22 0.55 9.500000
## 2341 27.0 156.0 3.49 0.59 10.300000
## 2342 40.0 167.0 3.48 0.62 9.700000
## 2343 27.0 95.0 3.21 0.59 12.300000
## 2344 39.0 149.0 3.40 0.52 10.500000
## 2345 21.0 90.0 3.22 0.55 9.500000
## 2346 41.0 211.0 3.11 0.49 10.000000
## 2347 58.0 179.0 3.08 0.44 8.800000
## 2348 24.0 98.0 3.00 0.54 10.900000
## 2349 14.0 141.0 2.95 0.77 12.200000
## 2351 46.0 212.0 3.47 0.59 10.000000
## 2352 53.0 202.0 3.11 0.57 9.600000
## 2353 36.0 126.0 3.13 0.46 8.700000
## 2354 46.0 89.0 3.39 0.48 10.700000
## 2355 26.0 66.0 3.43 0.48 11.100000
## 2356 14.0 130.0 3.25 0.45 12.500000
## 2357 29.0 130.0 3.30 0.50 10.400000
## 2358 20.0 93.0 3.20 0.37 11.500000
## 2359 60.0 221.0 3.05 0.66 9.400000
## 2361 30.0 121.0 3.17 0.49 10.100000
## 2362 14.0 102.0 3.28 0.58 9.700000
## 2363 39.0 144.0 3.49 0.50 10.500000
## 2364 44.0 182.0 3.42 0.42 9.700000
## 2365 42.5 204.0 3.59 0.51 9.200000
## 2366 24.0 138.0 3.19 0.44 9.800000
## 2367 40.0 227.0 3.12 0.52 9.000000
## 2368 40.0 188.0 3.15 0.49 9.100000
## 2369 70.0 169.0 3.25 0.37 10.400000
## 2370 29.0 144.0 3.68 0.46 10.700000
## 2371 25.0 107.0 3.59 0.49 10.500000
## 2373 5.0 85.0 3.28 0.40 11.500000
## 2374 5.0 57.0 3.05 0.54 10.400000
## 2375 43.0 188.0 3.30 0.41 12.000000
## 2376 41.0 150.0 3.38 0.43 12.200000
## 2377 43.0 188.0 3.30 0.41 12.000000
## 2378 24.0 90.0 3.29 0.46 9.800000
## 2380 21.0 191.0 3.49 0.63 9.600000
## 2381 21.0 196.0 3.49 0.64 9.500000
## 2382 37.0 144.0 3.50 0.59 10.200000
## 2383 14.0 107.0 3.24 0.46 10.400000
## 2384 26.0 74.0 3.28 0.53 11.000000
## 2385 14.0 107.0 3.24 0.46 10.400000
## 2386 56.0 160.0 3.05 0.41 8.700000
## 2387 24.0 189.0 3.29 0.54 9.900000
## 2388 24.0 186.0 3.29 0.54 9.900000
## 2389 7.0 106.0 3.06 0.45 11.300000
## 2390 28.0 83.0 3.38 0.51 12.000000
## 2391 34.0 130.0 3.43 0.50 10.700000
## 2392 32.0 156.0 3.13 0.70 10.100000
## 2393 42.0 135.0 3.25 0.49 9.600000
## 2394 43.0 136.0 3.25 0.49 9.600000
## 2396 28.0 199.0 3.54 0.59 10.300000
## 2398 13.0 101.0 3.17 0.41 11.800000
## 2399 26.0 93.0 3.15 0.49 11.900000
## 2400 17.0 77.0 3.66 0.57 10.300000
## 2401 16.0 104.0 3.09 0.66 10.000000
## 2402 18.0 107.0 3.10 0.53 10.200000
## 2403 72.0 202.0 3.12 0.56 10.000000
## 2405 23.0 130.0 3.04 0.67 9.600000
## 2406 59.0 188.0 3.16 0.49 9.500000
## 2407 23.0 100.0 3.17 0.52 12.700000
## 2408 23.0 109.0 3.34 0.54 11.000000
## 2410 23.0 111.0 3.35 0.64 10.200000
## 2411 30.0 220.0 3.38 0.58 10.100000
## 2412 50.0 208.0 3.05 0.50 9.200000
## 2413 50.0 212.0 3.47 0.66 9.400000
## 2414 23.0 111.0 3.35 0.64 10.200000
## 2415 28.0 195.0 3.53 0.71 9.200000
## 2416 23.0 106.0 2.98 0.50 10.000000
## 2417 30.0 220.0 3.38 0.58 10.100000
## 2419 25.0 98.0 3.16 0.42 9.500000
## 2420 67.0 207.0 3.39 0.53 9.100000
## 2421 23.0 118.0 3.05 0.46 13.300000
## 2422 53.0 198.0 3.26 0.55 9.500000
## 2423 28.0 210.0 3.56 0.72 9.200000
## 2424 17.0 117.0 3.36 0.68 10.100000
## 2425 28.0 210.0 3.56 0.72 9.200000
## 2426 17.0 117.0 3.36 0.68 10.100000
## 2427 32.0 172.0 3.27 0.48 11.200000
## 2428 70.0 230.0 3.14 0.55 9.800000
## 2429 32.0 172.0 3.27 0.48 11.200000
## 2430 70.0 230.0 3.14 0.55 9.800000
## 2431 61.0 195.0 3.22 0.46 9.400000
## 2432 50.0 177.0 3.23 0.42 9.000000
## 2433 60.0 198.0 3.21 0.47 9.400000
## 2434 63.0 229.0 3.11 0.50 8.900000
## 2435 48.0 253.0 3.02 0.56 9.100000
## 2436 9.0 148.0 3.17 0.50 9.800000
## 2437 29.0 183.0 3.17 0.43 9.400000
## 2438 34.0 150.0 3.13 0.50 10.000000
## 2439 29.0 183.0 3.17 0.43 9.400000
## 2440 36.0 130.0 3.48 0.75 9.900000
## 2441 49.0 159.0 3.14 0.47 10.000000
## 2443 32.0 201.0 3.00 0.45 9.200000
## 2444 40.0 219.5 3.15 0.60 10.000000
## 2445 32.0 201.0 3.00 0.45 9.200000
## 2446 40.5 210.0 3.15 0.61 10.000000
## 2447 40.0 210.0 3.15 0.60 10.000000
## 2448 21.0 133.0 3.43 0.64 9.800000
## 2449 19.0 114.0 3.36 0.62 10.500000
## 2450 61.0 181.0 3.45 0.63 10.600000
## 2451 38.0 157.0 3.28 0.52 9.400000
## 2452 38.0 157.0 3.28 0.52 9.400000
## 2453 35.0 136.0 3.38 0.54 11.000000
## 2454 36.0 141.0 3.53 0.56 10.800000
## 2455 58.0 201.0 3.30 0.67 9.000000
## 2456 47.0 194.0 3.07 0.58 9.600000
## 2457 36.0 156.0 3.19 0.54 10.600000
## 2458 36.0 156.0 3.19 0.54 10.600000
## 2459 47.0 194.0 3.07 0.58 9.600000
## 2460 31.0 147.0 3.08 0.52 9.200000
## 2461 31.0 147.0 3.08 0.52 9.200000
## 2462 11.0 71.0 2.89 0.49 9.500000
## 2463 12.0 72.0 2.89 0.48 9.500000
## 2464 37.0 184.0 3.47 0.58 10.300000
## 2465 35.0 124.0 3.08 0.46 8.800000
## 2468 27.0 128.0 3.20 0.62 10.200000
## 2469 26.0 77.0 3.25 0.51 10.100000
## 2470 29.0 118.0 3.21 0.41 9.500000
## 2471 34.0 176.0 3.10 0.51 9.500000
## 2472 23.0 174.0 3.54 0.50 11.600000
## 2473 12.0 97.0 3.13 0.40 10.700000
## 2474 20.0 142.0 3.11 0.54 10.100000
## 2475 17.0 83.0 3.32 0.44 11.100000
## 2476 19.0 117.0 3.22 0.53 9.800000
## 2477 52.0 148.0 3.08 0.49 9.000000
## 2478 17.0 83.0 3.32 0.44 11.100000
## 2479 58.0 215.0 3.19 0.48 9.500000
## 2480 18.0 143.0 3.37 0.49 9.400000
## 2481 22.0 113.0 3.24 0.61 10.200000
## 2482 39.5 216.5 3.10 0.50 9.800000
## 2483 54.0 201.0 3.19 0.48 9.500000
## 2484 58.0 215.0 3.19 0.48 9.500000
## 2485 55.0 191.0 3.17 0.49 9.000000
## 2486 61.0 204.0 3.10 0.55 10.100000
## 2487 37.0 122.0 3.02 0.45 8.800000
## 2488 25.0 122.0 2.97 0.51 11.900000
## 2489 25.0 122.0 2.97 0.51 11.900000
## 2490 32.0 174.0 3.19 0.44 9.300000
## 2491 11.0 110.0 3.33 0.76 10.000000
## 2492 49.0 201.0 3.21 0.43 9.500000
## 2493 32.0 174.0 3.19 0.44 9.300000
## 2494 20.0 139.0 3.16 0.50 9.700000
## 2495 20.0 139.0 3.16 0.50 9.700000
## 2496 45.0 155.0 3.19 0.48 10.200000
## 2497 13.0 96.0 3.11 0.40 10.800000
## 2498 32.0 133.0 3.27 0.48 8.800000
## 2499 32.0 133.0 3.27 0.48 8.800000
## 2500 37.0 175.0 3.32 0.49 11.400000
## 2501 32.0 133.0 3.27 0.48 8.800000
## 2502 39.0 191.0 3.14 0.52 9.800000
## 2503 11.0 119.0 3.17 0.47 9.400000
## 2504 11.0 119.0 3.17 0.47 9.400000
## 2505 54.0 174.0 3.21 0.43 9.400000
## 2506 37.0 194.0 3.20 0.63 9.400000
## 2507 63.0 212.0 3.22 0.48 9.700000
## 2508 36.0 140.0 3.35 0.47 12.300000
## 2509 45.0 178.0 3.33 0.43 9.800000
## 2510 18.0 134.0 3.12 0.68 9.000000
## 2511 46.0 203.0 3.26 0.46 9.200000
## 2512 68.0 215.0 3.19 0.60 9.400000
## 2513 20.0 67.0 3.28 0.48 9.900000
## 2514 13.0 145.0 3.07 0.52 9.800000
## 2515 34.0 148.0 3.36 0.49 12.300000
## 2516 15.0 37.0 3.02 0.52 11.900000
## 2517 33.0 170.0 3.27 0.64 10.200000
## 2518 61.0 224.0 3.14 0.56 9.500000
## 2519 15.0 37.0 3.02 0.52 11.900000
## 2520 67.0 216.0 3.24 0.50 9.200000
## 2521 28.0 174.0 3.18 0.49 9.700000
## 2522 35.0 138.0 3.36 0.60 11.500000
## 2523 32.0 162.0 3.17 0.38 10.400000
## 2524 41.0 174.0 3.22 0.41 11.600000
## 2525 28.0 174.0 3.18 0.49 9.700000
## 2526 32.0 162.0 3.17 0.38 10.400000
## 2527 35.0 138.0 3.36 0.60 11.500000
## 2528 29.0 108.0 3.27 0.51 10.200000
## 2529 27.0 109.0 3.38 0.50 9.800000
## 2530 26.0 158.0 3.24 0.47 9.000000
## 2531 57.0 163.0 3.38 0.59 10.500000
## 2532 8.0 178.0 3.16 0.38 9.400000
## 2533 8.0 178.0 3.16 0.38 9.400000
## 2534 53.0 149.0 3.21 0.34 10.800000
## 2535 19.0 95.0 3.17 0.46 10.700000
## 2536 21.0 162.0 3.08 0.50 10.600000
## 2537 15.0 110.0 3.15 0.42 9.200000
## 2538 30.0 142.0 3.28 0.44 9.500000
## 2539 30.0 142.0 3.28 0.44 9.500000
## 2540 20.0 111.0 3.41 0.50 10.000000
## 2541 34.0 177.0 3.13 0.47 10.600000
## 2542 21.0 162.0 3.08 0.50 10.600000
## 2543 19.5 166.0 3.13 0.48 10.600000
## 2544 15.0 110.0 3.15 0.42 9.200000
## 2545 28.0 117.0 3.24 0.48 11.000000
## 2546 17.0 159.0 3.25 0.53 11.200000
## 2547 26.0 175.0 3.32 0.54 9.600000
## 2548 27.0 128.0 3.21 0.48 9.400000
## 2549 62.0 209.0 3.20 0.53 9.500000
## 2550 51.0 188.0 3.09 0.62 9.300000
## 2551 27.0 128.0 3.21 0.48 9.400000
## 2552 62.0 209.0 3.20 0.53 9.500000
## 2553 8.0 110.0 3.07 0.46 9.400000
## 2554 63.0 146.0 3.13 0.72 11.200000
## 2555 67.0 150.0 3.14 0.73 11.200000
## 2556 63.0 146.0 3.13 0.72 11.200000
## 2557 54.0 170.0 3.00 0.53 8.800000
## 2558 67.0 150.0 3.14 0.73 11.200000
## 2559 63.0 146.0 3.13 0.72 11.200000
## 2561 11.0 103.0 3.06 0.42 11.100000
## 2562 36.0 131.0 3.08 0.46 9.600000
## 2563 11.0 103.0 3.06 0.42 11.100000
## 2565 28.0 160.0 2.95 0.45 10.600000
## 2566 59.0 240.0 3.13 0.45 8.900000
## 2567 17.0 80.0 3.15 0.46 12.300000
## 2568 39.0 132.0 3.34 0.46 11.400000
## 2569 60.0 207.0 3.16 0.49 9.600000
## 2570 25.0 135.0 3.33 0.59 10.300000
## 2571 39.0 132.0 3.34 0.46 11.400000
## 2572 29.0 80.0 3.23 0.36 12.100000
## 2573 10.0 56.0 3.46 0.45 9.900000
## 2574 31.0 185.0 3.15 0.49 9.700000
## 2575 70.0 154.0 3.18 0.52 10.500000
## 2576 85.0 182.0 3.04 0.44 8.900000
## 2577 74.0 227.0 3.18 0.50 9.400000
## 2578 63.0 206.0 3.18 0.50 9.600000
## 2579 45.0 104.0 3.40 0.56 12.600000
## 2581 36.0 174.0 3.20 0.50 10.400000
## 2582 19.0 171.0 3.00 0.52 9.000000
## 2583 19.0 171.0 3.00 0.52 9.000000
## 2584 19.0 171.0 3.00 0.52 9.000000
## 2585 19.0 171.0 3.00 0.52 9.000000
## 2586 19.0 171.0 3.00 0.52 9.000000
## 2587 19.0 171.0 3.00 0.52 9.000000
## 2588 15.0 89.0 3.22 0.43 9.200000
## 2589 19.0 171.0 3.00 0.52 9.000000
## 2590 25.0 154.0 3.20 0.48 9.700000
## 2591 47.0 132.0 3.34 0.42 10.100000
## 2592 24.0 152.0 3.46 0.64 11.000000
## 2593 32.0 144.0 3.20 0.55 10.800000
## 2594 49.0 147.0 3.22 0.38 10.800000
## 2596 18.0 167.0 3.24 0.39 10.600000
## 2597 28.0 208.0 3.23 0.64 9.800000
## 2598 56.0 115.0 3.18 0.70 11.700000
## 2599 28.0 208.0 3.23 0.64 9.800000
## 2600 58.0 185.0 3.34 0.60 9.000000
## 2601 51.0 132.0 3.18 0.74 11.300000
## 2602 64.0 185.0 3.31 0.61 9.400000
## 2603 56.0 115.0 3.18 0.70 11.700000
## 2604 37.0 107.0 3.31 0.63 11.300000
## 2605 37.0 107.0 3.31 0.63 11.300000
## 2606 4.0 28.0 3.20 0.36 12.000000
## 2607 22.0 157.0 3.48 0.49 10.600000
## 2608 47.0 202.0 3.13 0.46 10.800000
## 2609 53.0 209.0 3.12 0.46 10.800000
## 2610 4.0 28.0 3.20 0.36 12.000000
## 2611 44.0 177.0 3.18 0.67 9.400000
## 2612 61.0 219.0 3.19 0.50 9.400000
## 2613 37.0 107.0 3.31 0.63 11.300000
## 2614 29.0 140.0 3.07 0.40 9.400000
## 2615 20.0 80.0 3.39 0.47 12.000000
## 2616 47.0 129.0 3.28 0.72 10.300000
## 2617 47.0 129.0 3.28 0.72 10.300000
## 2618 47.0 129.0 3.28 0.72 10.300000
## 2619 48.0 126.0 3.22 0.38 11.300000
## 2620 31.0 150.0 3.10 0.47 9.400000
## 2621 40.0 144.0 3.14 0.38 8.700000
## 2622 29.0 140.0 3.07 0.40 9.400000
## 2623 48.0 126.0 3.22 0.38 11.300000
## 2624 47.0 129.0 3.28 0.72 10.300000
## 2625 20.0 80.0 3.39 0.47 12.000000
## 2627 36.0 136.0 3.44 0.51 10.400000
## 2628 39.0 128.0 3.37 0.41 10.700000
## 2629 42.0 219.0 3.47 0.46 10.200000
## 2631 23.0 109.0 3.30 0.36 10.500000
## 2632 36.0 100.0 3.26 0.39 11.700000
## 2633 61.0 186.0 3.13 0.45 8.600000
## 2634 40.0 174.0 3.20 0.44 9.000000
## 2636 26.0 87.0 3.10 0.47 12.800000
## 2637 40.0 174.0 3.20 0.44 9.000000
## 2639 42.0 104.0 3.28 0.53 11.800000
## 2640 36.0 84.0 3.05 0.55 11.600000
## 2641 28.0 89.0 3.14 0.61 11.800000
## 2642 55.0 158.0 3.24 0.37 10.600000
## 2643 14.0 91.0 3.17 0.80 9.700000
## 2644 24.0 151.0 3.22 0.47 10.300000
## 2645 56.0 178.0 3.15 0.44 10.200000
## 2646 38.0 113.0 3.33 0.44 10.100000
## 2648 43.0 127.0 3.24 0.51 9.300000
## 2649 29.0 144.0 3.33 0.54 10.200000
## 2650 56.0 178.0 3.15 0.44 10.200000
## 2651 43.0 162.0 3.11 0.53 9.500000
## 2652 25.0 146.0 3.18 0.40 9.300000
## 2653 45.0 80.0 3.06 0.34 12.900000
## 2654 45.0 148.0 3.14 0.46 8.700000
## 2656 71.0 204.0 3.23 0.69 10.100000
## 2657 60.0 196.0 3.19 0.78 10.000000
## 2658 51.0 129.0 3.27 0.69 11.100000
## 2659 65.0 158.0 3.26 0.70 10.300000
## 2660 27.0 73.0 3.24 0.41 12.200000
## 2661 35.0 156.0 3.11 0.48 9.300000
## 2662 46.0 178.0 3.19 0.56 11.300000
## 2663 46.0 110.0 3.04 0.65 10.800000
## 2664 15.0 86.0 2.98 0.39 11.200000
## 2665 36.0 91.0 3.32 0.45 12.500000
## 2666 15.0 122.0 3.39 0.49 9.300000
## 2667 38.0 142.0 3.40 0.41 12.900000
## 2668 21.0 131.0 3.20 0.45 11.200000
## 2670 45.0 179.0 3.20 0.49 9.300000
## 2671 38.0 142.0 3.40 0.41 12.900000
## 2672 38.0 142.0 3.41 0.41 12.900000
## 2673 46.0 120.0 3.20 0.36 9.500000
## 2674 5.0 24.0 3.19 0.36 11.900000
## 2675 23.0 120.0 2.93 0.66 10.300000
## 2676 23.0 120.0 2.92 0.66 10.300000
## 2677 33.0 93.0 3.06 0.68 11.200000
## 2678 32.0 150.0 3.18 0.31 12.000000
## 2679 21.0 144.0 3.13 0.40 9.600000
## 2680 29.0 110.0 3.20 0.42 9.200000
## 2681 52.0 119.0 3.03 0.33 12.900000
## 2682 46.0 149.0 2.99 0.59 9.300000
## 2683 15.0 136.0 3.10 0.44 12.100000
## 2684 21.0 144.0 3.13 0.40 9.600000
## 2685 35.0 128.0 3.37 0.48 11.200000
## 2686 28.0 98.0 3.11 0.37 11.200000
## 2687 52.0 119.0 3.03 0.33 12.900000
## 2688 56.0 187.0 3.21 0.46 9.200000
## 2689 46.0 149.0 2.99 0.59 9.300000
## 2690 29.0 110.0 3.20 0.42 9.200000
## 2691 26.0 124.0 3.18 0.50 9.300000
## 2692 26.0 108.0 3.20 0.36 10.700000
## 2693 20.0 166.0 3.05 0.54 9.800000
## 2694 28.0 143.0 3.30 0.54 10.300000
## 2695 26.0 108.0 3.20 0.36 10.700000
## 2696 26.0 121.0 3.28 0.38 11.300000
## 2697 36.0 182.0 3.02 0.49 8.800000
## 2698 16.0 104.0 3.18 0.50 10.800000
## 2699 20.0 166.0 3.05 0.54 9.800000
## 2700 26.0 124.0 3.18 0.50 9.300000
## 2701 15.0 72.0 3.26 0.60 11.500000
## 2702 43.0 133.0 3.26 0.41 8.800000
## 2703 43.0 133.0 3.26 0.41 8.800000
## 2704 43.0 133.0 3.26 0.41 8.800000
## 2707 59.0 209.0 3.16 0.63 9.600000
## 2708 43.0 133.0 3.26 0.41 8.800000
## 2709 56.0 189.0 3.22 0.48 9.300000
## 2710 66.0 184.0 3.22 0.75 8.900000
## 2711 66.0 184.0 3.22 0.75 8.900000
## 2713 47.0 182.0 3.24 0.46 9.100000
## 2714 56.0 189.0 3.22 0.48 9.300000
## 2715 59.0 188.0 3.20 0.50 9.400000
## 2716 46.0 179.0 3.14 0.60 10.100000
## 2717 66.0 184.0 3.22 0.75 8.900000
## 2718 59.0 143.0 3.20 0.40 10.800000
## 2719 18.0 69.0 3.24 0.54 10.000000
## 2720 53.0 160.0 3.03 0.38 10.900000
## 2721 29.0 92.0 3.15 0.38 12.000000
## 2723 32.0 101.0 3.22 0.62 12.300000
## 2724 29.0 129.0 3.45 0.56 10.400000
## 2725 53.0 160.0 3.03 0.38 10.900000
## 2726 62.0 153.0 3.22 0.42 10.500000
## 2727 22.0 91.0 3.41 0.50 9.800000
## 2728 34.0 121.0 3.06 0.46 10.500000
## 2729 86.0 213.0 3.16 0.51 9.900000
## 2730 24.0 79.0 3.27 0.69 11.400000
## 2732 30.0 173.0 3.09 0.53 9.700000
## 2733 13.0 135.0 3.09 0.51 10.000000
## 2734 24.0 79.0 3.27 0.69 11.400000
## 2735 50.0 141.0 3.13 0.49 10.300000
## 2736 86.0 213.0 3.16 0.51 9.900000
## 2737 34.0 121.0 3.06 0.46 10.500000
## 2738 29.0 95.0 3.16 0.47 9.800000
## 2739 24.0 131.0 3.19 0.34 9.300000
## 2740 25.0 100.0 3.08 0.47 12.400000
## 2741 54.0 145.0 3.16 0.42 9.300000
## 2742 24.0 131.0 3.19 0.34 9.300000
## 2743 49.0 165.0 3.26 0.72 9.500000
## 2744 9.0 45.0 3.08 0.40 10.500000
## 2745 9.0 45.0 3.08 0.40 10.500000
## 2746 19.0 99.0 3.26 0.53 12.800000
## 2747 44.0 142.0 2.99 0.45 10.800000
## 2748 48.0 127.0 3.10 0.55 10.000000
## 2750 48.0 127.0 3.10 0.55 10.000000
## 2752 38.0 108.0 3.19 0.66 12.000000
## 2753 15.0 138.0 3.18 0.46 12.600000
## 2754 15.0 70.0 3.37 0.40 11.900000
## 2755 5.0 28.0 3.13 0.32 10.600000
## 2756 47.0 240.0 3.42 0.48 9.200000
## 2757 42.0 240.0 3.17 0.52 10.000000
## 2758 18.0 97.0 3.36 0.46 9.200000
## 2759 19.0 103.0 3.36 0.47 9.300000
## 2760 25.0 144.0 3.24 0.54 10.200000
## 2761 25.0 148.0 3.25 0.54 10.200000
## 2762 51.0 154.0 3.14 0.51 8.700000
## 2763 8.0 163.0 3.24 0.42 10.700000
## 2764 4.0 119.0 3.18 0.34 12.100000
## 2765 58.0 152.0 3.12 0.37 9.500000
## 2766 17.0 118.0 3.18 0.37 11.200000
## 2767 36.0 95.0 2.93 0.59 12.000000
## 2768 58.0 152.0 3.12 0.37 9.500000
## 2769 4.0 119.0 3.18 0.34 12.100000
## 2770 8.0 163.0 3.24 0.42 10.700000
## 2771 29.0 228.0 3.26 0.54 8.800000
## 2773 39.0 138.0 3.31 0.37 13.100000
## 2774 22.0 93.0 3.08 0.60 12.500000
## 2775 37.0 131.0 3.09 0.33 11.700000
## 2776 37.0 131.0 3.09 0.33 11.700000
## 2777 35.0 135.0 3.09 0.33 11.600000
## 2778 24.0 111.0 3.29 0.54 11.300000
## 2779 22.0 93.0 3.08 0.60 12.500000
## 2780 42.0 103.0 3.11 0.45 11.400000
## 2781 4.0 117.0 3.40 0.44 12.200000
## 2783 32.0 211.0 3.31 0.59 10.400000
## 2784 32.0 211.0 3.31 0.59 10.400000
## 2785 32.0 211.0 3.31 0.59 10.400000
## 2786 35.0 157.0 3.17 0.50 9.100000
## 2787 8.0 70.0 3.05 0.41 12.200000
## 2788 35.0 157.0 3.17 0.50 9.100000
## 2789 41.0 176.0 3.12 0.54 9.400000
## 2790 42.0 178.0 3.11 0.53 9.400000
## 2791 32.0 211.0 3.31 0.59 10.400000
## 2792 61.0 189.0 3.22 0.49 9.200000
## 2793 52.0 183.0 3.20 0.51 9.400000
## 2794 39.0 107.0 3.22 0.53 13.500000
## 2795 37.0 151.0 3.07 0.40 9.400000
## 2796 15.0 83.0 3.13 0.55 10.900000
## 2797 39.0 107.0 3.22 0.53 13.500000
## 2798 37.0 151.0 3.07 0.40 9.400000
## 2799 34.0 114.0 3.19 0.45 11.400000
## 2800 45.0 125.0 3.19 0.51 12.400000
## 2801 61.0 189.0 3.22 0.49 9.200000
## 2802 52.0 183.0 3.20 0.51 9.400000
## 2803 8.0 79.0 3.30 0.39 10.500000
## 2804 16.0 99.0 3.26 0.38 11.500000
## 2805 15.0 83.0 3.13 0.55 10.900000
## 2806 36.0 123.0 3.34 0.44 10.800000
## 2807 52.0 148.0 3.03 0.46 8.900000
## 2808 53.0 151.0 3.03 0.46 8.900000
## 2809 60.0 184.0 3.20 0.50 9.400000
## 2810 25.0 153.0 3.44 0.73 12.200000
## 2811 22.0 100.0 2.99 0.47 12.100000
## 2812 23.0 128.0 3.17 0.66 10.900000
## 2813 27.0 109.0 3.34 0.58 10.100000
## 2814 25.0 153.0 3.44 0.73 12.200000
## 2815 14.0 71.0 3.31 0.38 13.000000
## 2816 15.0 72.0 3.23 0.39 11.000000
## 2817 24.0 126.0 3.19 0.49 10.800000
## 2818 14.0 71.0 3.31 0.38 13.000000
## 2820 63.0 123.0 3.44 0.42 11.400000
## 2822 42.0 241.0 3.50 0.60 9.900000
## 2823 25.0 150.0 3.22 0.44 10.500000
## 2824 18.0 56.0 3.06 0.48 12.400000
## 2825 52.0 172.0 3.18 0.53 9.500000
## 2826 41.0 161.0 3.16 0.50 10.500000
## 2827 52.0 196.0 3.23 0.48 9.100000
## 2828 53.0 138.0 3.38 0.35 11.500000
## 2829 53.0 138.0 3.38 0.35 11.500000
## 2830 31.0 170.0 3.17 0.37 11.200000
## 2831 59.0 140.0 3.22 0.40 10.800000
## 2832 31.0 186.0 3.12 0.44 9.400000
## 2833 13.0 73.0 3.17 0.58 11.000000
## 2834 22.0 112.0 3.21 0.37 11.300000
## 2835 51.0 117.0 3.28 0.38 11.200000
## 2836 41.0 161.0 3.16 0.50 10.500000
## 2837 52.0 196.0 3.23 0.48 9.100000
## 2838 35.0 154.0 3.21 0.50 10.400000
## 2839 14.0 82.0 3.10 0.58 11.200000
## 2840 34.0 89.0 3.14 0.36 11.100000
## 2841 23.0 92.0 3.18 0.38 11.200000
## 2842 17.0 98.0 3.29 0.39 10.500000
## 2843 23.0 92.0 3.20 0.45 10.000000
## 2844 24.0 90.0 3.20 0.47 10.000000
## 2845 24.0 97.0 3.10 0.42 10.900000
## 2846 16.0 87.0 3.15 0.56 10.900000
## 2847 14.0 82.0 3.10 0.58 11.200000
## 2848 40.0 86.0 3.50 0.42 11.700000
## 2849 55.0 144.0 3.16 0.42 10.000000
## 2851 55.0 136.0 3.03 0.52 9.000000
## 2852 19.0 86.0 3.04 0.56 10.000000
## 2853 37.0 154.0 3.08 0.43 11.900000
## 2854 40.0 101.0 3.57 0.59 10.600000
## 2855 29.0 101.0 3.15 0.40 11.000000
## 2856 46.0 143.0 3.25 0.43 11.200000
## 2857 29.0 129.0 3.51 0.60 12.000000
## 2858 39.0 96.0 3.24 0.60 12.600000
## 2859 46.0 143.0 3.25 0.43 11.200000
## 2860 48.0 113.0 3.24 0.68 10.500000
## 2861 66.0 144.0 3.11 0.52 10.200000
## 2862 29.0 101.0 3.15 0.40 11.000000
## 2863 12.0 90.0 3.57 0.52 12.200000
## 2864 19.0 76.0 3.18 0.41 12.300000
## 2865 40.0 101.0 3.57 0.59 10.600000
## 2866 33.0 115.0 3.36 0.50 10.400000
## 2867 29.0 129.0 3.51 0.60 12.000000
## 2868 22.0 121.0 3.15 0.53 12.700000
## 2869 18.0 128.0 3.05 0.28 10.600000
## 2870 25.0 108.0 3.14 0.34 12.300000
## 2871 22.0 121.0 3.15 0.53 12.700000
## 2872 20.0 84.0 3.09 0.53 11.400000
## 2874 38.0 95.0 3.23 0.94 12.400000
## 2876 20.0 84.0 3.09 0.53 11.400000
## 2877 57.0 135.0 3.21 0.38 10.700000
## 2879 35.0 138.0 3.37 0.42 12.700000
## 2880 24.0 88.0 3.18 0.39 11.700000
## 2881 22.0 64.0 2.93 0.49 10.700000
## 2882 38.0 94.0 2.99 0.43 11.800000
## 2883 37.0 125.0 3.20 0.39 9.900000
## 2884 16.0 81.0 3.23 0.53 13.400000
## 2885 30.0 114.0 3.12 0.64 12.800000
## 2886 24.0 87.0 3.15 0.45 12.800000
## 2887 18.0 101.0 3.13 0.41 10.500000
## 2888 24.0 84.0 3.31 0.55 11.500000
## 2889 5.0 25.0 3.04 0.37 10.500000
## 2890 21.0 132.0 2.95 0.39 13.000000
## 2891 64.0 138.0 3.19 0.34 12.400000
## 2892 40.0 148.0 3.16 0.35 10.200000
## 2893 67.0 234.0 3.23 0.50 9.000000
## 2895 22.0 68.0 3.15 0.50 11.700000
## 2896 20.0 180.0 3.58 0.57 10.000000
## 2897 42.0 218.0 3.37 0.54 10.300000
## 2898 67.0 234.0 3.23 0.50 9.000000
## 2899 25.0 78.0 2.99 0.38 11.100000
## 2900 59.0 150.0 3.31 0.46 9.000000
## 2901 37.0 97.0 3.40 0.58 10.500000
## 2902 36.0 92.0 3.27 0.59 11.900000
## 2903 38.0 155.0 3.27 0.50 9.400000
## 2904 26.0 81.0 3.31 0.52 11.400000
## 2905 40.0 114.0 3.31 0.58 10.800000
## 2906 40.0 157.0 3.10 0.46 9.800000
## 2907 59.0 183.0 3.20 0.45 9.300000
## 2908 26.0 81.0 3.31 0.52 11.400000
## 2909 22.0 73.0 3.24 0.52 11.300000
## 2910 23.0 73.0 3.23 0.52 11.300000
## 2911 49.0 170.0 3.22 0.48 9.500000
## 2912 38.0 155.0 3.27 0.50 9.400000
## 2913 36.0 92.0 3.27 0.59 11.900000
## 2914 49.0 199.0 3.03 0.38 9.300000
## 2915 22.0 81.0 3.03 0.54 11.400000
## 2916 22.0 81.0 3.03 0.54 11.400000
## 2917 57.0 128.0 3.22 0.39 12.700000
## 2918 26.0 118.0 3.20 0.45 13.500000
## 2919 15.0 65.0 3.06 0.52 11.200000
## 2920 38.0 118.0 3.19 0.41 10.700000
## 2921 13.0 92.0 3.01 0.46 10.800000
## 2922 27.0 202.0 3.46 0.57 10.500000
## 2923 44.0 137.0 3.13 0.32 13.000000
## 2924 41.0 131.0 3.08 0.49 10.800000
## 2925 39.0 118.0 3.05 0.50 9.100000
## 2926 67.0 196.0 3.10 0.50 10.100000
## 2927 13.0 59.0 3.30 0.84 11.900000
## 2928 45.0 140.0 2.98 0.31 12.000000
## 2929 45.0 140.0 2.98 0.31 12.000000
## 2930 39.0 118.0 3.05 0.50 9.100000
## 2932 13.0 59.0 3.30 0.84 11.900000
## 2933 69.0 192.0 3.14 0.50 10.200000
## 2934 41.0 131.0 3.08 0.49 10.800000
## 2935 11.0 66.0 3.30 0.40 9.800000
## 2936 3.0 89.0 2.95 0.30 11.400000
## 2937 11.0 68.0 3.30 0.41 9.800000
## 2938 67.0 196.0 3.10 0.50 10.100000
## 2939 41.0 98.0 3.19 0.38 9.800000
## 2940 41.0 98.0 3.19 0.38 9.800000
## 2941 49.0 128.0 3.21 0.40 10.700000
## 2942 14.0 111.0 3.11 0.61 10.600000
## 2943 49.0 173.0 3.17 0.47 9.300000
## 2944 41.0 98.0 3.19 0.38 9.800000
## 2945 49.0 128.0 3.21 0.40 10.700000
## 2946 39.0 150.0 3.33 0.59 14.000000
## 2947 27.0 107.0 3.36 0.37 11.000000
## 2948 27.0 107.0 3.36 0.37 11.000000
## 2949 55.0 182.0 3.21 0.45 9.400000
## 2950 30.0 139.0 3.10 0.36 9.000000
## 2951 8.0 108.0 3.08 0.55 9.000000
## 2952 17.0 101.0 3.37 0.53 10.000000
## 2953 9.0 109.0 3.08 0.54 9.000000
## 2954 8.0 108.0 3.08 0.55 9.000000
## 2955 25.0 79.0 3.29 0.60 12.400000
## 2956 28.0 123.0 3.14 0.44 11.300000
## 2957 36.0 86.0 2.80 0.55 12.000000
## 2958 37.0 94.0 3.01 0.56 11.700000
## 2959 17.0 101.0 3.37 0.53 10.000000
## 2960 26.0 90.0 2.84 0.54 13.200000
## 2961 41.0 114.0 3.07 0.59 11.000000
## 2962 30.0 114.0 3.22 0.54 11.000000
## 2963 14.0 94.0 3.02 0.48 9.200000
## 2964 38.0 113.0 3.08 0.48 13.000000
## 2965 38.0 128.0 3.77 0.60 10.600000
## 2966 31.0 119.0 3.55 0.49 13.000000
## 2967 33.0 118.0 3.04 0.54 9.000000
## 2968 33.0 118.0 3.04 0.54 9.000000
## 2969 52.0 148.0 2.93 0.32 11.500000
## 2970 17.0 76.0 3.11 0.44 11.000000
## 2971 52.0 148.0 2.93 0.32 11.500000
## 2972 10.0 112.0 3.11 0.43 9.900000
## 2973 31.0 128.0 3.12 0.46 10.400000
## 2974 33.0 118.0 3.04 0.54 9.000000
## 2975 50.0 110.0 3.06 0.52 9.900000
## 2976 71.0 162.0 3.07 0.47 11.000000
## 2977 34.0 124.0 3.18 0.35 12.100000
## 2978 45.0 131.0 2.96 0.51 9.700000
## 2979 45.0 131.0 2.96 0.51 9.700000
## 2980 39.0 123.0 2.99 0.30 12.200000
## 2981 31.0 113.0 3.15 0.31 12.400000
## 2982 30.0 97.0 3.03 0.39 10.500000
## 2983 29.0 213.0 3.28 0.57 10.400000
## 2984 48.0 180.0 3.15 0.34 12.000000
## 2985 4.0 28.0 3.07 0.32 12.700000
## 2986 29.0 115.0 3.11 0.45 10.900000
## 2987 29.0 115.0 3.11 0.45 10.900000
## 2988 29.0 113.0 3.11 0.45 10.900000
## 2989 17.0 103.0 3.15 0.52 11.400000
## 2990 74.0 184.0 3.22 0.41 11.000000
## 2991 58.0 178.0 3.45 0.31 12.600000
## 2992 45.0 152.0 3.29 0.46 11.600000
## 2993 29.0 130.0 3.11 0.44 10.500000
## 2994 29.0 113.0 3.11 0.45 10.900000
## 2995 29.0 113.0 3.11 0.45 10.900000
## 2996 42.0 119.0 3.03 0.37 12.500000
## 2997 32.0 111.0 3.11 0.50 12.100000
## 2998 35.0 158.0 3.02 0.58 11.300000
## 2999 18.0 112.0 3.07 0.64 13.300000
## 3000 29.0 113.0 3.11 0.45 10.900000
## 3001 29.0 115.0 3.11 0.45 10.900000
## 3002 29.0 130.0 3.11 0.44 10.500000
## 3003 45.0 152.0 3.29 0.46 11.600000
## 3004 17.0 103.0 3.15 0.52 11.400000
## 3005 26.0 111.0 3.16 0.51 11.000000
## 3006 40.0 156.0 3.08 0.36 12.100000
## 3007 74.0 184.0 3.22 0.41 11.000000
## 3008 58.0 178.0 3.45 0.31 12.600000
## 3009 54.0 173.0 3.36 0.30 13.000000
## 3010 50.0 221.0 2.94 0.64 8.800000
## 3011 30.5 218.0 3.16 0.53 9.500000
## 3012 30.0 105.0 3.20 0.47 11.800000
## 3013 29.0 93.0 3.14 0.45 12.200000
## 3014 36.0 105.0 3.05 0.55 10.700000
## 3016 14.0 104.0 2.99 0.44 11.400000
## 3017 36.0 105.0 3.05 0.55 10.700000
## 3018 57.0 135.0 3.09 0.34 12.000000
## 3019 33.0 121.0 3.02 0.39 11.900000
## 3020 14.0 104.0 2.99 0.44 11.400000
## 3021 3.0 46.0 3.02 0.34 11.800000
## 3022 6.0 88.0 3.34 0.48 10.600000
## 3023 24.0 133.0 3.06 0.38 9.700000
## 3025 36.0 105.0 3.05 0.55 10.700000
## 3027 17.0 118.0 2.99 0.34 10.500000
## 3028 44.0 150.0 3.10 0.45 10.400000
## 3029 21.0 138.0 3.20 0.55 10.500000
## 3030 22.0 142.0 3.12 0.48 12.000000
## 3031 22.0 142.0 3.12 0.48 12.000000
## 3032 33.0 124.0 3.22 0.41 9.200000
## 3033 15.0 92.0 3.37 0.49 10.900000
## 3034 50.0 185.0 3.15 0.50 9.500000
## 3035 36.0 156.0 3.15 0.55 9.400000
## 3036 31.0 85.0 3.13 0.50 11.300000
## 3037 26.0 189.0 3.42 0.58 10.400000
## 3038 57.0 170.0 3.26 0.57 9.400000
## 3039 43.0 104.0 3.02 0.52 11.300000
## 3040 59.0 196.0 3.14 0.40 8.800000
## 3041 58.0 130.0 3.20 0.35 10.800000
## 3042 58.0 173.0 3.25 0.57 9.400000
## 3043 57.0 170.0 3.26 0.57 9.400000
## 3045 15.0 144.0 3.12 0.53 10.300000
## 3046 21.0 99.0 3.09 0.57 9.900000
## 3047 38.0 112.0 3.19 0.34 12.400000
## 3048 42.0 167.0 3.11 0.44 11.900000
## 3049 33.0 132.0 3.11 0.56 11.700000
## 3050 49.0 199.0 2.98 0.57 9.400000
## 3052 49.0 199.0 2.98 0.57 9.400000
## 3054 26.0 102.0 3.09 0.47 9.500000
## 3055 7.0 73.0 3.20 0.43 11.900000
## 3056 36.0 116.0 3.18 0.40 12.500000
## 3057 6.0 55.0 3.16 0.40 13.400000
## 3058 27.0 114.0 3.13 0.84 12.700000
## 3059 54.0 208.0 3.17 0.46 9.100000
## 3060 23.0 58.0 2.90 0.50 10.500000
## 3061 58.0 176.0 3.19 0.70 10.400000
## 3062 58.0 176.0 3.19 0.70 10.400000
## 3063 30.0 110.0 3.08 0.59 12.500000
## 3064 58.0 176.0 3.19 0.70 10.400000
## 3066 54.0 120.0 3.18 0.42 9.800000
## 3068 29.0 142.0 3.17 0.43 10.700000
## 3069 28.0 111.0 3.16 0.49 12.400000
## 3070 6.0 76.0 3.08 0.50 12.500000
## 3071 30.0 110.0 3.08 0.59 12.500000
## 3072 20.0 82.0 3.10 0.43 12.100000
## 3074 48.0 122.0 3.25 0.43 12.000000
## 3075 29.0 141.0 3.28 0.60 10.400000
## 3076 23.0 87.0 3.11 0.46 12.200000
## 3077 24.0 115.0 3.05 0.43 8.600000
## 3078 54.0 208.0 3.17 0.46 9.100000
## 3079 35.0 91.0 2.96 0.33 12.100000
## 3080 9.0 125.0 3.32 0.81 12.000000
## 3081 23.0 58.0 2.90 0.50 10.500000
## 3082 58.0 176.0 3.19 0.70 10.400000
## 3083 10.0 102.0 3.46 0.42 11.900000
## 3084 28.0 94.0 3.25 0.52 13.700000
## 3085 33.0 78.0 3.22 0.72 11.300000
## 3086 24.0 88.0 3.02 0.42 10.500000
## 3087 28.0 94.0 3.25 0.52 13.700000
## 3088 38.0 201.0 3.14 0.44 10.100000
## 3089 12.0 76.0 2.94 0.39 12.300000
## 3090 20.0 89.0 3.06 0.33 12.000000
## 3091 33.0 78.0 3.22 0.72 11.300000
## 3092 61.0 183.0 3.12 0.51 9.500000
## 3093 28.0 152.0 3.02 0.53 11.400000
## 3094 40.0 118.0 3.16 0.48 11.900000
## 3097 19.0 102.0 3.23 0.60 11.300000
## 3099 44.0 129.0 3.36 0.39 11.000000
## 3100 34.0 111.0 2.97 0.48 12.200000
## 3101 57.0 124.0 2.91 0.54 10.700000
## 3102 25.0 84.0 3.11 0.34 10.900000
## 3103 18.0 113.0 3.17 0.38 10.200000
## 3104 40.0 118.0 3.16 0.48 11.900000
## 3105 20.0 130.0 3.15 0.48 11.100000
## 3106 26.0 159.0 3.00 0.50 11.200000
## 3107 28.0 152.0 3.02 0.53 11.400000
## 3108 31.0 169.0 3.07 0.57 10.600000
## 3109 33.0 151.0 3.03 0.53 10.300000
## 3110 31.0 203.0 3.40 0.57 10.400000
## 3111 19.0 111.0 3.10 0.62 11.900000
## 3112 41.0 98.0 3.19 0.43 11.900000
## 3113 24.0 129.0 3.12 0.70 10.400000
## 3114 22.0 126.0 3.11 0.47 9.200000
## 3115 37.0 117.0 3.24 0.43 11.300000
## 3116 37.0 117.0 3.24 0.43 11.300000
## 3117 35.0 89.0 3.25 0.50 11.000000
## 3118 41.0 98.0 3.19 0.43 11.900000
## 3119 47.0 147.0 3.08 0.64 12.900000
## 3120 3.0 21.0 3.09 0.31 10.800000
## 3121 53.0 206.0 3.16 0.47 9.100000
## 3122 24.0 129.0 3.12 0.70 10.400000
## 3123 31.0 103.0 3.35 0.37 12.900000
## 3124 10.0 86.0 3.46 0.44 12.200000
## 3125 22.0 126.0 3.11 0.47 9.200000
## 3126 41.0 150.0 3.06 0.46 10.300000
## 3127 47.0 128.0 3.08 0.46 11.000000
## 3128 10.0 98.0 3.17 0.65 11.000000
## 3129 31.0 100.0 3.69 0.62 11.700000
## 3130 37.0 122.0 3.20 0.43 12.000000
## 3131 30.0 148.0 3.17 0.43 12.700000
## 3132 59.0 198.0 3.11 0.49 8.800000
## 3133 37.0 117.0 3.24 0.43 11.300000
## 3134 38.0 121.0 3.19 0.40 12.800000
## 3135 45.0 114.0 3.18 0.44 11.200000
## 3136 51.0 221.0 3.26 0.51 8.900000
## 3137 52.0 103.0 3.50 0.39 11.200000
## 3138 42.0 135.0 3.23 0.40 11.100000
## 3139 34.0 115.0 3.05 0.51 10.800000
## 3140 33.0 126.0 3.18 0.42 9.300000
## 3141 51.0 221.0 3.26 0.51 8.900000
## 3142 9.0 34.0 3.22 0.36 12.700000
## 3143 35.0 140.0 3.16 0.40 12.000000
## 3144 52.0 103.0 3.50 0.39 11.200000
## 3145 37.0 130.0 3.23 0.43 8.800000
## 3146 37.0 130.0 3.23 0.43 8.800000
## 3147 37.0 130.0 3.23 0.43 8.800000
## 3148 45.0 154.0 3.20 0.47 10.400000
## 3149 37.0 130.0 3.23 0.43 8.800000
## 3150 45.0 154.0 3.20 0.47 10.400000
## 3151 12.0 88.0 3.38 0.45 14.000000
## 3152 37.0 130.0 3.23 0.43 8.800000
## 3154 30.0 88.0 3.25 0.42 12.300000
## 3155 40.0 109.0 3.27 0.46 12.600000
## 3156 38.0 133.0 3.18 0.44 12.000000
## 3157 28.0 124.0 2.87 0.47 9.500000
## 3158 38.0 133.0 3.18 0.44 12.000000
## 3159 39.0 114.0 3.08 0.49 12.700000
## 3160 30.0 130.0 3.40 0.39 10.500000
## 3161 6.0 80.0 3.15 0.54 12.900000
## 3162 28.0 124.0 2.87 0.47 9.500000
## 3163 38.0 133.0 3.18 0.44 12.000000
## 3164 39.0 114.0 3.08 0.49 12.700000
## 3165 20.0 198.0 3.06 0.66 11.900000
## 3167 42.0 133.0 3.25 0.41 12.500000
## 3168 36.0 118.0 3.21 0.43 12.100000
## 3169 22.0 82.0 3.05 0.36 12.500000
## 3170 28.0 113.0 3.06 0.58 9.900000
## 3171 63.0 147.0 3.02 0.41 10.700000
## 3172 24.0 87.0 2.94 0.35 12.000000
## 3173 34.0 116.0 2.97 0.31 12.200000
## 3174 39.0 124.0 2.99 0.32 12.400000
## 3175 37.0 125.0 3.00 0.32 12.400000
## 3176 55.0 140.0 3.02 0.31 10.300000
## 3177 24.0 87.0 2.94 0.35 12.000000
## 3178 44.0 154.0 3.30 0.40 10.500000
## 3179 23.0 98.0 3.10 0.44 9.500000
## 3180 31.0 106.0 3.00 0.35 10.500000
## 3181 31.0 90.0 3.24 0.36 12.300000
## 3182 38.0 107.0 2.93 0.37 11.900000
## 3183 23.0 131.0 3.25 0.45 9.800000
## 3184 31.0 90.0 3.24 0.36 12.300000
## 3185 17.0 76.0 3.14 0.56 11.400000
## 3186 49.0 115.0 3.21 0.43 11.000000
## 3187 10.0 70.0 3.06 0.56 10.800000
## 3188 42.0 125.0 3.24 0.37 12.800000
## 3189 42.0 123.0 3.11 0.50 11.000000
## 3190 42.0 148.0 3.15 0.36 10.200000
## 3191 31.0 114.0 3.32 0.60 12.500000
## 3192 49.0 146.0 3.06 0.37 11.600000
## 3193 38.0 107.0 2.93 0.37 11.900000
## 3194 23.0 131.0 3.25 0.45 9.800000
## 3195 7.0 89.0 3.26 0.48 11.000000
## 3196 36.0 123.0 3.14 0.52 10.900000
## 3197 35.0 127.0 2.97 0.30 11.000000
## 3198 47.0 126.0 2.96 0.37 12.500000
## 3199 35.0 127.0 2.97 0.30 11.000000
## 3200 40.0 121.0 3.18 0.53 12.000000
## 3201 46.0 145.0 3.14 0.31 12.400000
## 3202 47.0 126.0 2.96 0.37 12.500000
## 3203 34.0 97.0 3.22 0.38 12.800000
## 3204 35.0 127.0 2.97 0.30 11.000000
## 3205 34.0 177.0 3.33 0.43 9.100000
## 3206 28.0 156.0 3.11 0.40 12.400000
## 3207 22.0 98.0 3.15 0.80 12.900000
## 3208 24.0 126.0 3.09 0.87 10.900000
## 3209 39.0 164.0 3.53 0.58 10.800000
## 3210 56.0 142.0 3.11 0.38 10.600000
## 3211 29.0 106.0 3.13 0.52 9.000000
## 3212 52.0 154.0 3.04 0.33 12.000000
## 3213 23.0 131.0 3.25 0.35 11.800000
## 3214 67.0 158.0 3.01 0.38 10.600000
## 3215 17.0 74.0 3.34 0.48 12.300000
## 3216 20.0 54.0 3.19 0.64 11.500000
## 3217 48.0 111.0 2.97 0.45 11.100000
## 3218 29.0 106.0 3.13 0.52 9.000000
## 3219 8.0 111.0 3.00 0.44 9.900000
## 3220 37.0 92.0 3.27 0.53 12.800000
## 3221 19.0 76.0 2.93 0.57 12.900000
## 3222 8.0 74.0 3.10 0.57 12.900000
## 3223 41.0 115.0 3.01 0.68 12.000000
## 3224 52.0 154.0 3.04 0.33 12.000000
## 3225 57.0 151.0 3.22 0.27 11.200000
## 3226 35.0 86.0 3.11 0.39 13.300000
## 3227 38.0 125.0 3.34 0.50 9.900000
## 3228 52.0 192.0 3.11 0.52 9.500000
## 3229 58.0 200.0 3.12 0.49 9.400000
## 3230 42.0 119.0 3.48 0.60 11.000000
## 3231 60.0 150.0 2.96 0.43 9.400000
## 3232 27.0 107.0 2.98 0.82 11.500000
## 3233 6.0 79.0 3.14 0.34 12.500000
## 3234 21.0 93.0 3.18 0.34 11.900000
## 3235 22.0 141.0 3.26 0.47 10.400000
## 3236 57.0 151.0 3.22 0.27 11.200000
## 3237 44.0 141.0 3.11 0.33 12.500000
## 3238 43.0 147.0 3.18 0.40 11.000000
## 3239 37.0 115.0 3.09 0.37 9.800000
## 3240 29.0 99.0 3.10 0.40 12.300000
## 3241 29.0 113.0 3.18 0.52 11.000000
## 3242 19.0 113.0 3.10 0.46 12.600000
## 3243 42.0 109.0 3.31 0.62 11.600000
## 3244 29.0 99.0 3.10 0.40 12.300000
## 3245 20.0 86.0 3.19 0.22 13.400000
## 3246 37.0 115.0 3.09 0.37 9.800000
## 3247 39.0 116.0 3.18 0.46 11.500000
## 3248 46.0 139.0 3.04 0.38 11.600000
## 3249 41.0 147.0 3.18 0.40 11.100000
## 3250 43.0 147.0 3.18 0.40 11.000000
## 3251 52.0 131.0 3.06 0.54 11.300000
## 3252 64.0 173.0 3.08 0.53 9.900000
## 3253 31.0 105.0 3.06 0.33 12.600000
## 3254 37.0 100.0 3.30 0.36 11.800000
## 3255 54.0 201.0 3.03 0.50 11.400000
## 3256 39.0 193.0 3.10 0.50 9.200000
## 3257 39.0 193.0 3.10 0.50 9.200000
## 3258 39.0 193.0 3.10 0.50 9.200000
## 3259 39.0 193.0 3.10 0.50 9.200000
## 3260 39.0 193.0 3.10 0.50 9.200000
## 3261 39.0 193.0 3.10 0.50 9.200000
## 3262 24.0 101.0 3.21 0.42 13.000000
## 3263 32.0 193.0 3.10 0.50 9.300000
## 3264 36.0 92.0 3.22 0.62 12.600000
## 3265 60.0 247.0 3.34 0.44 9.600000
## 3267 34.0 105.0 3.11 0.42 11.800000
## 3268 39.0 154.0 3.21 0.39 10.200000
## 3269 26.0 126.0 3.32 0.53 12.700000
## 3270 42.0 214.0 3.31 0.56 9.400000
## 3271 21.0 115.0 3.10 0.38 10.200000
## 3272 27.0 91.0 3.28 0.60 12.000000
## 3273 29.0 100.0 3.08 0.60 11.300000
## 3274 40.0 118.0 3.32 0.53 11.800000
## 3275 40.0 129.0 3.45 0.59 10.900000
## 3276 32.0 99.0 3.14 0.47 9.800000
## 3277 29.0 154.0 3.23 0.49 12.200000
## 3278 21.0 125.0 3.23 0.44 11.100000
## 3279 42.0 214.0 3.31 0.56 9.400000
## 3280 23.0 140.0 3.06 0.47 11.400000
## 3281 21.0 115.0 3.10 0.38 10.200000
## 3282 20.0 127.0 3.13 0.52 12.800000
## 3283 43.0 125.0 3.07 0.67 10.100000
## 3285 38.0 103.0 2.91 0.23 12.200000
## 3286 40.0 121.0 3.07 0.65 10.900000
## 3287 40.0 122.0 3.06 0.64 10.900000
## 3288 40.0 121.0 3.07 0.65 10.900000
## 3290 60.0 196.0 3.14 0.48 9.400000
## 3291 10.0 80.0 3.08 0.38 11.400000
## 3292 21.0 73.0 3.17 0.32 12.900000
## 3293 59.0 194.0 3.14 0.48 9.400000
## 3294 29.0 84.0 2.91 0.57 12.000000
## 3295 19.0 113.0 3.38 0.56 10.100000
## 3296 59.0 194.0 3.14 0.48 9.400000
## 3297 60.0 196.0 3.14 0.48 9.400000
## 3298 54.0 184.0 3.17 0.45 9.200000
## 3299 43.0 109.0 3.34 0.44 11.800000
## 3300 31.0 105.0 3.00 0.34 12.300000
## 3301 10.0 80.0 3.08 0.38 11.400000
## 3302 21.0 73.0 3.17 0.32 12.900000
## 3303 26.0 91.0 3.13 0.32 12.300000
## 3304 36.0 93.0 3.27 0.36 13.500000
## 3305 41.0 142.0 3.29 0.42 12.800000
## 3306 33.0 96.0 3.04 0.54 12.800000
## 3307 41.0 142.0 3.29 0.42 12.800000
## 3309 19.0 124.0 3.20 0.43 10.600000
## 3310 35.0 96.0 3.16 0.44 12.400000
## 3311 33.0 142.0 3.22 0.46 12.900000
## 3312 67.0 152.0 3.54 0.59 11.100000
## 3313 36.0 95.0 3.08 0.64 12.900000
## 3314 14.0 64.0 3.10 0.37 11.800000
## 3315 66.0 243.0 3.23 0.54 9.100000
## 3316 19.0 74.0 3.09 0.49 12.700000
## 3317 31.0 96.0 3.16 0.48 12.000000
## 3318 32.0 105.0 3.24 0.47 11.200000
## 3319 26.0 105.0 3.19 0.75 12.400000
## 3320 48.0 148.0 3.50 0.49 10.400000
## 3321 29.0 124.0 3.06 0.54 10.400000
## 3322 15.0 80.0 3.29 0.50 12.700000
## 3323 30.0 105.0 3.48 0.52 12.500000
## 3324 15.0 103.0 3.14 0.50 12.000000
## 3325 13.0 117.0 3.16 0.51 11.600000
## 3326 42.0 126.0 3.12 0.38 12.600000
## 3327 62.0 178.0 3.15 0.42 10.200000
## 3328 11.0 70.0 3.43 0.68 10.400000
## 3329 18.0 122.0 3.30 0.42 11.500000
## 3330 36.0 112.0 3.02 0.50 11.000000
## 3331 45.0 176.0 3.11 0.52 10.100000
## 3332 47.0 159.0 3.08 0.52 10.500000
## 3333 29.0 151.0 3.23 0.41 12.100000
## 3334 42.0 146.0 3.18 0.55 9.900000
## 3335 23.0 87.0 3.05 0.41 11.400000
## 3336 52.0 189.0 3.00 0.60 9.500000
## 3337 52.0 189.0 3.00 0.60 9.500000
## 3338 52.0 189.0 3.00 0.60 9.500000
## 3339 6.0 41.0 3.17 0.39 10.900000
## 3340 23.0 98.0 3.08 0.47 9.500000
## 3341 19.0 125.0 3.32 0.54 12.600000
## 3342 23.0 98.0 3.08 0.47 9.500000
## 3343 34.0 104.0 3.18 0.42 11.100000
## 3344 51.0 189.0 3.00 0.60 9.500000
## 3345 52.0 189.0 3.00 0.60 9.500000
## 3346 64.0 188.0 3.13 0.51 10.600000
## 3347 64.0 185.0 3.12 0.50 10.600000
## 3348 43.0 157.0 3.15 0.52 10.800000
## 3349 6.0 41.0 3.17 0.39 10.900000
## 3350 26.0 101.0 3.34 0.50 9.900000
## 3351 41.0 132.0 3.08 0.59 11.300000
## 3352 47.0 90.0 3.22 0.38 12.600000
## 3353 29.0 81.0 2.96 0.39 12.500000
## 3354 31.0 87.0 3.02 0.38 12.400000
## 3355 29.0 132.0 3.31 0.57 11.800000
## 3356 26.0 119.0 3.18 0.53 12.200000
## 3357 54.0 136.0 3.19 0.37 10.700000
## 3358 25.0 97.0 3.17 0.42 11.300000
## 3359 29.0 81.0 2.96 0.39 12.500000
## 3360 31.0 87.0 3.02 0.38 12.400000
## 3361 12.0 72.0 3.05 0.53 11.300000
## 3362 26.0 101.0 3.34 0.50 9.900000
## 3363 41.0 132.0 3.08 0.59 11.300000
## 3364 47.0 90.0 3.22 0.38 12.600000
## 3365 38.0 67.0 3.14 0.38 11.500000
## 3366 26.0 76.0 2.98 0.49 12.300000
## 3367 31.0 111.0 2.97 0.42 12.200000
## 3368 30.0 114.0 3.08 0.43 13.200000
## 3369 53.0 161.0 3.13 0.45 10.200000
## 3370 32.0 117.0 3.05 0.55 11.500000
## 3371 30.0 114.0 3.08 0.43 13.200000
## 3372 31.0 111.0 2.97 0.42 12.200000
## 3373 51.0 139.0 3.47 0.50 11.000000
## 3374 49.0 121.0 2.98 0.43 13.200000
## 3375 57.0 135.0 3.32 0.44 9.500000
## 3376 38.0 132.0 3.25 0.53 10.200000
## 3377 53.0 161.0 3.13 0.45 10.200000
## 3378 51.0 189.0 3.00 0.55 11.400000
## 3379 56.0 140.0 3.16 0.42 12.500000
## 3380 87.0 221.0 3.01 0.43 9.200000
## 3381 29.0 121.0 3.28 0.48 12.100000
## 3382 51.0 125.0 3.10 0.44 10.700000
## 3383 29.0 121.0 3.28 0.48 12.100000
## 3384 50.0 156.0 3.38 0.55 11.200000
## 3385 42.0 179.0 3.25 0.56 10.600000
## 3386 34.0 126.0 3.06 0.45 11.800000
## 3387 56.0 140.0 3.16 0.42 12.500000
## 3388 87.0 221.0 3.01 0.43 9.200000
## 3389 22.0 80.0 2.95 0.54 12.600000
## 3390 11.0 77.0 3.13 0.55 12.800000
## 3391 35.0 112.0 3.00 0.37 12.300000
## 3392 37.0 113.0 2.99 0.38 12.300000
## 3393 35.0 91.0 2.98 0.37 12.400000
## 3394 35.0 115.0 2.93 0.42 12.300000
## 3395 52.0 188.0 3.20 0.53 9.100000
## 3396 48.0 186.0 3.20 0.54 9.100000
## 3397 43.0 138.0 3.10 0.47 10.600000
## 3398 44.0 189.0 3.19 0.47 10.300000
## 3399 52.0 183.0 3.39 0.65 9.500000
## 3400 25.0 95.0 3.25 0.49 11.100000
## 3401 18.0 143.0 3.12 0.51 10.800000
## 3402 34.0 120.0 2.94 0.47 11.200000
## 3403 18.0 143.0 3.12 0.51 10.800000
## 3404 52.0 99.0 2.87 0.49 11.400000
## 3405 9.0 94.0 3.21 0.52 11.200000
## 3406 14.0 119.0 3.19 0.50 10.200000
## 3407 25.0 95.0 3.25 0.49 11.100000
## 3408 52.0 183.0 3.39 0.65 9.500000
## 3409 63.0 192.0 3.12 0.49 10.200000
## 3410 24.0 111.0 3.37 0.43 11.000000
## 3411 32.0 148.0 3.15 0.45 11.500000
## 3412 37.0 127.0 3.05 0.57 9.800000
## 3413 56.0 157.0 3.11 0.51 10.100000
## 3414 31.0 195.0 2.95 0.75 8.800000
## 3415 32.0 148.0 3.15 0.45 11.500000
## 3416 50.0 163.0 3.39 0.43 12.700000
## 3417 34.0 214.0 3.10 0.51 9.800000
## 3418 18.0 76.0 3.16 0.60 12.900000
## 3419 34.0 214.0 3.10 0.51 9.800000
## 3420 50.0 163.0 3.39 0.43 12.700000
## 3421 30.0 145.0 3.01 0.44 8.500000
## 3422 28.0 81.0 3.24 0.56 12.700000
## 3423 22.0 105.0 2.98 0.64 13.100000
## 3424 48.0 156.0 3.35 0.78 9.100000
## 3425 18.0 122.0 3.36 0.71 12.500000
## 3426 47.0 156.0 3.34 0.78 9.100000
## 3427 47.0 156.0 3.34 0.78 9.100000
## 3428 63.0 162.0 3.33 0.50 11.200000
## 3429 18.0 122.0 3.36 0.71 12.500000
## 3430 48.0 156.0 3.35 0.78 9.100000
## 3431 47.0 156.0 3.34 0.78 9.100000
## 3432 45.0 158.0 3.34 0.77 9.100000
## 3433 41.0 117.0 3.24 0.35 11.500000
## 3434 30.0 86.0 3.05 0.59 12.900000
## 3435 19.0 92.0 2.95 0.39 12.500000
## 3436 26.0 83.0 3.25 0.33 12.300000
## 3437 20.0 97.0 3.10 0.85 11.400000
## 3438 24.0 113.0 3.22 0.45 9.400000
## 3439 65.0 224.0 3.11 0.53 9.100000
## 3440 24.0 113.0 3.22 0.45 9.400000
## 3441 35.0 106.0 3.16 0.66 12.000000
## 3442 31.0 111.0 3.18 0.53 11.100000
## 3443 14.0 97.0 3.10 0.33 11.800000
## 3444 36.0 106.0 3.24 0.32 11.400000
## 3445 65.0 224.0 3.11 0.53 9.100000
## 3446 59.0 128.0 3.19 0.71 12.100000
## 3447 34.0 178.0 3.15 0.44 10.400000
## 3448 33.0 98.0 3.12 0.36 9.200000
## 3449 29.0 134.0 3.29 0.46 13.000000
## 3450 59.0 128.0 3.19 0.71 12.100000
## 3451 43.0 106.0 2.93 0.43 11.500000
## 3452 43.0 106.0 2.93 0.43 11.500000
## 3453 13.0 134.0 3.23 0.70 10.000000
## 3454 23.0 89.0 3.25 0.49 11.100000
## 3455 40.0 107.0 3.26 0.35 12.400000
## 3456 29.0 86.0 2.90 0.38 12.200000
## 3457 60.0 172.0 3.06 0.52 10.600000
## 3458 55.0 145.0 3.41 0.41 11.100000
## 3459 17.0 123.0 3.36 0.78 13.900000
## 3460 68.0 143.0 2.99 0.30 9.200000
## 3461 41.0 103.0 2.98 0.56 10.500000
## 3463 38.0 111.0 3.24 0.45 12.900000
## 3464 40.0 106.0 3.26 0.39 12.900000
## 3465 52.0 171.0 3.12 0.51 9.600000
## 3466 41.0 108.0 3.25 0.45 12.900000
## 3467 38.0 111.0 3.24 0.45 12.900000
## 3468 54.0 219.0 3.04 0.45 8.800000
## 3469 27.0 93.0 3.23 0.34 13.200000
## 3470 68.0 143.0 2.99 0.30 9.200000
## 3472 41.0 103.0 2.98 0.56 10.500000
## 3473 24.0 131.0 3.30 0.59 10.500000
## 3474 37.0 97.0 3.20 0.60 12.600000
## 3475 36.0 191.0 3.05 0.50 9.500000
## 3476 22.0 184.0 3.31 0.56 9.800000
## 3477 19.0 86.0 3.04 0.26 13.400000
## 3478 39.0 150.0 3.05 0.44 11.800000
## 3479 22.0 184.0 3.31 0.56 9.800000
## 3480 34.0 94.0 3.22 0.57 13.100000
## 3481 37.0 97.0 3.20 0.60 12.600000
## 3482 36.0 131.0 3.26 0.45 10.400000
## 3483 20.0 102.0 3.22 0.27 13.400000
## 3484 14.0 88.0 3.06 0.27 13.000000
## 3485 19.0 86.0 3.04 0.26 13.400000
## 3486 39.0 113.0 3.11 0.52 10.200000
## 3487 16.0 98.0 3.07 0.39 11.700000
## 3488 36.0 191.0 3.05 0.50 9.500000
## 3489 25.0 83.0 3.03 0.46 11.700000
## 3490 7.0 81.0 3.04 0.47 11.400000
## 3491 39.0 150.0 3.05 0.44 11.800000
## 3492 24.0 111.0 3.09 0.32 11.200000
## 3493 31.0 134.0 3.19 0.44 13.000000
## 3494 31.0 134.0 3.19 0.44 13.000000
## 3495 42.0 123.0 3.34 0.52 10.900000
## 3496 38.0 102.0 3.14 0.37 11.600000
## 3497 61.0 134.0 3.30 0.54 11.300000
## 3499 18.0 141.0 3.38 0.53 10.500000
## 3500 30.0 124.0 3.31 0.40 13.100000
## 3501 31.0 134.0 3.19 0.44 13.000000
## 3502 42.0 123.0 3.34 0.52 10.900000
## 3503 30.0 181.0 3.14 0.57 9.100000
## 3504 21.0 93.0 3.18 0.48 13.400000
## 3505 29.0 133.0 3.33 0.64 11.500000
## 3506 26.0 118.0 3.38 0.68 11.200000
## 3507 21.0 155.0 3.36 0.57 10.900000
## 3508 35.0 115.0 3.19 0.44 13.500000
## 3509 30.0 181.0 3.14 0.57 9.100000
## 3510 66.0 179.0 3.17 0.55 9.900000
## 3511 75.0 167.0 2.98 0.56 10.500000
## 3512 22.0 90.0 3.18 0.51 11.700000
## 3513 30.0 117.0 3.49 0.68 11.000000
## 3514 13.0 63.0 2.99 0.43 13.000000
## 3515 28.0 95.0 2.93 0.41 13.600000
## 3516 22.0 87.0 3.08 0.62 12.300000
## 3517 61.0 171.0 3.25 0.53 13.300000
## 3518 38.0 102.0 3.08 0.42 13.700000
## 3519 26.0 131.0 3.19 0.52 11.100000
## 3520 46.0 132.0 3.23 0.43 13.400000
## 3522 61.0 152.0 3.31 0.50 11.300000
## 3523 55.0 178.0 3.20 0.46 9.400000
## 3525 40.0 132.0 3.37 0.40 11.600000
## 3526 40.0 132.0 3.37 0.40 11.600000
## 3527 29.0 128.0 3.01 0.35 12.400000
## 3528 65.0 146.0 3.11 0.32 9.800000
## 3529 19.0 50.0 3.09 0.25 11.100000
## 3530 28.0 134.0 3.26 0.38 13.100000
## 3531 45.0 178.0 3.14 0.53 9.700000
## 3532 49.0 179.0 3.15 0.48 9.200000
## 3533 17.0 85.0 3.10 0.78 11.700000
## 3534 50.0 136.0 3.14 0.37 10.600000
## 3535 45.0 178.0 3.14 0.53 9.700000
## 3536 49.0 179.0 3.15 0.48 9.200000
## 3537 30.0 92.0 3.10 0.39 10.900000
## 3538 28.0 105.0 3.23 0.51 10.100000
## 3539 54.0 128.0 3.17 0.44 12.200000
## 3540 27.0 80.0 3.03 0.33 12.700000
## 3541 27.0 99.0 2.98 0.37 13.000000
## 3542 43.0 123.0 3.16 0.33 11.200000
## 3543 46.0 153.0 3.20 0.48 9.400000
## 3544 49.0 159.0 3.41 0.53 11.000000
## 3545 49.0 159.0 3.41 0.53 11.000000
## 3546 69.0 237.0 3.10 0.48 9.200000
## 3547 46.0 153.0 3.20 0.48 9.400000
## 3548 69.0 237.0 3.10 0.48 9.200000
## 3549 24.0 142.0 3.22 0.45 12.300000
## 3550 49.0 159.0 3.41 0.53 11.000000
## 3551 48.0 116.0 3.04 0.67 10.000000
## 3552 39.0 110.0 3.24 0.48 9.000000
## 3553 39.0 110.0 3.24 0.48 9.000000
## 3554 39.0 110.0 3.24 0.48 9.000000
## 3555 49.0 87.0 2.92 0.36 11.100000
## 3556 27.0 123.0 3.06 0.60 9.900000
## 3557 17.0 112.0 3.66 0.48 12.200000
## 3558 49.0 87.0 2.92 0.36 11.100000
## 3559 39.0 110.0 3.24 0.48 9.000000
## 3560 5.0 34.0 3.01 0.36 11.800000
## 3561 19.0 78.0 3.11 0.62 12.900000
## 3562 23.0 86.0 2.86 0.35 9.000000
## 3563 42.0 162.0 3.01 0.33 12.400000
## 3564 23.0 86.0 2.86 0.35 9.000000
## 3565 19.0 78.0 3.11 0.62 12.900000
## 3566 15.0 85.0 2.99 0.36 11.200000
## 3567 7.0 112.0 3.00 0.41 12.600000
## 3568 20.0 80.0 3.12 0.39 11.500000
## 3569 31.0 93.0 3.07 0.72 11.300000
## 3570 15.0 85.0 2.99 0.36 11.200000
## 3571 20.0 80.0 3.12 0.39 11.500000
## 3572 8.0 31.0 3.32 0.51 10.500000
## 3573 7.0 112.0 3.00 0.41 12.600000
## 3574 20.0 87.0 3.15 0.48 11.900000
## 3575 24.0 119.0 3.18 0.52 10.100000
## 3576 32.0 112.0 3.15 0.45 11.000000
## 3577 35.0 161.0 3.14 0.56 10.600000
## 3578 39.0 120.0 3.04 0.59 11.300000
## 3579 5.0 124.0 3.10 0.37 11.200000
## 3580 14.0 78.0 2.94 0.37 11.500000
## 3581 33.0 143.0 2.92 0.35 11.100000
## 3582 19.0 130.0 3.14 0.49 12.800000
## 3583 12.0 76.0 3.30 0.46 12.300000
## 3584 15.0 102.0 3.26 0.53 10.400000
## 3585 14.0 78.0 2.94 0.37 11.500000
## 3586 42.0 104.0 3.16 0.37 11.700000
## 3587 52.0 158.0 3.35 0.44 10.700000
## 3591 37.0 107.0 3.18 0.68 12.000000
## 3592 28.0 186.0 3.31 0.45 10.800000
## 3593 52.0 158.0 3.35 0.44 10.700000
## 3594 52.0 158.0 3.35 0.44 10.700000
## 3595 37.0 107.0 3.12 0.44 10.700000
## 3596 40.0 123.0 3.12 0.40 12.100000
## 3597 55.0 108.0 3.00 0.52 11.900000
## 3598 54.0 137.0 3.18 0.37 10.800000
## 3599 65.0 169.0 3.59 0.56 12.300000
## 3600 49.0 226.0 3.30 0.57 9.400000
## 3601 32.0 88.0 3.20 0.35 9.900000
## 3602 29.0 140.0 3.35 0.61 10.400000
## 3603 28.0 137.0 3.35 0.60 10.400000
## 3604 37.0 122.0 3.15 0.60 12.600000
## 3605 31.0 69.0 2.93 0.36 12.500000
## 3606 35.0 167.0 3.04 0.47 9.400000
## 3607 41.0 151.0 3.11 0.60 9.200000
## 3608 30.0 90.0 3.27 0.54 11.200000
## 3609 27.0 149.0 2.91 0.46 9.200000
## 3610 27.0 149.0 2.91 0.46 9.200000
## 3611 35.0 167.0 3.04 0.47 9.400000
## 3612 30.0 90.0 3.27 0.54 11.200000
## 3613 31.0 114.0 3.27 0.55 10.800000
## 3614 27.0 149.0 2.91 0.46 9.200000
## 3615 41.0 151.0 3.11 0.60 9.200000
## 3616 11.0 95.0 2.96 0.36 12.500000
## 3617 66.0 188.0 3.00 0.54 9.300000
## 3618 20.0 117.0 3.21 0.50 11.400000
## 3619 48.0 118.0 3.04 0.56 10.000000
## 3622 48.0 118.0 3.04 0.56 10.000000
## 3623 11.0 95.0 2.96 0.36 12.500000
## 3625 12.0 93.0 3.19 0.27 12.800000
## 3626 66.0 188.0 3.00 0.54 9.300000
## 3627 20.0 117.0 3.21 0.50 11.400000
## 3628 61.0 183.0 3.24 0.43 9.500000
## 3629 57.0 181.0 3.24 0.43 9.500000
## 3630 61.0 172.0 3.24 0.43 9.500000
## 3631 21.0 124.0 3.06 0.38 10.800000
## 3632 21.0 124.0 3.06 0.38 10.800000
## 3633 34.0 125.0 3.20 0.47 8.800000
## 3634 21.0 124.0 3.06 0.38 10.800000
## 3635 57.0 156.0 3.08 0.38 11.000000
## 3636 33.0 96.0 3.29 0.38 12.400000
## 3637 12.0 66.0 3.25 0.75 11.300000
## 3638 23.0 127.0 3.12 0.49 11.200000
## 3639 34.0 89.0 3.24 0.66 12.500000
## 3640 32.0 99.0 3.12 0.44 10.000000
## 3641 42.0 130.0 3.12 0.56 11.000000
## 3642 56.0 152.0 3.16 0.88 10.500000
## 3643 56.0 152.0 3.16 0.88 10.500000
## 3644 42.0 130.0 3.12 0.56 11.000000
## 3645 30.0 133.0 3.12 0.54 11.400000
## 3646 50.0 139.0 3.16 0.44 11.300000
## 3647 10.0 73.0 2.97 0.52 12.200000
## 3648 31.0 95.0 2.90 0.66 12.600000
## 3649 30.0 138.0 2.90 0.37 11.100000
## 3650 34.0 126.0 3.26 0.47 12.300000
## 3651 6.0 122.0 2.92 0.59 10.400000
## 3652 51.0 190.0 3.13 0.48 8.800000
## 3653 17.0 109.0 3.27 0.61 9.500000
## 3654 51.0 190.0 3.13 0.48 8.800000
## 3655 17.0 109.0 3.42 0.44 10.400000
## 3656 27.0 130.0 3.11 0.27 13.000000
## 3657 25.0 191.0 3.16 0.46 12.200000
## 3658 49.0 128.0 3.03 0.34 10.500000
## 3659 41.0 149.0 3.33 0.42 10.800000
## 3660 34.0 128.0 3.20 0.53 13.200000
## 3661 46.0 115.0 3.16 0.57 13.000000
## 3662 26.0 152.0 3.50 0.47 10.000000
## 3663 11.0 76.0 3.42 0.48 10.400000
## 3664 59.0 145.0 3.16 0.54 12.400000
## 3665 54.0 155.0 3.27 0.34 12.900000
## 3666 34.0 128.0 3.20 0.53 13.200000
## 3667 61.0 152.0 3.02 0.56 10.500000
## 3668 46.0 115.0 3.16 0.57 13.000000
## 3669 2.0 82.0 3.07 0.36 11.200000
## 3670 41.0 102.0 3.41 0.55 12.700000
## 3671 61.0 155.0 3.14 0.52 9.400000
## 3672 29.0 95.0 3.03 0.32 12.900000
## 3673 26.0 74.0 2.96 0.35 13.000000
## 3674 25.0 93.0 3.31 0.40 13.600000
## 3675 26.0 112.0 3.32 0.55 9.100000
## 3676 42.0 166.0 3.25 0.43 10.400000
## 3677 25.0 93.0 3.31 0.40 13.600000
## 3679 19.0 111.0 3.10 0.51 8.700000
## 3680 19.0 105.0 3.04 0.37 10.500000
## 3681 79.5 183.0 3.24 0.78 10.200000
## 3682 37.0 122.0 3.06 0.34 12.500000
## 3683 39.0 122.0 3.11 0.75 11.300000
## 3684 79.5 183.0 3.24 0.78 10.200000
## 3685 33.0 122.0 3.13 0.63 12.600000
## 3686 79.5 183.0 3.24 0.78 10.200000
## 3687 27.0 177.0 3.09 0.50 9.800000
## 3688 39.0 98.0 3.15 0.34 10.800000
## 3689 41.0 186.0 3.32 0.56 12.500000
## 3690 37.0 122.0 3.06 0.34 12.500000
## 3691 37.0 150.0 3.30 0.31 11.500000
## 3692 23.0 112.0 2.98 0.41 11.400000
## 3693 19.0 105.0 3.04 0.37 10.500000
## 3694 33.0 122.0 3.13 0.63 12.600000
## 3695 19.0 111.0 3.10 0.51 8.700000
## 3696 61.0 146.0 3.17 0.68 11.000000
## 3697 39.0 122.0 3.11 0.75 11.300000
## 3698 79.5 182.0 3.24 0.78 10.200000
## 3699 32.0 96.0 3.06 0.74 11.600000
## 3700 27.0 177.0 3.09 0.50 9.800000
## 3701 24.0 145.0 3.10 0.52 10.100000
## 3702 23.0 139.0 3.06 0.50 9.200000
## 3703 26.0 180.0 3.05 0.53 9.100000
## 3704 26.0 180.0 3.05 0.53 9.100000
## 3705 26.0 180.0 3.05 0.53 9.100000
## 3706 26.0 180.0 3.05 0.53 9.100000
## 3707 45.0 79.0 2.96 0.50 11.700000
## 3708 29.0 114.0 3.23 0.44 12.600000
## 3709 61.0 183.0 2.86 0.47 9.000000
## 3710 53.0 141.0 3.12 0.44 10.100000
## 3712 26.0 180.0 3.05 0.53 9.100000
## 3713 57.0 159.0 3.09 0.54 9.200000
## 3714 45.0 190.0 3.12 0.51 8.800000
## 3715 34.0 95.0 2.83 0.36 10.000000
## 3716 20.0 196.0 3.47 0.48 9.100000
## 3717 29.0 182.0 3.04 0.35 11.200000
## 3718 20.0 119.0 3.11 0.52 9.200000
## 3719 23.0 139.0 3.06 0.50 9.200000
## 3720 54.0 200.0 3.18 0.48 9.500000
## 3721 40.0 152.0 3.35 0.60 11.900000
## 3722 28.0 138.0 3.11 0.62 9.800000
## 3723 29.0 134.0 3.11 0.62 9.800000
## 3724 46.0 150.0 3.36 0.44 10.800000
## 3725 29.0 122.0 3.37 0.66 11.300000
## 3726 13.0 121.0 3.17 0.34 12.100000
## 3727 22.0 111.0 3.38 0.34 11.300000
## 3728 46.0 150.0 3.36 0.44 10.800000
## 3729 21.0 75.0 3.36 0.41 13.500000
## 3730 11.0 126.0 3.28 0.45 10.300000
## 3731 58.0 184.0 3.11 0.53 9.000000
## 3732 51.0 166.0 3.08 0.35 11.600000
## 3733 11.0 126.0 3.28 0.45 10.300000
## 3734 39.0 116.0 3.21 0.68 12.500000
## 3735 28.0 125.0 3.39 0.45 8.600000
## 3737 18.0 88.0 3.22 0.79 12.700000
## 3739 18.0 135.0 3.32 0.35 10.200000
## 3740 29.0 149.0 2.96 0.39 9.000000
## 3741 29.0 149.0 2.96 0.39 9.000000
## 3742 29.0 149.0 2.96 0.39 9.000000
## 3743 29.0 149.0 2.96 0.39 9.000000
## 3744 29.0 149.0 2.96 0.39 9.000000
## 3745 29.0 149.0 2.96 0.39 9.000000
## 3746 29.0 149.0 2.96 0.39 9.000000
## 3747 45.0 121.0 3.02 0.40 11.900000
## 3748 67.0 194.0 2.89 0.42 9.000000
## 3749 47.0 134.0 3.30 0.51 9.000000
## 3750 40.0 143.0 3.43 0.59 11.000000
## 3751 29.0 149.0 2.96 0.39 9.000000
## 3752 10.0 108.0 3.28 0.50 10.000000
## 3753 25.0 184.0 3.29 0.46 10.700000
## 3754 24.0 183.0 3.29 0.46 10.700000
## 3755 29.0 130.0 3.39 0.77 13.400000
## 3756 47.0 124.0 2.99 0.39 11.000000
## 3757 10.0 108.0 3.28 0.50 10.000000
## 3758 25.0 184.0 3.29 0.46 10.700000
## 3759 24.0 183.0 3.29 0.46 10.700000
## 3760 47.0 124.0 2.99 0.39 11.000000
## 3761 31.0 101.0 2.99 0.39 11.000000
## 3762 22.0 98.0 3.16 0.37 11.100000
## 3763 10.0 40.0 2.79 0.52 10.900000
## 3764 22.0 80.0 3.03 0.37 11.500000
## 3765 29.0 130.0 3.39 0.77 13.400000
## 3766 59.0 186.0 3.08 0.49 9.400000
## 3767 59.0 186.0 3.08 0.49 9.400000
## 3768 59.0 186.0 3.08 0.49 9.400000
## 3769 53.0 134.0 3.17 0.38 10.600000
## 3770 59.0 186.0 3.08 0.49 9.400000
## 3771 15.0 143.0 3.03 0.65 12.000000
## 3772 61.0 125.0 3.14 0.42 10.200000
## 3773 53.0 134.0 3.17 0.38 10.600000
## 3775 61.0 248.0 3.31 0.58 9.700000
## 3776 41.0 103.0 3.24 0.32 12.200000
## 3777 29.0 135.0 3.11 0.57 12.300000
## 3778 41.0 103.0 3.24 0.32 12.200000
## 3779 38.0 100.0 3.42 0.57 11.400000
## 3780 31.0 97.0 3.20 0.70 12.700000
## 3781 61.0 248.0 3.31 0.58 9.700000
## 3782 31.0 113.0 3.13 0.29 10.800000
## 3783 23.0 96.0 3.08 0.29 11.000000
## 3784 52.0 196.0 3.18 0.48 9.500000
## 3785 29.0 140.0 3.20 0.49 10.100000
## 3786 11.0 100.0 3.46 0.40 13.200000
## 3787 61.5 182.0 3.02 0.34 8.800000
## 3788 54.0 201.0 3.18 0.48 9.500000
## 3789 53.0 202.0 3.18 0.48 9.500000
## 3790 52.0 191.0 3.16 0.47 9.500000
## 3791 52.0 196.0 3.18 0.48 9.500000
## 3792 46.0 197.0 3.18 0.47 9.500000
## 3793 53.0 133.0 3.03 0.58 10.400000
## 3794 63.0 170.0 3.14 0.55 9.900000
## 3795 22.0 113.0 3.22 0.48 10.000000
## 3796 29.0 140.0 3.20 0.49 10.100000
## 3797 33.0 95.0 3.17 0.39 9.400000
## 3798 13.0 91.0 3.03 0.47 9.300000
## 3799 21.0 138.0 3.05 0.52 10.900000
## 3800 21.0 177.0 3.20 0.57 11.400000
## 3801 7.0 49.0 2.99 0.73 10.300000
## 3802 20.0 57.0 3.02 0.51 11.000000
## 3803 21.0 138.0 3.05 0.52 10.900000
## 3804 16.0 111.0 2.99 0.40 10.800000
## 3805 7.0 49.0 2.99 0.73 10.300000
## 3806 20.0 57.0 3.02 0.51 11.000000
## 3807 13.0 91.0 3.03 0.47 9.300000
## 3808 7.0 113.0 2.96 0.59 10.200000
## 3809 7.0 109.0 2.96 0.59 10.200000
## 3810 16.0 111.0 2.99 0.40 10.800000
## 3811 42.0 162.0 3.24 0.52 10.500000
## 3812 23.0 156.0 3.13 0.52 11.100000
## 3813 21.0 138.0 3.05 0.52 10.900000
## 3814 21.0 177.0 3.20 0.57 11.400000
## 3815 31.0 149.0 3.22 0.49 10.300000
## 3816 18.0 106.0 3.28 0.33 12.900000
## 3817 28.0 131.0 3.12 0.59 9.900000
## 3818 43.0 131.0 3.24 0.44 11.300000
## 3819 36.0 120.0 3.38 0.40 11.500000
## 3820 36.0 120.0 3.38 0.40 11.500000
## 3821 34.0 132.0 3.00 0.38 10.700000
## 3822 52.0 139.0 3.03 0.56 10.400000
## 3823 39.0 204.0 3.17 0.64 12.500000
## 3824 48.0 197.0 3.19 0.48 9.500000
## 3825 31.0 104.0 3.05 0.56 11.300000
## 3826 12.0 88.0 3.26 0.54 13.000000
## 3827 36.0 120.0 3.38 0.40 11.500000
## 3828 13.0 99.0 3.22 0.39 11.500000
## 3829 43.0 131.0 3.24 0.44 11.300000
## 3830 24.0 100.0 3.15 0.57 13.200000
## 3831 23.0 111.0 3.46 0.28 11.500000
## 3832 30.0 130.0 2.83 0.44 9.600000
## 3833 30.0 130.0 2.83 0.44 9.600000
## 3834 45.0 110.0 3.15 0.37 9.700000
## 3835 49.0 142.0 3.14 0.62 9.200000
## 3836 34.0 113.0 3.16 0.48 8.400000
## 3837 41.0 103.0 3.00 0.45 12.400000
## 3838 41.0 103.0 3.00 0.45 12.400000
## 3839 49.0 142.0 3.14 0.62 9.200000
## 3840 34.0 113.0 3.16 0.48 8.400000
## 3841 24.0 84.0 3.14 0.36 11.700000
## 3842 41.0 191.0 2.96 0.56 11.000000
## 3843 36.0 109.0 2.97 0.43 11.900000
## 3844 46.0 100.0 3.20 0.50 13.200000
## 3845 24.0 84.0 3.14 0.36 11.700000
## 3846 36.0 176.0 3.26 0.54 9.100000
## 3847 20.0 109.0 3.34 0.35 12.600000
## 3848 36.0 176.0 3.26 0.54 9.100000
## 3850 18.0 87.0 3.23 0.64 10.600000
## 3851 20.0 109.0 3.34 0.35 12.600000
## 3852 32.0 123.0 3.41 0.33 13.700000
## 3853 38.0 93.0 3.36 0.49 12.000000
## 3854 26.0 120.0 3.40 0.73 12.500000
## 3855 40.0 110.0 3.55 0.68 12.100000
## 3856 68.0 137.0 3.21 0.38 11.300000
## 3857 38.0 93.0 3.36 0.49 12.000000
## 3858 28.0 104.0 3.46 0.55 10.300000
## 3859 47.0 136.0 3.27 0.31 12.700000
## 3860 52.0 207.0 3.12 0.37 9.200000
## 3861 52.0 207.0 3.12 0.37 9.200000
## 3865 17.0 98.0 3.25 0.53 13.000000
## 3866 41.0 101.0 3.24 0.56 13.100000
## 3867 59.0 113.0 3.10 0.55 11.000000
## 3868 52.0 207.0 3.12 0.37 9.200000
## 3871 74.0 134.0 3.16 0.40 10.200000
## 3873 63.0 193.0 3.06 0.49 8.600000
## 3874 58.0 181.0 2.91 0.51 9.000000
## 3875 50.0 194.0 3.13 0.50 9.600000
## 3876 45.0 98.0 3.29 0.44 9.900000
## 3877 54.0 135.0 3.20 0.38 10.500000
## 3878 20.0 98.0 3.15 0.50 11.400000
## 3879 58.0 170.0 3.18 0.49 9.400000
## 3880 25.0 65.0 3.12 0.28 11.100000
## 3881 42.0 111.0 3.10 0.45 8.900000
## 3882 42.0 111.0 3.10 0.45 8.900000
## 3883 28.0 129.0 3.15 0.52 10.800000
## 3884 34.0 143.0 3.06 0.55 12.200000
## 3885 42.0 111.0 3.10 0.45 8.900000
## 3886 21.0 63.0 3.13 0.63 12.500000
## 3887 34.0 143.0 3.06 0.55 12.200000
## 3888 21.0 63.0 3.13 0.63 12.500000
## 3889 42.0 111.0 3.10 0.45 8.900000
## 3890 43.0 127.0 3.16 0.37 10.800000
## 3891 28.0 98.0 2.99 0.31 11.400000
## 3892 28.0 129.0 3.15 0.52 10.800000
## 3893 47.0 127.0 3.18 0.39 10.600000
## 3894 17.0 63.0 3.01 0.39 9.200000
## 3895 21.0 134.0 3.24 0.46 12.200000
## 3896 17.0 76.0 3.26 0.45 12.300000
## 3897 40.0 179.0 3.23 0.56 10.400000
## 3898 72.0 172.0 2.99 0.57 10.400000
## 3899 54.0 110.0 3.07 0.55 11.000000
## 3900 47.0 127.0 3.18 0.39 10.600000
## 3901 17.0 63.0 3.01 0.39 9.200000
## 3904 26.0 69.0 3.10 0.38 11.500000
## 3906 34.0 88.0 3.25 0.63 12.500000
## 3907 34.0 88.0 3.25 0.63 12.500000
## 3908 30.0 83.0 3.09 0.36 12.800000
## 3909 45.0 138.0 3.23 0.43 11.200000
## 3910 45.0 138.0 3.23 0.43 11.200000
## 3911 49.0 139.0 3.17 0.27 13.600000
## 3913 34.0 88.0 3.25 0.63 12.500000
## 3914 24.0 105.0 3.17 0.48 11.100000
## 3915 45.0 138.0 3.23 0.43 11.200000
## 3917 49.0 139.0 3.17 0.27 13.600000
## 3918 49.0 206.0 3.18 0.52 9.400000
## 3919 31.0 113.0 3.12 0.40 14.200000
## 3920 28.0 107.0 3.00 0.40 13.200000
## 3921 24.0 132.0 3.04 0.53 11.200000
## 3922 46.0 173.0 3.14 0.57 10.200000
## 3923 30.0 83.0 3.09 0.36 12.800000
## 3924 16.0 109.0 2.95 0.39 10.100000
## 3925 16.0 109.0 2.95 0.39 10.100000
## 3926 38.0 95.0 2.83 0.31 10.300000
## 3927 30.0 91.0 3.19 0.33 9.900000
## 3928 17.0 106.0 3.15 0.31 11.500000
## 3929 27.0 173.0 3.18 0.56 9.000000
## 3930 27.0 173.0 3.18 0.56 9.000000
## 3931 25.0 101.0 3.03 0.41 12.100000
## 3932 28.0 106.0 3.14 0.41 13.300000
## 3933 43.0 116.0 3.22 0.60 11.500000
## 3934 28.0 67.0 2.96 0.52 11.000000
## 3935 26.0 84.0 3.28 0.53 10.700000
## 3936 50.0 184.0 3.08 0.56 9.400000
## 3937 16.0 108.0 3.44 0.61 10.300000
## 3939 41.0 92.0 2.88 0.60 12.000000
## 3940 47.0 159.0 3.21 0.60 11.000000
## 3941 36.0 148.0 3.16 0.50 9.300000
## 3942 32.0 143.0 3.24 0.40 10.100000
## 3943 26.0 106.0 3.18 0.47 11.100000
## 3944 26.0 113.0 2.99 0.58 9.900000
## 3945 47.0 161.0 3.22 0.60 11.000000
## 3946 47.0 159.0 3.21 0.60 11.000000
## 3947 31.0 127.0 3.32 0.42 12.500000
## 3948 41.0 142.0 3.31 0.44 12.700000
## 3949 26.0 105.0 3.32 0.45 9.300000
## 3950 36.0 148.0 3.16 0.50 9.300000
## 3951 32.0 143.0 3.24 0.40 10.100000
## 3952 36.0 161.0 3.14 0.51 8.800000
## 3953 34.0 90.0 2.88 0.47 11.200000
## 3954 45.0 122.0 3.13 0.54 10.800000
## 3955 36.0 161.0 3.14 0.51 8.800000
## 3956 34.0 90.0 2.88 0.47 11.200000
## 3957 22.0 145.0 3.24 0.46 10.300000
## 3958 15.0 87.0 3.11 0.48 12.000000
## 3959 36.0 110.0 3.26 0.41 9.500000
## 3960 36.0 110.0 3.26 0.41 9.500000
## 3961 54.0 159.0 3.14 0.54 9.800000
## 3962 55.0 170.0 2.91 0.51 9.000000
## 3963 40.0 118.0 3.17 0.53 13.000000
## 3964 13.0 116.0 3.39 0.44 11.800000
## 3965 61.0 176.5 2.97 0.52 8.800000
## 3966 18.0 102.0 3.10 0.55 11.200000
## 3967 36.0 110.0 3.26 0.41 9.500000
## 3968 35.0 200.0 3.16 0.54 9.400000
## 3969 35.0 192.0 3.16 0.51 9.500000
## 3970 33.0 125.0 3.03 0.49 10.400000
## 3971 42.0 143.0 3.08 0.49 9.800000
## 3972 33.0 125.0 3.03 0.49 10.400000
## 3974 35.0 200.0 3.16 0.54 9.400000
## 3975 35.0 192.0 3.16 0.51 9.500000
## 3976 61.0 134.0 3.19 0.81 11.900000
## 3977 35.0 124.0 3.15 0.65 12.800000
## 3978 18.0 117.0 3.09 0.38 13.000000
## 3979 41.0 192.0 3.26 0.59 10.400000
## 3980 41.0 193.0 3.25 0.59 10.400000
## 3981 54.0 135.0 3.21 0.40 10.700000
## 3983 61.0 134.0 3.19 0.81 11.900000
## 3984 31.0 101.0 3.19 0.42 10.400000
## 3985 35.0 124.0 3.15 0.65 12.800000
## 3986 45.0 104.0 3.20 0.37 9.900000
## 3987 45.0 104.0 3.20 0.37 9.900000
## 3988 73.0 223.0 3.16 0.71 9.400000
## 3989 46.0 129.0 3.30 0.43 11.400000
## 3990 45.0 104.0 3.20 0.37 9.900000
## 3991 73.0 223.0 3.16 0.71 9.400000
## 3992 36.0 104.0 2.99 0.39 9.200000
## 3993 26.0 76.0 2.90 0.57 10.500000
## 3994 32.0 111.0 3.25 0.54 11.000000
## 3995 32.0 111.0 3.25 0.54 11.000000
## 3996 3.0 127.0 2.90 0.72 12.100000
## 3997 32.0 111.0 3.25 0.54 11.000000
## 3998 37.0 144.0 3.22 0.39 12.800000
## 4002 21.0 122.0 3.00 0.40 9.500000
## 4003 25.0 94.0 3.07 0.45 9.200000
## 4004 40.0 117.0 3.07 0.72 11.100000
## 4005 33.0 112.0 3.06 0.50 12.300000
## 4006 40.0 117.0 3.07 0.72 11.100000
## 4007 10.0 51.0 3.04 0.58 12.600000
## 4008 21.0 122.0 3.00 0.40 9.500000
## 4009 25.0 94.0 3.07 0.45 9.200000
## 4010 40.0 152.0 3.20 0.57 10.800000
## 4011 39.0 122.0 3.00 0.60 11.300000
## 4012 37.0 144.0 3.22 0.39 12.800000
## 4014 56.0 171.0 3.08 0.56 9.800000
## 4015 56.0 183.0 2.98 0.61 8.500000
## 4016 6.0 97.0 3.16 0.50 9.300000
## 4017 45.0 151.0 3.20 0.52 9.200000
## 4018 32.0 115.0 3.21 0.51 11.400000
## 4019 56.0 183.0 2.98 0.61 8.500000
## 4020 6.0 97.0 3.16 0.50 9.300000
## 4021 6.0 91.0 3.06 0.46 8.400000
## 4022 35.0 100.0 3.04 0.40 9.200000
## 4023 45.0 151.0 3.20 0.52 9.200000
## 4024 52.0 151.0 3.18 0.79 10.400000
## 4025 50.0 147.0 3.27 0.56 11.600000
## 4026 37.0 94.0 3.25 0.60 12.400000
## 4027 52.0 151.0 3.18 0.79 10.400000
## 4028 22.0 176.0 3.09 0.54 9.300000
## 4029 37.0 81.0 3.20 0.46 12.200000
## 4030 33.0 139.0 3.22 0.46 11.000000
## 4031 30.0 105.0 3.11 0.38 11.400000
## 4032 15.0 120.0 3.06 0.41 9.500000
## 4033 16.0 116.0 3.07 0.53 9.200000
## 4034 23.0 125.0 3.13 0.62 11.100000
## 4035 16.0 116.0 3.07 0.53 9.200000
## 4036 53.0 172.0 3.24 0.58 11.000000
## 4037 40.0 177.0 3.14 0.48 9.900000
## 4038 43.0 176.0 3.14 0.46 9.900000
## 4039 15.0 120.0 3.06 0.41 9.500000
## 4041 48.0 185.0 3.21 0.50 9.400000
## 4042 45.0 149.0 3.23 0.52 9.300000
## 4043 25.0 135.0 2.90 0.43 8.700000
## 4044 25.0 135.0 2.90 0.43 8.700000
## 4045 25.0 135.0 2.90 0.43 8.700000
## 4046 25.0 135.0 2.90 0.43 8.700000
## 4047 33.0 154.0 2.94 0.43 9.000000
## 4048 49.0 118.0 3.00 0.63 10.700000
## 4049 49.0 118.0 3.00 0.63 10.700000
## 4050 32.0 98.0 3.02 0.58 11.300000
## 4051 25.0 135.0 2.90 0.43 8.700000
## 4052 22.0 97.0 2.96 0.38 11.700000
## 4053 45.0 149.0 3.23 0.52 9.300000
## 4054 25.0 135.0 2.90 0.43 8.700000
## 4055 33.0 154.0 2.94 0.43 9.000000
## 4056 22.0 97.0 2.96 0.38 11.700000
## 4057 25.0 131.0 3.23 0.51 10.700000
## 4058 38.0 110.0 3.05 0.54 11.400000
## 4059 49.0 118.0 3.00 0.63 10.700000
## 4060 32.0 98.0 3.02 0.58 11.300000
## 4061 20.0 70.0 3.19 0.42 10.000000
## 4062 20.0 70.0 3.19 0.42 10.000000
## 4063 27.0 119.0 3.15 0.49 11.200000
## 4064 44.0 130.0 3.07 0.41 9.700000
## 4065 23.0 85.0 3.42 0.42 12.500000
## 4067 60.0 160.0 3.16 0.36 11.800000
## 4068 22.0 166.0 3.16 0.72 10.600000
## 4069 60.0 160.0 3.16 0.36 11.800000
## 4070 54.0 133.0 3.19 0.37 10.700000
## 4071 41.0 162.0 3.21 0.51 9.900000
## 4072 23.0 76.0 2.96 0.46 12.000000
## 4073 70.5 163.0 3.15 0.82 10.400000
## 4074 11.0 107.0 3.19 0.39 8.500000
## 4075 15.0 82.0 3.13 0.38 9.900000
## 4076 52.5 120.0 3.08 0.45 9.400000
## 4077 33.0 134.0 3.13 0.46 10.400000
## 4078 21.0 108.0 3.30 0.59 11.000000
## 4079 21.0 110.0 3.30 0.57 11.000000
## 4080 27.0 91.0 3.19 0.38 10.400000
## 4081 58.0 116.0 3.10 0.50 9.800000
## 4082 52.5 106.0 3.08 0.45 9.400000
## 4083 37.0 142.0 3.23 0.53 10.600000
## 4084 32.0 185.0 3.28 0.44 10.100000
## 4085 20.0 96.0 3.06 0.30 11.500000
## 4086 14.0 73.0 3.06 0.45 11.400000
## 4087 30.0 93.0 3.03 0.38 9.200000
## 4088 33.0 101.0 3.12 0.38 9.700000
## 4089 16.0 79.0 3.07 0.46 11.300000
## 4090 36.0 127.0 3.15 0.49 9.600000
## 4091 44.0 179.0 2.86 0.46 8.900000
## 4092 21.0 82.0 3.26 0.36 10.000000
## 4093 19.0 112.0 3.18 0.40 9.200000
## 4094 20.0 103.0 3.08 0.41 9.000000
## 4095 29.0 98.0 3.09 0.58 12.800000
## 4096 20.0 103.0 3.08 0.41 9.000000
## 4097 13.0 136.0 3.08 0.55 9.500000
## 4098 21.0 82.0 3.26 0.36 10.000000
## 4099 30.0 140.0 3.22 0.38 11.000000
## 4100 19.0 112.0 3.18 0.40 9.200000
## 4101 24.0 99.0 3.08 0.38 10.600000
## 4102 54.0 166.0 3.23 0.42 10.000000
## 4103 54.0 166.0 3.23 0.42 10.000000
## 4104 22.0 86.0 3.31 0.38 11.700000
## 4105 17.0 80.0 3.12 0.36 12.500000
## 4106 36.0 122.0 3.07 0.47 11.100000
## 4107 46.0 141.0 3.16 0.62 9.700000
## 4109 43.0 105.0 3.18 0.38 12.200000
## 4110 46.0 153.0 3.75 0.76 11.300000
## 4111 23.0 193.0 3.22 0.38 11.600000
## 4112 18.0 75.0 3.31 0.56 11.300000
## 4113 30.0 95.0 3.27 0.56 11.100000
## 4114 32.0 92.0 3.26 0.57 11.200000
## 4115 35.0 107.0 3.15 0.45 11.300000
## 4116 29.0 94.0 3.07 0.45 12.000000
## 4117 33.0 158.0 3.15 0.50 8.800000
## 4118 33.0 158.0 3.15 0.50 8.800000
## 4119 19.0 143.0 3.15 0.34 12.000000
## 4120 22.0 147.0 3.15 0.31 12.000000
## 4121 48.0 122.0 3.01 0.44 9.000000
## 4122 42.0 151.0 3.12 0.60 9.300000
## 4123 33.0 171.0 3.14 0.56 8.700000
## 4124 13.0 75.0 3.10 0.63 12.800000
## 4125 23.0 72.0 3.10 0.50 11.500000
## 4126 44.0 147.0 3.08 0.54 10.000000
## 4127 45.0 147.0 3.09 0.54 10.000000
## 4128 51.0 215.0 3.33 0.56 10.300000
## 4129 62.0 227.0 3.25 0.56 10.400000
## 4130 18.0 68.0 3.22 0.29 13.400000
## 4131 18.0 130.0 3.05 0.62 11.200000
## 4132 47.0 206.0 3.26 0.36 9.100000
## 4133 47.0 206.0 3.26 0.36 9.100000
## 4134 24.0 120.0 3.33 0.31 10.800000
## 4135 26.0 89.0 3.24 0.34 12.500000
## 4136 27.0 132.0 3.63 0.73 11.300000
## 4138 47.0 206.0 3.26 0.36 9.100000
## 4139 8.0 72.0 3.22 0.39 12.700000
## 4140 53.0 143.0 3.10 0.54 11.000000
## 4141 51.0 149.0 3.02 0.58 10.400000
## 4142 51.0 149.0 3.02 0.58 10.400000
## 4143 43.0 136.0 3.25 0.53 10.700000
## 4144 56.0 131.0 3.22 0.35 10.900000
## 4145 51.0 149.0 3.02 0.58 10.400000
## 4146 54.0 160.0 3.03 0.58 10.400000
## 4147 56.0 115.5 3.16 0.41 9.700000
## 4148 53.0 143.0 3.10 0.54 11.000000
## 4149 8.0 120.0 3.19 0.53 9.600000
## 4150 40.0 76.0 3.10 0.29 13.900000
## 4151 6.0 194.0 3.07 0.61 9.400000
## 4152 29.0 193.0 3.10 0.67 12.500000
## 4153 8.0 120.0 3.19 0.53 9.600000
## 4154 50.0 187.0 3.19 0.45 9.500000
## 4155 61.0 186.0 3.19 0.45 9.600000
## 4156 50.0 187.0 3.19 0.45 9.500000
## 4157 63.0 186.0 3.18 0.44 9.600000
## 4158 33.0 168.0 2.90 0.44 8.700000
## 4159 33.0 168.0 2.90 0.44 8.700000
## 4160 33.0 168.0 2.90 0.44 8.700000
## 4161 33.0 168.0 2.90 0.44 8.700000
## 4162 33.0 168.0 2.90 0.44 8.700000
## 4163 33.0 168.0 2.90 0.44 8.700000
## 4164 12.0 120.0 3.18 0.46 10.400000
## 4165 13.0 119.0 3.22 0.50 10.700000
## 4166 23.0 83.0 3.17 0.48 12.000000
## 4167 35.0 158.0 3.19 0.37 12.100000
## 4168 39.0 118.0 3.31 0.40 13.100000
## 4169 30.0 104.0 3.32 0.41 12.400000
## 4170 45.0 123.0 3.24 0.36 12.600000
## 4171 33.0 168.0 2.90 0.44 8.700000
## 4172 31.0 101.0 3.15 0.66 12.000000
## 4173 14.0 169.0 3.27 0.57 11.600000
## 4175 65.0 179.0 3.06 0.58 9.300000
## 4176 25.0 157.0 3.20 0.54 11.100000
## 4177 68.0 161.0 3.10 0.69 10.200000
## 4178 35.0 113.0 3.23 0.66 10.600000
## 4179 49.0 133.0 3.16 0.42 11.300000
## 4180 81.0 198.0 3.20 0.69 9.400000
## 4181 31.0 123.0 3.09 0.50 9.300000
## 4182 15.0 68.0 2.96 0.52 11.100000
## 4183 15.0 170.0 3.13 0.65 9.900000
## 4184 29.0 82.0 3.31 0.61 11.800000
## 4185 24.0 81.0 3.26 0.64 12.600000
## 4186 81.0 198.0 3.20 0.69 9.400000
## 4187 23.0 72.0 3.06 0.68 10.500000
## 4188 40.0 108.0 3.19 0.50 12.300000
## 4189 25.0 119.0 3.32 0.62 11.300000
## 4190 21.0 105.0 3.07 0.46 9.600000
## 4191 14.0 63.0 3.20 0.33 12.000000
## 4192 36.0 140.0 3.09 0.45 11.200000
## 4193 28.0 100.0 3.12 0.33 10.200000
## 4194 26.0 100.0 2.98 0.44 12.400000
## 4195 28.0 100.0 3.12 0.33 10.200000
## 4196 24.0 87.0 2.94 0.38 13.400000
## 4197 25.0 68.0 3.24 0.35 12.600000
## 4198 34.0 149.0 3.18 0.53 9.800000
## 4199 63.0 139.0 2.94 0.45 9.100000
## 4200 26.0 100.0 2.98 0.44 12.400000
## 4201 28.0 101.0 3.03 0.43 12.500000
## 4202 25.0 85.0 3.05 0.34 11.700000
## 4203 37.0 113.0 3.29 0.46 12.900000
## 4204 27.0 183.0 3.30 0.43 10.100000
## 4205 33.0 139.0 3.06 0.50 10.300000
## 4206 25.0 85.0 3.05 0.34 11.700000
## 4207 29.0 144.0 3.24 0.41 10.300000
## 4208 42.0 107.0 3.34 0.56 10.800000
## 4209 19.0 89.0 3.25 0.51 11.200000
## 4210 26.0 102.0 3.29 0.60 11.800000
## 4211 26.0 134.0 3.08 0.54 9.800000
## 4212 32.0 193.0 3.04 0.49 10.000000
## 4213 13.0 164.0 3.24 0.39 8.800000
## 4214 5.0 69.0 3.14 0.52 10.100000
## 4215 68.0 210.0 3.05 0.50 9.500000
## 4216 68.0 210.0 3.05 0.50 9.500000
## 4217 68.0 210.0 3.05 0.50 9.500000
## 4218 27.0 113.0 3.07 0.34 9.200000
## 4219 31.0 180.0 2.92 0.74 12.200000
## 4220 68.0 210.0 3.05 0.50 9.500000
## 4221 29.0 92.0 3.22 0.53 11.300000
## 4222 44.0 129.0 3.26 0.29 12.100000
## 4223 27.0 113.0 3.07 0.34 9.200000
## 4224 6.0 51.0 3.51 0.48 11.200000
## 4225 26.0 87.0 3.29 0.44 12.500000
## 4226 38.0 187.0 3.31 0.56 10.600000
## 4227 66.0 171.0 3.25 0.61 10.400000
## 4228 16.0 93.0 3.44 0.53 10.100000
## 4229 33.0 201.0 3.11 0.56 9.900000
## 4230 11.0 133.0 2.97 0.68 11.000000
## 4231 10.0 122.0 2.94 0.63 10.000000
## 4232 29.0 89.0 3.14 0.42 12.700000
## 4233 10.0 92.0 3.07 0.35 12.100000
## 4234 23.0 118.0 3.23 0.46 10.400000
## 4235 23.0 120.0 3.24 0.47 10.400000
## 4236 21.0 116.0 3.14 0.50 9.200000
## 4237 21.0 116.0 3.14 0.50 9.200000
## 4238 27.0 80.0 3.05 0.68 10.500000
## 4239 21.0 116.0 3.14 0.50 9.200000
## 4241 47.0 130.0 3.08 0.40 10.100000
## 4242 62.0 140.0 3.10 0.59 11.100000
## 4243 69.0 144.0 3.13 0.74 10.800000
## 4244 23.5 72.0 3.16 0.47 11.800000
## 4245 44.0 116.0 3.04 0.48 9.200000
## 4246 42.0 116.0 3.04 0.50 9.200000
## 4247 21.0 95.0 3.07 0.54 12.300000
## 4248 26.0 124.0 3.09 0.56 10.100000
## 4249 26.0 114.0 3.25 0.45 11.400000
## 4250 39.0 161.0 3.19 0.43 10.400000
## 4251 44.0 95.0 3.20 0.35 9.800000
## 4252 29.0 91.0 3.30 0.43 9.900000
## 4253 44.0 95.0 3.20 0.35 9.800000
## 4254 11.0 74.0 3.48 0.54 11.200000
## 4255 25.0 115.0 3.15 0.46 10.900000
## 4256 16.0 119.0 3.15 0.41 9.200000
## 4257 16.0 119.0 3.15 0.41 9.200000
## 4258 39.0 121.0 2.96 0.35 12.000000
## 4259 37.0 121.0 2.96 0.34 12.100000
## 4261 44.0 145.0 3.22 0.40 11.200000
## 4262 19.0 120.0 3.32 0.41 12.700000
## 4263 23.0 169.0 3.26 0.47 12.200000
## 4264 19.0 164.0 3.26 0.46 12.200000
## 4265 44.0 99.0 3.23 0.37 12.200000
## 4266 44.0 145.0 3.22 0.40 11.200000
## 4267 19.0 120.0 3.32 0.41 12.700000
## 4268 20.0 117.0 3.31 0.41 12.700000
## 4269 27.0 146.0 3.17 0.36 12.100000
## 4270 44.0 192.0 3.11 0.53 9.400000
## 4271 64.0 174.0 3.07 0.50 10.100000
## 4272 57.0 201.0 3.08 0.54 9.400000
## 4273 41.0 113.0 3.22 0.46 8.900000
## 4274 41.0 113.0 3.22 0.46 8.900000
## 4275 41.0 113.0 3.22 0.46 8.900000
## 4276 41.0 113.0 3.22 0.46 8.900000
## 4277 27.0 117.0 3.56 0.45 13.000000
## 4278 37.0 183.0 3.08 0.50 10.300000
## 4279 5.0 47.0 3.07 0.45 10.100000
## 4280 48.0 129.0 3.23 0.38 10.500000
## 4281 41.0 113.0 3.22 0.46 8.900000
## 4282 23.0 124.0 3.30 0.50 10.100000
## 4283 23.0 124.0 3.30 0.50 10.100000
## 4284 22.0 93.0 3.15 0.42 11.000000
## 4285 22.0 93.0 3.15 0.42 11.000000
## 4286 22.0 93.0 3.15 0.42 11.000000
## 4287 22.0 93.0 3.15 0.42 11.000000
## 4288 28.0 117.0 3.08 0.43 10.000000
## 4289 25.0 76.0 2.88 0.54 10.500000
## 4290 28.0 112.0 2.87 0.49 9.700000
## 4291 23.0 124.0 3.30 0.50 10.100000
## 4292 68.0 183.0 3.25 0.76 9.400000
## 4293 20.0 119.0 3.17 0.55 11.200000
## 4294 68.0 183.0 3.25 0.76 9.400000
## 4295 22.0 121.0 3.10 0.55 10.800000
## 4296 68.0 183.0 3.25 0.76 9.400000
## 4297 20.0 119.0 3.17 0.55 11.200000
## 4298 31.0 103.0 3.13 0.49 11.000000
## 4299 13.0 111.0 3.44 0.46 12.400000
## 4302 22.0 155.0 3.01 0.58 9.500000
## 4303 25.0 204.0 3.05 0.52 10.000000
## 4304 33.0 114.0 3.16 0.31 12.500000
## 4305 24.0 115.0 3.39 0.59 10.900000
## 4306 21.0 113.0 3.38 0.58 10.500000
## 4307 51.0 133.0 3.22 0.37 10.800000
## 4308 36.0 116.0 3.38 0.57 11.000000
## 4309 16.0 87.0 3.33 0.61 11.800000
## 4310 16.0 121.0 3.36 0.71 12.600000
## 4311 59.0 140.0 3.17 0.39 10.200000
## 4312 33.0 103.0 3.12 0.31 12.000000
## 4313 33.0 114.0 3.16 0.31 12.500000
## 4314 19.0 86.0 3.32 0.65 11.500000
## 4315 23.0 117.0 3.20 0.39 11.940000
## 4316 33.0 115.0 3.12 0.44 12.893333
## 4317 17.0 94.0 3.13 0.40 9.400000
## 4318 58.0 138.0 3.00 0.47 12.200000
## 4319 23.0 117.0 3.20 0.39 11.940000
## 4320 33.0 115.0 3.12 0.44 12.893333
## 4321 45.0 191.0 3.16 0.50 9.500000
## 4322 27.0 150.0 3.00 0.33 10.600000
## 4323 47.0 121.0 3.04 0.68 10.500000
## 4324 36.0 129.0 2.89 0.30 11.466667
## 4325 45.0 100.0 3.40 0.41 11.400000
## 4326 47.0 182.0 3.12 0.50 9.500000
## 4327 44.0 168.0 3.11 0.52 9.200000
## 4328 47.0 182.0 3.12 0.50 9.500000
## 4329 28.0 145.0 3.23 0.53 10.980000
## 4330 47.0 181.0 3.12 0.49 9.400000
## 4331 47.0 182.0 3.12 0.50 9.500000
## 4332 44.0 168.0 3.11 0.52 9.200000
## 4333 45.0 155.0 2.94 0.41 8.800000
## 4334 45.0 155.0 2.94 0.41 8.800000
## 4335 45.0 155.0 2.94 0.41 8.800000
## 4336 45.0 155.0 2.94 0.41 8.800000
## 4337 45.0 155.0 2.94 0.41 8.800000
## 4338 45.0 155.0 2.94 0.41 8.800000
## 4339 45.0 155.0 2.94 0.41 8.800000
## 4340 15.0 96.0 3.23 0.64 10.400000
## 4341 45.0 155.0 2.94 0.41 8.800000
## 4342 36.0 139.0 3.04 0.62 10.033333
## 4343 39.0 141.0 3.44 0.69 11.300000
## 4344 21.0 109.0 3.37 0.58 10.400000
## 4346 21.0 107.0 3.11 0.54 11.100000
## 4348 62.0 148.0 3.03 0.56 11.300000
## 4349 61.0 148.0 2.98 0.47 9.100000
## 4350 43.0 187.0 2.96 0.57 9.400000
## 4351 14.0 73.0 2.82 0.59 13.200000
## 4352 34.0 137.0 3.22 0.38 12.700000
## 4353 31.0 148.0 3.18 0.47 10.700000
## 4354 34.0 166.0 3.11 0.42 11.433333
## 4355 48.0 169.0 3.27 0.45 11.100000
## 4356 34.0 137.0 3.22 0.38 12.700000
## 4357 35.0 178.0 3.25 0.51 10.533333
## 4358 50.0 194.0 3.31 0.52 11.600000
## 4359 44.0 179.0 3.18 0.48 9.533333
## 4360 52.0 203.0 3.17 0.44 9.800000
## 4361 31.0 148.0 3.18 0.47 10.700000
## 4362 36.0 110.0 3.22 0.65 12.000000
## 4363 30.0 123.0 3.12 0.37 12.800000
## 4364 32.0 136.0 3.14 0.40 9.500000
## 4365 36.0 119.0 2.99 0.34 10.933333
## 4366 63.0 133.0 2.86 0.41 9.100000
## 4367 16.0 117.0 3.26 0.42 12.600000
## 4368 32.0 136.0 3.14 0.40 9.500000
## 4369 29.0 109.0 2.98 0.30 10.900000
## 4370 36.0 119.0 2.99 0.34 10.933333
## 4371 16.0 115.0 3.02 0.44 9.600000
## 4372 16.0 92.0 3.18 0.56 9.300000
## 4373 23.0 112.0 3.05 0.37 11.366667
## 4374 24.0 98.0 3.14 0.44 12.500000
## 4375 46.0 171.0 3.16 0.50 9.500000
## 4376 40.0 186.0 3.22 0.54 11.000000
## 4377 17.0 133.0 3.02 0.53 9.400000
## 4378 32.0 76.0 3.21 0.76 11.333333
## 4379 9.0 126.0 2.94 0.51 8.800000
## 4380 17.0 133.0 3.02 0.53 9.400000
## 4381 33.0 143.0 3.31 0.50 11.066667
## 4382 27.0 151.0 3.22 0.49 12.200000
## 4383 31.0 110.0 3.20 0.53 11.000000
## 4384 32.0 76.0 3.21 0.76 11.333333
## 4385 51.0 182.0 3.23 0.48 9.500000
## 4386 51.0 182.0 3.23 0.48 9.500000
## 4387 54.0 170.0 3.28 0.52 11.000000
## 4388 34.0 97.0 3.11 0.75 11.200000
## 4389 28.0 100.0 3.08 0.36 9.300000
## 4390 30.0 111.0 3.05 0.31 10.800000
## 4391 39.0 167.0 3.14 0.51 9.200000
## 4392 70.0 203.0 3.25 0.77 9.400000
## 4393 39.0 167.0 3.14 0.51 9.200000
## 4394 53.0 139.0 3.25 0.35 10.500000
## 4395 60.0 143.0 3.26 0.35 10.800000
## 4396 35.0 146.0 3.10 0.67 9.400000
## 4397 55.0 173.0 3.11 0.60 9.800000
## 4398 55.0 173.0 3.11 0.60 9.800000
## 4399 55.0 173.0 3.11 0.60 9.800000
## 4400 35.0 146.0 3.10 0.67 9.400000
## 4401 55.0 173.0 3.11 0.60 9.800000
## 4403 40.0 176.0 3.17 0.41 12.300000
## 4404 41.0 187.0 3.19 0.42 9.733333
## 4405 48.0 197.0 3.21 0.36 9.400000
## 4406 48.0 197.0 3.21 0.36 9.400000
## 4407 32.0 140.0 3.17 0.36 12.800000
## 4408 18.0 80.0 2.92 0.47 11.050000
## 4409 48.0 197.0 3.21 0.36 9.400000
## 4410 32.0 140.0 3.17 0.36 12.800000
## 4411 35.0 182.0 3.11 0.46 9.733333
## 4412 22.0 86.0 3.23 0.58 13.100000
## 4413 26.0 114.0 3.04 0.52 11.500000
## 4414 22.0 86.0 3.23 0.58 13.100000
## 4415 26.0 114.0 3.04 0.52 11.500000
## 4416 26.0 141.0 3.08 0.50 9.100000
## 4417 35.0 182.0 3.11 0.46 9.750000
## 4418 24.0 125.0 3.19 0.48 10.500000
## 4419 37.0 118.0 3.08 0.46 8.800000
## 4420 37.0 118.0 3.08 0.46 8.800000
## 4421 37.0 118.0 3.08 0.46 8.800000
## 4422 37.0 118.0 3.08 0.46 8.800000
## 4423 24.0 125.0 3.19 0.48 10.500000
## 4424 24.0 125.0 3.19 0.48 10.500000
## 4425 37.0 118.0 3.08 0.46 8.800000
## 4426 30.0 122.0 3.22 0.49 9.900000
## 4427 28.0 123.0 3.22 0.49 9.900000
## 4428 24.0 205.0 3.11 0.58 9.900000
## 4429 33.0 166.0 3.20 0.42 12.200000
## 4430 59.5 162.0 3.27 0.47 10.800000
## 4431 60.0 134.0 2.96 0.39 8.700000
## 4432 17.0 67.0 3.21 0.47 13.200000
## 4433 15.0 94.0 3.15 0.38 12.700000
## 4434 55.0 193.0 3.21 0.44 9.400000
## 4435 18.0 161.0 3.25 0.53 11.200000
## 4436 25.0 166.0 3.24 0.56 11.333333
## 4437 14.0 92.0 3.36 0.58 11.900000
## 4438 25.0 166.0 3.24 0.56 11.350000
## 4439 51.0 131.0 3.22 0.39 10.500000
## 4440 14.0 125.0 3.09 0.49 9.800000
## 4441 20.0 146.0 3.06 0.54 9.100000
## 4442 36.0 111.0 3.16 0.37 12.400000
## 4443 20.0 146.0 3.06 0.54 9.100000
## 4444 14.0 125.0 3.09 0.49 9.800000
## 4445 24.0 116.0 3.39 0.40 11.300000
## 4446 24.0 116.0 3.39 0.40 11.300000
## 4447 31.0 111.0 3.48 0.34 13.100000
## 4448 15.0 101.0 3.04 0.37 12.500000
## 4449 32.0 122.0 3.18 0.54 10.300000
## 4450 51.0 150.0 3.23 0.43 10.700000
## 4451 29.0 136.0 3.05 0.65 10.400000
## 4452 47.0 184.0 3.22 0.48 9.500000
## 4453 53.0 173.0 3.24 0.45 9.800000
## 4454 15.0 101.0 3.04 0.37 12.500000
## 4455 17.0 149.0 3.00 0.43 9.400000
## 4456 36.0 174.0 3.14 0.50 9.000000
## 4457 36.0 174.0 3.14 0.50 9.000000
## 4458 36.0 174.0 3.14 0.50 9.000000
## 4459 19.0 129.0 3.24 0.48 13.000000
## 4460 28.0 120.0 3.27 0.50 9.900000
## 4461 17.0 149.0 3.00 0.43 9.400000
## 4462 29.0 157.0 3.27 0.56 10.600000
## 4463 28.0 109.0 3.23 0.47 13.400000
## 4464 31.0 114.0 3.12 0.35 12.500000
## 4465 32.0 141.0 3.11 0.49 9.300000
## 4466 32.0 141.0 3.11 0.49 9.300000
## 4467 34.0 149.0 3.36 0.52 11.000000
## 4468 40.0 158.0 3.20 0.48 10.300000
## 4469 31.0 95.0 3.24 0.57 11.300000
## 4470 35.0 100.0 3.03 0.63 10.900000
## 4471 35.0 90.0 3.76 0.49 11.300000
## 4472 24.0 78.0 3.36 0.47 12.100000
## 4473 12.0 83.0 3.18 0.65 11.100000
## 4475 50.0 125.0 3.20 0.45 10.100000
## 4476 37.0 110.0 3.26 0.58 12.400000
## 4477 37.0 104.0 3.11 0.52 12.700000
## 4478 53.0 180.0 3.14 0.50 9.600000
## 4479 53.0 180.0 3.14 0.50 9.600000
## 4480 17.0 126.0 3.24 0.46 9.100000
## 4482 53.0 180.0 3.14 0.50 9.600000
## 4483 37.0 155.0 3.18 0.37 12.400000
## 4484 7.0 108.0 3.23 0.58 9.550000
## 4485 17.0 126.0 3.24 0.46 9.100000
## 4486 12.0 74.0 3.29 0.65 12.500000
## 4487 13.0 68.0 3.16 0.40 9.900000
## 4488 32.0 87.0 3.47 0.52 11.200000
## 4489 28.0 122.0 3.13 0.40 13.000000
## 4490 28.0 122.0 3.13 0.40 13.000000
## 4491 25.0 116.0 3.20 0.44 11.700000
## 4492 13.0 95.0 2.97 0.70 13.100000
## 4493 17.0 50.0 3.08 0.66 12.000000
## 4494 30.0 165.0 3.36 0.55 10.550000
## 4495 34.0 84.0 3.04 0.39 11.450000
## 4496 71.0 194.0 3.18 0.64 10.200000
## 4497 34.0 84.0 3.04 0.39 11.450000
## 4499 22.0 106.0 3.09 0.54 10.800000
## 4500 20.0 103.0 3.27 0.45 12.200000
## 4501 36.0 175.0 3.20 0.55 11.000000
## 4502 41.0 182.0 3.35 0.54 10.400000
## 4503 32.0 156.0 3.14 0.51 11.400000
## 4505 20.0 138.0 3.03 0.42 10.700000
## 4506 50.0 162.0 3.15 0.52 10.200000
## 4507 38.0 100.0 3.22 0.69 11.200000
## 4508 17.0 73.0 3.40 0.51 12.333333
## 4509 75.0 129.0 3.20 0.38 11.500000
## 4510 14.0 100.0 3.07 0.55 9.500000
## 4511 35.0 147.0 3.24 0.56 13.400000
## 4512 24.0 110.0 3.36 0.40 12.500000
## 4513 24.0 110.0 3.36 0.40 12.500000
## 4514 27.0 97.0 3.12 0.42 11.200000
## 4515 28.5 259.0 3.19 0.50 8.800000
## 4516 50.0 118.0 3.06 0.59 11.200000
## 4517 15.0 70.0 3.16 0.48 12.700000
## 4518 26.0 82.0 3.00 0.38 9.800000
## 4519 10.0 40.0 3.14 0.36 9.800000
## 4521 55.0 230.0 3.19 0.46 9.800000
## 4522 48.0 191.0 3.17 0.51 9.600000
## 4523 10.0 40.0 3.14 0.36 9.800000
## 4524 79.0 149.0 3.12 0.37 9.700000
## 4525 59.5 137.0 3.16 0.38 10.000000
## 4527 42.0 206.0 3.32 0.38 12.300000
## 4528 26.0 82.0 3.00 0.38 9.800000
## 4529 18.0 101.0 3.03 0.38 9.000000
## 4530 60.5 164.5 3.06 0.45 9.100000
## 4531 62.0 162.5 3.06 0.45 9.100000
## 4532 62.0 162.5 3.06 0.45 9.100000
## 4533 35.0 121.0 3.32 0.33 11.400000
## 4534 41.0 124.0 3.14 0.35 10.500000
## 4535 35.0 105.0 3.13 0.30 12.400000
## 4536 60.5 156.0 3.06 0.45 9.100000
## 4537 62.0 152.0 3.06 0.45 9.100000
## 4538 6.0 94.0 3.18 0.52 10.100000
## 4539 24.0 134.0 2.99 0.39 10.900000
## 4540 13.0 60.0 3.13 0.35 11.050000
## 4541 36.0 105.0 3.26 0.58 12.750000
## 4542 23.0 111.0 3.36 0.37 12.700000
## 4543 16.0 76.0 3.05 0.54 11.100000
## 4544 16.0 76.0 3.05 0.54 11.100000
## 4545 36.0 105.0 3.26 0.58 12.750000
## 4546 41.0 101.0 3.19 0.31 13.000000
## 4547 32.0 95.0 2.96 0.61 12.000000
## 4548 17.0 47.0 3.35 0.35 11.500000
## 4549 51.0 183.0 3.39 0.60 10.500000
## 4550 16.0 76.0 3.05 0.54 11.100000
## 4551 20.0 101.0 3.10 0.46 11.100000
## 4552 25.0 113.0 3.11 0.47 11.100000
## 4553 20.0 104.0 3.22 0.73 13.100000
## 4554 36.0 105.0 3.26 0.58 12.750000
## 4555 23.0 111.0 3.36 0.37 12.700000
## 4556 23.0 97.0 3.09 0.44 9.600000
## 4557 32.0 138.0 3.26 0.72 11.700000
## 4558 61.0 210.0 3.17 0.59 9.700000
## 4559 22.0 130.0 3.38 0.59 10.900000
## 4560 22.0 110.0 3.34 0.54 10.700000
## 4561 29.0 107.0 3.33 0.54 13.800000
## 4562 10.0 72.0 3.11 0.48 12.150000
## 4563 28.0 131.0 3.49 0.42 10.800000
## 4564 27.0 119.0 3.40 0.34 10.700000
## 4565 31.0 113.0 3.16 0.48 10.800000
## 4567 43.5 171.0 3.03 0.49 12.000000
## 4569 17.0 135.0 3.23 0.44 12.200000
## 4570 17.0 126.0 3.18 0.55 9.400000
## 4571 12.0 83.0 3.30 0.40 11.400000
## 4572 26.0 101.0 3.35 0.38 12.500000
## 4573 29.0 97.0 3.20 0.46 13.050000
## 4574 31.0 99.0 3.10 0.40 12.400000
## 4575 39.0 102.0 3.08 0.56 12.900000
## 4576 25.0 133.0 3.34 0.59 12.000000
## 4577 23.0 56.0 3.19 0.38 11.300000
## 4578 25.0 96.0 3.21 0.49 10.000000
## 4579 40.0 98.0 3.42 0.64 11.800000
## 4580 53.0 125.0 2.99 0.69 9.400000
## 4582 32.0 138.0 3.46 0.43 11.100000
## 4584 60.0 150.0 2.86 0.49 9.300000
## 4585 12.0 110.0 3.02 0.54 11.400000
## 4586 23.0 158.0 3.41 0.64 11.800000
## 4587 31.0 132.0 3.28 0.36 12.400000
## 4588 22.0 108.0 3.12 0.36 11.600000
## 4589 30.0 137.0 3.26 0.58 11.100000
## 4590 31.0 132.0 3.28 0.36 12.400000
## 4591 42.0 168.0 3.22 0.49 11.100000
## 4593 27.0 165.0 3.12 0.46 12.200000
## 4594 20.0 113.0 3.20 0.56 11.000000
## 4595 26.0 129.0 3.32 0.47 12.900000
## 4596 29.0 124.0 3.07 0.42 10.900000
## 4597 20.0 114.0 3.22 0.59 13.400000
## 4599 20.0 113.0 3.20 0.56 11.000000
## 4600 23.0 75.0 3.30 0.39 11.400000
## 4601 20.0 116.0 3.00 0.47 10.200000
## 4602 45.0 116.0 2.80 0.54 11.000000
## 4603 45.0 139.0 3.06 0.43 9.100000
## 4604 40.0 124.0 3.18 0.40 11.000000
## 4605 40.0 146.0 3.11 0.37 11.500000
## 4606 38.0 93.0 3.16 0.59 12.000000
## 4607 16.0 112.0 3.04 0.58 11.200000
## 4608 31.0 177.0 3.12 0.39 11.200000
## 4609 13.0 73.0 2.90 0.69 12.600000
## 4610 8.0 50.0 3.14 0.40 11.000000
## 4611 12.0 73.0 3.22 0.48 10.800000
## 4612 19.0 77.0 3.25 0.48 10.900000
## 4613 48.0 146.0 3.16 0.49 9.800000
## 4614 42.0 145.0 3.15 0.48 9.800000
## 4615 27.0 166.0 2.90 0.49 9.500000
## 4616 43.0 132.0 3.26 0.47 11.266667
## 4617 26.0 99.0 3.01 0.62 10.800000
## 4618 23.0 129.0 3.36 0.77 13.400000
## 4619 43.0 132.0 3.26 0.47 11.300000
## 4620 33.0 196.0 3.22 0.48 8.900000
## 4621 36.0 119.0 3.07 0.42 11.200000
## 4622 30.0 95.0 3.22 0.52 11.500000
## 4623 35.0 131.0 3.26 0.55 13.000000
## 4624 20.0 125.0 3.36 0.73 12.600000
## 4625 15.0 91.0 3.26 0.52 13.100000
## 4626 6.0 158.0 3.05 0.48 11.200000
## 4628 24.0 99.0 3.18 0.50 10.900000
## 4629 24.0 99.0 3.18 0.50 10.900000
## 4630 14.0 73.0 3.04 0.45 11.600000
## 4631 43.0 127.0 3.23 0.53 10.400000
## 4632 31.0 102.0 3.22 0.58 10.900000
## 4634 50.0 188.0 3.23 0.64 10.800000
## 4635 49.0 136.0 3.11 0.59 11.200000
## 4636 26.0 120.0 3.25 0.49 10.000000
## 4637 39.0 177.0 3.28 0.57 10.566667
## 4638 42.0 118.0 3.04 0.64 11.733333
## 4639 39.0 177.0 3.28 0.57 10.600000
## 4640 59.0 195.0 3.26 0.54 10.500000
## 4641 42.0 118.0 3.04 0.64 11.750000
## 4642 43.0 126.0 3.01 0.63 11.400000
## 4643 25.0 98.0 3.37 0.43 12.400000
## 4644 47.0 197.0 3.24 0.50 10.100000
## 4645 40.0 122.0 3.09 0.47 12.300000
## 4646 49.0 158.0 3.32 0.32 13.100000
## 4647 24.0 88.0 3.29 0.55 10.650000
## 4648 35.0 101.0 3.36 0.48 11.400000
## 4650 9.0 84.0 3.44 0.44 10.200000
## 4651 9.0 84.0 3.44 0.44 10.200000
## 4652 49.0 113.0 3.26 0.58 13.100000
## 4653 59.0 210.0 3.24 0.50 9.600000
## 4654 18.0 73.0 3.10 0.47 12.800000
## 4655 55.0 149.0 3.09 0.59 10.966667
## 4656 55.0 149.0 3.09 0.59 10.966667
## 4657 55.0 149.0 3.09 0.59 10.966667
## 4658 55.0 149.0 3.09 0.59 11.000000
## 4659 43.0 132.0 3.21 0.47 13.400000
## 4660 28.0 85.0 2.87 0.48 11.200000
## 4661 14.0 79.0 3.27 0.63 12.400000
## 4662 35.0 150.0 3.09 0.47 11.200000
## 4663 44.0 111.0 3.14 0.41 12.400000
## 4664 30.0 111.0 3.32 0.58 10.133333
## 4665 31.0 114.0 3.32 0.58 10.133333
## 4666 44.0 111.0 3.14 0.41 12.400000
## 4667 36.0 221.0 3.17 0.44 9.100000
## 4668 31.0 114.0 3.32 0.58 10.150000
## 4669 30.0 111.0 3.32 0.58 10.150000
## 4670 12.0 117.0 3.46 0.44 11.500000
## 4671 57.0 137.0 3.08 0.54 8.900000
## 4672 69.0 168.0 3.47 0.46 10.466667
## 4673 69.0 168.0 3.47 0.46 10.466667
## 4674 37.0 104.0 3.28 0.51 11.800000
## 4675 41.0 151.0 3.35 0.58 11.633333
## 4676 58.0 140.0 3.29 0.62 10.600000
## 4677 41.0 128.0 3.18 0.52 9.600000
## 4678 37.0 104.0 3.28 0.51 11.800000
## 4679 57.0 137.0 3.08 0.54 8.900000
## 4680 69.0 168.0 3.47 0.46 10.500000
## 4681 25.0 133.0 3.17 0.39 10.200000
## 4682 11.0 49.0 3.29 0.33 13.100000
## 4683 15.0 66.0 3.11 0.31 11.800000
## 4684 39.0 120.0 3.06 0.37 12.200000
## 4685 52.0 184.0 3.44 0.44 11.450000
## 4686 23.0 114.0 3.23 0.49 10.500000
## 4687 25.0 133.0 3.17 0.39 10.200000
## 4688 18.0 156.0 2.88 0.36 9.000000
## 4689 18.0 156.0 2.88 0.36 9.000000
## 4690 18.0 156.0 2.88 0.36 9.000000
## 4691 18.0 156.0 2.88 0.36 9.000000
## 4692 38.0 167.0 2.93 0.52 9.100000
## 4693 26.0 173.0 3.38 0.54 8.800000
## 4694 18.0 156.0 2.88 0.36 9.000000
## 4695 38.0 167.0 2.93 0.52 9.100000
## 4696 29.0 113.0 3.13 0.65 12.900000
## 4698 29.0 113.0 3.13 0.65 12.900000
## 4700 60.0 168.0 3.10 0.56 9.800000
## 4701 60.0 168.0 3.10 0.56 9.800000
## 4702 34.0 144.0 3.26 0.38 10.100000
## 4703 34.0 144.0 3.26 0.38 10.100000
## 4704 36.0 83.0 3.33 0.42 10.900000
## 4705 51.0 202.0 3.20 0.51 9.600000
## 4706 32.0 111.0 3.36 0.37 10.400000
## 4707 25.0 111.0 3.03 0.30 11.800000
## 4708 31.0 115.0 3.40 0.38 10.800000
## 4709 26.0 109.0 3.28 0.57 10.600000
## 4710 45.0 142.0 3.35 0.50 12.700000
## 4711 27.0 108.0 3.30 0.43 12.200000
## 4712 31.0 115.0 3.40 0.38 10.800000
## 4713 32.0 111.0 3.36 0.37 10.400000
## 4714 19.0 98.0 3.25 0.47 11.100000
## 4715 25.0 111.0 3.03 0.30 11.800000
## 4716 17.0 81.0 3.29 0.31 10.000000
## 4717 10.0 69.0 3.12 0.59 10.800000
## 4718 47.0 130.0 3.31 0.40 10.300000
## 4719 32.0 134.0 3.24 0.48 9.900000
## 4720 17.0 81.0 3.29 0.31 10.000000
## 4721 18.0 93.0 3.11 0.56 12.250000
## 4722 27.0 98.0 3.34 0.52 10.200000
## 4723 37.0 132.0 3.06 0.50 9.400000
## 4724 58.0 180.0 3.18 0.46 9.700000
## 4725 27.0 98.0 3.34 0.52 10.200000
## 4726 33.0 116.0 3.04 0.65 10.400000
## 4727 35.0 96.0 3.49 0.74 12.200000
## 4728 37.0 132.0 3.06 0.50 9.400000
## 4729 36.0 122.0 3.12 0.40 10.600000
## 4730 4.0 65.0 3.27 0.47 10.700000
## 4731 13.0 106.0 3.24 0.49 11.850000
## 4732 53.0 140.0 3.34 0.46 11.700000
## 4733 53.0 140.0 3.34 0.46 11.700000
## 4734 47.0 123.0 3.55 0.44 10.150000
## 4735 31.0 68.0 3.33 0.44 11.633333
## 4736 14.0 61.0 3.22 0.54 10.800000
## 4737 13.0 61.0 3.22 0.54 10.800000
## 4738 41.0 134.0 3.25 0.26 12.300000
## 4739 33.0 118.0 3.36 0.66 12.500000
## 4740 31.0 68.0 3.33 0.44 11.650000
## 4741 56.0 189.0 3.24 0.49 9.600000
## 4742 42.0 137.0 3.24 0.46 10.900000
## 4743 36.0 133.0 3.23 0.46 10.800000
## 4744 63.0 148.0 3.32 0.44 11.200000
## 4745 17.0 101.0 3.67 0.57 10.000000
## 4747 61.0 132.0 2.86 0.46 9.100000
## 4748 25.0 93.0 3.23 0.49 10.500000
## 4749 33.0 184.0 3.12 0.61 9.300000
## 4750 28.0 182.0 3.13 0.62 9.300000
## 4751 63.0 148.0 3.32 0.44 11.200000
## 4752 48.0 185.0 3.14 0.62 10.600000
## 4753 40.0 78.0 3.23 0.64 12.100000
## 4754 35.0 100.0 3.43 0.77 12.000000
## 4755 40.0 106.0 3.16 0.50 9.700000
## 4756 21.0 92.0 3.12 0.48 12.400000
## 4757 38.0 111.0 3.18 0.47 13.600000
## 4758 38.0 111.0 3.18 0.47 13.600000
## 4759 27.0 140.0 2.98 0.53 11.800000
## 4760 45.0 128.0 3.16 0.37 10.000000
## 4761 45.0 128.0 3.16 0.37 10.000000
## 4762 46.0 116.0 3.12 0.38 9.100000
## 4763 19.0 78.0 3.47 0.42 11.900000
## 4764 45.0 130.0 3.31 0.58 11.750000
## 4765 34.0 116.0 3.24 0.41 11.400000
## 4766 18.0 96.0 3.56 0.48 13.000000
## 4767 28.0 138.0 3.27 0.50 12.400000
## 4768 34.0 181.0 3.30 0.42 9.400000
## 4769 69.0 160.0 3.16 0.50 9.600000
## 4770 69.0 160.0 3.16 0.50 9.600000
## 4771 69.0 160.0 3.16 0.50 9.600000
## 4772 69.0 160.0 3.16 0.50 9.600000
## 4773 47.0 223.0 3.16 0.51 9.100000
## 4774 17.0 61.0 3.24 0.37 12.000000
## 4775 6.0 132.0 3.16 0.46 11.200000
## 4776 42.0 124.0 3.32 0.47 10.100000
## 4777 47.0 130.0 3.13 0.45 10.300000
## 4778 31.0 102.0 3.16 0.56 12.300000
## 4779 28.0 106.0 2.97 0.40 10.550000
## 4780 30.0 95.0 3.10 0.40 10.900000
## 4781 36.0 138.0 3.15 0.48 9.700000
## 4782 34.0 142.0 3.14 0.48 9.800000
## 4783 38.0 127.0 3.04 0.53 8.900000
## 4784 38.0 127.0 3.04 0.53 8.900000
## 4785 55.0 161.0 3.02 0.59 10.200000
## 4786 28.0 76.0 3.01 0.36 11.700000
## 4787 31.0 127.0 3.46 0.36 12.800000
## 4788 29.0 118.0 3.57 0.36 12.800000
## 4789 55.0 161.0 3.02 0.59 10.200000
## 4790 24.0 118.0 3.15 0.39 13.550000
## 4791 28.0 128.0 3.13 0.38 11.600000
## 4792 38.0 127.0 3.04 0.53 8.900000
## 4796 44.0 140.0 3.17 0.55 10.700000
## 4797 44.0 140.0 3.17 0.55 10.700000
## 4798 28.0 93.0 3.31 0.50 12.300000
## 4799 37.0 115.0 3.16 0.43 10.300000
## 4800 35.0 111.0 3.11 0.42 10.400000
## 4801 45.0 126.0 3.31 0.45 11.600000
## 4802 44.0 140.0 3.17 0.55 10.700000
## 4803 24.0 125.0 3.36 0.33 12.800000
## 4804 42.0 111.0 3.18 0.53 11.900000
## 4805 9.0 65.0 3.24 0.35 12.100000
## 4806 26.0 99.0 3.23 0.41 9.200000
## 4807 37.0 131.0 2.93 0.62 9.500000
## 4808 39.0 104.0 2.91 0.57 11.000000
## 4809 10.0 100.0 3.19 0.50 10.900000
## 4810 66.0 150.0 3.21 0.62 10.400000
## 4811 29.0 147.0 3.42 0.52 9.100000
## 4812 19.0 71.0 3.32 0.62 11.400000
## 4813 46.0 113.0 3.35 0.43 11.400000
## 4815 17.0 113.0 3.18 0.67 12.400000
## 4817 54.0 136.0 2.91 0.43 10.600000
## 4818 38.0 122.0 3.20 0.63 11.200000
## 4820 17.0 113.0 3.18 0.67 12.400000
## 4822 18.0 131.0 3.19 0.45 11.000000
## 4823 35.0 165.0 3.18 0.45 11.300000
## 4824 22.0 130.0 3.20 0.46 12.000000
## 4825 54.0 140.0 3.23 0.47 9.200000
## 4826 29.0 134.0 3.48 0.57 10.700000
## 4827 29.0 134.0 3.48 0.57 10.700000
## 4828 36.0 86.0 3.10 0.76 11.400000
## 4829 54.0 140.0 3.23 0.47 9.200000
## 4830 22.0 90.0 3.10 0.43 12.100000
## 4831 17.0 140.0 3.23 0.35 11.100000
## 4832 20.0 140.0 3.27 0.43 9.700000
## 4833 17.0 141.0 3.24 0.36 10.700000
## 4834 33.0 97.0 3.49 0.58 10.900000
## 4835 35.0 95.0 3.36 0.56 12.000000
## 4836 40.0 102.0 3.47 0.56 10.600000
## 4837 18.0 92.0 3.11 0.49 9.600000
## 4838 54.0 216.0 3.03 0.42 13.100000
## 4839 28.0 114.0 3.38 0.51 11.000000
## 4840 10.0 44.0 3.52 0.40 11.600000
## 4841 44.0 128.0 3.28 0.35 11.950000
## 4843 50.0 92.0 3.17 0.36 11.500000
## 4844 47.0 182.0 3.21 0.40 11.300000
## 4845 38.0 180.0 3.28 0.34 11.900000
## 4846 15.0 93.0 3.18 0.60 9.500000
## 4847 40.0 150.0 3.29 0.46 12.200000
## 4848 52.0 97.0 3.41 0.40 12.200000
## 4849 67.0 161.0 3.05 0.56 11.100000
## 4850 52.0 164.0 3.10 0.48 9.600000
## 4851 67.0 161.0 3.05 0.56 11.100000
## 4852 52.0 164.0 3.10 0.48 9.600000
## 4853 12.0 113.0 3.30 0.73 11.400000
## 4854 20.0 77.0 3.32 0.62 11.400000
## 4855 22.0 79.0 3.10 0.59 12.066667
## 4856 26.0 172.0 2.90 0.46 9.000000
## 4857 26.0 172.0 2.90 0.46 9.000000
## 4858 19.0 116.0 3.08 0.42 11.400000
## 4859 53.0 177.0 3.12 0.45 9.600000
## 4860 25.0 118.0 3.03 0.37 11.000000
## 4861 24.0 119.0 3.04 0.38 11.000000
## 4862 16.0 102.0 3.23 0.56 11.200000
## 4863 42.0 86.0 3.31 0.47 11.550000
## 4864 44.0 92.0 3.20 0.50 13.300000
## 4865 22.0 148.0 3.30 0.47 9.633333
## 4866 31.0 95.0 3.06 0.46 13.600000
## 4867 30.0 112.0 3.29 0.55 11.200000
## 4868 3.0 60.0 3.27 0.38 13.000000
## 4869 42.0 124.0 3.31 0.64 10.800000
## 4870 8.0 81.0 3.19 0.51 9.800000
## 4871 29.0 132.0 3.15 0.36 11.450000
## 4872 20.0 98.0 3.37 0.55 12.050000
## 4873 50.0 179.0 3.14 0.60 9.700000
## 4874 33.0 122.0 3.33 0.52 11.900000
## 4875 16.0 125.0 3.49 0.49 10.000000
## 4876 18.0 97.0 3.12 0.41 9.700000
## 4877 34.0 117.0 3.36 0.59 11.600000
## 4878 12.0 82.0 3.25 0.36 8.800000
## 4879 6.0 81.0 3.24 0.35 9.500000
## 4880 68.0 170.0 3.15 0.50 9.533333
## 4881 68.0 170.0 3.15 0.50 9.533333
## 4882 34.0 118.0 3.07 0.50 9.400000
## 4883 45.0 156.0 3.26 0.38 10.700000
## 4884 60.0 148.0 3.27 0.35 11.500000
## 4885 68.0 174.0 3.14 0.50 9.600000
## 4886 68.0 170.0 3.15 0.50 9.550000
## 4888 5.0 56.0 3.04 0.79 13.000000
## 4889 38.0 127.0 3.04 0.54 9.200000
## 4890 34.0 118.0 3.07 0.50 9.400000
## 4891 25.0 100.0 3.06 0.44 11.800000
## 4892 38.0 121.0 3.24 0.46 10.600000
## 4893 29.0 112.0 3.29 0.54 9.700000
## 4894 24.0 92.0 3.27 0.50 11.200000
## 4895 57.0 168.0 3.15 0.46 9.600000
## 4896 30.0 111.0 2.99 0.46 9.400000
## 4897 20.0 110.0 3.34 0.38 12.800000
## 4898 22.0 98.0 3.26 0.32 11.800000
## 4899 11.0 34.0 3.51 0.56 9.400000
## 4900 25.0 67.0 3.20 0.68 9.800000
## 4901 15.0 54.0 3.26 0.65 9.800000
## 4902 17.0 60.0 3.16 0.58 9.800000
## 4903 11.0 34.0 3.51 0.56 9.400000
## 4904 13.0 40.0 3.51 0.56 9.400000
## 4905 15.0 59.0 3.30 0.46 9.400000
## 4906 15.0 21.0 3.39 0.47 10.000000
## 4907 9.0 18.0 3.36 0.57 9.500000
## 4908 17.0 102.0 3.35 0.80 10.500000
## 4909 15.0 65.0 3.28 0.54 9.200000
## 4910 17.0 102.0 3.35 0.80 10.500000
## 4911 16.0 59.0 3.58 0.52 9.900000
## 4915 35.0 103.0 3.30 0.75 10.500000
## 4917 6.0 29.0 3.38 0.50 9.000000
## 4919 29.0 60.0 3.39 0.53 9.400000
## 4920 23.0 71.0 3.52 0.65 9.700000
## 4921 10.0 37.0 3.17 0.91 9.500000
## 4922 9.0 67.0 3.17 0.53 9.400000
## 4923 21.0 40.0 3.43 0.63 9.700000
## 4924 11.0 23.0 3.34 0.56 9.300000
## 4925 4.0 11.0 3.28 0.59 9.500000
## 4926 10.0 37.0 3.17 0.91 9.500000
## 4927 14.0 35.0 3.47 0.55 9.400000
## 4928 8.0 16.0 3.38 0.59 9.800000
## 4929 17.0 82.0 3.35 0.54 10.100000
## 4930 22.0 37.0 3.46 0.57 10.600000
## 4931 15.0 113.0 3.17 0.66 9.800000
## 4932 40.0 83.0 3.45 0.52 9.400000
## 4933 13.0 50.0 3.38 0.55 9.200000
## 4934 5.0 18.0 3.40 0.55 9.600000
## 4935 3.0 15.0 3.42 0.60 10.800000
## 4936 13.0 30.0 3.23 0.73 9.700000
## 4938 12.0 87.0 3.33 0.83 10.500000
## 4939 12.0 87.0 3.33 0.83 10.500000
## 4940 17.0 46.0 3.26 0.51 9.300000
## 4943 5.0 11.0 3.48 0.52 9.500000
## 4946 12.0 37.0 3.25 0.58 9.500000
## 4947 5.0 12.0 3.34 0.56 9.200000
## 4948 12.0 96.0 3.32 0.58 9.200000
## 4949 4.0 23.0 3.15 0.74 9.200000
## 4950 8.0 15.0 3.40 0.63 9.400000
## 4951 6.0 14.0 3.39 0.64 9.400000
## 4952 30.0 119.0 3.20 0.56 9.400000
## 4953 33.0 73.0 3.17 0.63 10.200000
## 4954 25.0 45.0 3.34 0.53 9.500000
## 4955 4.0 10.0 3.04 0.63 9.600000
## 4956 50.0 110.0 3.26 0.77 9.400000
## 4957 17.0 54.0 3.43 0.59 10.000000
## 4958 9.0 46.0 3.41 0.54 9.400000
## 4959 19.0 52.0 3.44 0.64 9.200000
## 4960 20.0 112.0 3.21 0.71 9.300000
## 4961 12.0 35.0 3.38 0.62 9.500000
## 4962 13.0 54.0 3.39 0.57 9.800000
## 4963 4.0 11.0 3.41 0.39 10.900000
## 4964 4.0 11.0 3.41 0.39 10.900000
## 4965 11.0 39.0 3.42 0.58 9.600000
## 4966 6.0 15.0 3.44 0.58 10.700000
## 4967 27.0 65.0 3.28 0.79 10.700000
## 4968 8.0 19.0 3.34 0.95 10.500000
## 4969 15.0 27.0 3.32 0.54 9.500000
## 4970 17.0 96.0 3.32 0.48 9.500000
## 4971 18.0 94.0 3.31 0.48 9.500000
## 4972 11.0 43.0 3.31 0.53 9.200000
## 4973 28.0 83.0 3.28 0.82 9.600000
## 4974 9.0 42.0 3.54 0.66 10.500000
## 4975 9.0 42.0 3.54 0.66 10.500000
## 4976 14.0 30.0 3.52 0.55 10.700000
## 4977 12.0 80.0 3.38 0.52 10.100000
## 4979 3.0 15.0 3.41 0.56 9.200000
## 4981 21.0 73.0 3.36 0.57 9.100000
## 4983 18.0 61.0 3.44 0.78 10.300000
## 4984 19.0 40.0 3.41 0.59 10.100000
## 4986 9.0 31.0 3.39 0.64 9.600000
## 4988 8.0 24.0 3.48 0.53 9.000000
## 4989 42.0 140.0 3.23 0.54 9.500000
## 4992 9.0 31.0 3.39 0.64 9.600000
## 4995 8.0 23.0 3.45 0.56 10.700000
## 4996 3.0 22.0 3.25 0.63 9.200000
## 4997 5.0 10.0 3.39 0.56 9.800000
## 4998 13.0 35.0 3.30 0.59 9.000000
## 4999 11.0 50.0 3.40 0.61 10.200000
## 5000 8.0 22.0 3.31 0.56 10.400000
## 5001 13.0 35.0 3.30 0.59 9.000000
## 5002 12.0 65.0 3.29 0.51 9.200000
## 5003 5.0 36.0 3.33 0.48 9.400000
## 5004 12.0 65.0 3.29 0.51 9.200000
## 5006 15.0 64.0 3.46 0.79 9.300000
## 5007 18.0 80.0 3.37 0.80 9.600000
## 5009 12.0 47.0 3.19 0.93 9.500000
## 5010 11.0 108.0 3.15 0.66 9.800000
## 5011 14.0 111.0 3.15 0.66 9.800000
## 5012 22.0 46.0 3.32 0.67 9.700000
## 5013 12.0 47.0 3.19 0.93 9.500000
## 5014 13.0 62.0 3.07 0.63 10.500000
## 5015 11.0 40.0 3.39 0.61 10.000000
## 5016 7.0 28.0 3.37 0.50 9.400000
## 5017 14.0 56.0 3.21 0.60 10.900000
## 5018 22.0 89.0 3.34 0.54 9.200000
## 5020 14.0 56.0 3.21 0.60 10.900000
## 5021 3.0 13.0 3.49 0.52 9.200000
## 5022 11.0 34.0 3.44 0.53 9.500000
## 5023 21.0 102.0 3.39 0.48 9.500000
## 5024 27.0 90.0 3.16 0.70 9.400000
## 5027 3.0 16.0 3.42 0.92 10.500000
## 5028 6.0 19.0 3.42 0.57 9.400000
## 5029 30.0 134.0 3.24 0.66 9.400000
## 5032 17.0 26.0 3.40 0.58 9.800000
## 5034 16.0 63.0 3.19 0.82 9.600000
## 5035 10.0 52.0 3.23 0.77 9.500000
## 5036 13.0 45.0 3.48 0.64 9.200000
## 5037 15.0 105.0 3.33 0.54 9.500000
## 5038 17.0 108.0 3.32 0.54 9.500000
## 5039 16.0 63.0 3.19 0.82 9.600000
## 5040 10.0 52.0 3.23 0.77 9.500000
## 5042 3.0 20.0 3.34 0.58 9.400000
## 5044 32.0 141.0 3.17 0.62 9.400000
## 5045 21.0 94.0 3.54 0.52 10.000000
## 5047 12.0 30.0 3.42 0.58 10.200000
## 5048 11.0 43.0 3.53 0.61 10.500000
## 5049 5.0 11.0 3.33 0.53 10.300000
## 5051 25.0 99.0 3.35 0.54 10.100000
## 5052 25.0 99.0 3.35 0.54 10.100000
## 5053 29.0 129.0 3.42 0.72 10.500000
## 5054 28.0 128.0 3.42 0.71 10.500000
## 5055 29.0 129.0 3.42 0.72 10.500000
## 5056 28.0 128.0 3.42 0.71 10.500000
## 5057 12.0 22.0 3.48 0.50 9.300000
## 5058 18.0 86.0 3.59 0.57 9.300000
## 5059 7.0 20.0 3.20 0.56 9.600000
## 5061 17.0 31.0 3.33 0.56 10.000000
## 5062 36.0 121.0 3.37 0.49 9.400000
## 5063 35.0 121.0 3.37 0.49 9.400000
## 5064 14.0 96.0 3.19 0.62 9.500000
## 5065 18.0 101.0 3.34 0.52 10.200000
## 5066 17.0 42.0 3.37 0.48 9.000000
## 5067 11.0 44.0 3.47 0.55 10.400000
## 5070 6.0 18.0 3.29 0.61 9.200000
## 5071 6.0 18.0 3.29 0.61 9.200000
## 5072 24.0 42.0 3.42 0.57 11.500000
## 5073 7.0 35.0 3.33 0.47 9.500000
## 5074 19.0 49.0 3.35 0.78 9.500000
## 5075 7.0 35.0 3.33 0.47 9.500000
## 5076 8.0 38.0 3.58 0.61 10.500000
## 5077 7.0 20.0 3.48 0.56 9.600000
## 5078 10.0 42.0 3.19 0.59 9.500000
## 5079 10.0 42.0 3.19 0.59 9.500000
## 5081 16.0 42.0 3.44 0.52 9.300000
## 5082 11.0 65.0 3.54 0.58 9.300000
## 5083 8.0 62.0 3.52 0.58 9.300000
## 5084 26.0 85.0 3.26 0.53 9.700000
## 5085 14.0 67.0 3.34 0.55 9.200000
## 5086 9.0 26.0 3.39 0.49 9.700000
## 5087 15.0 143.0 3.20 0.55 9.500000
## 5088 17.0 144.0 3.20 0.55 9.500000
## 5089 21.0 127.0 3.23 0.62 9.400000
## 5090 21.0 49.0 3.57 0.62 9.800000
## 5091 16.0 126.0 3.28 0.61 9.500000
## 5092 7.0 28.0 3.28 0.55 9.700000
## 5093 7.0 28.0 3.28 0.55 9.700000
## 5094 24.0 120.0 3.25 0.54 9.400000
## 5095 15.0 55.0 3.46 0.59 10.200000
## 5099 9.0 24.0 3.22 0.82 10.300000
## 5100 39.0 145.0 3.04 1.03 9.300000
## 5101 16.0 49.0 3.36 0.79 9.500000
## 5102 16.0 39.0 3.34 0.55 9.200000
## 5103 14.0 37.0 3.34 0.56 9.200000
## 5106 26.0 120.0 3.29 0.53 9.300000
## 5107 18.0 95.0 3.22 0.67 9.400000
## 5108 7.0 19.0 3.31 0.88 10.500000
## 5109 5.0 19.0 3.30 0.86 12.400000
## 5110 10.0 62.0 3.35 0.56 10.000000
## 5112 28.0 65.0 3.30 0.43 10.100000
## 5113 10.0 41.0 3.24 0.71 9.800000
## 5114 26.0 121.0 3.34 0.76 10.500000
## 5115 13.0 49.0 3.14 0.57 11.000000
## 5116 11.0 41.0 3.36 0.55 9.100000
## 5117 10.0 44.0 3.39 0.54 9.700000
## 5118 24.0 144.0 3.30 0.60 9.500000
## 5119 24.0 58.0 3.34 0.59 9.400000
## 5120 16.0 72.0 3.15 0.57 9.400000
## 5121 5.0 10.0 3.42 0.60 9.500000
## 5122 8.0 28.0 3.28 0.60 10.000000
## 5123 15.0 55.0 3.31 0.57 10.400000
## 5124 29.0 63.0 3.37 0.58 10.500000
## 5126 9.0 23.0 3.39 0.63 9.800000
## 5127 29.0 63.0 3.37 0.58 10.500000
## 5128 10.0 37.0 3.46 0.50 11.000000
## 5129 19.0 106.0 3.54 0.62 12.200000
## 5130 12.0 49.0 3.37 0.52 9.900000
## 5131 18.0 58.0 3.34 0.70 9.600000
## 5132 10.0 37.0 3.46 0.50 11.000000
## 5134 14.0 38.0 3.37 0.58 9.000000
## 5135 14.0 38.0 3.37 0.58 9.000000
## 5136 15.0 39.0 3.37 0.58 9.200000
## 5137 14.0 38.0 3.37 0.58 9.000000
## 5140 6.0 24.0 3.14 0.71 10.900000
## 5141 28.0 109.0 3.08 0.49 9.800000
## 5144 6.0 23.0 3.61 0.96 9.900000
## 5145 16.0 51.0 3.38 0.52 9.500000
## 5146 11.0 73.0 3.20 0.45 9.300000
## 5147 9.0 39.0 3.35 0.48 9.800000
## 5148 6.0 23.0 3.61 0.96 9.900000
## 5149 16.0 37.0 3.22 0.78 10.000000
## 5150 16.0 34.0 3.47 0.70 9.900000
## 5151 5.0 21.0 3.17 0.53 10.500000
## 5152 8.0 86.0 3.23 0.59 9.500000
## 5153 16.0 34.0 3.47 0.70 9.900000
## 5154 17.0 119.0 3.26 0.57 9.300000
## 5155 5.0 13.0 3.22 0.62 9.200000
## 5156 12.0 56.0 3.49 0.67 9.200000
## 5158 14.0 33.0 3.36 0.80 10.500000
## 5159 18.0 45.0 3.29 0.65 9.300000
## 5161 10.0 35.0 3.34 0.57 10.000000
## 5162 23.0 49.0 3.28 0.67 9.300000
## 5165 26.0 61.0 3.60 0.72 9.800000
## 5167 7.0 27.0 3.69 0.91 9.400000
## 5169 27.0 61.0 3.36 0.67 10.700000
## 5171 17.0 65.0 3.22 0.78 10.100000
## 5172 10.0 38.0 3.31 0.64 9.400000
## 5173 27.0 94.0 3.38 0.77 9.400000
## 5174 27.0 61.0 3.36 0.67 10.700000
## 5175 7.0 27.0 3.69 0.91 9.400000
## 5177 5.0 13.0 3.23 0.82 12.600000
## 5178 10.0 47.0 3.38 0.77 10.500000
## 5181 12.0 53.0 3.36 0.57 9.100000
## 5182 10.0 47.0 3.38 0.77 10.500000
## 5183 32.0 71.0 3.31 0.71 9.800000
## 5184 32.0 71.0 3.31 0.71 9.800000
## 5185 25.0 49.0 3.10 0.76 10.300000
## 5186 29.0 53.0 3.37 0.70 10.300000
## 5187 20.0 49.0 3.34 0.86 10.600000
## 5188 33.0 98.0 3.20 0.95 9.200000
## 5189 20.0 49.0 3.34 0.86 10.600000
## 5191 18.0 48.0 3.22 0.64 10.300000
## 5192 5.0 16.0 3.41 0.60 10.100000
## 5194 5.0 27.0 3.05 0.64 9.500000
## 5195 26.0 70.0 3.16 0.52 9.900000
## 5196 8.0 29.0 3.67 0.73 9.600000
## 5197 5.0 31.0 3.67 0.80 9.700000
## 5198 8.0 33.0 3.68 0.71 9.600000
## 5199 20.0 44.0 3.38 0.59 10.700000
## 5200 7.0 15.0 3.22 0.64 10.100000
## 5201 12.0 28.0 3.51 0.72 10.000000
## 5203 12.0 90.0 3.20 0.52 9.200000
## 5204 6.0 25.0 3.12 0.59 9.300000
## 5205 7.0 54.0 3.36 0.52 9.400000
## 5208 9.0 30.0 3.41 0.53 9.500000
## 5209 6.0 25.0 3.12 0.59 9.300000
## 5210 15.0 105.0 3.27 0.54 9.400000
## 5211 19.0 98.0 3.32 0.63 9.500000
## 5212 30.0 135.0 3.30 0.53 9.400000
## 5213 26.0 72.0 3.39 0.68 11.000000
## 5214 20.0 53.0 3.42 0.65 11.000000
## 5215 37.0 92.0 3.30 0.65 10.100000
## 5216 30.0 74.0 3.30 0.64 10.400000
## 5217 21.0 59.0 3.37 0.71 11.500000
## 5218 30.0 74.0 3.30 0.64 10.400000
## 5219 21.0 59.0 3.37 0.71 11.500000
## 5220 25.0 87.0 3.24 0.62 9.700000
## 5221 6.0 18.0 3.29 0.63 9.300000
## 5222 35.0 73.0 3.28 0.70 9.500000
## 5223 13.0 50.0 3.16 0.69 9.200000
## 5224 13.0 50.0 3.16 0.69 9.200000
## 5225 6.0 14.0 3.05 0.74 11.500000
## 5226 5.0 13.0 3.28 0.83 11.500000
## 5228 7.0 15.0 3.18 0.62 9.500000
## 5231 21.0 114.0 3.22 0.54 9.400000
## 5232 16.0 44.0 3.13 0.52 11.000000
## 5233 17.0 38.0 3.34 0.74 11.700000
## 5235 6.0 16.0 3.35 0.70 12.500000
## 5236 29.0 58.0 3.31 0.64 10.300000
## 5240 5.0 18.0 3.21 0.87 11.300000
## 5241 6.0 14.0 3.30 0.75 9.800000
## 5242 6.0 14.0 3.30 0.75 9.800000
## 5243 6.0 32.0 3.12 0.78 10.700000
## 5244 40.0 63.0 3.60 0.81 9.900000
## 5245 17.0 34.0 3.58 0.89 12.300000
## 5247 15.0 46.0 3.11 0.92 10.000000
## 5248 11.0 28.0 3.36 0.86 9.400000
## 5249 17.0 34.0 3.28 0.98 9.900000
## 5250 11.0 26.0 3.35 0.83 9.400000
## 5251 8.0 19.0 3.27 0.73 9.300000
## 5253 40.5 165.0 3.25 0.59 11.900000
## 5255 29.0 55.0 3.26 0.88 11.000000
## 5256 12.0 29.0 3.24 0.75 11.700000
## 5257 10.0 23.0 3.15 0.85 10.400000
## 5259 14.0 81.0 3.19 0.70 9.400000
## 5260 21.0 50.0 3.37 0.91 9.900000
## 5264 7.0 21.0 3.26 0.93 11.800000
## 5266 11.0 24.0 3.16 0.69 9.000000
## 5267 15.0 75.0 3.18 0.64 9.400000
## 5269 35.0 63.0 3.57 0.78 9.900000
## 5270 11.0 25.0 3.32 0.87 8.700000
## 5271 26.0 46.0 3.32 1.04 10.600000
## 5272 12.0 72.0 3.05 0.63 9.200000
## 5278 24.0 60.0 3.31 0.70 10.800000
## 5279 11.0 27.0 3.21 0.80 9.400000
## 5281 11.0 27.0 3.21 0.80 9.400000
## 5282 11.0 27.0 3.21 0.80 9.400000
## 5283 23.0 54.0 3.42 0.74 9.200000
## 5284 11.0 37.0 3.43 0.76 9.700000
## 5285 23.0 48.0 3.41 0.74 9.200000
## 5286 17.0 42.0 3.31 0.54 9.600000
## 5287 23.0 53.0 3.43 0.74 9.200000
## 5288 16.0 49.0 3.19 0.70 10.000000
## 5291 6.0 26.0 3.18 0.51 9.500000
## 5292 13.0 95.0 3.16 0.54 9.100000
## 5296 13.0 49.0 3.18 0.65 11.000000
## 5297 13.0 49.0 3.18 0.65 11.000000
## 5298 9.0 42.0 3.10 0.55 9.400000
## 5300 20.0 38.0 3.29 0.47 10.800000
## 5301 19.0 64.0 3.10 0.61 10.500000
## 5302 10.0 41.0 3.15 0.63 10.500000
## 5303 15.0 27.0 3.26 0.61 9.100000
## 5304 11.0 25.0 3.36 0.76 10.100000
## 5305 9.0 28.0 3.24 0.65 10.800000
## 5306 12.0 30.0 3.18 0.63 10.800000
## 5309 26.0 86.0 3.38 0.62 9.500000
## 5310 23.0 78.0 3.38 0.62 9.500000
## 5311 15.0 77.0 3.27 0.64 9.300000
## 5312 6.0 19.0 3.27 0.82 11.700000
## 5313 24.0 122.0 3.26 0.61 9.500000
## 5315 6.0 20.0 3.26 0.66 11.700000
## 5316 34.0 124.0 3.44 0.48 10.500000
## 5317 7.0 20.0 3.24 0.76 10.400000
## 5318 34.0 52.0 3.62 0.68 9.900000
## 5319 35.0 67.0 3.28 0.73 11.800000
## 5322 6.0 24.0 3.15 0.90 11.000000
## 5325 19.0 48.0 3.49 0.49 11.400000
## 5326 6.0 32.0 3.26 0.56 10.600000
## 5327 9.0 30.0 3.24 0.60 9.300000
## 5329 6.0 24.0 3.15 0.90 11.000000
## 5330 21.0 66.0 3.25 0.56 9.200000
## 5333 22.0 54.0 3.15 0.89 9.900000
## 5335 38.0 62.0 3.26 0.56 10.200000
## 5336 6.0 22.0 3.17 0.66 11.200000
## 5337 22.0 54.0 3.15 0.89 9.900000
## 5338 7.0 50.0 3.08 0.60 9.300000
## 5340 7.0 27.0 3.06 0.68 11.300000
## 5342 11.0 19.0 3.23 0.63 11.600000
## 5343 5.0 27.0 3.57 0.84 12.500000
## 5344 6.0 31.0 3.23 0.56 10.100000
## 5345 31.0 72.0 3.10 0.73 10.500000
## 5346 6.0 16.0 3.22 0.72 11.200000
## 5347 7.0 27.0 3.20 0.56 10.200000
## 5348 17.0 35.0 3.10 0.61 10.800000
## 5349 17.0 35.0 3.10 0.61 10.800000
## 5351 18.0 35.0 3.44 0.63 10.000000
## 5353 21.0 67.0 3.50 0.63 11.100000
## 5355 5.0 22.0 3.37 0.58 10.300000
## 5356 29.0 65.0 3.28 0.58 9.600000
## 5359 14.0 23.0 3.35 0.61 11.300000
## 5360 6.0 19.0 3.26 0.61 9.300000
## 5361 10.0 25.0 3.18 0.61 11.800000
## 5363 5.0 15.0 2.98 0.70 9.200000
## 5364 10.0 26.0 3.48 0.91 9.700000
## 5365 21.0 51.0 3.16 0.72 11.500000
## 5367 6.0 21.0 3.17 0.62 9.200000
## 5370 25.0 52.0 3.20 0.71 11.400000
## 5372 5.0 14.0 3.26 0.79 10.600000
## 5373 10.0 24.0 3.20 0.89 9.400000
## 5374 5.0 28.0 3.14 0.60 10.200000
## 5375 6.0 16.0 3.28 0.70 9.700000
## 5377 5.0 28.0 3.14 0.60 10.200000
## 5378 6.0 31.0 3.19 0.70 10.100000
## 5380 6.0 17.0 3.15 0.92 11.700000
## 5384 6.0 17.0 3.17 0.47 10.000000
## 5385 6.0 17.0 3.17 0.47 10.000000
## 5386 5.0 14.0 3.17 0.42 10.000000
## 5388 10.0 26.0 3.34 0.75 10.200000
## 5389 24.0 56.0 3.31 0.67 10.600000
## 5390 12.0 25.0 3.34 0.79 13.300000
## 5391 13.0 27.0 3.32 0.90 13.400000
## 5393 28.0 91.0 3.44 0.55 12.100000
## 5394 5.0 16.0 3.15 0.65 11.000000
## 5395 14.0 38.0 3.43 0.65 9.000000
## 5396 43.0 113.0 3.32 0.79 11.100000
## 5397 5.0 16.0 3.15 0.65 11.000000
## 5399 14.0 38.0 3.43 0.65 9.000000
## 5402 6.0 24.0 3.18 1.04 10.900000
## 5404 10.0 26.0 3.16 0.78 12.500000
## 5405 6.0 21.0 3.25 1.02 10.800000
## 5406 6.0 13.0 3.17 0.71 9.500000
## 5407 26.0 62.0 3.18 0.63 10.200000
## 5410 26.0 62.0 3.18 0.63 10.200000
## 5411 15.0 49.0 3.03 0.81 9.700000
## 5412 6.0 15.0 3.09 0.66 11.800000
## 5413 6.0 15.0 3.09 0.66 11.800000
## 5417 11.0 32.0 3.22 0.68 11.700000
## 5418 39.0 106.0 3.36 0.78 11.000000
## 5419 15.0 33.0 3.42 0.90 10.000000
## 5420 16.0 43.0 3.48 0.64 9.100000
## 5421 47.0 133.0 3.38 0.99 9.800000
## 5422 38.0 142.0 3.22 0.55 9.400000
## 5423 23.0 116.0 3.23 0.64 9.500000
## 5424 29.0 53.0 3.24 0.67 9.900000
## 5425 39.0 106.0 3.36 0.78 11.000000
## 5426 33.0 85.0 3.39 0.77 11.400000
## 5427 32.0 55.0 3.34 0.75 8.700000
## 5428 6.0 33.0 3.09 0.57 9.400000
## 5429 1.0 28.0 3.41 0.87 10.300000
## 5430 12.0 42.0 3.16 0.61 10.300000
## 5431 12.0 42.0 3.16 0.61 10.300000
## 5433 13.0 32.0 3.28 0.56 10.000000
## 5434 1.0 28.0 3.41 0.87 10.300000
## 5435 6.0 33.0 3.09 0.57 9.400000
## 5436 5.0 13.0 3.37 0.77 10.700000
## 5439 20.0 47.0 3.26 0.67 9.600000
## 5440 5.0 17.0 3.21 0.73 11.000000
## 5441 5.0 20.0 3.12 0.59 9.900000
## 5442 16.0 53.0 3.06 0.72 11.000000
## 5444 38.0 106.0 3.08 0.59 9.100000
## 5445 10.0 28.0 3.45 0.78 9.500000
## 5446 6.0 21.0 3.26 0.86 10.700000
## 5447 27.0 69.0 3.12 0.75 10.400000
## 5448 6.0 25.0 3.27 0.61 9.400000
## 5449 9.0 25.0 3.33 0.56 9.500000
## 5450 14.0 45.0 3.19 0.73 10.000000
## 5451 14.0 44.0 3.12 0.74 10.000000
## 5460 26.0 121.0 3.23 0.58 9.200000
## 5461 41.0 110.0 3.08 0.61 9.200000
## 5462 25.0 60.0 3.31 0.61 10.100000
## 5468 19.0 42.0 3.57 0.57 11.700000
## 5469 10.0 37.0 3.32 0.91 11.000000
## 5470 19.0 42.0 3.57 0.57 11.700000
## 5471 10.0 28.0 3.14 0.61 10.400000
## 5472 14.0 47.0 3.30 0.56 9.600000
## 5473 20.0 78.0 3.19 0.70 10.000000
## 5475 6.0 14.0 3.34 0.52 10.000000
## 5476 18.0 111.0 3.30 0.60 9.500000
## 5477 17.0 110.0 3.29 0.60 9.800000
## 5478 18.0 40.0 3.14 0.51 9.800000
## 5481 5.0 15.0 3.19 0.43 9.200000
## 5482 10.0 21.0 2.98 0.66 9.900000
## 5484 8.0 38.0 3.47 0.66 9.600000
## 5485 16.0 47.0 3.12 1.02 10.600000
## 5486 18.0 102.0 3.26 0.59 9.300000
## 5488 5.0 13.0 3.05 0.74 10.500000
## 5489 21.0 75.0 3.35 0.57 9.700000
## 5490 23.0 149.0 3.12 0.50 11.500000
## 5491 21.0 75.0 3.35 0.57 9.700000
## 5492 9.0 43.0 3.29 0.58 9.000000
## 5493 20.0 38.0 3.40 0.53 9.500000
## 5494 30.0 109.0 3.27 0.57 9.300000
## 5497 5.0 30.0 3.20 0.48 9.800000
## 5499 7.0 23.0 3.26 0.47 10.000000
## 5501 6.0 14.0 3.30 0.52 9.300000
## 5503 14.0 63.0 3.17 0.62 9.100000
## 5504 6.0 24.0 3.31 0.59 9.200000
## 5505 10.0 20.0 3.34 0.79 12.200000
## 5506 26.0 52.0 3.31 0.53 10.500000
## 5509 25.0 57.0 3.39 0.54 9.200000
## 5511 18.0 29.0 3.32 0.60 10.000000
## 5512 10.0 29.0 3.26 0.74 9.800000
## 5514 28.0 71.0 3.50 0.57 9.700000
## 5515 28.0 71.0 3.50 0.57 9.700000
## 5516 14.0 28.0 3.03 0.93 9.800000
## 5517 4.0 17.0 3.13 0.70 10.200000
## 5518 6.0 16.0 3.09 0.80 9.300000
## 5519 16.0 112.0 3.27 0.61 9.400000
## 5520 14.0 104.0 3.28 0.62 9.400000
## 5521 9.0 32.0 3.13 0.55 9.500000
## 5522 21.0 45.0 3.49 0.96 12.100000
## 5523 21.0 58.0 3.46 0.72 10.200000
## 5524 21.0 58.0 3.46 0.72 10.200000
## 5525 5.0 15.0 3.36 0.49 9.100000
## 5526 5.0 15.0 3.36 0.49 9.100000
## 5527 7.0 31.0 3.27 0.60 9.300000
## 5528 20.0 84.0 3.21 0.61 9.300000
## 5529 7.0 31.0 3.27 0.60 9.300000
## 5530 5.0 19.0 3.25 0.63 9.500000
## 5531 21.0 43.0 3.32 0.57 10.500000
## 5533 46.0 102.0 3.27 0.58 9.500000
## 5537 7.0 23.0 3.35 0.65 10.200000
## 5539 16.0 40.0 3.39 0.62 9.400000
## 5540 21.0 68.0 3.46 0.63 9.500000
## 5541 16.0 40.0 3.39 0.62 9.400000
## 5542 21.0 68.0 3.46 0.63 9.500000
## 5543 16.0 40.0 3.39 0.62 9.400000
## 5544 5.0 11.0 3.37 0.69 10.100000
## 5545 6.0 20.0 3.40 0.63 10.100000
## 5546 5.0 14.0 3.32 0.58 11.000000
## 5547 10.0 28.0 3.33 0.67 11.200000
## 5548 24.0 148.0 3.16 0.57 11.300000
## 5549 8.0 32.0 2.89 0.50 9.600000
## 5553 7.0 29.0 3.08 0.46 9.500000
## 5554 20.0 53.0 3.14 0.61 9.400000
## 5555 8.0 32.0 2.89 0.50 9.600000
## 5556 23.0 42.0 2.92 0.68 10.500000
## 5557 5.0 20.0 3.32 0.81 9.600000
## 5558 5.0 13.0 3.41 0.57 11.000000
## 5559 5.0 20.0 3.32 0.81 9.600000
## 5560 15.0 42.0 3.31 0.64 9.000000
## 5561 9.0 27.0 3.36 0.70 9.600000
## 5562 5.0 13.0 3.04 0.79 10.200000
## 5563 15.0 54.0 3.03 0.66 10.200000
## 5564 25.0 48.0 3.14 0.56 9.700000
## 5566 6.0 15.0 2.94 0.66 9.200000
## 5567 15.0 31.0 3.15 0.57 11.000000
## 5568 6.0 15.0 2.94 0.66 9.200000
## 5569 30.0 45.0 3.26 0.58 10.000000
## 5570 5.0 13.0 3.20 0.52 9.500000
## 5572 5.0 13.0 3.20 0.52 9.500000
## 5573 7.0 17.0 3.08 0.67 9.300000
## 5574 12.0 31.0 3.26 0.65 10.200000
## 5575 7.0 17.0 3.08 0.67 9.300000
## 5576 12.0 31.0 3.40 0.48 9.900000
## 5577 45.0 87.0 3.48 0.53 10.000000
## 5578 20.0 49.0 3.13 0.54 9.600000
## 5580 16.0 29.0 3.21 0.49 10.200000
## 5581 32.0 58.0 3.33 0.54 9.800000
## 5582 5.0 15.0 3.37 0.56 11.300000
## 5584 5.0 15.0 3.37 0.56 11.300000
## 5585 13.0 40.0 3.44 0.60 9.100000
## 5586 13.0 38.0 3.28 0.59 9.700000
## 5587 4.0 9.0 3.40 0.47 9.400000
## 5592 21.0 122.0 3.32 0.62 9.400000
## 5593 24.0 125.0 3.31 0.61 9.400000
## 5595 8.0 25.0 3.47 0.67 9.500000
## 5596 8.0 25.0 3.47 0.67 9.500000
## 5597 18.0 72.0 3.31 0.53 9.700000
## 5598 5.0 19.0 3.11 0.62 10.800000
## 5600 8.0 25.0 3.47 0.67 9.500000
## 5601 9.0 23.0 3.47 0.67 9.400000
## 5602 22.0 84.0 3.32 0.70 9.600000
## 5603 4.0 14.0 3.29 0.54 9.700000
## 5605 10.0 19.0 3.40 0.47 10.000000
## 5606 16.0 37.0 3.37 0.51 10.500000
## 5607 11.0 35.0 3.34 0.61 11.600000
## 5608 13.0 33.0 3.27 0.66 10.000000
## 5610 16.0 112.0 3.38 0.61 9.500000
## 5611 13.0 33.0 3.36 0.45 9.400000
## 5612 10.0 48.0 3.34 0.46 9.400000
## 5613 21.0 77.0 3.28 0.51 9.800000
## 5614 13.0 34.0 3.29 0.48 9.200000
## 5615 10.0 48.0 3.34 0.46 9.400000
## 5616 12.0 49.0 3.21 0.57 10.000000
## 5617 10.0 22.0 3.22 0.44 9.600000
## 5618 17.0 45.0 3.46 0.54 9.500000
## 5619 10.0 22.0 3.22 0.44 9.600000
## 5620 35.0 106.0 3.10 0.53 9.200000
## 5621 15.0 48.0 3.21 0.59 10.000000
## 5624 5.0 13.0 3.29 0.55 10.400000
## 5626 4.0 11.0 3.46 0.68 9.500000
## 5627 4.0 11.0 3.46 0.68 9.500000
## 5631 10.0 19.0 3.39 0.47 9.600000
## 5632 16.0 72.0 3.55 0.60 9.500000
## 5633 9.0 39.0 3.48 0.62 9.300000
## 5634 11.0 22.0 3.26 0.50 9.500000
## 5635 11.0 22.0 3.26 0.50 9.500000
## 5636 19.0 58.0 3.50 0.65 9.300000
## 5637 28.0 104.0 3.10 0.56 9.200000
## 5638 19.0 38.0 3.35 0.60 9.300000
## 5639 12.0 16.0 3.45 0.68 11.500000
## 5640 28.0 139.0 3.21 0.57 9.500000
## 5641 9.0 18.0 3.46 0.65 9.200000
## 5642 25.0 101.0 3.13 0.53 10.000000
## 5643 21.0 101.0 3.13 0.51 9.500000
## 5644 12.0 28.0 3.52 0.73 9.500000
## 5645 12.0 57.0 3.30 0.47 9.000000
## 5646 16.0 68.0 3.30 0.48 9.400000
## 5647 12.0 31.0 3.52 0.72 9.600000
## 5648 12.0 28.0 3.52 0.73 9.500000
## 5649 17.0 40.0 3.29 0.55 9.500000
## 5650 17.0 40.0 3.29 0.55 9.500000
## 5651 24.0 66.0 3.39 0.61 9.400000
## 5652 17.0 40.0 3.29 0.55 9.500000
## 5656 10.0 31.0 3.25 0.50 9.800000
## 5657 10.0 31.0 3.25 0.50 9.800000
## 5658 33.0 88.0 3.19 0.52 9.200000
## 5659 9.0 104.0 3.23 0.57 9.700000
## 5660 5.0 35.0 3.25 0.42 9.600000
## 5661 8.0 19.0 3.31 0.53 10.000000
## 5662 5.0 35.0 3.25 0.42 9.600000
## 5663 11.0 44.0 3.31 0.55 9.500000
## 5664 12.0 48.0 3.31 0.54 9.500000
## 5665 12.0 74.0 3.14 0.54 9.400000
## 5666 13.0 98.0 3.45 0.62 9.500000
## 5667 24.0 94.0 3.55 0.53 9.700000
## 5668 7.0 32.0 3.39 0.54 9.600000
## 5669 24.0 94.0 3.55 0.53 9.700000
## 5670 23.0 143.0 3.28 0.55 9.400000
## 5671 23.0 144.0 3.27 0.55 9.400000
## 5672 1.0 44.0 3.30 0.92 9.500000
## 5673 2.0 45.0 3.31 0.91 9.500000
## 5677 7.0 34.0 3.36 0.61 10.500000
## 5678 21.0 92.0 3.50 0.60 9.800000
## 5680 9.0 37.0 3.66 0.65 9.800000
## 5681 26.0 96.0 3.36 0.53 10.000000
## 5682 9.0 37.0 3.66 0.65 9.800000
## 5683 20.0 85.0 3.55 0.59 9.800000
## 5684 11.0 61.0 3.21 0.50 9.500000
## 5685 11.0 61.0 3.21 0.50 9.500000
## 5686 19.0 58.0 3.18 0.56 10.100000
## 5687 19.0 58.0 3.18 0.56 10.100000
## 5688 21.0 119.0 3.09 0.52 9.300000
## 5689 18.0 82.0 3.33 0.68 9.700000
## 5690 25.0 130.0 3.23 0.54 9.600000
## 5691 17.0 87.0 3.48 0.60 9.700000
## 5692 7.0 13.0 3.38 0.56 10.800000
## 5693 7.0 26.0 3.17 0.53 12.500000
## 5695 24.0 64.0 3.10 0.74 9.600000
## 5696 21.0 42.0 3.24 0.81 10.800000
## 5697 5.0 14.0 3.29 0.52 10.700000
## 5698 5.0 14.0 3.29 0.52 10.700000
## 5699 26.0 108.0 3.25 0.51 9.400000
## 5700 8.0 17.0 3.23 0.44 10.000000
## 5702 14.0 46.0 3.24 0.66 9.600000
## 5703 4.0 18.0 3.26 0.57 9.900000
## 5704 4.0 10.0 3.33 0.70 12.800000
## 5705 4.0 10.0 3.27 0.71 12.500000
## 5706 4.0 10.0 3.33 0.70 12.800000
## 5707 4.0 12.0 3.26 0.86 9.200000
## 5708 4.0 15.0 3.22 0.55 10.300000
## 5709 4.0 14.0 3.30 0.47 10.500000
## 5711 20.0 38.0 3.24 0.71 10.800000
## 5712 4.0 7.0 3.44 0.58 11.400000
## 5714 20.0 38.0 3.24 0.71 10.800000
## 5715 8.0 30.0 3.23 0.58 10.500000
## 5716 19.0 27.0 3.28 0.73 11.900000
## 5717 21.0 47.0 3.29 0.45 9.400000
## 5718 9.0 59.0 3.28 0.54 9.600000
## 5719 9.0 22.0 3.34 0.60 9.700000
## 5721 15.0 36.0 3.61 0.64 9.800000
## 5722 15.0 36.0 3.61 0.64 9.800000
## 5723 6.0 16.0 3.24 0.53 10.300000
## 5724 15.0 37.0 3.36 0.49 10.700000
## 5725 4.0 8.0 3.40 0.64 11.000000
## 5726 15.0 37.0 3.36 0.49 10.700000
## 5727 34.0 45.0 3.46 0.74 12.700000
## 5728 16.0 24.0 3.56 0.77 11.100000
## 5729 5.0 9.0 3.38 0.55 10.900000
## 5730 16.0 24.0 3.56 0.77 11.100000
## 5731 34.0 48.0 3.38 0.86 9.900000
## 5733 16.0 23.0 3.32 0.47 9.400000
## 5734 27.0 55.0 3.39 0.51 9.300000
## 5735 36.0 100.0 3.26 0.39 11.700000
## 5736 36.0 100.0 3.26 0.39 11.700000
## 5737 9.0 28.0 3.24 0.83 11.200000
## 5738 13.0 26.0 3.46 0.47 10.000000
## 5739 9.0 34.0 3.24 0.77 12.100000
## 5740 21.0 31.0 3.45 0.63 10.300000
## 5741 34.0 68.0 3.23 0.72 10.900000
## 5742 9.0 92.0 3.28 0.62 9.400000
## 5743 26.0 42.0 3.18 0.83 10.600000
## 5744 14.0 31.0 3.59 0.66 9.800000
## 5745 14.0 31.0 3.59 0.66 9.800000
## 5746 12.0 39.0 3.50 0.70 9.900000
## 5747 14.0 31.0 3.59 0.66 9.800000
## 5748 12.0 32.0 3.58 0.66 9.800000
## 5749 9.0 22.0 3.28 0.55 9.500000
## 5750 9.0 22.0 3.28 0.55 9.500000
## 5751 26.0 122.0 3.22 1.07 9.700000
## 5752 41.0 55.0 3.47 0.73 10.900000
## 5753 41.0 55.0 3.47 0.73 10.900000
## 5754 10.0 14.0 3.51 0.71 11.700000
## 5755 41.0 55.0 3.47 0.73 10.900000
## 5756 16.0 47.0 3.40 0.78 11.300000
## 5757 17.0 32.0 3.15 0.67 10.600000
## 5758 15.0 24.0 3.40 0.82 11.200000
## 5759 15.0 85.0 3.51 0.54 9.500000
## 5761 7.0 25.0 3.24 0.44 10.400000
## 5762 17.0 84.0 3.51 0.53 9.700000
## 5763 15.0 85.0 3.51 0.54 9.500000
## 5764 16.0 86.0 3.51 0.54 9.700000
## 5765 13.0 24.0 3.41 0.83 11.300000
## 5766 13.0 22.0 3.40 0.84 11.200000
## 5767 15.0 24.0 3.40 0.82 11.200000
## 5768 27.0 43.0 3.44 0.64 10.900000
## 5769 31.0 43.0 3.41 0.57 11.800000
## 5770 36.0 46.0 3.53 0.57 10.600000
## 5771 28.0 48.0 3.43 0.54 10.000000
## 5772 6.0 10.0 3.23 0.58 11.100000
## 5773 6.0 10.0 3.12 0.65 11.800000
## 5774 7.0 16.0 3.31 0.79 11.800000
## 5775 7.0 14.0 3.40 0.58 10.900000
## 5776 31.0 43.0 3.41 0.57 11.800000
## 5777 30.0 69.0 3.22 0.50 10.000000
## 5778 18.0 88.0 3.53 0.55 9.500000
## 5779 10.0 21.0 3.15 0.49 9.900000
## 5780 30.0 35.0 3.48 0.65 11.400000
## 5782 18.0 88.0 3.53 0.55 9.500000
## 5783 30.0 69.0 3.22 0.50 10.000000
## 5784 9.0 30.0 3.34 0.64 10.500000
## 5785 8.0 28.0 3.33 0.65 10.400000
## 5786 29.0 56.0 3.15 0.79 12.100000
## 5787 32.0 64.0 3.43 0.56 11.200000
## 5789 30.0 52.0 3.44 0.58 10.100000
## 5790 16.0 86.0 3.53 0.57 9.700000
## 5791 10.0 18.0 3.22 0.65 9.300000
## 5792 16.0 86.0 3.53 0.57 9.700000
## 5793 17.0 88.0 3.53 0.58 9.800000
## 5794 27.0 43.0 3.42 0.58 10.700000
## 5795 17.0 43.0 3.31 0.77 12.500000
## 5796 27.0 43.0 3.42 0.58 10.700000
## 5797 17.0 43.0 3.31 0.77 12.500000
## 5799 10.0 39.0 3.40 0.69 11.800000
## 5800 16.0 33.0 3.58 0.69 10.800000
## 5801 16.0 33.0 3.58 0.69 10.800000
## 5802 11.0 18.0 3.41 0.59 10.800000
## 5803 11.0 18.0 3.41 0.59 10.800000
## 5804 15.0 115.0 3.23 0.59 9.500000
## 5805 12.0 78.0 3.39 0.71 11.000000
## 5806 6.0 9.0 3.59 0.54 11.500000
## 5807 34.0 61.0 3.43 0.59 10.800000
## 5808 7.0 11.0 3.29 0.52 11.500000
## 5810 3.0 9.0 3.18 0.60 10.900000
## 5811 4.0 8.0 3.33 0.62 12.200000
## 5812 3.0 10.0 3.27 0.64 12.200000
## 5813 7.0 11.0 3.29 0.52 11.500000
## 5814 3.0 6.0 3.27 0.67 11.900000
## 5816 26.0 45.0 3.38 0.64 10.100000
## 5817 32.0 79.0 3.30 0.72 11.000000
## 5818 38.0 46.0 3.38 0.89 11.800000
## 5819 10.0 23.0 3.24 0.56 10.500000
## 5820 32.0 79.0 3.30 0.72 11.000000
## 5821 38.0 46.0 3.38 0.89 11.800000
## 5822 26.0 45.0 3.38 0.64 10.100000
## 5823 14.0 28.0 3.18 0.80 11.200000
## 5824 53.0 77.0 3.47 0.87 11.000000
## 5826 11.0 75.0 3.20 0.59 9.200000
## 5827 14.0 28.0 3.18 0.80 11.200000
## 5828 10.0 19.0 3.30 0.73 12.000000
## 5829 8.0 25.0 3.69 0.73 10.500000
## 5830 13.0 38.0 3.48 0.65 9.800000
## 5831 29.0 66.0 3.45 0.59 9.500000
## 5832 13.0 38.0 3.48 0.65 9.800000
## 5833 8.0 25.0 3.69 0.73 10.500000
## 5834 19.0 72.0 3.39 0.72 11.800000
## 5835 19.0 72.0 3.39 0.72 11.800000
## 5836 6.0 26.0 3.07 0.60 10.400000
## 5837 23.0 42.0 3.34 0.72 12.900000
## 5838 7.0 11.0 3.61 0.54 11.400000
## 5839 13.0 25.0 3.36 0.76 12.400000
## 5840 9.0 17.0 3.19 0.52 12.500000
## 5841 13.0 52.0 3.22 0.64 10.000000
## 5842 10.0 45.0 3.24 0.60 9.700000
## 5843 11.0 24.0 3.27 0.64 12.100000
## 5844 7.0 20.0 3.14 0.79 11.100000
## 5845 11.0 24.0 3.29 0.99 12.000000
## 5846 6.0 12.0 3.26 0.62 12.400000
## 5847 10.0 21.0 3.41 0.76 11.900000
## 5848 10.0 21.0 3.41 0.76 11.900000
## 5849 10.0 21.0 3.41 0.76 11.900000
## 5850 6.0 12.0 3.26 0.62 12.400000
## 5851 6.0 10.0 3.31 0.68 11.200000
## 5852 5.0 9.0 3.20 0.69 12.100000
## 5853 6.0 11.0 3.44 0.54 12.200000
## 5854 9.0 23.0 3.36 0.67 10.400000
## 5855 5.0 10.0 3.31 0.62 11.300000
## 5856 12.0 51.0 3.29 0.58 11.100000
## 5857 25.0 36.0 3.47 0.71 11.300000
## 5858 12.0 32.0 3.36 0.61 10.000000
## 5859 18.0 38.0 3.16 0.85 11.100000
## 5860 7.0 18.0 3.27 0.62 9.300000
## 5861 6.0 16.0 3.38 0.69 9.500000
## 5862 20.0 27.0 3.15 0.69 11.200000
## 5863 18.0 38.0 3.16 0.85 11.100000
## 5864 24.0 48.0 3.34 0.86 11.000000
## 5865 6.0 10.0 3.13 0.58 11.900000
## 5866 23.0 113.0 3.13 0.48 9.200000
## 5867 29.0 46.0 3.20 0.60 12.200000
## 5868 7.0 22.0 3.46 0.61 10.200000
## 5869 6.0 10.0 3.33 0.87 10.900000
## 5870 6.0 10.0 3.33 0.87 10.900000
## 5871 6.0 13.0 3.22 0.65 11.600000
## 5872 6.0 12.0 3.52 0.63 10.700000
## 5873 7.0 13.0 3.30 0.62 12.100000
## 5874 35.0 72.0 3.44 0.52 9.400000
## 5875 35.0 72.0 3.44 0.52 9.400000
## 5876 31.0 119.0 3.15 0.50 9.100000
## 5877 9.0 29.0 3.28 0.49 11.300000
## 5879 8.0 17.0 3.32 0.71 10.500000
## 5880 13.0 28.0 3.25 0.62 10.000000
## 5882 8.0 17.0 3.32 0.71 10.500000
## 5884 7.0 11.0 3.45 0.58 11.300000
## 5885 3.0 7.0 3.19 0.55 11.400000
## 5886 35.0 70.0 3.44 0.50 9.400000
## 5887 19.0 27.0 3.16 0.49 9.400000
## 5888 14.0 21.0 3.14 0.51 10.900000
## 5889 19.0 27.0 3.16 0.49 9.400000
## 5890 31.0 68.0 3.45 0.48 9.400000
## 5891 30.0 47.0 3.36 0.48 9.400000
## 5892 31.0 68.0 3.45 0.48 9.400000
## 5893 20.0 88.0 3.15 0.43 9.400000
## 5894 19.0 41.0 3.39 0.62 10.100000
## 5895 3.0 11.0 3.71 0.63 12.800000
## 5896 3.0 11.0 3.71 0.63 12.800000
## 5898 7.0 12.0 3.47 0.53 12.900000
## 5899 6.0 12.0 3.44 0.72 11.500000
## 5900 31.0 47.0 3.26 0.82 10.600000
## 5901 13.0 27.0 3.26 0.84 11.700000
## 5902 4.0 8.0 3.36 0.55 12.800000
## 5903 27.0 45.0 3.25 0.54 10.300000
## 5904 4.0 8.0 3.36 0.55 12.800000
## 5905 13.0 27.0 3.26 0.84 11.700000
## 5906 12.0 25.0 3.26 0.84 11.700000
## 5907 12.0 24.0 3.23 0.70 12.000000
## 5908 26.0 55.0 3.18 0.68 10.900000
## 5909 7.0 12.0 3.25 0.55 12.300000
## 5910 12.0 19.0 3.17 0.55 10.400000
## 5912 22.0 31.0 3.38 0.58 10.000000
## 5913 3.0 7.0 3.22 0.58 11.200000
## 5914 14.0 27.0 3.06 0.84 11.400000
## 5915 12.0 28.0 3.27 0.75 12.600000
## 5916 36.0 109.0 2.89 0.44 12.700000
## 5917 36.0 109.0 2.89 0.44 12.700000
## 5918 10.0 23.0 3.53 0.61 10.400000
## 5921 4.0 9.0 3.35 0.54 10.500000
## 5922 3.0 9.0 3.27 0.55 12.300000
## 5923 12.0 18.0 3.32 0.56 10.500000
## 5924 17.0 43.0 3.33 0.60 10.400000
## 5925 14.0 36.0 3.41 0.56 12.600000
## 5926 28.0 52.0 3.49 0.52 11.600000
## 5927 41.0 68.0 3.37 0.54 10.100000
## 5928 12.0 18.0 3.32 0.56 10.500000
## 5929 9.0 14.0 3.42 0.55 11.500000
## 5930 9.0 15.0 3.35 0.58 11.000000
## 5931 5.0 14.0 3.36 0.53 9.600000
## 5932 14.0 27.0 3.30 0.59 10.400000
## 5933 15.0 48.0 3.20 0.47 9.700000
## 5934 5.0 17.0 3.17 0.65 10.600000
## 5935 26.0 35.0 3.22 0.59 12.500000
## 5936 20.0 56.0 3.35 0.56 9.200000
## 5937 25.0 42.0 3.24 0.77 12.600000
## 5938 21.0 39.0 3.33 0.83 11.100000
## 5939 16.0 32.0 3.58 0.67 10.200000
## 5940 13.0 26.0 3.38 0.64 9.800000
## 5941 21.0 39.0 3.33 0.83 11.100000
## 5942 18.0 39.0 3.29 0.81 10.900000
## 5943 12.0 53.0 3.36 0.62 12.200000
## 5944 32.0 38.0 3.32 0.58 11.400000
## 5945 33.0 45.0 3.31 0.62 10.700000
## 5946 27.0 51.0 3.49 0.64 10.400000
## 5947 3.0 14.0 3.27 0.78 10.900000
## 5948 6.0 17.0 3.27 0.77 10.800000
## 5949 27.0 51.0 3.49 0.64 10.400000
## 5951 19.0 25.0 3.56 0.55 12.900000
## 5952 9.0 20.0 3.38 0.77 12.700000
## 5953 5.0 77.0 3.13 0.62 9.100000
## 5954 5.0 77.0 3.13 0.62 9.100000
## 5955 3.0 10.0 3.21 0.59 12.100000
## 5956 28.0 90.0 3.15 0.57 9.100000
## 5957 30.0 52.0 3.19 0.76 11.600000
## 5958 3.0 10.0 3.21 0.59 12.100000
## 5959 3.0 8.0 3.14 0.70 9.900000
## 5960 7.0 16.0 3.21 0.69 12.500000
## 5961 6.0 15.0 3.30 0.64 11.400000
## 5962 6.0 17.0 3.22 0.63 11.800000
## 5963 5.0 10.0 3.28 0.57 11.800000
## 5964 6.0 20.0 3.29 0.60 10.200000
## 5965 13.0 26.0 3.40 0.72 12.500000
## 5966 3.0 10.0 3.02 0.83 10.900000
## 5967 3.0 10.0 3.02 0.83 10.900000
## 5968 28.0 52.0 3.31 0.62 10.800000
## 5969 19.0 37.0 3.18 0.89 11.100000
## 5970 30.0 92.0 3.20 0.58 9.200000
## 5971 33.0 75.0 3.40 0.58 9.500000
## 5972 16.0 37.0 3.31 0.58 10.700000
## 5973 30.0 92.0 3.20 0.58 9.200000
## 5974 45.0 67.0 3.44 0.86 10.200000
## 5975 3.0 8.0 3.15 0.73 11.400000
## 5976 3.0 8.0 3.27 0.58 11.000000
## 5977 3.0 8.0 3.27 0.58 11.000000
## 5979 3.0 8.0 3.16 0.51 11.800000
## 5981 31.0 70.0 3.42 0.59 9.500000
## 5982 32.0 59.0 3.33 0.77 12.000000
## 5983 31.0 70.0 3.42 0.59 9.500000
## 5984 40.0 64.0 3.12 0.49 9.600000
## 5985 3.0 9.0 3.38 0.66 11.600000
## 5986 18.0 30.0 3.29 0.69 11.200000
## 5987 22.0 41.0 3.02 0.76 9.900000
## 5988 22.0 41.0 3.02 0.76 9.900000
## 5989 42.0 74.0 2.98 0.63 11.800000
## 5990 8.0 19.0 3.35 0.60 11.400000
## 5991 10.0 16.0 3.43 0.59 11.500000
## 5992 11.0 31.0 3.33 0.86 12.000000
## 5993 9.0 17.0 3.35 0.49 10.800000
## 5994 6.0 20.0 3.15 0.50 10.500000
## 5995 9.0 17.0 3.35 0.49 10.800000
## 5996 5.0 18.0 3.20 0.52 9.400000
## 5998 5.0 18.0 3.20 0.52 9.400000
## 5999 23.0 36.0 3.11 0.78 12.400000
## 6000 14.0 25.0 3.35 0.63 12.000000
## 6001 18.0 30.0 3.45 0.54 11.200000
## 6002 14.0 25.0 3.35 0.63 12.000000
## 6003 16.0 25.0 3.28 0.66 12.400000
## 6004 13.0 49.0 3.41 0.60 12.800000
## 6005 9.0 17.0 3.21 0.54 12.300000
## 6006 10.0 24.0 3.27 0.85 11.700000
## 6007 4.0 13.0 3.36 0.49 9.500000
## 6008 27.0 66.0 3.17 0.76 10.800000
## 6009 6.0 14.0 3.25 0.64 10.000000
## 6011 6.0 35.0 3.29 0.71 11.000000
## 6012 3.0 10.0 3.12 0.59 9.500000
## 6013 29.0 80.0 3.49 0.66 13.600000
## 6014 15.0 21.0 3.38 0.60 11.300000
## 6015 15.0 21.0 3.38 0.60 11.300000
## 6016 15.0 21.0 3.38 0.60 11.300000
## 6017 14.0 24.0 3.30 0.53 13.300000
## 6018 7.0 15.0 3.52 0.58 12.900000
## 6019 8.0 17.0 3.20 0.72 13.100000
## 6020 21.0 28.0 3.44 0.55 12.300000
## 6021 27.0 33.0 3.45 0.48 12.300000
## 6022 17.0 29.0 3.12 0.65 11.200000
## 6023 3.0 13.0 3.62 0.62 11.500000
## 6024 13.0 27.0 3.14 0.59 11.300000
## 6025 3.0 11.0 3.39 0.54 13.500000
## 6026 26.0 52.0 3.51 0.60 11.500000
## 6027 28.0 89.0 3.22 0.68 10.000000
## 6028 24.0 70.0 3.21 0.69 10.500000
## 6029 5.0 10.0 3.18 0.63 10.400000
## 6030 57.0 135.0 3.32 0.44 9.500000
## 6031 18.0 38.0 3.38 0.88 13.600000
## 6032 10.0 18.0 3.37 0.68 11.200000
## 6033 6.0 15.0 3.30 0.74 11.800000
## 6034 22.0 50.0 3.38 0.60 11.900000
## 6035 6.0 13.0 3.22 0.76 11.400000
## 6036 6.0 13.0 3.22 0.76 11.400000
## 6037 29.0 94.0 3.14 0.58 9.100000
## 6038 16.0 86.0 3.34 0.64 9.500000
## 6039 33.0 79.0 3.41 0.65 9.500000
## 6040 24.0 71.0 3.27 0.85 11.000000
## 6041 6.0 12.0 3.30 0.65 11.400000
## 6042 16.0 20.0 3.61 0.82 10.000000
## 6043 35.0 70.0 3.43 0.62 10.100000
## 6044 31.0 51.0 3.53 0.81 10.400000
## 6046 6.0 14.0 3.21 0.49 11.800000
## 6047 9.0 21.0 3.39 0.66 11.600000
## 6048 6.0 11.0 3.23 0.52 12.000000
## 6049 4.0 12.0 3.30 0.76 12.800000
## 6050 16.0 70.0 3.46 0.65 12.500000
## 6051 9.0 38.0 3.15 0.53 9.800000
## 6052 17.0 38.0 3.23 0.66 11.100000
## 6053 50.0 63.0 3.59 0.68 11.400000
## 6054 9.0 38.0 3.15 0.53 9.800000
## 6055 45.0 88.0 3.33 0.76 11.800000
## 6058 11.0 37.0 3.16 0.67 10.800000
## 6059 6.0 20.0 3.14 0.72 11.100000
## 6060 12.0 21.0 3.21 0.75 10.200000
## 6061 12.0 19.0 3.14 0.71 11.800000
## 6062 10.0 21.0 3.29 0.67 10.000000
## 6063 10.0 21.0 3.29 0.67 10.000000
## 6065 7.0 60.0 2.94 0.98 10.200000
## 6066 29.0 48.0 3.32 0.88 12.400000
## 6067 8.0 44.0 3.21 0.56 12.000000
## 6068 5.0 14.0 3.32 0.62 11.500000
## 6069 5.0 12.0 3.20 0.67 10.500000
## 6070 26.0 44.0 3.42 0.68 10.800000
## 6071 5.0 16.0 3.27 0.74 12.300000
## 6072 26.0 65.0 3.46 0.62 9.500000
## 6073 26.0 65.0 3.46 0.62 9.500000
## 6074 48.0 59.0 3.61 0.70 11.500000
## 6075 23.0 47.0 3.58 0.50 11.200000
## 6076 6.0 11.0 3.35 0.66 12.700000
## 6078 11.0 47.0 3.27 0.81 11.000000
## 6079 11.0 47.0 3.27 0.81 11.000000
## 6080 5.0 11.0 3.19 0.46 11.400000
## 6081 41.0 54.0 3.38 0.86 10.500000
## 6082 16.0 61.0 3.29 0.60 9.300000
## 6083 11.0 119.0 3.36 0.70 10.900000
## 6084 6.0 39.0 3.33 0.46 11.900000
## 6085 6.0 12.0 3.52 0.50 12.200000
## 6086 6.0 39.0 3.33 0.46 11.900000
## 6087 11.0 119.0 3.36 0.70 10.900000
## 6089 6.0 20.0 3.28 0.57 12.500000
## 6091 11.0 41.0 3.52 0.80 12.400000
## 6093 15.0 64.0 3.22 0.59 9.500000
## 6094 21.0 56.0 3.52 0.60 9.500000
## 6095 23.0 94.0 3.21 0.58 9.500000
## 6096 4.0 9.0 3.16 0.54 9.800000
## 6097 19.0 77.0 3.15 0.79 10.900000
## 6098 23.0 94.0 3.21 0.58 9.500000
## 6099 4.0 9.0 3.16 0.54 9.800000
## 6100 5.0 10.0 3.27 0.54 11.200000
## 6101 6.0 12.0 3.35 0.69 11.700000
## 6102 33.0 76.0 3.14 0.55 9.400000
## 6103 24.0 44.0 3.40 0.85 11.000000
## 6104 24.0 44.0 3.40 0.85 11.000000
## 6105 24.0 44.0 3.40 0.85 11.000000
## 6107 24.0 44.0 3.40 0.85 11.000000
## 6108 14.0 24.0 3.45 0.87 11.200000
## 6109 8.0 15.0 3.35 0.62 10.400000
## 6110 22.0 53.0 3.32 0.62 9.300000
## 6111 8.0 15.0 3.35 0.62 10.400000
## 6112 5.0 13.0 3.15 0.75 10.500000
## 6113 6.0 9.0 3.10 0.48 10.400000
## 6114 20.0 29.0 3.26 0.56 11.300000
## 6115 10.0 79.0 3.29 0.69 9.500000
## 6116 43.0 74.0 3.23 0.81 12.000000
## 6117 8.0 24.0 3.24 0.69 10.600000
## 6118 25.0 50.0 3.20 0.83 10.900000
## 6119 17.0 44.0 3.28 0.77 11.500000
## 6120 17.0 44.0 3.28 0.77 11.500000
## 6121 33.0 89.0 3.26 0.46 9.600000
## 6122 9.0 23.0 3.23 0.76 12.000000
## 6124 18.0 77.0 3.15 0.51 9.400000
## 6125 27.0 46.0 3.02 0.47 9.200000
## 6126 8.0 21.0 3.27 0.72 9.600000
## 6128 19.0 66.0 3.40 0.64 9.500000
## 6129 15.0 58.0 3.37 0.78 11.800000
## 6130 48.0 90.0 3.38 0.62 10.800000
## 6131 19.0 66.0 3.40 0.64 9.500000
## 6132 14.0 36.0 3.23 0.49 9.300000
## 6133 11.0 18.0 3.39 0.40 12.800000
## 6134 6.0 113.0 3.30 0.56 11.500000
## 6135 7.0 17.0 3.26 0.64 9.400000
## 6136 11.0 18.0 3.39 0.40 12.800000
## 6137 12.0 24.0 3.38 0.46 9.600000
## 6138 11.0 20.0 3.45 0.56 11.800000
## 6139 36.0 60.0 3.10 0.40 9.300000
## 6140 28.0 65.0 3.16 0.59 9.800000
## 6141 15.0 40.0 3.22 0.60 12.200000
## 6142 10.0 86.0 3.37 0.62 9.500000
## 6143 72.0 160.0 3.33 0.54 10.300000
## 6144 15.0 34.0 3.49 0.68 10.500000
## 6145 15.0 48.0 3.12 0.48 10.000000
## 6146 15.0 34.0 3.49 0.68 10.500000
## 6147 22.0 36.0 3.41 0.75 11.100000
## 6148 24.0 37.0 3.40 0.61 10.900000
## 6149 24.0 37.0 3.40 0.61 10.900000
## 6150 27.0 60.0 3.28 0.59 9.800000
## 6151 6.0 14.0 3.45 0.58 9.800000
## 6152 6.0 13.0 3.43 0.58 9.500000
## 6153 20.0 35.0 3.40 0.69 10.900000
## 6154 26.0 46.0 3.47 0.45 11.000000
## 6155 43.0 60.0 3.10 0.42 9.200000
## 6156 12.0 69.0 3.32 0.70 11.000000
## 6157 15.0 33.0 3.44 0.63 11.300000
## 6158 15.0 33.0 3.44 0.63 11.300000
## 6161 34.0 66.0 3.15 0.58 9.800000
## 6162 13.0 26.0 3.37 0.46 9.600000
## 6163 26.0 51.0 3.38 0.72 11.800000
## 6164 16.0 36.0 3.38 0.60 10.300000
## 6165 16.0 36.0 3.38 0.60 10.300000
## 6166 13.0 19.0 3.10 0.87 11.400000
## 6167 21.0 51.0 3.47 0.55 9.500000
## 6170 24.0 64.0 3.38 0.57 11.700000
## 6171 25.0 44.0 3.50 0.53 11.200000
## 6172 34.0 44.0 3.10 0.43 9.300000
## 6173 17.0 36.0 3.24 0.53 11.200000
## 6174 13.0 81.0 3.24 0.54 9.500000
## 6175 3.0 10.0 3.28 0.56 12.000000
## 6176 3.0 10.0 3.35 0.60 9.700000
## 6177 13.0 81.0 3.24 0.54 9.500000
## 6178 3.0 9.0 3.14 0.57 11.500000
## 6179 28.0 54.0 3.37 0.64 10.400000
## 6180 28.0 54.0 3.37 0.64 10.400000
## 6181 9.0 22.0 3.33 0.68 10.900000
## 6182 17.0 69.0 3.26 0.63 10.200000
## 6183 18.0 36.0 3.39 0.56 10.900000
## 6184 20.0 47.0 3.15 0.57 10.500000
## 6185 17.0 31.0 3.35 0.54 12.400000
## 6186 3.0 7.0 3.22 0.37 13.000000
## 6189 6.0 12.0 3.36 0.59 11.000000
## 6190 25.0 60.0 3.29 0.75 10.900000
## 6191 14.0 28.0 3.62 0.67 12.400000
## 6192 6.0 12.0 3.34 0.49 9.700000
## 6193 25.0 60.0 3.29 0.75 10.900000
## 6194 51.0 77.5 3.20 0.45 9.500000
## 6195 51.0 77.5 3.20 0.45 9.500000
## 6196 15.0 29.0 3.35 0.61 12.100000
## 6197 11.0 18.0 3.45 0.56 12.200000
## 6200 20.0 57.0 3.60 0.74 11.700000
## 6201 4.0 15.0 3.30 0.80 11.200000
## 6202 28.0 68.0 3.36 0.66 11.200000
## 6203 21.0 68.0 3.12 0.44 9.200000
## 6204 24.0 88.0 3.30 0.53 9.800000
## 6205 22.0 91.0 3.29 0.62 10.100000
## 6206 15.0 29.0 3.41 0.52 11.100000
## 6207 22.0 91.0 3.29 0.62 10.100000
## 6208 27.0 63.0 3.28 0.61 9.200000
## 6209 24.0 88.0 3.30 0.53 9.800000
## 6210 12.0 27.0 3.33 0.59 12.800000
## 6212 20.0 65.0 3.40 0.54 10.100000
## 6213 24.0 69.0 3.40 0.53 10.100000
## 6214 17.0 91.0 3.26 0.58 9.800000
## 6216 10.0 41.0 3.18 0.69 11.900000
## 6217 17.0 91.0 3.26 0.58 9.800000
## 6219 12.0 88.0 3.26 0.66 10.100000
## 6221 9.0 18.0 3.18 0.55 11.400000
## 6222 21.0 55.0 3.18 0.82 11.000000
## 6223 18.0 34.0 3.39 0.60 10.600000
## 6224 18.0 34.0 3.39 0.60 10.600000
## 6225 18.0 34.0 3.39 0.60 10.600000
## 6226 18.0 34.0 3.39 0.60 10.600000
## 6227 13.0 38.0 3.34 0.52 9.300000
## 6228 17.0 91.0 3.29 0.56 9.800000
## 6229 17.0 91.0 3.29 0.56 9.800000
## 6230 31.0 67.0 3.26 0.46 9.200000
## 6231 6.0 25.0 3.09 0.43 9.700000
## 6232 12.0 48.0 3.18 0.51 9.600000
## 6234 19.0 40.0 3.38 0.66 12.600000
## 6235 15.0 26.0 3.36 0.45 9.500000
## 6236 15.0 26.0 3.36 0.45 9.500000
## 6237 15.0 26.0 3.36 0.45 9.500000
## 6238 13.0 31.0 3.36 0.54 10.500000
## 6239 13.0 31.0 3.36 0.54 10.500000
## 6240 13.0 31.0 3.36 0.54 10.500000
## 6241 17.0 31.0 3.37 0.51 10.400000
## 6242 13.0 31.0 3.36 0.54 10.500000
## 6243 8.0 20.0 3.09 0.53 11.000000
## 6244 10.0 28.0 3.25 0.53 10.200000
## 6245 5.0 13.0 3.52 0.56 11.400000
## 6246 7.0 12.0 3.34 0.39 9.500000
## 6247 7.0 12.0 3.34 0.39 9.500000
## 6248 21.0 41.0 3.41 0.52 10.800000
## 6249 32.0 73.0 3.34 0.57 10.000000
## 6250 8.0 46.0 3.32 0.51 11.800000
## 6251 14.0 57.0 3.37 0.46 10.300000
## 6252 14.0 57.0 3.37 0.46 10.300000
## 6253 7.0 28.0 3.35 0.52 10.000000
## 6254 5.0 32.0 3.36 0.44 10.100000
## 6255 4.0 28.0 3.36 0.44 10.100000
## 6256 27.0 67.0 3.60 0.59 11.100000
## 6257 52.0 98.0 3.28 0.50 9.500000
## 6258 6.0 28.0 3.07 0.65 10.033333
## 6259 11.0 38.0 3.24 0.56 10.900000
## 6260 13.0 54.0 3.36 0.54 10.100000
## 6261 6.0 28.0 3.07 0.65 10.033333
## 6262 11.0 63.0 3.29 0.48 9.800000
## 6263 10.0 31.0 3.46 0.53 11.800000
## 6264 10.0 42.0 3.18 0.62 9.500000
## 6265 10.0 45.0 3.24 0.50 9.800000
## 6267 16.0 74.0 3.27 0.50 9.800000
## 6268 4.0 8.0 3.33 0.37 10.400000
## 6272 34.0 89.0 3.24 0.45 9.300000
## 6274 13.0 100.0 3.26 0.52 9.900000
## 6275 7.0 31.0 3.11 0.46 10.000000
## 6277 10.0 28.0 3.29 0.51 9.900000
## 6278 11.0 35.0 3.36 0.62 10.800000
## 6279 11.0 35.0 3.36 0.62 10.800000
## 6280 4.0 25.0 3.38 0.45 9.600000
## 6281 25.0 105.0 3.30 0.49 9.900000
## 6282 25.0 105.0 3.30 0.49 9.900000
## 6283 20.0 84.0 3.19 0.50 9.500000
## 6284 34.0 85.0 3.19 0.42 9.200000
## 6285 8.0 23.0 3.30 0.58 9.600000
## 6286 8.0 23.0 3.30 0.58 9.600000
## 6287 7.0 49.0 3.35 0.68 10.300000
## 6288 36.0 111.0 3.10 0.53 9.700000
## 6289 15.0 33.0 3.58 0.59 12.500000
## 6290 5.0 33.0 3.37 0.58 11.000000
## 6291 5.0 12.0 3.17 0.48 9.800000
## 6292 19.0 59.0 3.30 0.48 10.200000
## 6293 27.0 73.0 3.32 0.48 9.200000
## 6294 3.0 12.0 3.31 0.65 9.550000
## 6295 4.0 11.0 3.31 0.65 9.550000
## 6296 17.0 104.0 3.28 0.52 9.900000
## 6297 13.0 28.0 3.52 0.62 10.200000
## 6298 10.0 24.0 3.42 0.72 11.100000
## 6299 33.0 141.0 3.25 0.51 9.900000
## 6300 33.0 141.0 3.25 0.51 9.900000
## 6301 6.0 24.0 3.44 0.82 11.900000
## 6303 12.0 46.0 3.43 0.62 10.700000
## 6304 18.0 34.0 3.28 0.90 11.300000
## 6305 8.0 22.0 3.22 0.94 10.900000
## 6306 40.0 54.0 3.54 0.93 10.700000
## 6308 40.0 54.0 3.54 0.93 10.700000
## 6310 8.0 19.0 3.56 0.73 10.600000
## 6311 8.0 22.0 3.22 0.94 10.900000
## 6312 12.0 89.0 3.04 0.90 10.100000
## 6313 3.0 15.0 3.20 0.78 9.600000
## 6314 8.0 18.0 3.56 0.84 9.400000
## 6315 3.0 15.0 3.20 0.78 9.600000
## 6316 21.0 37.0 3.35 0.77 12.100000
## 6317 3.0 19.0 3.16 0.46 9.800000
## 6318 32.0 133.0 3.27 0.45 9.900000
## 6319 3.0 19.0 3.16 0.46 9.800000
## 6320 24.0 58.0 3.34 0.58 9.400000
## 6321 39.0 55.0 3.39 0.84 11.400000
## 6322 14.0 31.0 3.50 0.67 11.000000
## 6323 8.0 23.0 3.26 0.70 9.600000
## 6324 8.0 23.0 3.26 0.70 9.600000
## 6326 6.0 23.0 3.30 0.58 11.200000
## 6327 27.0 55.0 3.31 0.63 11.000000
## 6328 38.0 67.0 3.33 0.93 11.300000
## 6329 18.0 47.0 3.37 0.62 10.400000
## 6330 13.0 74.0 3.26 0.54 9.900000
## 6331 3.0 11.0 3.48 0.85 11.700000
## 6332 11.0 25.0 3.42 0.74 10.100000
## 6335 27.0 90.0 3.15 0.65 8.500000
## 6337 3.0 8.0 3.41 0.47 10.300000
## 6338 31.0 92.0 3.32 0.68 11.066667
## 6339 15.0 28.0 3.23 0.73 11.300000
## 6340 19.0 98.0 3.16 0.52 9.566667
## 6341 18.0 30.0 3.40 0.75 9.800000
## 6342 8.0 22.0 3.38 0.49 11.700000
## 6343 31.0 92.0 3.32 0.68 11.100000
## 6344 19.0 98.0 3.16 0.52 9.600000
## 6345 18.0 30.0 3.40 0.75 9.800000
## 6346 22.0 39.0 3.40 0.74 9.700000
## 6347 40.0 54.0 3.40 0.73 9.700000
## 6348 15.0 29.0 3.23 0.76 11.300000
## 6349 15.0 28.0 3.23 0.73 11.300000
## 6350 8.0 17.0 3.33 0.78 11.000000
## 6351 37.0 53.0 3.35 0.76 11.600000
## 6352 27.0 85.0 3.41 0.58 9.000000
## 6353 7.0 23.0 3.21 0.69 10.900000
## 6354 9.0 17.0 3.50 0.63 10.900000
## 6355 38.0 89.0 3.30 0.50 10.550000
## 6356 27.0 85.0 3.41 0.58 9.000000
## 6357 8.0 20.0 3.39 0.60 10.500000
## 6358 7.0 15.0 3.32 0.80 11.900000
## 6360 6.0 13.0 3.59 0.61 10.000000
## 6361 14.0 31.0 3.36 0.58 10.400000
## 6362 14.0 39.0 3.34 0.53 10.800000
## 6363 34.0 53.0 3.41 0.67 9.700000
## 6364 34.0 53.0 3.41 0.67 9.700000
## 6365 31.0 54.0 3.30 0.65 10.000000
## 6367 31.0 54.0 3.30 0.65 10.000000
## 6369 8.0 24.0 2.88 0.47 9.700000
## 6370 8.0 16.0 3.43 0.52 12.600000
## 6371 23.0 44.0 3.38 0.79 11.100000
## 6372 14.0 45.0 3.38 0.54 11.000000
## 6377 3.0 14.0 3.40 0.52 10.200000
## 6378 10.0 22.0 3.39 0.68 10.600000
## 6379 6.0 13.0 3.66 0.62 10.100000
## 6380 10.0 22.0 3.39 0.68 10.600000
## 6382 6.0 12.0 3.35 0.61 10.700000
## 6383 4.0 11.0 3.53 0.64 10.900000
## 6384 8.0 25.0 3.37 0.55 9.700000
## 6385 9.0 23.0 3.38 0.60 10.300000
## 6386 9.0 17.0 3.52 0.78 10.600000
## 6387 5.0 13.0 3.72 0.58 11.400000
## 6388 4.0 11.0 3.44 0.76 10.800000
## 6389 8.0 18.0 3.39 0.56 12.400000
## 6390 5.0 13.0 3.72 0.58 11.400000
## 6391 6.0 18.0 3.57 0.54 11.950000
## 6392 23.0 147.0 3.26 0.59 9.700000
## 6393 15.0 28.0 3.42 0.70 10.000000
## 6394 15.0 28.0 3.35 0.81 10.600000
## 6395 23.0 147.0 3.26 0.59 9.700000
## 6396 7.0 16.0 3.45 0.63 11.500000
## 6397 7.0 13.0 3.53 0.58 10.800000
## 6398 7.0 16.0 3.45 0.63 11.500000
## 6399 8.0 15.0 3.26 0.53 9.600000
## 6400 21.0 64.0 3.16 0.53 9.400000
## 6401 15.0 60.0 3.31 0.54 9.800000
## 6402 6.0 14.0 3.51 0.69 11.000000
## 6403 5.0 12.0 3.36 0.55 11.400000
## 6404 6.0 12.0 3.55 0.63 9.950000
## 6405 6.0 14.0 3.51 0.66 10.800000
## 6406 5.0 12.0 3.36 0.55 11.400000
## 6408 7.0 20.0 3.28 0.70 11.100000
## 6409 26.0 48.0 3.47 0.77 9.700000
## 6410 19.0 27.0 3.44 0.67 9.800000
## 6411 11.0 17.0 3.53 0.65 10.400000
## 6412 17.0 65.0 3.33 0.60 10.500000
## 6413 16.0 65.0 3.53 0.72 9.233333
## 6414 16.0 65.0 3.53 0.72 9.250000
## 6416 29.0 44.0 3.38 0.83 10.300000
## 6417 7.0 20.0 3.32 0.63 10.500000
## 6418 14.0 27.0 3.44 0.58 10.200000
## 6419 29.0 44.0 3.38 0.83 10.300000
## 6420 9.0 23.0 3.39 0.43 9.050000
## 6422 29.0 61.0 3.34 0.60 10.400000
## 6423 22.0 47.0 3.39 0.78 10.000000
## 6424 18.0 34.0 3.33 0.64 9.700000
## 6425 18.0 38.0 3.30 0.65 9.600000
## 6426 15.0 24.0 3.29 0.66 10.800000
## 6427 21.0 59.0 3.31 0.67 10.100000
## 6428 42.0 52.0 3.42 0.60 10.200000
## 6429 9.0 18.0 3.42 0.69 11.300000
## 6430 13.0 28.0 3.60 0.66 10.200000
## 6431 18.0 22.0 3.21 0.68 9.900000
## 6432 32.0 84.0 3.39 0.61 9.000000
## 6433 13.0 29.0 3.42 0.62 11.700000
## 6434 15.0 35.0 3.36 0.59 9.700000
## 6435 24.0 45.0 3.60 0.68 10.300000
## 6436 20.0 31.0 3.50 0.64 10.200000
## 6437 15.0 26.0 3.57 0.63 12.000000
## 6438 34.0 60.0 3.46 0.78 9.900000
## 6439 11.0 32.0 3.56 0.63 11.600000
## 6440 19.0 49.0 3.40 0.76 10.900000
## 6441 29.0 38.0 3.30 0.56 10.750000
## 6442 14.0 19.0 3.25 0.57 10.400000
## 6443 12.0 19.0 3.17 0.81 11.200000
## 6444 16.0 28.0 3.36 0.64 10.100000
## 6445 17.0 26.0 3.36 0.61 10.200000
## 6446 12.0 26.0 3.55 0.51 12.100000
## 6447 19.0 50.0 3.10 0.58 10.400000
## 6448 17.0 24.0 3.24 0.70 11.400000
## 6449 17.0 26.0 3.45 0.53 9.500000
## 6450 18.0 27.0 3.44 0.54 9.400000
## 6451 32.0 54.0 3.51 0.66 11.300000
## 6452 18.0 28.0 3.41 0.60 9.400000
## 6453 15.0 23.0 3.54 0.60 11.000000
## 6454 15.0 24.0 3.44 0.68 10.550000
## 6455 12.0 20.0 3.53 0.56 9.900000
## 6456 15.0 23.0 3.54 0.60 11.000000
## 6458 31.0 131.0 3.21 0.52 9.900000
## 6459 31.0 131.0 3.21 0.52 9.900000
## 6460 31.0 131.0 3.21 0.52 9.900000
## 6461 12.0 20.0 3.29 0.54 10.100000
## 6462 12.0 20.0 3.29 0.54 10.100000
## 6463 12.0 20.0 3.29 0.54 10.100000
## 6464 26.0 42.0 3.39 0.82 10.900000
## 6466 12.0 20.0 3.29 0.54 10.100000
## 6467 25.0 42.0 3.34 0.59 9.200000
## 6468 15.0 34.0 3.48 0.57 11.500000
## 6470 15.0 25.0 3.44 0.65 11.100000
## 6471 35.0 104.0 3.33 0.51 9.500000
## 6472 15.0 50.0 3.58 0.67 12.500000
## 6474 12.0 20.0 3.26 0.64 11.800000
## 6475 16.0 29.0 3.30 0.78 10.800000
## 6476 13.0 27.0 3.54 0.60 11.900000
## 6477 13.0 20.0 3.42 0.67 11.300000
## 6478 24.0 32.0 3.54 0.60 11.300000
## 6479 9.0 26.0 3.36 0.60 11.900000
## 6480 24.0 32.0 3.54 0.60 11.300000
## 6481 13.0 27.0 3.57 0.50 11.900000
## 6482 32.0 98.0 3.33 0.62 9.800000
## 6483 24.0 34.0 3.29 0.80 11.600000
## 6484 22.0 48.0 3.30 0.84 11.500000
## 6485 34.0 60.0 3.34 0.85 11.400000
## 6486 18.0 28.0 3.55 0.66 10.900000
## 6487 34.0 102.0 3.27 0.78 12.800000
## 6488 29.0 79.0 3.29 0.54 9.200000
## 6489 26.0 35.0 3.32 0.82 11.600000
## 6490 16.0 26.0 3.67 0.56 11.600000
## 6491 29.0 40.0 3.42 0.75 11.000000
## 6492 28.0 38.0 3.42 0.82 9.500000
## 6493 32.0 44.0 3.45 0.58 10.500000
## 6494 39.0 51.0 3.52 0.76 11.200000
## 6495 29.0 40.0 3.42 0.75 11.000000
## 6496 32.0 44.0 3.57 0.71 10.200000
## 6497 18.0 42.0 3.39 0.66 11.000000
## quality_label
## 1 Good
## 2 Good
## 3 Good
## 4 Good
## 5 Good
## 6 Good
## 7 Good
## 8 Good
## 9 Good
## 10 Good
## 11 Bad
## 12 Bad
## 13 Bad
## 14 Very Good
## 15 Bad
## 16 Very Good
## 17 Good
## 19 Good
## 20 Bad
## 22 Very Good
## 23 Very Good
## 24 Bad
## 25 Good
## 26 Good
## 27 Good
## 28 Good
## 29 Good
## 30 Very Good
## 31 Good
## 33 Good
## 34 Good
## 35 Bad
## 36 Bad
## 37 Bad
## 38 Good
## 39 Bad
## 40 Bad
## 43 Good
## 44 Good
## 45 Good
## 46 Very Good
## 47 Very Bad
## 48 Bad
## 49 Good
## 50 Bad
## 51 Good
## 52 Very Good
## 53 Very Good
## 54 Good
## 56 Good
## 57 Good
## 58 Good
## 59 Good
## 60 Good
## 61 Good
## 62 Good
## 63 Bad
## 64 Good
## 65 Good
## 66 Bad
## 67 Very Good
## 68 Bad
## 69 Very Good
## 70 Bad
## 71 Good
## 72 Bad
## 73 Bad
## 74 Good
## 75 Very Good
## 76 Bad
## 77 Very Good
## 78 Very Good
## 79 Bad
## 80 Bad
## 81 Good
## 82 Good
## 83 Bad
## 84 Good
## 85 Bad
## 86 Good
## 87 Good
## 88 Good
## 89 Bad
## 90 Good
## 91 Good
## 92 Bad
## 93 Very Good
## 94 Very Good
## 95 Very Good
## 96 Good
## 98 Very Good
## 101 Bad
## 102 Bad
## 103 Bad
## 104 Bad
## 105 Bad
## 106 Good
## 107 Bad
## 108 Good
## 109 Good
## 110 Bad
## 111 Good
## 112 Bad
## 113 Bad
## 114 Bad
## 115 Bad
## 116 Very Bad
## 117 Good
## 118 Good
## 119 Bad
## 120 Bad
## 121 Bad
## 122 Bad
## 123 Bad
## 124 Good
## 125 Good
## 126 Good
## 127 Bad
## 128 Very Good
## 129 Very Good
## 130 Good
## 131 Bad
## 132 Very Good
## 133 Bad
## 134 Bad
## 135 Bad
## 136 Bad
## 137 Good
## 138 Bad
## 139 Very Good
## 140 Good
## 141 Bad
## 142 Bad
## 143 Good
## 144 Good
## 145 Good
## 146 Good
## 147 Good
## 148 Very Bad
## 149 Very Good
## 150 Good
## 151 Very Good
## 152 Good
## 153 Good
## 154 Bad
## 155 Good
## 156 Good
## 157 Good
## 158 Very Good
## 159 Very Good
## 160 Very Good
## 161 Very Good
## 162 Bad
## 163 Bad
## 164 Good
## 165 Bad
## 166 Bad
## 167 Good
## 168 Very Good
## 169 Bad
## 171 Good
## 172 Good
## 173 Very Bad
## 174 Very Good
## 175 Bad
## 176 Good
## 177 Very Bad
## 178 Bad
## 179 Very Bad
## 180 Good
## 181 Good
## 182 Bad
## 183 Bad
## 184 Good
## 185 Bad
## 186 Bad
## 187 Good
## 188 Bad
## 189 Very Good
## 190 Very Bad
## 191 Good
## 192 Bad
## 193 Good
## 194 Bad
## 198 Bad
## 199 Bad
## 200 Bad
## 201 Bad
## 202 Bad
## 203 Bad
## 204 Good
## 205 Very Bad
## 206 Bad
## 207 Bad
## 209 Bad
## 210 Good
## 211 Bad
## 212 Very Good
## 213 Bad
## 214 Good
## 215 Very Good
## 216 Bad
## 217 Bad
## 218 Bad
## 219 Bad
## 220 Bad
## 221 Bad
## 222 Good
## 223 Very Good
## 224 Good
## 225 Good
## 226 Bad
## 227 Good
## 228 Good
## 229 Good
## 230 Bad
## 231 Very Bad
## 232 Good
## 233 Good
## 234 Good
## 235 Good
## 236 Good
## 237 Good
## 238 Good
## 239 Very Good
## 240 Good
## 241 Bad
## 242 Bad
## 243 Very Good
## 244 Good
## 245 Bad
## 247 Very Good
## 248 Very Good
## 249 Very Good
## 250 Bad
## 251 Very Bad
## 252 Very Bad
## 253 Bad
## 254 Very Bad
## 255 Good
## 256 Very Good
## 257 Very Good
## 258 Very Good
## 259 Good
## 260 Very Bad
## 261 Good
## 262 Bad
## 263 Bad
## 264 Good
## 265 Good
## 266 Bad
## 267 Good
## 268 Bad
## 269 Good
## 270 Good
## 271 Good
## 272 Bad
## 273 Bad
## 274 Bad
## 275 Bad
## 276 Good
## 277 Good
## 278 Bad
## 279 Very Bad
## 280 Very Good
## 281 Very Good
## 282 Very Good
## 283 Very Bad
## 284 Bad
## 285 Bad
## 286 Bad
## 287 Good
## 288 Very Good
## 289 Very Good
## 290 Very Good
## 291 Very Good
## 292 Good
## 293 Bad
## 294 Very Good
## 295 Very Bad
## 296 Good
## 297 Bad
## 298 Very Good
## 299 Good
## 300 Good
## 301 Good
## 302 Good
## 303 Good
## 304 Good
## 305 Good
## 306 Good
## 307 Bad
## 308 Good
## 309 Very Good
## 310 Good
## 311 Very Good
## 312 Very Good
## 313 Good
## 314 Good
## 315 Bad
## 316 Good
## 317 Good
## 318 Bad
## 319 Very Good
## 320 Good
## 321 Very Good
## 322 Bad
## 323 Good
## 324 Good
## 327 Good
## 328 Good
## 329 Good
## 330 Bad
## 331 Very Good
## 332 Bad
## 333 Good
## 334 Bad
## 335 Bad
## 336 Good
## 337 Good
## 338 Good
## 339 Bad
## 340 Very Good
## 341 Very Good
## 342 Good
## 343 Good
## 344 Bad
## 345 Good
## 346 Good
## 347 Very Good
## 348 Good
## 349 Good
## 350 Bad
## 351 Very Good
## 352 Very Good
## 353 Good
## 354 Very Good
## 355 Good
## 356 Good
## 357 Good
## 358 Good
## 359 Good
## 360 Good
## 361 Good
## 362 Bad
## 363 Good
## 364 Good
## 365 Very Good
## 366 Very Good
## 367 Good
## 368 Good
## 369 Good
## 370 Bad
## 371 Good
## 372 Good
## 374 Good
## 375 Very Good
## 376 Very Good
## 377 Very Good
## 378 Very Good
## 379 Good
## 380 Very Good
## 381 Very Good
## 382 Good
## 383 Good
## 384 Good
## 385 Very Good
## 386 Very Good
## 387 Very Good
## 388 Bad
## 389 Good
## 390 Very Good
## 391 Very Good
## 392 Bad
## 393 Good
## 394 Good
## 395 Bad
## 397 Bad
## 398 Good
## 399 Bad
## 400 Good
## 401 Good
## 402 Bad
## 403 Bad
## 404 Bad
## 405 Good
## 407 Very Good
## 408 Bad
## 409 Good
## 410 Bad
## 411 Good
## 412 Good
## 413 Bad
## 414 Bad
## 415 Good
## 416 Good
## 417 Good
## 418 Bad
## 419 Good
## 420 Good
## 421 Very Good
## 422 Good
## 423 Good
## 424 Good
## 425 Very Good
## 426 Good
## 427 Good
## 428 Bad
## 429 Bad
## 430 Bad
## 431 Bad
## 432 Bad
## 433 Very Good
## 434 Very Bad
## 435 Very Good
## 436 Very Good
## 437 Bad
## 438 Very Good
## 439 Very Good
## 440 Bad
## 441 Very Good
## 442 Good
## 443 Very Good
## 444 Good
## 445 Good
## 446 Very Bad
## 447 Bad
## 448 Good
## 449 Good
## 450 Very Good
## 451 Bad
## 452 Bad
## 453 Very Good
## 454 Very Good
## 455 Very Good
## 456 Good
## 457 Very Good
## 458 Bad
## 459 Good
## 460 Bad
## 461 Bad
## 462 Bad
## 463 Bad
## 464 Good
## 465 Bad
## 466 Bad
## 467 Good
## 468 Good
## 469 Bad
## 470 Bad
## 471 Good
## 472 Bad
## 473 Good
## 474 Very Good
## 475 Good
## 476 Bad
## 477 Very Good
## 478 Good
## 479 Good
## 480 Good
## 481 Bad
## 482 Good
## 483 Bad
## 484 Bad
## 486 Good
## 487 Good
## 488 Good
## 489 Good
## 490 Good
## 491 Good
## 492 Very Good
## 493 Good
## 494 Good
## 495 Good
## 496 Good
## 497 Very Bad
## 498 Good
## 499 Bad
## 500 Very Bad
## 501 Good
## 502 Good
## 505 Good
## 506 Good
## 507 Bad
## 508 Very Good
## 509 Good
## 510 Very Good
## 511 Good
## 512 Good
## 513 Good
## 514 Good
## 515 Very Good
## 516 Good
## 517 Bad
## 518 Good
## 519 Good
## 520 Bad
## 521 Bad
## 522 Bad
## 523 Good
## 524 Good
## 525 Bad
## 526 Good
## 527 Very Bad
## 528 Good
## 529 Good
## 530 Good
## 531 Good
## 533 Good
## 534 Good
## 535 Good
## 536 Bad
## 537 Bad
## 538 Good
## 539 Bad
## 540 Good
## 541 Very Bad
## 543 Good
## 544 Good
## 545 Good
## 546 Good
## 547 Good
## 548 Good
## 549 Very Good
## 551 Very Good
## 552 Very Good
## 553 Very Good
## 554 Very Good
## 555 Very Good
## 556 Very Good
## 557 Bad
## 558 Good
## 559 Bad
## 560 Good
## 561 Very Good
## 562 Bad
## 563 Good
## 564 Very Good
## 565 Bad
## 566 Good
## 567 Good
## 568 Bad
## 569 Good
## 570 Good
## 572 Very Good
## 573 Bad
## 574 Very Good
## 575 Very Good
## 576 Good
## 577 Good
## 578 Very Good
## 579 Very Good
## 580 Very Good
## 582 Bad
## 583 Good
## 584 Good
## 585 Very Good
## 586 Good
## 587 Good
## 588 Very Good
## 589 Very Good
## 590 Good
## 591 Bad
## 592 Good
## 593 Bad
## 594 Bad
## 595 Bad
## 596 Very Good
## 597 Bad
## 598 Good
## 599 Very Good
## 600 Very Good
## 602 Good
## 603 Bad
## 604 Bad
## 605 Good
## 606 Good
## 607 Bad
## 608 Bad
## 609 Bad
## 610 Good
## 611 Very Good
## 612 Good
## 613 Bad
## 614 Bad
## 615 Bad
## 616 Bad
## 617 Very Good
## 618 Good
## 619 Good
## 620 Good
## 621 Bad
## 622 Bad
## 623 Good
## 624 Bad
## 625 Bad
## 626 Very Good
## 627 Very Bad
## 628 Good
## 629 Good
## 630 Good
## 631 Bad
## 632 Bad
## 633 Good
## 634 Bad
## 635 Good
## 636 Good
## 637 Very Good
## 638 Bad
## 639 Bad
## 640 Bad
## 641 Very Good
## 642 Very Bad
## 643 Good
## 644 Bad
## 645 Bad
## 646 Bad
## 648 Good
## 649 Bad
## 650 Very Good
## 651 Very Good
## 652 Very Good
## 653 Very Good
## 654 Good
## 655 Very Good
## 656 Good
## 657 Good
## 658 Bad
## 659 Bad
## 661 Bad
## 662 Very Good
## 663 Very Bad
## 664 Bad
## 665 Good
## 666 Bad
## 667 Good
## 668 Good
## 669 Good
## 670 Bad
## 671 Good
## 672 Good
## 673 Very Good
## 674 Good
## 675 Bad
## 676 Good
## 677 Good
## 678 Very Good
## 679 Very Good
## 680 Very Good
## 681 Bad
## 683 Good
## 685 Bad
## 686 Bad
## 687 Very Good
## 689 Good
## 690 Very Good
## 691 Very Bad
## 692 Good
## 693 Bad
## 694 Bad
## 695 Good
## 696 Bad
## 697 Good
## 698 Bad
## 699 Bad
## 700 Bad
## 701 Bad
## 702 Very Good
## 703 Very Bad
## 704 Good
## 705 Good
## 706 Bad
## 707 Bad
## 708 Good
## 709 Good
## 710 Bad
## 711 Bad
## 712 Good
## 713 Good
## 714 Bad
## 715 Good
## 716 Very Good
## 717 Good
## 718 Bad
## 719 Very Good
## 720 Very Good
## 721 Bad
## 722 Bad
## 723 Good
## 724 Very Good
## 725 Very Good
## 726 Bad
## 727 Very Good
## 728 Bad
## 729 Bad
## 731 Good
## 732 Good
## 733 Very Good
## 734 Good
## 735 Bad
## 736 Good
## 737 Good
## 738 Bad
## 739 Very Good
## 740 Good
## 741 Very Bad
## 742 Good
## 743 Good
## 744 Bad
## 745 Bad
## 747 Good
## 748 Good
## 749 Good
## 750 Good
## 751 Good
## 752 Good
## 753 Good
## 754 Good
## 755 Bad
## 756 Very Good
## 757 Bad
## 758 Good
## 761 Good
## 762 Good
## 763 Bad
## 764 Good
## 765 Good
## 766 Good
## 768 Good
## 769 Very Good
## 770 Very Good
## 771 Very Good
## 774 Bad
## 775 Very Good
## 776 Good
## 777 Good
## 778 Bad
## 779 Very Good
## 780 Very Good
## 781 Very Bad
## 782 Good
## 783 Very Good
## 784 Very Good
## 785 Bad
## 786 Good
## 787 Good
## 788 Good
## 789 Very Good
## 790 Good
## 791 Good
## 792 Very Good
## 793 Bad
## 794 Very Good
## 795 Bad
## 796 Bad
## 797 Good
## 798 Good
## 799 Good
## 800 Very Good
## 801 Good
## 802 Bad
## 803 Bad
## 804 Very Good
## 805 Good
## 806 Good
## 807 Bad
## 808 Good
## 809 Good
## 810 Good
## 811 Bad
## 812 Good
## 813 Very Good
## 814 Good
## 815 Good
## 816 Bad
## 817 Bad
## 818 Bad
## 819 Bad
## 820 Bad
## 821 Very Good
## 822 Good
## 823 Bad
## 824 Good
## 825 Bad
## 826 Good
## 827 Good
## 828 Very Good
## 829 Very Good
## 830 Very Good
## 831 Good
## 832 Very Bad
## 833 Very Good
## 834 Good
## 835 Good
## 836 Very Good
## 837 Very Good
## 838 Very Good
## 839 Very Good
## 840 Very Good
## 841 Very Good
## 842 Very Good
## 843 Very Good
## 844 Very Good
## 845 Very Good
## 846 Very Good
## 847 Bad
## 848 Bad
## 849 Very Good
## 850 Good
## 851 Very Good
## 852 Bad
## 854 Bad
## 856 Very Good
## 857 Bad
## 858 Bad
## 859 Very Good
## 861 Very Good
## 862 Very Good
## 863 Good
## 864 Good
## 865 Bad
## 866 Good
## 868 Very Good
## 869 Very Good
## 870 Good
## 872 Bad
## 873 Good
## 875 Bad
## 876 Very Good
## 877 Very Good
## 878 Good
## 879 Good
## 880 Very Good
## 881 Very Good
## 882 Good
## 883 Good
## 884 Good
## 885 Good
## 886 Very Good
## 887 Good
## 888 Very Good
## 889 Good
## 890 Very Good
## 891 Good
## 892 Very Good
## 893 Bad
## 894 Very Good
## 895 Very Good
## 896 Good
## 897 Good
## 898 Good
## 899 Good
## 900 Good
## 901 Very Good
## 902 Good
## 903 Bad
## 904 Good
## 905 Very Good
## 906 Very Bad
## 907 Very Bad
## 908 Very Good
## 909 Very Bad
## 910 Bad
## 911 Bad
## 912 Bad
## 913 Bad
## 914 Bad
## 915 Very Bad
## 916 Bad
## 917 Very Good
## 918 Good
## 919 Good
## 920 Very Good
## 921 Very Good
## 922 Good
## 923 Good
## 924 Good
## 925 Very Good
## 926 Bad
## 927 Bad
## 928 Very Good
## 929 Bad
## 930 Bad
## 931 Very Good
## 932 Bad
## 933 Good
## 934 Bad
## 935 Bad
## 936 Bad
## 937 Bad
## 938 Bad
## 939 Good
## 940 Very Good
## 941 Bad
## 942 Good
## 943 Very Good
## 944 Very Good
## 945 Very Good
## 946 Very Good
## 948 Bad
## 949 Very Bad
## 950 Bad
## 951 Bad
## 952 Good
## 953 Good
## 954 Bad
## 955 Good
## 956 Bad
## 957 Bad
## 958 Very Good
## 959 Very Good
## 960 Good
## 961 Good
## 962 Very Good
## 963 Good
## 964 Good
## 965 Good
## 966 Bad
## 967 Good
## 968 Good
## 969 Very Good
## 970 Very Good
## 971 Very Good
## 972 Very Good
## 973 Good
## 974 Very Good
## 975 Good
## 976 Bad
## 977 Good
## 978 Bad
## 979 Very Good
## 982 Very Good
## 983 Good
## 984 Good
## 985 Bad
## 986 Good
## 987 Good
## 988 Good
## 989 Bad
## 990 Very Good
## 991 Good
## 992 Very Bad
## 993 Bad
## 994 Very Bad
## 995 Good
## 996 Good
## 997 Bad
## 998 Good
## 999 Good
## 1000 Very Good
## 1001 Very Good
## 1002 Bad
## 1003 Good
## 1004 Very Good
## 1005 Good
## 1006 Good
## 1007 Good
## 1008 Bad
## 1009 Very Good
## 1010 Good
## 1011 Good
## 1012 Very Good
## 1013 Good
## 1014 Bad
## 1016 Bad
## 1017 Bad
## 1018 Good
## 1019 Good
## 1020 Good
## 1021 Very Good
## 1022 Very Good
## 1023 Very Good
## 1024 Good
## 1026 Good
## 1027 Good
## 1028 Very Bad
## 1029 Very Good
## 1030 Very Bad
## 1031 Good
## 1032 Good
## 1033 Good
## 1034 Good
## 1036 Good
## 1037 Bad
## 1038 Bad
## 1039 Very Good
## 1040 Bad
## 1041 Very Bad
## 1042 Bad
## 1043 Very Bad
## 1044 Bad
## 1045 Very Good
## 1046 Bad
## 1047 Bad
## 1048 Bad
## 1049 Bad
## 1050 Good
## 1051 Bad
## 1053 Bad
## 1054 Very Bad
## 1055 Bad
## 1056 Bad
## 1057 Good
## 1058 Bad
## 1059 Good
## 1060 Very Bad
## 1061 Very Good
## 1062 Bad
## 1063 Bad
## 1064 Bad
## 1065 Good
## 1066 Bad
## 1067 Good
## 1068 Very Good
## 1069 Very Good
## 1070 Good
## 1071 Very Good
## 1072 Bad
## 1073 Very Good
## 1074 Bad
## 1075 Good
## 1076 Very Good
## 1077 Good
## 1078 Bad
## 1079 Bad
## 1080 Good
## 1081 Very Good
## 1082 Good
## 1083 Good
## 1084 Good
## 1085 Very Good
## 1086 Bad
## 1087 Very Good
## 1088 Very Good
## 1089 Good
## 1090 Very Good
## 1091 Good
## 1092 Good
## 1093 Good
## 1094 Very Good
## 1095 Bad
## 1096 Very Good
## 1097 Good
## 1098 Very Good
## 1099 Good
## 1100 Very Good
## 1101 Good
## 1102 Good
## 1103 Bad
## 1104 Bad
## 1105 Bad
## 1106 Very Good
## 1107 Very Good
## 1108 Very Good
## 1109 Very Good
## 1110 Very Bad
## 1111 Very Good
## 1112 Good
## 1113 Good
## 1114 Bad
## 1115 Very Bad
## 1116 Very Good
## 1117 Bad
## 1118 Bad
## 1119 Bad
## 1120 Bad
## 1121 Good
## 1122 Good
## 1123 Very Good
## 1124 Bad
## 1125 Bad
## 1126 Good
## 1128 Very Good
## 1129 Bad
## 1130 Very Good
## 1131 Good
## 1132 Good
## 1133 Bad
## 1134 Bad
## 1135 Bad
## 1136 Good
## 1137 Very Good
## 1138 Very Good
## 1139 Bad
## 1140 Bad
## 1141 Good
## 1142 Bad
## 1143 Bad
## 1144 Bad
## 1145 Bad
## 1146 Bad
## 1147 Bad
## 1148 Bad
## 1149 Good
## 1150 Bad
## 1151 Bad
## 1152 Bad
## 1153 Very Bad
## 1154 Good
## 1155 Very Bad
## 1156 Very Bad
## 1157 Good
## 1158 Good
## 1160 Good
## 1161 Good
## 1162 Good
## 1163 Very Good
## 1165 Good
## 1166 Bad
## 1167 Bad
## 1168 Good
## 1169 Bad
## 1170 Good
## 1171 Good
## 1172 Bad
## 1173 Good
## 1174 Bad
## 1175 Good
## 1176 Bad
## 1177 Very Good
## 1178 Good
## 1179 Bad
## 1180 Bad
## 1181 Bad
## 1182 Good
## 1183 Bad
## 1184 Good
## 1185 Very Good
## 1186 Bad
## 1187 Bad
## 1188 Very Good
## 1189 Good
## 1190 Bad
## 1191 Good
## 1192 Very Good
## 1193 Good
## 1194 Very Good
## 1195 Good
## 1196 Good
## 1197 Very Good
## 1198 Very Good
## 1199 Good
## 1200 Very Good
## 1201 Good
## 1202 Very Good
## 1203 Bad
## 1204 Good
## 1205 Good
## 1207 Good
## 1208 Bad
## 1209 Good
## 1210 Good
## 1211 Good
## 1212 Bad
## 1213 Good
## 1214 Good
## 1215 Good
## 1216 Bad
## 1217 Very Good
## 1219 Very Good
## 1220 Very Good
## 1221 Good
## 1222 Very Good
## 1223 Good
## 1224 Bad
## 1225 Very Good
## 1226 Good
## 1227 Very Good
## 1228 Bad
## 1229 Good
## 1230 Very Bad
## 1231 Good
## 1232 Very Good
## 1233 Very Good
## 1234 Good
## 1235 Good
## 1236 Bad
## 1237 Good
## 1238 Bad
## 1239 Very Good
## 1240 Bad
## 1241 Good
## 1242 Very Good
## 1243 Very Good
## 1244 Very Good
## 1245 Bad
## 1247 Very Good
## 1248 Good
## 1249 Very Good
## 1250 Bad
## 1251 Very Good
## 1252 Bad
## 1253 Good
## 1254 Very Good
## 1256 Good
## 1257 Good
## 1258 Good
## 1259 Good
## 1260 Good
## 1261 Good
## 1262 Good
## 1263 Good
## 1265 Bad
## 1266 Very Good
## 1267 Very Good
## 1268 Very Good
## 1269 Bad
## 1270 Good
## 1271 Very Good
## 1272 Bad
## 1273 Bad
## 1274 Bad
## 1275 Good
## 1276 Good
## 1277 Very Good
## 1278 Bad
## 1279 Good
## 1280 Good
## 1281 Good
## 1282 Very Good
## 1283 Bad
## 1284 Very Good
## 1285 Very Good
## 1286 Good
## 1287 Very Good
## 1288 Very Good
## 1289 Very Good
## 1290 Good
## 1291 Good
## 1292 Good
## 1293 Good
## 1294 Very Bad
## 1295 Very Bad
## 1296 Good
## 1297 Good
## 1298 Very Good
## 1299 Good
## 1300 Bad
## 1301 Good
## 1302 Bad
## 1303 Good
## 1304 Good
## 1306 Very Good
## 1307 Very Good
## 1308 Bad
## 1309 Good
## 1310 Good
## 1311 Good
## 1312 Good
## 1313 Bad
## 1314 Bad
## 1315 Good
## 1316 Good
## 1317 Good
## 1318 Bad
## 1319 Good
## 1320 Bad
## 1321 Good
## 1322 Good
## 1323 Good
## 1324 Bad
## 1325 Good
## 1326 Very Good
## 1327 Good
## 1328 Good
## 1329 Good
## 1330 Bad
## 1331 Bad
## 1332 Good
## 1333 Very Good
## 1334 Very Good
## 1335 Good
## 1336 Good
## 1337 Very Good
## 1338 Bad
## 1339 Bad
## 1340 Good
## 1341 Good
## 1342 Bad
## 1343 Good
## 1344 Good
## 1345 Very Good
## 1346 Very Good
## 1347 Very Good
## 1348 Very Good
## 1349 Very Good
## 1350 Very Bad
## 1351 Very Good
## 1352 Very Good
## 1353 Good
## 1354 Bad
## 1355 Bad
## 1356 Bad
## 1357 Good
## 1358 Good
## 1359 Very Good
## 1360 Very Good
## 1361 Good
## 1362 Very Good
## 1363 Very Good
## 1364 Very Bad
## 1365 Bad
## 1366 Very Good
## 1367 Good
## 1368 Bad
## 1369 Good
## 1371 Good
## 1372 Very Good
## 1373 Good
## 1374 Good
## 1375 Very Good
## 1376 Very Good
## 1377 Good
## 1378 Good
## 1379 Very Good
## 1380 Good
## 1381 Very Good
## 1382 Very Good
## 1383 Good
## 1384 Good
## 1385 Good
## 1386 Bad
## 1388 Good
## 1389 Very Good
## 1390 Good
## 1391 Good
## 1392 Good
## 1393 Good
## 1394 Good
## 1396 Very Good
## 1397 Very Good
## 1398 Very Good
## 1399 Very Good
## 1400 Good
## 1401 Very Good
## 1403 Very Good
## 1404 Very Good
## 1405 Bad
## 1406 Very Bad
## 1407 Very Good
## 1408 Good
## 1409 Very Good
## 1410 Good
## 1411 Good
## 1412 Good
## 1413 Very Good
## 1414 Good
## 1415 Good
## 1416 Bad
## 1417 Good
## 1420 Very Good
## 1421 Very Bad
## 1422 Good
## 1423 Bad
## 1424 Very Bad
## 1425 Good
## 1426 Good
## 1427 Good
## 1428 Bad
## 1429 Very Good
## 1430 Bad
## 1431 Very Bad
## 1432 Bad
## 1433 Very Good
## 1434 Good
## 1435 Bad
## 1436 Bad
## 1438 Very Good
## 1439 Bad
## 1440 Bad
## 1441 Bad
## 1442 Bad
## 1443 Bad
## 1444 Good
## 1445 Good
## 1446 Good
## 1447 Good
## 1448 Good
## 1449 Good
## 1450 Good
## 1451 Good
## 1452 Bad
## 1453 Good
## 1454 Very Good
## 1455 Bad
## 1457 Good
## 1458 Good
## 1459 Good
## 1460 Good
## 1461 Good
## 1462 Good
## 1463 Good
## 1464 Good
## 1465 Very Good
## 1467 Good
## 1468 Very Good
## 1469 Bad
## 1470 Bad
## 1471 Very Good
## 1472 Good
## 1473 Bad
## 1474 Good
## 1475 Very Bad
## 1476 Good
## 1478 Good
## 1479 Good
## 1480 Good
## 1481 Good
## 1482 Good
## 1483 Good
## 1484 Very Bad
## 1485 Very Bad
## 1486 Good
## 1487 Good
## 1489 Good
## 1490 Bad
## 1491 Good
## 1492 Bad
## 1493 Bad
## 1494 Very Good
## 1495 Very Good
## 1496 Very Good
## 1497 Bad
## 1498 Very Good
## 1499 Good
## 1500 Good
## 1501 Very Good
## 1502 Bad
## 1503 Bad
## 1504 Very Good
## 1506 Very Good
## 1507 Good
## 1508 Good
## 1509 Good
## 1510 Bad
## 1511 Bad
## 1512 Good
## 1513 Very Good
## 1514 Good
## 1515 Very Good
## 1516 Good
## 1517 Good
## 1518 Good
## 1519 Good
## 1520 Bad
## 1521 Good
## 1522 Bad
## 1523 Bad
## 1524 Good
## 1525 Good
## 1526 Bad
## 1528 Good
## 1529 Good
## 1530 Good
## 1531 Bad
## 1532 Very Good
## 1533 Very Good
## 1534 Good
## 1536 Good
## 1537 Bad
## 1538 Good
## 1539 Good
## 1540 Good
## 1542 Very Bad
## 1543 Good
## 1544 Good
## 1545 Bad
## 1546 Good
## 1547 Good
## 1548 Good
## 1549 Good
## 1550 Good
## 1551 Good
## 1553 Very Good
## 1554 Very Good
## 1555 Very Good
## 1556 Very Good
## 1557 Good
## 1558 Good
## 1559 Very Bad
## 1560 Very Bad
## 1561 Good
## 1562 Bad
## 1563 Very Good
## 1564 Good
## 1565 Bad
## 1566 Good
## 1567 Bad
## 1568 Bad
## 1569 Good
## 1570 Bad
## 1571 Bad
## 1572 Good
## 1573 Good
## 1574 Bad
## 1575 Very Bad
## 1577 Good
## 1578 Very Bad
## 1580 Very Bad
## 1581 Bad
## 1582 Good
## 1583 Very Good
## 1585 Good
## 1586 Bad
## 1587 Bad
## 1588 Good
## 1589 Bad
## 1590 Good
## 1591 Good
## 1592 Good
## 1593 Good
## 1594 Good
## 1595 Good
## 1596 Good
## 1597 Bad
## 1598 Good
## 1601 Good
## 1602 Good
## 1603 Bad
## 1604 Very Good
## 1605 Bad
## 1606 Very Good
## 1607 Good
## 1608 Very Good
## 1609 Bad
## 1610 Very Good
## 1611 Good
## 1612 Good
## 1613 Very Good
## 1614 Very Good
## 1615 Bad
## 1616 Good
## 1617 Good
## 1618 Good
## 1619 Good
## 1620 Very Good
## 1621 Very Good
## 1622 Bad
## 1623 Good
## 1624 Good
## 1625 Very Good
## 1626 Good
## 1627 Good
## 1628 Bad
## 1629 Good
## 1630 Good
## 1631 Bad
## 1632 Good
## 1633 Very Good
## 1634 Very Good
## 1635 Good
## 1636 Good
## 1637 Bad
## 1638 Good
## 1640 Bad
## 1641 Bad
## 1642 Good
## 1643 Very Good
## 1644 Very Good
## 1645 Very Good
## 1646 Very Good
## 1647 Good
## 1648 Very Good
## 1649 Bad
## 1650 Very Bad
## 1651 Very Good
## 1653 Very Bad
## 1655 Bad
## 1656 Bad
## 1657 Bad
## 1658 Good
## 1659 Bad
## 1660 Bad
## 1661 Good
## 1662 Good
## 1663 Very Good
## 1665 Very Bad
## 1666 Very Good
## 1667 Bad
## 1668 Good
## 1669 Very Good
## 1670 Good
## 1671 Good
## 1672 Very Good
## 1673 Bad
## 1674 Bad
## 1675 Good
## 1676 Bad
## 1677 Very Good
## 1678 Good
## 1679 Good
## 1680 Bad
## 1681 Bad
## 1683 Very Good
## 1684 Very Good
## 1685 Very Good
## 1686 Very Good
## 1687 Bad
## 1688 Very Good
## 1690 Good
## 1691 Very Bad
## 1692 Very Good
## 1693 Good
## 1694 Bad
## 1695 Good
## 1696 Good
## 1697 Good
## 1698 Good
## 1699 Good
## 1700 Good
## 1701 Good
## 1702 Bad
## 1703 Very Bad
## 1704 Bad
## 1705 Bad
## 1706 Good
## 1707 Good
## 1708 Bad
## 1709 Very Bad
## 1710 Bad
## 1711 Bad
## 1712 Bad
## 1713 Good
## 1714 Good
## 1715 Bad
## 1716 Very Good
## 1717 Good
## 1718 Good
## 1719 Very Bad
## 1720 Good
## 1721 Very Good
## 1724 Very Good
## 1725 Good
## 1726 Good
## 1727 Good
## 1729 Bad
## 1730 Good
## 1731 Good
## 1733 Bad
## 1734 Good
## 1735 Good
## 1736 Good
## 1737 Bad
## 1738 Good
## 1739 Bad
## 1740 Very Bad
## 1741 Good
## 1742 Good
## 1743 Good
## 1744 Good
## 1746 Bad
## 1747 Bad
## 1748 Good
## 1749 Bad
## 1750 Good
## 1751 Good
## 1752 Very Good
## 1753 Good
## 1754 Very Good
## 1755 Good
## 1756 Good
## 1757 Bad
## 1758 Bad
## 1759 Bad
## 1760 Bad
## 1761 Good
## 1762 Good
## 1763 Very Good
## 1764 Good
## 1765 Bad
## 1766 Bad
## 1767 Bad
## 1768 Bad
## 1769 Bad
## 1770 Very Good
## 1771 Good
## 1772 Good
## 1773 Good
## 1774 Good
## 1775 Good
## 1777 Bad
## 1778 Good
## 1779 Very Good
## 1780 Very Good
## 1781 Bad
## 1783 Good
## 1784 Good
## 1785 Very Good
## 1786 Good
## 1787 Very Good
## 1788 Very Good
## 1789 Bad
## 1790 Very Good
## 1791 Bad
## 1792 Bad
## 1793 Good
## 1794 Bad
## 1795 Bad
## 1796 Good
## 1797 Bad
## 1798 Very Good
## 1799 Good
## 1800 Good
## 1801 Good
## 1802 Bad
## 1803 Good
## 1804 Good
## 1805 Good
## 1806 Bad
## 1807 Bad
## 1808 Good
## 1809 Bad
## 1810 Good
## 1811 Good
## 1812 Bad
## 1813 Good
## 1814 Good
## 1815 Very Good
## 1816 Good
## 1817 Very Good
## 1818 Very Bad
## 1819 Good
## 1820 Good
## 1821 Good
## 1822 Bad
## 1823 Very Good
## 1824 Good
## 1825 Bad
## 1826 Bad
## 1827 Bad
## 1828 Good
## 1829 Good
## 1830 Very Good
## 1831 Very Good
## 1832 Very Good
## 1833 Very Good
## 1834 Very Good
## 1835 Good
## 1837 Good
## 1838 Very Good
## 1839 Good
## 1840 Good
## 1841 Bad
## 1842 Very Good
## 1843 Good
## 1844 Good
## 1845 Good
## 1846 Bad
## 1847 Bad
## 1848 Bad
## 1850 Good
## 1851 Very Good
## 1852 Good
## 1853 Very Good
## 1854 Bad
## 1855 Very Good
## 1856 Good
## 1858 Bad
## 1859 Bad
## 1860 Good
## 1861 Good
## 1862 Good
## 1863 Very Good
## 1864 Bad
## 1865 Good
## 1867 Good
## 1868 Good
## 1869 Very Good
## 1870 Very Good
## 1871 Good
## 1872 Good
## 1873 Bad
## 1874 Bad
## 1875 Bad
## 1876 Bad
## 1877 Good
## 1878 Good
## 1879 Good
## 1880 Good
## 1881 Bad
## 1882 Good
## 1883 Bad
## 1884 Bad
## 1885 Bad
## 1886 Good
## 1887 Bad
## 1888 Bad
## 1889 Bad
## 1890 Bad
## 1891 Bad
## 1892 Bad
## 1893 Bad
## 1894 Bad
## 1895 Bad
## 1896 Good
## 1897 Good
## 1898 Good
## 1899 Good
## 1900 Very Good
## 1902 Bad
## 1903 Good
## 1904 Bad
## 1905 Good
## 1906 Good
## 1907 Bad
## 1908 Very Good
## 1909 Very Good
## 1910 Bad
## 1911 Bad
## 1912 Good
## 1913 Good
## 1914 Good
## 1915 Good
## 1916 Very Good
## 1917 Bad
## 1918 Good
## 1919 Good
## 1920 Good
## 1921 Very Good
## 1922 Bad
## 1923 Bad
## 1924 Bad
## 1925 Very Bad
## 1928 Bad
## 1929 Good
## 1930 Bad
## 1931 Good
## 1934 Bad
## 1935 Good
## 1936 Bad
## 1937 Good
## 1938 Very Good
## 1939 Bad
## 1940 Bad
## 1941 Bad
## 1942 Bad
## 1943 Bad
## 1944 Bad
## 1946 Good
## 1947 Good
## 1949 Very Good
## 1950 Bad
## 1951 Bad
## 1953 Very Good
## 1954 Good
## 1955 Bad
## 1956 Bad
## 1957 Bad
## 1958 Good
## 1960 Bad
## 1961 Bad
## 1962 Bad
## 1963 Bad
## 1965 Bad
## 1966 Good
## 1967 Good
## 1968 Very Good
## 1969 Good
## 1970 Very Good
## 1971 Good
## 1972 Very Good
## 1973 Bad
## 1974 Bad
## 1975 Bad
## 1976 Good
## 1977 Bad
## 1978 Good
## 1979 Good
## 1980 Good
## 1981 Very Good
## 1982 Very Good
## 1983 Very Good
## 1984 Very Good
## 1985 Very Good
## 1986 Good
## 1987 Good
## 1988 Bad
## 1989 Good
## 1990 Very Good
## 1991 Very Bad
## 1992 Very Good
## 1993 Bad
## 1994 Good
## 1995 Good
## 1996 Good
## 1997 Good
## 1998 Good
## 1999 Good
## 2000 Good
## 2001 Bad
## 2002 Bad
## 2003 Good
## 2004 Good
## 2005 Good
## 2006 Good
## 2007 Good
## 2008 Good
## 2009 Bad
## 2010 Very Good
## 2011 Good
## 2012 Bad
## 2013 Bad
## 2014 Good
## 2015 Bad
## 2016 Good
## 2017 Very Good
## 2018 Bad
## 2019 Very Good
## 2020 Good
## 2021 Good
## 2022 Good
## 2023 Good
## 2024 Good
## 2028 Bad
## 2029 Good
## 2030 Good
## 2031 Good
## 2032 Bad
## 2033 Good
## 2034 Bad
## 2035 Bad
## 2036 Bad
## 2038 Bad
## 2039 Bad
## 2040 Bad
## 2041 Good
## 2042 Bad
## 2043 Good
## 2044 Good
## 2045 Good
## 2046 Bad
## 2047 Bad
## 2048 Bad
## 2049 Bad
## 2050 Very Good
## 2052 Bad
## 2053 Bad
## 2054 Bad
## 2055 Bad
## 2056 Good
## 2057 Bad
## 2058 Very Good
## 2059 Bad
## 2060 Bad
## 2061 Bad
## 2062 Good
## 2063 Bad
## 2064 Bad
## 2065 Good
## 2066 Bad
## 2067 Bad
## 2068 Bad
## 2069 Good
## 2070 Very Good
## 2071 Good
## 2072 Good
## 2073 Bad
## 2074 Bad
## 2075 Good
## 2076 Bad
## 2077 Bad
## 2078 Good
## 2079 Good
## 2080 Very Bad
## 2081 Bad
## 2082 Bad
## 2083 Good
## 2084 Bad
## 2085 Good
## 2086 Good
## 2087 Bad
## 2088 Good
## 2089 Good
## 2090 Good
## 2091 Bad
## 2092 Bad
## 2093 Bad
## 2094 Bad
## 2095 Bad
## 2096 Bad
## 2097 Bad
## 2098 Bad
## 2099 Good
## 2100 Bad
## 2101 Bad
## 2102 Good
## 2103 Bad
## 2104 Bad
## 2105 Bad
## 2106 Bad
## 2107 Bad
## 2108 Good
## 2109 Good
## 2110 Good
## 2111 Bad
## 2112 Bad
## 2113 Bad
## 2114 Bad
## 2115 Good
## 2116 Bad
## 2117 Very Bad
## 2118 Bad
## 2119 Good
## 2120 Very Bad
## 2121 Bad
## 2122 Very Good
## 2123 Bad
## 2124 Bad
## 2125 Very Good
## 2126 Bad
## 2127 Bad
## 2129 Good
## 2130 Bad
## 2131 Bad
## 2132 Good
## 2133 Good
## 2134 Good
## 2135 Good
## 2136 Bad
## 2137 Good
## 2138 Bad
## 2139 Bad
## 2140 Bad
## 2141 Bad
## 2142 Bad
## 2143 Bad
## 2144 Very Good
## 2145 Good
## 2146 Good
## 2147 Good
## 2148 Bad
## 2149 Bad
## 2150 Good
## 2151 Good
## 2152 Bad
## 2153 Good
## 2154 Good
## 2156 Bad
## 2157 Very Bad
## 2158 Good
## 2159 Good
## 2160 Very Bad
## 2161 Good
## 2162 Very Good
## 2163 Good
## 2164 Good
## 2166 Bad
## 2167 Bad
## 2168 Very Good
## 2169 Very Good
## 2170 Very Good
## 2171 Very Good
## 2172 Very Good
## 2173 Bad
## 2174 Bad
## 2175 Very Good
## 2176 Very Good
## 2177 Bad
## 2178 Very Good
## 2179 Bad
## 2180 Good
## 2181 Good
## 2182 Good
## 2183 Bad
## 2184 Bad
## 2185 Good
## 2186 Very Good
## 2188 Bad
## 2189 Good
## 2190 Good
## 2191 Good
## 2192 Bad
## 2193 Good
## 2194 Good
## 2195 Good
## 2196 Bad
## 2197 Good
## 2198 Good
## 2199 Bad
## 2200 Good
## 2201 Bad
## 2202 Good
## 2203 Bad
## 2204 Bad
## 2205 Bad
## 2206 Bad
## 2208 Very Good
## 2209 Bad
## 2210 Good
## 2211 Very Good
## 2212 Good
## 2213 Good
## 2214 Good
## 2215 Bad
## 2216 Good
## 2217 Bad
## 2218 Good
## 2219 Good
## 2220 Very Good
## 2221 Good
## 2222 Good
## 2223 Very Good
## 2224 Good
## 2225 Very Good
## 2226 Very Bad
## 2227 Bad
## 2228 Bad
## 2229 Very Good
## 2230 Good
## 2231 Very Good
## 2232 Good
## 2233 Good
## 2234 Bad
## 2235 Bad
## 2236 Good
## 2237 Bad
## 2238 Very Bad
## 2239 Good
## 2240 Good
## 2241 Bad
## 2242 Bad
## 2243 Bad
## 2244 Bad
## 2245 Bad
## 2246 Very Good
## 2247 Very Bad
## 2248 Good
## 2249 Good
## 2250 Bad
## 2251 Good
## 2252 Very Good
## 2253 Bad
## 2254 Bad
## 2255 Good
## 2256 Good
## 2257 Bad
## 2258 Good
## 2259 Bad
## 2260 Good
## 2261 Bad
## 2262 Good
## 2263 Good
## 2264 Bad
## 2265 Good
## 2266 Bad
## 2267 Bad
## 2268 Good
## 2269 Good
## 2270 Good
## 2271 Very Good
## 2272 Good
## 2273 Good
## 2274 Bad
## 2275 Very Good
## 2276 Very Bad
## 2277 Good
## 2278 Good
## 2279 Good
## 2280 Bad
## 2281 Good
## 2282 Good
## 2283 Bad
## 2284 Bad
## 2285 Bad
## 2286 Bad
## 2287 Bad
## 2288 Bad
## 2289 Bad
## 2290 Very Good
## 2291 Very Good
## 2292 Good
## 2293 Good
## 2294 Very Good
## 2295 Very Good
## 2296 Good
## 2297 Very Good
## 2298 Good
## 2299 Very Good
## 2300 Very Good
## 2301 Very Good
## 2302 Bad
## 2303 Bad
## 2304 Bad
## 2305 Good
## 2306 Very Good
## 2307 Bad
## 2308 Bad
## 2309 Bad
## 2310 Good
## 2311 Bad
## 2312 Very Good
## 2313 Bad
## 2314 Very Good
## 2315 Good
## 2316 Good
## 2317 Very Good
## 2318 Bad
## 2319 Very Bad
## 2320 Very Good
## 2321 Good
## 2323 Good
## 2324 Good
## 2325 Bad
## 2326 Good
## 2327 Bad
## 2328 Good
## 2329 Bad
## 2330 Bad
## 2331 Good
## 2332 Bad
## 2333 Good
## 2336 Bad
## 2338 Very Bad
## 2339 Bad
## 2340 Good
## 2341 Good
## 2342 Bad
## 2343 Very Good
## 2344 Bad
## 2345 Good
## 2346 Good
## 2347 Very Bad
## 2348 Good
## 2349 Good
## 2351 Bad
## 2352 Good
## 2353 Good
## 2354 Very Good
## 2355 Good
## 2356 Very Good
## 2357 Good
## 2358 Bad
## 2359 Bad
## 2361 Good
## 2362 Bad
## 2363 Good
## 2364 Bad
## 2365 Bad
## 2366 Bad
## 2367 Bad
## 2368 Good
## 2369 Good
## 2370 Good
## 2371 Very Good
## 2373 Very Bad
## 2374 Very Bad
## 2375 Good
## 2376 Good
## 2377 Good
## 2378 Good
## 2380 Very Bad
## 2381 Very Bad
## 2382 Good
## 2383 Very Good
## 2384 Good
## 2385 Very Good
## 2386 Bad
## 2387 Very Bad
## 2388 Very Bad
## 2389 Very Bad
## 2390 Very Good
## 2391 Very Good
## 2392 Good
## 2393 Very Good
## 2394 Good
## 2396 Bad
## 2398 Good
## 2399 Good
## 2400 Good
## 2401 Very Bad
## 2402 Very Bad
## 2403 Good
## 2405 Bad
## 2406 Bad
## 2407 Good
## 2408 Good
## 2410 Very Bad
## 2411 Good
## 2412 Good
## 2413 Very Bad
## 2414 Very Bad
## 2415 Very Bad
## 2416 Bad
## 2417 Good
## 2419 Bad
## 2420 Bad
## 2421 Very Good
## 2422 Bad
## 2423 Bad
## 2424 Good
## 2425 Bad
## 2426 Good
## 2427 Good
## 2428 Good
## 2429 Good
## 2430 Good
## 2431 Bad
## 2432 Bad
## 2433 Bad
## 2434 Good
## 2435 Good
## 2436 Very Bad
## 2437 Bad
## 2438 Good
## 2439 Bad
## 2440 Good
## 2441 Bad
## 2443 Bad
## 2444 Bad
## 2445 Bad
## 2446 Bad
## 2447 Bad
## 2448 Good
## 2449 Good
## 2450 Good
## 2451 Bad
## 2452 Bad
## 2453 Very Good
## 2454 Good
## 2455 Bad
## 2456 Good
## 2457 Good
## 2458 Good
## 2459 Good
## 2460 Bad
## 2461 Bad
## 2462 Bad
## 2463 Bad
## 2464 Very Good
## 2465 Bad
## 2468 Good
## 2469 Good
## 2470 Bad
## 2471 Bad
## 2472 Very Good
## 2473 Good
## 2474 Good
## 2475 Very Good
## 2476 Bad
## 2477 Good
## 2478 Very Good
## 2479 Good
## 2480 Good
## 2481 Bad
## 2482 Good
## 2483 Good
## 2484 Good
## 2485 Bad
## 2486 Good
## 2487 Bad
## 2488 Good
## 2489 Good
## 2490 Good
## 2491 Good
## 2492 Bad
## 2493 Good
## 2494 Very Bad
## 2495 Very Bad
## 2496 Bad
## 2497 Bad
## 2498 Bad
## 2499 Bad
## 2500 Good
## 2501 Bad
## 2502 Bad
## 2503 Very Bad
## 2504 Very Bad
## 2505 Good
## 2506 Good
## 2507 Good
## 2508 Very Good
## 2509 Good
## 2510 Bad
## 2511 Good
## 2512 Good
## 2513 Good
## 2514 Bad
## 2515 Very Good
## 2516 Very Good
## 2517 Good
## 2518 Good
## 2519 Very Good
## 2520 Bad
## 2521 Bad
## 2522 Very Good
## 2523 Very Good
## 2524 Bad
## 2525 Bad
## 2526 Very Good
## 2527 Very Good
## 2528 Good
## 2529 Good
## 2530 Bad
## 2531 Good
## 2532 Very Bad
## 2533 Very Bad
## 2534 Bad
## 2535 Very Good
## 2536 Good
## 2537 Good
## 2538 Good
## 2539 Good
## 2540 Bad
## 2541 Bad
## 2542 Good
## 2543 Bad
## 2544 Good
## 2545 Good
## 2546 Good
## 2547 Bad
## 2548 Bad
## 2549 Good
## 2550 Bad
## 2551 Bad
## 2552 Good
## 2553 Bad
## 2554 Very Good
## 2555 Very Good
## 2556 Very Good
## 2557 Bad
## 2558 Very Good
## 2559 Very Good
## 2561 Good
## 2562 Bad
## 2563 Good
## 2565 Good
## 2566 Bad
## 2567 Very Good
## 2568 Bad
## 2569 Good
## 2570 Good
## 2571 Bad
## 2572 Good
## 2573 Bad
## 2574 Bad
## 2575 Bad
## 2576 Good
## 2577 Bad
## 2578 Bad
## 2579 Very Good
## 2581 Bad
## 2582 Very Good
## 2583 Very Good
## 2584 Very Good
## 2585 Very Good
## 2586 Very Good
## 2587 Very Good
## 2588 Good
## 2589 Very Good
## 2590 Very Bad
## 2591 Good
## 2592 Very Good
## 2593 Bad
## 2594 Bad
## 2596 Bad
## 2597 Bad
## 2598 Good
## 2599 Bad
## 2600 Good
## 2601 Very Good
## 2602 Bad
## 2603 Good
## 2604 Very Good
## 2605 Very Good
## 2606 Good
## 2607 Good
## 2608 Good
## 2609 Good
## 2610 Good
## 2611 Bad
## 2612 Bad
## 2613 Very Good
## 2614 Bad
## 2615 Bad
## 2616 Very Good
## 2617 Very Good
## 2618 Very Good
## 2619 Very Good
## 2620 Good
## 2621 Bad
## 2622 Bad
## 2623 Very Good
## 2624 Very Good
## 2625 Bad
## 2627 Very Good
## 2628 Very Good
## 2629 Good
## 2631 Good
## 2632 Very Good
## 2633 Bad
## 2634 Bad
## 2636 Good
## 2637 Bad
## 2639 Good
## 2640 Good
## 2641 Good
## 2642 Bad
## 2643 Bad
## 2644 Bad
## 2645 Good
## 2646 Very Good
## 2648 Bad
## 2649 Good
## 2650 Good
## 2651 Bad
## 2652 Bad
## 2653 Very Good
## 2654 Bad
## 2656 Bad
## 2657 Very Bad
## 2658 Very Good
## 2659 Very Good
## 2660 Good
## 2661 Good
## 2662 Good
## 2663 Good
## 2664 Very Good
## 2665 Very Good
## 2666 Bad
## 2667 Very Good
## 2668 Very Good
## 2670 Bad
## 2671 Very Good
## 2672 Very Good
## 2673 Very Good
## 2674 Good
## 2675 Very Good
## 2676 Very Good
## 2677 Good
## 2678 Good
## 2679 Bad
## 2680 Good
## 2681 Good
## 2682 Good
## 2683 Good
## 2684 Bad
## 2685 Good
## 2686 Very Good
## 2687 Good
## 2688 Bad
## 2689 Good
## 2690 Good
## 2691 Good
## 2692 Good
## 2693 Good
## 2694 Good
## 2695 Good
## 2696 Good
## 2697 Good
## 2698 Bad
## 2699 Good
## 2700 Good
## 2701 Very Good
## 2702 Bad
## 2703 Bad
## 2704 Bad
## 2707 Good
## 2708 Bad
## 2709 Good
## 2710 Bad
## 2711 Bad
## 2713 Bad
## 2714 Good
## 2715 Good
## 2716 Good
## 2717 Bad
## 2718 Good
## 2719 Good
## 2720 Good
## 2721 Very Good
## 2723 Very Good
## 2724 Good
## 2725 Good
## 2726 Bad
## 2727 Good
## 2728 Good
## 2729 Good
## 2730 Very Good
## 2732 Bad
## 2733 Bad
## 2734 Very Good
## 2735 Good
## 2736 Good
## 2737 Good
## 2738 Very Good
## 2739 Bad
## 2740 Very Good
## 2741 Good
## 2742 Bad
## 2743 Good
## 2744 Good
## 2745 Good
## 2746 Very Good
## 2747 Good
## 2748 Good
## 2750 Good
## 2752 Good
## 2753 Good
## 2754 Very Good
## 2755 Bad
## 2756 Bad
## 2757 Good
## 2758 Bad
## 2759 Good
## 2760 Good
## 2761 Good
## 2762 Bad
## 2763 Bad
## 2764 Good
## 2765 Good
## 2766 Good
## 2767 Good
## 2768 Good
## 2769 Good
## 2770 Bad
## 2771 Very Good
## 2773 Very Good
## 2774 Very Good
## 2775 Very Good
## 2776 Very Good
## 2777 Very Good
## 2778 Good
## 2779 Very Good
## 2780 Bad
## 2781 Bad
## 2783 Good
## 2784 Good
## 2785 Good
## 2786 Bad
## 2787 Good
## 2788 Bad
## 2789 Bad
## 2790 Bad
## 2791 Good
## 2792 Bad
## 2793 Bad
## 2794 Very Good
## 2795 Bad
## 2796 Very Good
## 2797 Very Good
## 2798 Bad
## 2799 Very Good
## 2800 Very Good
## 2801 Bad
## 2802 Bad
## 2803 Good
## 2804 Very Good
## 2805 Very Good
## 2806 Good
## 2807 Bad
## 2808 Bad
## 2809 Good
## 2810 Very Good
## 2811 Very Good
## 2812 Bad
## 2813 Good
## 2814 Very Good
## 2815 Very Good
## 2816 Bad
## 2817 Bad
## 2818 Very Good
## 2820 Good
## 2822 Bad
## 2823 Bad
## 2824 Good
## 2825 Good
## 2826 Good
## 2827 Good
## 2828 Very Good
## 2829 Very Good
## 2830 Bad
## 2831 Bad
## 2832 Bad
## 2833 Good
## 2834 Very Good
## 2835 Good
## 2836 Good
## 2837 Good
## 2838 Good
## 2839 Very Good
## 2840 Very Good
## 2841 Good
## 2842 Good
## 2843 Good
## 2844 Good
## 2845 Bad
## 2846 Very Good
## 2847 Very Good
## 2848 Bad
## 2849 Bad
## 2851 Bad
## 2852 Bad
## 2853 Bad
## 2854 Good
## 2855 Good
## 2856 Very Good
## 2857 Very Good
## 2858 Very Good
## 2859 Very Good
## 2860 Good
## 2861 Good
## 2862 Good
## 2863 Good
## 2864 Good
## 2865 Good
## 2866 Good
## 2867 Very Good
## 2868 Very Good
## 2869 Bad
## 2870 Good
## 2871 Very Good
## 2872 Good
## 2874 Very Good
## 2876 Good
## 2877 Bad
## 2879 Good
## 2880 Good
## 2881 Bad
## 2882 Very Good
## 2883 Bad
## 2884 Very Good
## 2885 Very Good
## 2886 Good
## 2887 Bad
## 2888 Bad
## 2889 Very Bad
## 2890 Good
## 2891 Very Good
## 2892 Good
## 2893 Bad
## 2895 Very Good
## 2896 Bad
## 2897 Bad
## 2898 Bad
## 2899 Bad
## 2900 Bad
## 2901 Good
## 2902 Very Good
## 2903 Bad
## 2904 Good
## 2905 Very Good
## 2906 Bad
## 2907 Bad
## 2908 Good
## 2909 Good
## 2910 Good
## 2911 Bad
## 2912 Bad
## 2913 Very Good
## 2914 Bad
## 2915 Good
## 2916 Good
## 2917 Good
## 2918 Very Good
## 2919 Good
## 2920 Bad
## 2921 Very Bad
## 2922 Good
## 2923 Very Good
## 2924 Good
## 2925 Good
## 2926 Bad
## 2927 Very Good
## 2928 Very Good
## 2929 Very Good
## 2930 Good
## 2932 Very Good
## 2933 Good
## 2934 Good
## 2935 Bad
## 2936 Very Bad
## 2937 Bad
## 2938 Bad
## 2939 Very Good
## 2940 Very Good
## 2941 Good
## 2942 Bad
## 2943 Bad
## 2944 Very Good
## 2945 Good
## 2946 Very Good
## 2947 Good
## 2948 Good
## 2949 Good
## 2950 Good
## 2951 Bad
## 2952 Bad
## 2953 Bad
## 2954 Bad
## 2955 Very Good
## 2956 Bad
## 2957 Good
## 2958 Good
## 2959 Bad
## 2960 Very Good
## 2961 Very Good
## 2962 Good
## 2963 Bad
## 2964 Very Good
## 2965 Bad
## 2966 Very Good
## 2967 Good
## 2968 Good
## 2969 Bad
## 2970 Good
## 2971 Bad
## 2972 Bad
## 2973 Good
## 2974 Good
## 2975 Good
## 2976 Good
## 2977 Good
## 2978 Good
## 2979 Good
## 2980 Very Good
## 2981 Very Good
## 2982 Very Good
## 2983 Good
## 2984 Good
## 2985 Good
## 2986 Very Good
## 2987 Very Good
## 2988 Very Good
## 2989 Very Good
## 2990 Good
## 2991 Very Good
## 2992 Very Good
## 2993 Very Good
## 2994 Very Good
## 2995 Very Good
## 2996 Good
## 2997 Very Good
## 2998 Good
## 2999 Very Good
## 3000 Very Good
## 3001 Very Good
## 3002 Very Good
## 3003 Very Good
## 3004 Very Good
## 3005 Good
## 3006 Good
## 3007 Good
## 3008 Very Good
## 3009 Very Good
## 3010 Good
## 3011 Bad
## 3012 Good
## 3013 Good
## 3014 Good
## 3016 Good
## 3017 Good
## 3018 Good
## 3019 Very Good
## 3020 Good
## 3021 Good
## 3022 Very Bad
## 3023 Bad
## 3025 Good
## 3027 Good
## 3028 Bad
## 3029 Good
## 3030 Very Good
## 3031 Very Good
## 3032 Good
## 3033 Bad
## 3034 Good
## 3035 Good
## 3036 Very Good
## 3037 Bad
## 3038 Good
## 3039 Good
## 3040 Good
## 3041 Bad
## 3042 Good
## 3043 Good
## 3045 Good
## 3046 Good
## 3047 Good
## 3048 Bad
## 3049 Good
## 3050 Bad
## 3052 Bad
## 3054 Bad
## 3055 Good
## 3056 Good
## 3057 Bad
## 3058 Bad
## 3059 Bad
## 3060 Good
## 3061 Bad
## 3062 Bad
## 3063 Very Good
## 3064 Bad
## 3066 Good
## 3068 Very Bad
## 3069 Good
## 3070 Very Good
## 3071 Very Good
## 3072 Very Good
## 3074 Bad
## 3075 Bad
## 3076 Very Good
## 3077 Bad
## 3078 Bad
## 3079 Bad
## 3080 Bad
## 3081 Good
## 3082 Bad
## 3083 Good
## 3084 Very Good
## 3085 Good
## 3086 Good
## 3087 Very Good
## 3088 Very Bad
## 3089 Good
## 3090 Very Good
## 3091 Good
## 3092 Good
## 3093 Good
## 3094 Very Good
## 3097 Very Good
## 3099 Very Good
## 3100 Very Good
## 3101 Very Good
## 3102 Good
## 3103 Good
## 3104 Very Good
## 3105 Bad
## 3106 Good
## 3107 Good
## 3108 Good
## 3109 Bad
## 3110 Very Bad
## 3111 Good
## 3112 Very Good
## 3113 Bad
## 3114 Good
## 3115 Good
## 3116 Good
## 3117 Very Good
## 3118 Very Good
## 3119 Very Good
## 3120 Bad
## 3121 Good
## 3122 Bad
## 3123 Good
## 3124 Bad
## 3125 Good
## 3126 Bad
## 3127 Very Good
## 3128 Bad
## 3129 Good
## 3130 Good
## 3131 Good
## 3132 Bad
## 3133 Good
## 3134 Good
## 3135 Good
## 3136 Good
## 3137 Bad
## 3138 Good
## 3139 Good
## 3140 Good
## 3141 Good
## 3142 Very Good
## 3143 Good
## 3144 Bad
## 3145 Good
## 3146 Good
## 3147 Good
## 3148 Good
## 3149 Good
## 3150 Good
## 3151 Good
## 3152 Good
## 3154 Good
## 3155 Good
## 3156 Very Good
## 3157 Bad
## 3158 Very Good
## 3159 Very Good
## 3160 Good
## 3161 Good
## 3162 Bad
## 3163 Very Good
## 3164 Very Good
## 3165 Good
## 3167 Good
## 3168 Very Good
## 3169 Good
## 3170 Good
## 3171 Good
## 3172 Good
## 3173 Very Good
## 3174 Very Good
## 3175 Very Good
## 3176 Good
## 3177 Good
## 3178 Bad
## 3179 Good
## 3180 Very Bad
## 3181 Good
## 3182 Good
## 3183 Bad
## 3184 Good
## 3185 Very Good
## 3186 Good
## 3187 Very Bad
## 3188 Very Good
## 3189 Very Good
## 3190 Bad
## 3191 Very Good
## 3192 Good
## 3193 Good
## 3194 Bad
## 3195 Bad
## 3196 Good
## 3197 Very Good
## 3198 Good
## 3199 Very Good
## 3200 Very Good
## 3201 Very Good
## 3202 Good
## 3203 Very Good
## 3204 Very Good
## 3205 Bad
## 3206 Very Good
## 3207 Very Good
## 3208 Good
## 3209 Bad
## 3210 Bad
## 3211 Bad
## 3212 Good
## 3213 Bad
## 3214 Good
## 3215 Good
## 3216 Good
## 3217 Bad
## 3218 Bad
## 3219 Very Bad
## 3220 Very Good
## 3221 Bad
## 3222 Good
## 3223 Good
## 3224 Good
## 3225 Good
## 3226 Very Good
## 3227 Good
## 3228 Good
## 3229 Good
## 3230 Very Good
## 3231 Good
## 3232 Good
## 3233 Bad
## 3234 Good
## 3235 Good
## 3236 Good
## 3237 Good
## 3238 Very Good
## 3239 Bad
## 3240 Very Good
## 3241 Good
## 3242 Very Good
## 3243 Good
## 3244 Very Good
## 3245 Very Good
## 3246 Bad
## 3247 Good
## 3248 Good
## 3249 Very Good
## 3250 Very Good
## 3251 Good
## 3252 Good
## 3253 Very Good
## 3254 Very Good
## 3255 Bad
## 3256 Good
## 3257 Good
## 3258 Good
## 3259 Good
## 3260 Good
## 3261 Good
## 3262 Bad
## 3263 Very Good
## 3264 Very Good
## 3265 Good
## 3267 Good
## 3268 Good
## 3269 Good
## 3270 Bad
## 3271 Bad
## 3272 Very Good
## 3273 Very Good
## 3274 Very Good
## 3275 Bad
## 3276 Very Bad
## 3277 Very Good
## 3278 Very Good
## 3279 Bad
## 3280 Good
## 3281 Bad
## 3282 Good
## 3283 Very Good
## 3285 Good
## 3286 Very Good
## 3287 Very Good
## 3288 Very Good
## 3290 Bad
## 3291 Bad
## 3292 Very Good
## 3293 Bad
## 3294 Very Good
## 3295 Good
## 3296 Bad
## 3297 Bad
## 3298 Bad
## 3299 Good
## 3300 Very Good
## 3301 Bad
## 3302 Very Good
## 3303 Good
## 3304 Very Good
## 3305 Very Good
## 3306 Very Good
## 3307 Very Good
## 3309 Good
## 3310 Very Good
## 3311 Very Good
## 3312 Very Good
## 3313 Very Good
## 3314 Very Good
## 3315 Good
## 3316 Very Good
## 3317 Good
## 3318 Good
## 3319 Very Good
## 3320 Bad
## 3321 Bad
## 3322 Good
## 3323 Very Good
## 3324 Good
## 3325 Good
## 3326 Very Good
## 3327 Bad
## 3328 Very Good
## 3329 Bad
## 3330 Good
## 3331 Good
## 3332 Good
## 3333 Very Good
## 3334 Good
## 3335 Good
## 3336 Good
## 3337 Good
## 3338 Good
## 3339 Good
## 3340 Good
## 3341 Good
## 3342 Good
## 3343 Bad
## 3344 Very Good
## 3345 Good
## 3346 Good
## 3347 Good
## 3348 Good
## 3349 Good
## 3350 Good
## 3351 Good
## 3352 Good
## 3353 Good
## 3354 Good
## 3355 Very Good
## 3356 Good
## 3357 Good
## 3358 Very Good
## 3359 Good
## 3360 Good
## 3361 Very Good
## 3362 Good
## 3363 Good
## 3364 Good
## 3365 Good
## 3366 Very Good
## 3367 Good
## 3368 Good
## 3369 Good
## 3370 Very Good
## 3371 Good
## 3372 Good
## 3373 Good
## 3374 Very Good
## 3375 Bad
## 3376 Good
## 3377 Good
## 3378 Good
## 3379 Very Good
## 3380 Bad
## 3381 Very Good
## 3382 Very Good
## 3383 Very Good
## 3384 Good
## 3385 Good
## 3386 Good
## 3387 Very Good
## 3388 Bad
## 3389 Good
## 3390 Very Good
## 3391 Good
## 3392 Very Good
## 3393 Good
## 3394 Good
## 3395 Bad
## 3396 Bad
## 3397 Good
## 3398 Good
## 3399 Bad
## 3400 Good
## 3401 Good
## 3402 Bad
## 3403 Good
## 3404 Bad
## 3405 Good
## 3406 Good
## 3407 Good
## 3408 Bad
## 3409 Good
## 3410 Very Bad
## 3411 Very Good
## 3412 Good
## 3413 Good
## 3414 Good
## 3415 Very Good
## 3416 Very Good
## 3417 Good
## 3418 Very Bad
## 3419 Good
## 3420 Very Good
## 3421 Bad
## 3422 Very Good
## 3423 Very Good
## 3424 Bad
## 3425 Good
## 3426 Good
## 3427 Good
## 3428 Good
## 3429 Good
## 3430 Bad
## 3431 Good
## 3432 Good
## 3433 Bad
## 3434 Very Good
## 3435 Good
## 3436 Good
## 3437 Good
## 3438 Bad
## 3439 Bad
## 3440 Bad
## 3441 Bad
## 3442 Bad
## 3443 Very Good
## 3444 Good
## 3445 Bad
## 3446 Very Good
## 3447 Good
## 3448 Good
## 3449 Very Good
## 3450 Very Good
## 3451 Very Good
## 3452 Very Good
## 3453 Bad
## 3454 Good
## 3455 Bad
## 3456 Good
## 3457 Bad
## 3458 Very Good
## 3459 Very Good
## 3460 Good
## 3461 Good
## 3463 Good
## 3464 Very Good
## 3465 Bad
## 3466 Good
## 3467 Good
## 3468 Bad
## 3469 Very Good
## 3470 Good
## 3472 Good
## 3473 Good
## 3474 Very Good
## 3475 Good
## 3476 Good
## 3477 Very Good
## 3478 Very Good
## 3479 Good
## 3480 Very Good
## 3481 Very Good
## 3482 Bad
## 3483 Very Good
## 3484 Very Good
## 3485 Very Good
## 3486 Very Good
## 3487 Good
## 3488 Good
## 3489 Good
## 3490 Very Good
## 3491 Very Good
## 3492 Good
## 3493 Very Good
## 3494 Very Good
## 3495 Good
## 3496 Very Good
## 3497 Very Good
## 3499 Good
## 3500 Very Good
## 3501 Very Good
## 3502 Good
## 3503 Bad
## 3504 Very Good
## 3505 Very Good
## 3506 Very Good
## 3507 Good
## 3508 Very Good
## 3509 Bad
## 3510 Good
## 3511 Good
## 3512 Very Good
## 3513 Good
## 3514 Good
## 3515 Good
## 3516 Very Good
## 3517 Very Good
## 3518 Very Good
## 3519 Bad
## 3520 Very Good
## 3522 Very Good
## 3523 Bad
## 3525 Good
## 3526 Good
## 3527 Good
## 3528 Good
## 3529 Very Bad
## 3530 Very Good
## 3531 Bad
## 3532 Bad
## 3533 Good
## 3534 Good
## 3535 Bad
## 3536 Bad
## 3537 Good
## 3538 Bad
## 3539 Very Good
## 3540 Good
## 3541 Good
## 3542 Good
## 3543 Good
## 3544 Good
## 3545 Good
## 3546 Good
## 3547 Good
## 3548 Good
## 3549 Good
## 3550 Good
## 3551 Good
## 3552 Good
## 3553 Good
## 3554 Good
## 3555 Good
## 3556 Good
## 3557 Very Good
## 3558 Good
## 3559 Good
## 3560 Very Bad
## 3561 Good
## 3562 Bad
## 3563 Good
## 3564 Bad
## 3565 Good
## 3566 Good
## 3567 Good
## 3568 Good
## 3569 Very Good
## 3570 Good
## 3571 Good
## 3572 Very Bad
## 3573 Good
## 3574 Good
## 3575 Good
## 3576 Very Good
## 3577 Bad
## 3578 Very Good
## 3579 Very Bad
## 3580 Very Good
## 3581 Bad
## 3582 Very Good
## 3583 Good
## 3584 Good
## 3585 Very Good
## 3586 Very Good
## 3587 Very Good
## 3591 Very Good
## 3592 Bad
## 3593 Very Good
## 3594 Very Good
## 3595 Very Good
## 3596 Very Good
## 3597 Very Good
## 3598 Good
## 3599 Very Good
## 3600 Good
## 3601 Good
## 3602 Very Good
## 3603 Good
## 3604 Very Good
## 3605 Good
## 3606 Bad
## 3607 Bad
## 3608 Good
## 3609 Good
## 3610 Good
## 3611 Bad
## 3612 Good
## 3613 Good
## 3614 Good
## 3615 Bad
## 3616 Good
## 3617 Bad
## 3618 Bad
## 3619 Very Good
## 3622 Very Good
## 3623 Good
## 3625 Very Good
## 3626 Bad
## 3627 Bad
## 3628 Bad
## 3629 Good
## 3630 Good
## 3631 Good
## 3632 Good
## 3633 Good
## 3634 Good
## 3635 Very Good
## 3636 Good
## 3637 Very Good
## 3638 Very Good
## 3639 Very Good
## 3640 Good
## 3641 Good
## 3642 Good
## 3643 Good
## 3644 Good
## 3645 Very Good
## 3646 Good
## 3647 Very Good
## 3648 Very Good
## 3649 Bad
## 3650 Good
## 3651 Very Bad
## 3652 Good
## 3653 Good
## 3654 Good
## 3655 Good
## 3656 Very Good
## 3657 Very Good
## 3658 Very Good
## 3659 Very Good
## 3660 Very Good
## 3661 Very Good
## 3662 Good
## 3663 Very Bad
## 3664 Good
## 3665 Very Good
## 3666 Very Good
## 3667 Very Good
## 3668 Very Good
## 3669 Bad
## 3670 Very Good
## 3671 Good
## 3672 Very Good
## 3673 Very Good
## 3674 Very Good
## 3675 Bad
## 3676 Good
## 3677 Very Good
## 3679 Bad
## 3680 Very Good
## 3681 Good
## 3682 Very Good
## 3683 Very Good
## 3684 Good
## 3685 Very Good
## 3686 Good
## 3687 Bad
## 3688 Bad
## 3689 Good
## 3690 Very Good
## 3691 Very Good
## 3692 Good
## 3693 Very Good
## 3694 Very Good
## 3695 Bad
## 3696 Good
## 3697 Very Good
## 3698 Good
## 3699 Good
## 3700 Bad
## 3701 Bad
## 3702 Bad
## 3703 Good
## 3704 Good
## 3705 Good
## 3706 Good
## 3707 Good
## 3708 Good
## 3709 Bad
## 3710 Bad
## 3712 Good
## 3713 Bad
## 3714 Bad
## 3715 Very Bad
## 3716 Good
## 3717 Bad
## 3718 Good
## 3719 Bad
## 3720 Bad
## 3721 Very Good
## 3722 Bad
## 3723 Bad
## 3724 Very Good
## 3725 Good
## 3726 Good
## 3727 Very Good
## 3728 Very Good
## 3729 Very Good
## 3730 Bad
## 3731 Good
## 3732 Good
## 3733 Bad
## 3734 Good
## 3735 Bad
## 3737 Very Bad
## 3739 Good
## 3740 Very Good
## 3741 Very Good
## 3742 Very Good
## 3743 Very Good
## 3744 Very Good
## 3745 Very Good
## 3746 Very Good
## 3747 Bad
## 3748 Good
## 3749 Bad
## 3750 Good
## 3751 Very Good
## 3752 Bad
## 3753 Bad
## 3754 Bad
## 3755 Very Good
## 3756 Good
## 3757 Bad
## 3758 Bad
## 3759 Bad
## 3760 Good
## 3761 Good
## 3762 Very Good
## 3763 Bad
## 3764 Bad
## 3765 Very Good
## 3766 Bad
## 3767 Bad
## 3768 Bad
## 3769 Good
## 3770 Bad
## 3771 Very Bad
## 3772 Good
## 3773 Good
## 3775 Bad
## 3776 Good
## 3777 Bad
## 3778 Good
## 3779 Very Good
## 3780 Very Good
## 3781 Bad
## 3782 Good
## 3783 Good
## 3784 Bad
## 3785 Good
## 3786 Very Good
## 3787 Bad
## 3788 Bad
## 3789 Bad
## 3790 Good
## 3791 Bad
## 3792 Bad
## 3793 Good
## 3794 Good
## 3795 Bad
## 3796 Good
## 3797 Good
## 3798 Bad
## 3799 Bad
## 3800 Bad
## 3801 Bad
## 3802 Good
## 3803 Bad
## 3804 Good
## 3805 Bad
## 3806 Good
## 3807 Bad
## 3808 Bad
## 3809 Good
## 3810 Good
## 3811 Very Bad
## 3812 Bad
## 3813 Bad
## 3814 Bad
## 3815 Bad
## 3816 Very Good
## 3817 Bad
## 3818 Good
## 3819 Good
## 3820 Good
## 3821 Bad
## 3822 Good
## 3823 Good
## 3824 Bad
## 3825 Very Good
## 3826 Good
## 3827 Good
## 3828 Bad
## 3829 Good
## 3830 Very Good
## 3831 Very Good
## 3832 Bad
## 3833 Bad
## 3834 Good
## 3835 Bad
## 3836 Bad
## 3837 Good
## 3838 Good
## 3839 Bad
## 3840 Bad
## 3841 Good
## 3842 Good
## 3843 Good
## 3844 Very Good
## 3845 Good
## 3846 Bad
## 3847 Good
## 3848 Bad
## 3850 Bad
## 3851 Good
## 3852 Very Good
## 3853 Good
## 3854 Very Good
## 3855 Good
## 3856 Good
## 3857 Good
## 3858 Good
## 3859 Good
## 3860 Bad
## 3861 Bad
## 3865 Very Good
## 3866 Good
## 3867 Good
## 3868 Bad
## 3871 Good
## 3873 Very Bad
## 3874 Bad
## 3875 Bad
## 3876 Very Good
## 3877 Bad
## 3878 Bad
## 3879 Bad
## 3880 Very Bad
## 3881 Good
## 3882 Good
## 3883 Bad
## 3884 Good
## 3885 Good
## 3886 Good
## 3887 Good
## 3888 Good
## 3889 Good
## 3890 Good
## 3891 Good
## 3892 Bad
## 3893 Bad
## 3894 Bad
## 3895 Good
## 3896 Good
## 3897 Good
## 3898 Good
## 3899 Very Good
## 3900 Bad
## 3901 Bad
## 3904 Good
## 3906 Very Good
## 3907 Very Good
## 3908 Very Good
## 3909 Very Good
## 3910 Very Good
## 3911 Good
## 3913 Very Good
## 3914 Good
## 3915 Very Good
## 3917 Good
## 3918 Bad
## 3919 Very Good
## 3920 Good
## 3921 Good
## 3922 Bad
## 3923 Very Good
## 3924 Bad
## 3925 Bad
## 3926 Bad
## 3927 Good
## 3928 Bad
## 3929 Bad
## 3930 Bad
## 3931 Good
## 3932 Good
## 3933 Very Good
## 3934 Very Bad
## 3935 Good
## 3936 Bad
## 3937 Good
## 3939 Good
## 3940 Good
## 3941 Bad
## 3942 Bad
## 3943 Good
## 3944 Good
## 3945 Good
## 3946 Good
## 3947 Good
## 3948 Very Good
## 3949 Bad
## 3950 Bad
## 3951 Bad
## 3952 Bad
## 3953 Good
## 3954 Very Good
## 3955 Bad
## 3956 Good
## 3957 Bad
## 3958 Bad
## 3959 Good
## 3960 Good
## 3961 Good
## 3962 Bad
## 3963 Very Good
## 3964 Very Good
## 3965 Bad
## 3966 Very Bad
## 3967 Good
## 3968 Very Bad
## 3969 Good
## 3970 Good
## 3971 Very Good
## 3972 Good
## 3974 Very Bad
## 3975 Good
## 3976 Very Good
## 3977 Very Good
## 3978 Good
## 3979 Very Good
## 3980 Good
## 3981 Bad
## 3983 Very Good
## 3984 Good
## 3985 Very Good
## 3986 Good
## 3987 Good
## 3988 Good
## 3989 Good
## 3990 Good
## 3991 Good
## 3992 Bad
## 3993 Very Good
## 3994 Very Good
## 3995 Very Good
## 3996 Bad
## 3997 Very Good
## 3998 Very Good
## 4002 Bad
## 4003 Good
## 4004 Good
## 4005 Very Good
## 4006 Good
## 4007 Good
## 4008 Bad
## 4009 Good
## 4010 Good
## 4011 Good
## 4012 Very Good
## 4014 Good
## 4015 Good
## 4016 Bad
## 4017 Bad
## 4018 Good
## 4019 Good
## 4020 Bad
## 4021 Very Bad
## 4022 Bad
## 4023 Bad
## 4024 Good
## 4025 Good
## 4026 Good
## 4027 Good
## 4028 Bad
## 4029 Good
## 4030 Good
## 4031 Bad
## 4032 Bad
## 4033 Bad
## 4034 Good
## 4035 Bad
## 4036 Good
## 4037 Bad
## 4038 Bad
## 4039 Bad
## 4041 Bad
## 4042 Bad
## 4043 Very Good
## 4044 Very Good
## 4045 Very Good
## 4046 Very Good
## 4047 Very Good
## 4048 Good
## 4049 Good
## 4050 Good
## 4051 Very Good
## 4052 Good
## 4053 Bad
## 4054 Very Good
## 4055 Very Good
## 4056 Good
## 4057 Bad
## 4058 Good
## 4059 Good
## 4060 Good
## 4061 Bad
## 4062 Bad
## 4063 Good
## 4064 Bad
## 4065 Bad
## 4067 Good
## 4068 Bad
## 4069 Good
## 4070 Good
## 4071 Bad
## 4072 Good
## 4073 Very Good
## 4074 Bad
## 4075 Very Bad
## 4076 Good
## 4077 Bad
## 4078 Good
## 4079 Good
## 4080 Good
## 4081 Good
## 4082 Good
## 4083 Good
## 4084 Bad
## 4085 Very Good
## 4086 Good
## 4087 Good
## 4088 Good
## 4089 Good
## 4090 Good
## 4091 Good
## 4092 Good
## 4093 Good
## 4094 Good
## 4095 Very Good
## 4096 Good
## 4097 Bad
## 4098 Good
## 4099 Bad
## 4100 Good
## 4101 Good
## 4102 Bad
## 4103 Bad
## 4104 Very Good
## 4105 Very Good
## 4106 Very Good
## 4107 Bad
## 4109 Good
## 4110 Good
## 4111 Bad
## 4112 Good
## 4113 Good
## 4114 Good
## 4115 Good
## 4116 Good
## 4117 Good
## 4118 Good
## 4119 Very Good
## 4120 Very Good
## 4121 Bad
## 4122 Good
## 4123 Good
## 4124 Good
## 4125 Very Good
## 4126 Bad
## 4127 Bad
## 4128 Bad
## 4129 Bad
## 4130 Very Good
## 4131 Good
## 4132 Bad
## 4133 Bad
## 4134 Good
## 4135 Good
## 4136 Bad
## 4138 Bad
## 4139 Good
## 4140 Very Good
## 4141 Good
## 4142 Good
## 4143 Good
## 4144 Good
## 4145 Good
## 4146 Good
## 4147 Very Good
## 4148 Very Good
## 4149 Good
## 4150 Very Good
## 4151 Bad
## 4152 Good
## 4153 Good
## 4154 Bad
## 4155 Bad
## 4156 Bad
## 4157 Bad
## 4158 Very Good
## 4159 Very Good
## 4160 Very Good
## 4161 Very Good
## 4162 Very Good
## 4163 Very Good
## 4164 Bad
## 4165 Bad
## 4166 Very Good
## 4167 Very Good
## 4168 Very Good
## 4169 Good
## 4170 Very Good
## 4171 Very Good
## 4172 Bad
## 4173 Good
## 4175 Good
## 4176 Very Good
## 4177 Good
## 4178 Good
## 4179 Very Good
## 4180 Bad
## 4181 Good
## 4182 Good
## 4183 Good
## 4184 Very Good
## 4185 Very Good
## 4186 Bad
## 4187 Bad
## 4188 Good
## 4189 Good
## 4190 Bad
## 4191 Good
## 4192 Bad
## 4193 Good
## 4194 Good
## 4195 Good
## 4196 Very Good
## 4197 Good
## 4198 Bad
## 4199 Bad
## 4200 Good
## 4201 Good
## 4202 Good
## 4203 Good
## 4204 Bad
## 4205 Good
## 4206 Good
## 4207 Good
## 4208 Very Good
## 4209 Good
## 4210 Good
## 4211 Good
## 4212 Good
## 4213 Very Bad
## 4214 Very Bad
## 4215 Bad
## 4216 Bad
## 4217 Bad
## 4218 Very Bad
## 4219 Good
## 4220 Bad
## 4221 Good
## 4222 Good
## 4223 Very Bad
## 4224 Very Bad
## 4225 Very Good
## 4226 Bad
## 4227 Very Good
## 4228 Very Good
## 4229 Good
## 4230 Good
## 4231 Good
## 4232 Good
## 4233 Good
## 4234 Good
## 4235 Good
## 4236 Bad
## 4237 Bad
## 4238 Bad
## 4239 Bad
## 4241 Good
## 4242 Good
## 4243 Very Good
## 4244 Good
## 4245 Bad
## 4246 Bad
## 4247 Good
## 4248 Good
## 4249 Good
## 4250 Good
## 4251 Good
## 4252 Good
## 4253 Good
## 4254 Very Bad
## 4255 Bad
## 4256 Bad
## 4257 Bad
## 4258 Bad
## 4259 Good
## 4261 Good
## 4262 Very Good
## 4263 Good
## 4264 Good
## 4265 Good
## 4266 Good
## 4267 Very Good
## 4268 Very Good
## 4269 Good
## 4270 Bad
## 4271 Good
## 4272 Bad
## 4273 Good
## 4274 Good
## 4275 Good
## 4276 Good
## 4277 Very Good
## 4278 Bad
## 4279 Very Bad
## 4280 Good
## 4281 Good
## 4282 Bad
## 4283 Bad
## 4284 Good
## 4285 Good
## 4286 Good
## 4287 Good
## 4288 Bad
## 4289 Good
## 4290 Good
## 4291 Bad
## 4292 Bad
## 4293 Good
## 4294 Bad
## 4295 Bad
## 4296 Bad
## 4297 Good
## 4298 Good
## 4299 Good
## 4302 Bad
## 4303 Good
## 4304 Good
## 4305 Good
## 4306 Good
## 4307 Good
## 4308 Very Good
## 4309 Good
## 4310 Good
## 4311 Good
## 4312 Bad
## 4313 Good
## 4314 Good
## 4315 Very Good
## 4316 Very Good
## 4317 Bad
## 4318 Very Good
## 4319 Very Good
## 4320 Very Good
## 4321 Bad
## 4322 Good
## 4323 Very Good
## 4324 Good
## 4325 Good
## 4326 Bad
## 4327 Bad
## 4328 Bad
## 4329 Bad
## 4330 Bad
## 4331 Bad
## 4332 Bad
## 4333 Very Good
## 4334 Very Good
## 4335 Very Good
## 4336 Very Good
## 4337 Very Good
## 4338 Very Good
## 4339 Very Good
## 4340 Very Good
## 4341 Very Good
## 4342 Good
## 4343 Good
## 4344 Good
## 4346 Good
## 4348 Very Good
## 4349 Good
## 4350 Bad
## 4351 Good
## 4352 Good
## 4353 Bad
## 4354 Good
## 4355 Good
## 4356 Good
## 4357 Bad
## 4358 Good
## 4359 Bad
## 4360 Good
## 4361 Bad
## 4362 Good
## 4363 Good
## 4364 Bad
## 4365 Good
## 4366 Bad
## 4367 Good
## 4368 Bad
## 4369 Good
## 4370 Good
## 4371 Bad
## 4372 Bad
## 4373 Good
## 4374 Good
## 4375 Bad
## 4376 Good
## 4377 Bad
## 4378 Good
## 4379 Bad
## 4380 Bad
## 4381 Good
## 4382 Good
## 4383 Good
## 4384 Good
## 4385 Bad
## 4386 Bad
## 4387 Good
## 4388 Good
## 4389 Good
## 4390 Very Bad
## 4391 Bad
## 4392 Bad
## 4393 Bad
## 4394 Good
## 4395 Good
## 4396 Bad
## 4397 Bad
## 4398 Bad
## 4399 Bad
## 4400 Bad
## 4401 Bad
## 4403 Good
## 4404 Bad
## 4405 Bad
## 4406 Bad
## 4407 Very Good
## 4408 Good
## 4409 Bad
## 4410 Very Good
## 4411 Bad
## 4412 Very Good
## 4413 Very Good
## 4414 Very Good
## 4415 Very Good
## 4416 Bad
## 4417 Bad
## 4418 Good
## 4419 Good
## 4420 Good
## 4421 Good
## 4422 Good
## 4423 Good
## 4424 Good
## 4425 Good
## 4426 Good
## 4427 Good
## 4428 Bad
## 4429 Good
## 4430 Good
## 4431 Bad
## 4432 Good
## 4433 Good
## 4434 Bad
## 4435 Good
## 4436 Good
## 4437 Good
## 4438 Good
## 4439 Bad
## 4440 Bad
## 4441 Bad
## 4442 Good
## 4443 Bad
## 4444 Bad
## 4445 Good
## 4446 Good
## 4447 Good
## 4448 Good
## 4449 Bad
## 4450 Good
## 4451 Good
## 4452 Bad
## 4453 Bad
## 4454 Good
## 4455 Good
## 4456 Bad
## 4457 Bad
## 4458 Bad
## 4459 Very Good
## 4460 Bad
## 4461 Good
## 4462 Good
## 4463 Good
## 4464 Good
## 4465 Bad
## 4466 Bad
## 4467 Bad
## 4468 Bad
## 4469 Good
## 4470 Good
## 4471 Good
## 4472 Good
## 4473 Bad
## 4475 Good
## 4476 Good
## 4477 Good
## 4478 Bad
## 4479 Bad
## 4480 Bad
## 4482 Bad
## 4483 Good
## 4484 Very Bad
## 4485 Bad
## 4486 Good
## 4487 Good
## 4488 Good
## 4489 Good
## 4490 Good
## 4491 Good
## 4492 Good
## 4493 Good
## 4494 Good
## 4495 Good
## 4496 Good
## 4497 Good
## 4499 Bad
## 4500 Good
## 4501 Good
## 4502 Good
## 4503 Good
## 4505 Bad
## 4506 Bad
## 4507 Good
## 4508 Bad
## 4509 Very Bad
## 4510 Bad
## 4511 Good
## 4512 Good
## 4513 Good
## 4514 Good
## 4515 Bad
## 4516 Good
## 4517 Good
## 4518 Good
## 4519 Good
## 4521 Bad
## 4522 Bad
## 4523 Good
## 4524 Bad
## 4525 Good
## 4527 Good
## 4528 Good
## 4529 Good
## 4530 Good
## 4531 Good
## 4532 Good
## 4533 Good
## 4534 Bad
## 4535 Good
## 4536 Good
## 4537 Good
## 4538 Bad
## 4539 Good
## 4540 Bad
## 4541 Good
## 4542 Good
## 4543 Bad
## 4544 Bad
## 4545 Good
## 4546 Good
## 4547 Good
## 4548 Good
## 4549 Bad
## 4550 Bad
## 4551 Good
## 4552 Good
## 4553 Good
## 4554 Good
## 4555 Good
## 4556 Bad
## 4557 Bad
## 4558 Good
## 4559 Good
## 4560 Very Good
## 4561 Good
## 4562 Good
## 4563 Very Good
## 4564 Very Good
## 4565 Very Good
## 4567 Bad
## 4569 Good
## 4570 Good
## 4571 Good
## 4572 Very Good
## 4573 Very Good
## 4574 Good
## 4575 Very Good
## 4576 Very Good
## 4577 Bad
## 4578 Good
## 4579 Very Good
## 4580 Good
## 4582 Good
## 4584 Good
## 4585 Good
## 4586 Good
## 4587 Good
## 4588 Good
## 4589 Bad
## 4590 Good
## 4591 Good
## 4593 Good
## 4594 Good
## 4595 Good
## 4596 Good
## 4597 Good
## 4599 Good
## 4600 Very Good
## 4601 Good
## 4602 Good
## 4603 Good
## 4604 Good
## 4605 Good
## 4606 Good
## 4607 Bad
## 4608 Good
## 4609 Very Good
## 4610 Very Bad
## 4611 Good
## 4612 Bad
## 4613 Bad
## 4614 Bad
## 4615 Bad
## 4616 Very Good
## 4617 Bad
## 4618 Very Good
## 4619 Very Good
## 4620 Bad
## 4621 Good
## 4622 Very Good
## 4623 Very Good
## 4624 Good
## 4625 Good
## 4626 Bad
## 4628 Good
## 4629 Good
## 4630 Very Good
## 4631 Very Good
## 4632 Very Good
## 4634 Good
## 4635 Good
## 4636 Good
## 4637 Bad
## 4638 Good
## 4639 Bad
## 4640 Good
## 4641 Good
## 4642 Good
## 4643 Very Good
## 4644 Good
## 4645 Good
## 4646 Very Good
## 4647 Very Good
## 4648 Very Good
## 4650 Bad
## 4651 Bad
## 4652 Very Good
## 4653 Bad
## 4654 Very Good
## 4655 Very Good
## 4656 Very Good
## 4657 Very Good
## 4658 Very Good
## 4659 Good
## 4660 Good
## 4661 Good
## 4662 Bad
## 4663 Good
## 4664 Very Good
## 4665 Very Good
## 4666 Good
## 4667 Bad
## 4668 Very Good
## 4669 Very Good
## 4670 Bad
## 4671 Good
## 4672 Bad
## 4673 Bad
## 4674 Very Good
## 4675 Very Good
## 4676 Good
## 4677 Good
## 4678 Very Good
## 4679 Good
## 4680 Bad
## 4681 Very Bad
## 4682 Good
## 4683 Good
## 4684 Good
## 4685 Good
## 4686 Bad
## 4687 Very Bad
## 4688 Good
## 4689 Good
## 4690 Good
## 4691 Good
## 4692 Very Good
## 4693 Bad
## 4694 Good
## 4695 Very Good
## 4696 Very Good
## 4698 Very Good
## 4700 Bad
## 4701 Bad
## 4702 Good
## 4703 Good
## 4704 Very Good
## 4705 Good
## 4706 Good
## 4707 Very Good
## 4708 Good
## 4709 Good
## 4710 Good
## 4711 Very Good
## 4712 Good
## 4713 Good
## 4714 Good
## 4715 Very Good
## 4716 Good
## 4717 Good
## 4718 Good
## 4719 Good
## 4720 Good
## 4721 Bad
## 4722 Good
## 4723 Good
## 4724 Good
## 4725 Good
## 4726 Good
## 4727 Good
## 4728 Good
## 4729 Good
## 4730 Bad
## 4731 Bad
## 4732 Good
## 4733 Good
## 4734 Good
## 4735 Good
## 4736 Good
## 4737 Good
## 4738 Very Good
## 4739 Good
## 4740 Good
## 4741 Bad
## 4742 Good
## 4743 Good
## 4744 Bad
## 4745 Bad
## 4747 Good
## 4748 Good
## 4749 Bad
## 4750 Good
## 4751 Bad
## 4752 Good
## 4753 Very Good
## 4754 Good
## 4755 Good
## 4756 Good
## 4757 Very Good
## 4758 Very Good
## 4759 Good
## 4760 Good
## 4761 Good
## 4762 Good
## 4763 Very Good
## 4764 Very Good
## 4765 Good
## 4766 Very Good
## 4767 Very Good
## 4768 Very Good
## 4769 Good
## 4770 Good
## 4771 Good
## 4772 Good
## 4773 Bad
## 4774 Very Good
## 4775 Very Bad
## 4776 Good
## 4777 Good
## 4778 Good
## 4779 Good
## 4780 Very Bad
## 4781 Bad
## 4782 Bad
## 4783 Good
## 4784 Good
## 4785 Bad
## 4786 Very Good
## 4787 Very Good
## 4788 Very Good
## 4789 Bad
## 4790 Good
## 4791 Good
## 4792 Good
## 4796 Very Good
## 4797 Very Good
## 4798 Good
## 4799 Bad
## 4800 Good
## 4801 Very Good
## 4802 Very Good
## 4803 Very Good
## 4804 Very Good
## 4805 Very Bad
## 4806 Good
## 4807 Good
## 4808 Good
## 4809 Bad
## 4810 Good
## 4811 Bad
## 4812 Good
## 4813 Very Good
## 4815 Good
## 4817 Good
## 4818 Good
## 4820 Good
## 4822 Good
## 4823 Good
## 4824 Very Good
## 4825 Bad
## 4826 Good
## 4827 Good
## 4828 Good
## 4829 Bad
## 4830 Very Good
## 4831 Good
## 4832 Good
## 4833 Bad
## 4834 Good
## 4835 Very Good
## 4836 Good
## 4837 Bad
## 4838 Good
## 4839 Good
## 4840 Very Bad
## 4841 Very Good
## 4843 Good
## 4844 Bad
## 4845 Good
## 4846 Bad
## 4847 Good
## 4848 Very Good
## 4849 Good
## 4850 Bad
## 4851 Good
## 4852 Bad
## 4853 Bad
## 4854 Bad
## 4855 Good
## 4856 Good
## 4857 Good
## 4858 Good
## 4859 Bad
## 4860 Good
## 4861 Good
## 4862 Good
## 4863 Good
## 4864 Very Good
## 4865 Bad
## 4866 Good
## 4867 Good
## 4868 Good
## 4869 Good
## 4870 Good
## 4871 Very Good
## 4872 Good
## 4873 Bad
## 4874 Good
## 4875 Good
## 4876 Good
## 4877 Very Good
## 4878 Bad
## 4879 Very Bad
## 4880 Good
## 4881 Good
## 4882 Good
## 4883 Bad
## 4884 Good
## 4885 Bad
## 4886 Good
## 4888 Very Good
## 4889 Bad
## 4890 Good
## 4891 Good
## 4892 Good
## 4893 Bad
## 4894 Good
## 4895 Bad
## 4896 Good
## 4897 Very Good
## 4898 Good
## 4899 Bad
## 4900 Bad
## 4901 Bad
## 4902 Good
## 4903 Bad
## 4904 Bad
## 4905 Bad
## 4906 Very Good
## 4907 Very Good
## 4908 Bad
## 4909 Bad
## 4910 Bad
## 4911 Bad
## 4915 Very Good
## 4917 Very Bad
## 4919 Good
## 4920 Bad
## 4921 Bad
## 4922 Bad
## 4923 Good
## 4924 Bad
## 4925 Bad
## 4926 Bad
## 4927 Bad
## 4928 Good
## 4929 Bad
## 4930 Good
## 4931 Bad
## 4932 Good
## 4933 Bad
## 4934 Good
## 4935 Good
## 4936 Very Good
## 4938 Bad
## 4939 Bad
## 4940 Very Bad
## 4943 Bad
## 4946 Bad
## 4947 Bad
## 4948 Bad
## 4949 Bad
## 4950 Good
## 4951 Good
## 4952 Bad
## 4953 Good
## 4954 Bad
## 4955 Bad
## 4956 Bad
## 4957 Bad
## 4958 Good
## 4959 Bad
## 4960 Bad
## 4961 Very Good
## 4962 Bad
## 4963 Bad
## 4964 Bad
## 4965 Bad
## 4966 Bad
## 4967 Bad
## 4968 Good
## 4969 Good
## 4970 Bad
## 4971 Bad
## 4972 Very Bad
## 4973 Bad
## 4974 Bad
## 4975 Bad
## 4976 Good
## 4977 Bad
## 4979 Bad
## 4981 Bad
## 4983 Good
## 4984 Bad
## 4986 Bad
## 4988 Bad
## 4989 Bad
## 4992 Bad
## 4995 Bad
## 4996 Bad
## 4997 Bad
## 4998 Good
## 4999 Good
## 5000 Good
## 5001 Good
## 5002 Bad
## 5003 Bad
## 5004 Bad
## 5006 Bad
## 5007 Good
## 5009 Bad
## 5010 Bad
## 5011 Bad
## 5012 Good
## 5013 Bad
## 5014 Good
## 5015 Good
## 5016 Good
## 5017 Good
## 5018 Good
## 5020 Good
## 5021 Bad
## 5022 Bad
## 5023 Bad
## 5024 Bad
## 5027 Very Good
## 5028 Bad
## 5029 Bad
## 5032 Good
## 5034 Bad
## 5035 Bad
## 5036 Bad
## 5037 Bad
## 5038 Bad
## 5039 Bad
## 5040 Bad
## 5042 Bad
## 5044 Bad
## 5045 Bad
## 5047 Good
## 5048 Good
## 5049 Good
## 5051 Bad
## 5052 Bad
## 5053 Bad
## 5054 Bad
## 5055 Bad
## 5056 Bad
## 5057 Bad
## 5058 Good
## 5059 Bad
## 5061 Good
## 5062 Bad
## 5063 Bad
## 5064 Bad
## 5065 Bad
## 5066 Very Bad
## 5067 Good
## 5070 Good
## 5071 Good
## 5072 Good
## 5073 Bad
## 5074 Bad
## 5075 Bad
## 5076 Good
## 5077 Bad
## 5078 Bad
## 5079 Bad
## 5081 Bad
## 5082 Bad
## 5083 Good
## 5084 Bad
## 5085 Bad
## 5086 Bad
## 5087 Bad
## 5088 Bad
## 5089 Bad
## 5090 Good
## 5091 Bad
## 5092 Bad
## 5093 Bad
## 5094 Bad
## 5095 Bad
## 5099 Very Good
## 5100 Bad
## 5101 Bad
## 5102 Bad
## 5103 Good
## 5106 Bad
## 5107 Bad
## 5108 Very Good
## 5109 Good
## 5110 Good
## 5112 Bad
## 5113 Good
## 5114 Bad
## 5115 Bad
## 5116 Bad
## 5117 Bad
## 5118 Bad
## 5119 Good
## 5120 Bad
## 5121 Bad
## 5122 Good
## 5123 Very Bad
## 5124 Good
## 5126 Bad
## 5127 Good
## 5128 Bad
## 5129 Very Good
## 5130 Good
## 5131 Good
## 5132 Bad
## 5134 Good
## 5135 Good
## 5136 Good
## 5137 Good
## 5140 Good
## 5141 Good
## 5144 Good
## 5145 Bad
## 5146 Bad
## 5147 Good
## 5148 Good
## 5149 Good
## 5150 Good
## 5151 Bad
## 5152 Bad
## 5153 Good
## 5154 Bad
## 5155 Bad
## 5156 Bad
## 5158 Very Good
## 5159 Bad
## 5161 Bad
## 5162 Bad
## 5165 Very Bad
## 5167 Good
## 5169 Good
## 5171 Bad
## 5172 Bad
## 5173 Bad
## 5174 Good
## 5175 Good
## 5177 Very Good
## 5178 Very Good
## 5181 Bad
## 5182 Very Good
## 5183 Bad
## 5184 Bad
## 5185 Good
## 5186 Good
## 5187 Very Good
## 5188 Bad
## 5189 Very Good
## 5191 Good
## 5192 Good
## 5194 Bad
## 5195 Bad
## 5196 Bad
## 5197 Bad
## 5198 Bad
## 5199 Good
## 5200 Good
## 5201 Bad
## 5203 Bad
## 5204 Good
## 5205 Bad
## 5208 Good
## 5209 Good
## 5210 Good
## 5211 Good
## 5212 Bad
## 5213 Bad
## 5214 Good
## 5215 Bad
## 5216 Good
## 5217 Very Good
## 5218 Good
## 5219 Very Good
## 5220 Bad
## 5221 Bad
## 5222 Good
## 5223 Good
## 5224 Good
## 5225 Very Good
## 5226 Bad
## 5228 Bad
## 5231 Good
## 5232 Bad
## 5233 Very Good
## 5235 Good
## 5236 Bad
## 5240 Good
## 5241 Good
## 5242 Good
## 5243 Good
## 5244 Bad
## 5245 Very Good
## 5247 Good
## 5248 Good
## 5249 Good
## 5250 Good
## 5251 Bad
## 5253 Good
## 5255 Bad
## 5256 Very Good
## 5257 Very Good
## 5259 Bad
## 5260 Good
## 5264 Good
## 5266 Bad
## 5267 Bad
## 5269 Bad
## 5270 Good
## 5271 Good
## 5272 Bad
## 5278 Good
## 5279 Good
## 5281 Good
## 5282 Good
## 5283 Bad
## 5284 Good
## 5285 Good
## 5286 Good
## 5287 Good
## 5288 Very Good
## 5291 Bad
## 5292 Bad
## 5296 Good
## 5297 Good
## 5298 Bad
## 5300 Good
## 5301 Good
## 5302 Good
## 5303 Bad
## 5304 Good
## 5305 Good
## 5306 Very Good
## 5309 Good
## 5310 Bad
## 5311 Bad
## 5312 Very Good
## 5313 Bad
## 5315 Good
## 5316 Bad
## 5317 Good
## 5318 Bad
## 5319 Very Good
## 5322 Very Good
## 5325 Good
## 5326 Good
## 5327 Bad
## 5329 Very Good
## 5330 Bad
## 5333 Good
## 5335 Good
## 5336 Good
## 5337 Good
## 5338 Bad
## 5340 Good
## 5342 Very Good
## 5343 Very Good
## 5344 Good
## 5345 Bad
## 5346 Bad
## 5347 Good
## 5348 Good
## 5349 Good
## 5351 Good
## 5353 Bad
## 5355 Bad
## 5356 Bad
## 5359 Good
## 5360 Bad
## 5361 Bad
## 5363 Good
## 5364 Bad
## 5365 Good
## 5367 Good
## 5370 Good
## 5372 Bad
## 5373 Good
## 5374 Bad
## 5375 Bad
## 5377 Bad
## 5378 Good
## 5380 Very Good
## 5384 Bad
## 5385 Bad
## 5386 Good
## 5388 Good
## 5389 Good
## 5390 Very Good
## 5391 Very Good
## 5393 Good
## 5394 Very Good
## 5395 Good
## 5396 Bad
## 5397 Very Good
## 5399 Good
## 5402 Very Good
## 5404 Very Good
## 5405 Very Good
## 5406 Good
## 5407 Good
## 5410 Good
## 5411 Good
## 5412 Very Good
## 5413 Very Good
## 5417 Good
## 5418 Bad
## 5419 Good
## 5420 Bad
## 5421 Bad
## 5422 Bad
## 5423 Bad
## 5424 Bad
## 5425 Bad
## 5426 Good
## 5427 Good
## 5428 Bad
## 5429 Good
## 5430 Bad
## 5431 Bad
## 5433 Good
## 5434 Good
## 5435 Bad
## 5436 Good
## 5439 Bad
## 5440 Good
## 5441 Bad
## 5442 Good
## 5444 Bad
## 5445 Good
## 5446 Good
## 5447 Good
## 5448 Good
## 5449 Good
## 5450 Good
## 5451 Good
## 5460 Bad
## 5461 Bad
## 5462 Good
## 5468 Good
## 5469 Good
## 5470 Good
## 5471 Bad
## 5472 Very Bad
## 5473 Good
## 5475 Very Bad
## 5476 Bad
## 5477 Bad
## 5478 Good
## 5481 Bad
## 5482 Very Good
## 5484 Good
## 5485 Very Good
## 5486 Bad
## 5488 Very Good
## 5489 Bad
## 5490 Good
## 5491 Bad
## 5492 Bad
## 5493 Bad
## 5494 Bad
## 5497 Good
## 5499 Very Bad
## 5501 Bad
## 5503 Good
## 5504 Good
## 5505 Very Good
## 5506 Good
## 5509 Bad
## 5511 Good
## 5512 Bad
## 5514 Bad
## 5515 Bad
## 5516 Good
## 5517 Bad
## 5518 Bad
## 5519 Bad
## 5520 Bad
## 5521 Bad
## 5522 Good
## 5523 Bad
## 5524 Bad
## 5525 Bad
## 5526 Bad
## 5527 Good
## 5528 Bad
## 5529 Good
## 5530 Bad
## 5531 Good
## 5533 Bad
## 5537 Very Good
## 5539 Bad
## 5540 Bad
## 5541 Bad
## 5542 Bad
## 5543 Bad
## 5544 Very Good
## 5545 Bad
## 5546 Very Bad
## 5547 Very Good
## 5548 Good
## 5549 Bad
## 5553 Bad
## 5554 Bad
## 5555 Bad
## 5556 Very Good
## 5557 Good
## 5558 Very Bad
## 5559 Good
## 5560 Bad
## 5561 Good
## 5562 Good
## 5563 Bad
## 5564 Bad
## 5566 Good
## 5567 Bad
## 5568 Good
## 5569 Bad
## 5570 Bad
## 5572 Bad
## 5573 Good
## 5574 Bad
## 5575 Good
## 5576 Bad
## 5577 Bad
## 5578 Bad
## 5580 Good
## 5581 Bad
## 5582 Bad
## 5584 Bad
## 5585 Bad
## 5586 Bad
## 5587 Bad
## 5592 Bad
## 5593 Bad
## 5595 Good
## 5596 Good
## 5597 Bad
## 5598 Good
## 5600 Good
## 5601 Good
## 5602 Very Bad
## 5603 Very Bad
## 5605 Bad
## 5606 Bad
## 5607 Good
## 5608 Good
## 5610 Bad
## 5611 Bad
## 5612 Bad
## 5613 Bad
## 5614 Good
## 5615 Bad
## 5616 Bad
## 5617 Bad
## 5618 Bad
## 5619 Bad
## 5620 Bad
## 5621 Bad
## 5624 Bad
## 5626 Bad
## 5627 Bad
## 5631 Bad
## 5632 Bad
## 5633 Bad
## 5634 Bad
## 5635 Bad
## 5636 Good
## 5637 Bad
## 5638 Bad
## 5639 Good
## 5640 Bad
## 5641 Bad
## 5642 Bad
## 5643 Bad
## 5644 Good
## 5645 Good
## 5646 Bad
## 5647 Good
## 5648 Good
## 5649 Bad
## 5650 Bad
## 5651 Bad
## 5652 Bad
## 5656 Bad
## 5657 Bad
## 5658 Bad
## 5659 Bad
## 5660 Bad
## 5661 Good
## 5662 Bad
## 5663 Good
## 5664 Good
## 5665 Bad
## 5666 Bad
## 5667 Good
## 5668 Bad
## 5669 Good
## 5670 Bad
## 5671 Bad
## 5672 Good
## 5673 Good
## 5677 Bad
## 5678 Bad
## 5680 Bad
## 5681 Bad
## 5682 Bad
## 5683 Bad
## 5684 Bad
## 5685 Bad
## 5686 Good
## 5687 Good
## 5688 Bad
## 5689 Good
## 5690 Bad
## 5691 Good
## 5692 Bad
## 5693 Good
## 5695 Bad
## 5696 Very Good
## 5697 Good
## 5698 Good
## 5699 Bad
## 5700 Bad
## 5702 Good
## 5703 Good
## 5704 Very Good
## 5705 Very Good
## 5706 Very Good
## 5707 Bad
## 5708 Good
## 5709 Bad
## 5711 Bad
## 5712 Very Bad
## 5714 Bad
## 5715 Good
## 5716 Good
## 5717 Bad
## 5718 Bad
## 5719 Bad
## 5721 Bad
## 5722 Bad
## 5723 Bad
## 5724 Bad
## 5725 Very Good
## 5726 Bad
## 5727 Very Good
## 5728 Good
## 5729 Very Bad
## 5730 Good
## 5731 Very Bad
## 5733 Bad
## 5734 Bad
## 5735 Very Good
## 5736 Very Good
## 5737 Very Good
## 5738 Bad
## 5739 Very Good
## 5740 Bad
## 5741 Good
## 5742 Bad
## 5743 Good
## 5744 Bad
## 5745 Bad
## 5746 Good
## 5747 Bad
## 5748 Bad
## 5749 Bad
## 5750 Bad
## 5751 Bad
## 5752 Good
## 5753 Good
## 5754 Very Good
## 5755 Good
## 5756 Very Good
## 5757 Very Good
## 5758 Good
## 5759 Bad
## 5761 Bad
## 5762 Bad
## 5763 Bad
## 5764 Bad
## 5765 Good
## 5766 Good
## 5767 Good
## 5768 Good
## 5769 Good
## 5770 Bad
## 5771 Very Bad
## 5772 Very Good
## 5773 Very Good
## 5774 Very Good
## 5775 Very Bad
## 5776 Good
## 5777 Good
## 5778 Bad
## 5779 Bad
## 5780 Good
## 5782 Bad
## 5783 Good
## 5784 Bad
## 5785 Good
## 5786 Very Good
## 5787 Good
## 5789 Bad
## 5790 Bad
## 5791 Good
## 5792 Bad
## 5793 Good
## 5794 Good
## 5795 Very Good
## 5796 Good
## 5797 Very Good
## 5799 Bad
## 5800 Very Good
## 5801 Very Good
## 5802 Very Good
## 5803 Very Good
## 5804 Bad
## 5805 Bad
## 5806 Good
## 5807 Good
## 5808 Good
## 5810 Good
## 5811 Good
## 5812 Very Good
## 5813 Good
## 5814 Good
## 5816 Good
## 5817 Good
## 5818 Good
## 5819 Bad
## 5820 Good
## 5821 Good
## 5822 Good
## 5823 Bad
## 5824 Very Good
## 5826 Very Bad
## 5827 Bad
## 5828 Very Good
## 5829 Bad
## 5830 Bad
## 5831 Good
## 5832 Bad
## 5833 Bad
## 5834 Good
## 5835 Good
## 5836 Very Bad
## 5837 Very Good
## 5838 Bad
## 5839 Very Good
## 5840 Very Good
## 5841 Very Good
## 5842 Very Good
## 5843 Very Good
## 5844 Very Good
## 5845 Very Good
## 5846 Very Good
## 5847 Very Good
## 5848 Very Good
## 5849 Very Good
## 5850 Very Good
## 5851 Very Good
## 5852 Very Good
## 5853 Good
## 5854 Bad
## 5855 Good
## 5856 Good
## 5857 Very Good
## 5858 Bad
## 5859 Good
## 5860 Bad
## 5861 Bad
## 5862 Good
## 5863 Good
## 5864 Good
## 5865 Very Good
## 5866 Bad
## 5867 Good
## 5868 Bad
## 5869 Good
## 5870 Good
## 5871 Very Good
## 5872 Bad
## 5873 Very Good
## 5874 Bad
## 5875 Bad
## 5876 Bad
## 5877 Very Good
## 5879 Good
## 5880 Bad
## 5882 Good
## 5884 Good
## 5885 Very Good
## 5886 Bad
## 5887 Bad
## 5888 Good
## 5889 Bad
## 5890 Bad
## 5891 Good
## 5892 Bad
## 5893 Bad
## 5894 Good
## 5895 Very Good
## 5896 Very Good
## 5898 Good
## 5899 Very Good
## 5900 Very Good
## 5901 Very Good
## 5902 Very Good
## 5903 Bad
## 5904 Very Good
## 5905 Very Good
## 5906 Very Good
## 5907 Very Good
## 5908 Bad
## 5909 Very Good
## 5910 Good
## 5912 Good
## 5913 Good
## 5914 Good
## 5915 Very Good
## 5916 Good
## 5917 Good
## 5918 Bad
## 5921 Bad
## 5922 Good
## 5923 Very Good
## 5924 Good
## 5925 Good
## 5926 Bad
## 5927 Good
## 5928 Very Good
## 5929 Very Good
## 5930 Very Good
## 5931 Bad
## 5932 Good
## 5933 Good
## 5934 Very Good
## 5935 Very Good
## 5936 Bad
## 5937 Very Good
## 5938 Good
## 5939 Bad
## 5940 Good
## 5941 Good
## 5942 Very Good
## 5943 Good
## 5944 Good
## 5945 Good
## 5946 Bad
## 5947 Good
## 5948 Good
## 5949 Bad
## 5951 Bad
## 5952 Very Good
## 5953 Good
## 5954 Good
## 5955 Very Good
## 5956 Bad
## 5957 Very Good
## 5958 Very Good
## 5959 Good
## 5960 Very Good
## 5961 Good
## 5962 Good
## 5963 Good
## 5964 Good
## 5965 Very Good
## 5966 Very Good
## 5967 Very Good
## 5968 Bad
## 5969 Very Good
## 5970 Bad
## 5971 Good
## 5972 Good
## 5973 Bad
## 5974 Very Good
## 5975 Good
## 5976 Bad
## 5977 Bad
## 5979 Good
## 5981 Good
## 5982 Good
## 5983 Good
## 5984 Bad
## 5985 Very Good
## 5986 Good
## 5987 Very Good
## 5988 Very Good
## 5989 Very Good
## 5990 Good
## 5991 Good
## 5992 Very Good
## 5993 Good
## 5994 Bad
## 5995 Good
## 5996 Bad
## 5998 Bad
## 5999 Good
## 6000 Good
## 6001 Good
## 6002 Good
## 6003 Good
## 6004 Bad
## 6005 Good
## 6006 Very Good
## 6007 Bad
## 6008 Good
## 6009 Good
## 6011 Good
## 6012 Good
## 6013 Good
## 6014 Good
## 6015 Good
## 6016 Good
## 6017 Good
## 6018 Bad
## 6019 Very Good
## 6020 Good
## 6021 Good
## 6022 Good
## 6023 Very Bad
## 6024 Very Good
## 6025 Good
## 6026 Good
## 6027 Bad
## 6028 Good
## 6029 Good
## 6030 Bad
## 6031 Very Good
## 6032 Very Good
## 6033 Very Good
## 6034 Good
## 6035 Good
## 6036 Good
## 6037 Bad
## 6038 Good
## 6039 Good
## 6040 Good
## 6041 Good
## 6042 Good
## 6043 Bad
## 6044 Good
## 6046 Very Good
## 6047 Good
## 6048 Good
## 6049 Very Good
## 6050 Good
## 6051 Bad
## 6052 Good
## 6053 Good
## 6054 Bad
## 6055 Very Good
## 6058 Bad
## 6059 Very Good
## 6060 Good
## 6061 Very Good
## 6062 Bad
## 6063 Bad
## 6065 Bad
## 6066 Very Good
## 6067 Good
## 6068 Good
## 6069 Good
## 6070 Good
## 6071 Good
## 6072 Good
## 6073 Good
## 6074 Good
## 6075 Very Bad
## 6076 Very Good
## 6078 Good
## 6079 Good
## 6080 Bad
## 6081 Good
## 6082 Bad
## 6083 Bad
## 6084 Good
## 6085 Bad
## 6086 Good
## 6087 Bad
## 6089 Good
## 6091 Very Good
## 6093 Good
## 6094 Good
## 6095 Good
## 6096 Good
## 6097 Good
## 6098 Good
## 6099 Good
## 6100 Very Good
## 6101 Very Good
## 6102 Bad
## 6103 Very Good
## 6104 Very Good
## 6105 Very Good
## 6107 Very Good
## 6108 Very Good
## 6109 Good
## 6110 Bad
## 6111 Good
## 6112 Good
## 6113 Good
## 6114 Good
## 6115 Good
## 6116 Good
## 6117 Good
## 6118 Good
## 6119 Good
## 6120 Good
## 6121 Good
## 6122 Good
## 6124 Bad
## 6125 Bad
## 6126 Bad
## 6128 Bad
## 6129 Good
## 6130 Bad
## 6131 Bad
## 6132 Very Bad
## 6133 Good
## 6134 Very Bad
## 6135 Good
## 6136 Good
## 6137 Very Bad
## 6138 Very Bad
## 6139 Bad
## 6140 Bad
## 6141 Good
## 6142 Bad
## 6143 Good
## 6144 Bad
## 6145 Bad
## 6146 Bad
## 6147 Good
## 6148 Good
## 6149 Good
## 6150 Bad
## 6151 Bad
## 6152 Bad
## 6153 Bad
## 6154 Bad
## 6155 Bad
## 6156 Good
## 6157 Good
## 6158 Good
## 6161 Bad
## 6162 Very Bad
## 6163 Good
## 6164 Good
## 6165 Good
## 6166 Good
## 6167 Good
## 6170 Good
## 6171 Bad
## 6172 Bad
## 6173 Good
## 6174 Good
## 6175 Very Bad
## 6176 Good
## 6177 Good
## 6178 Very Good
## 6179 Good
## 6180 Good
## 6181 Good
## 6182 Good
## 6183 Bad
## 6184 Bad
## 6185 Good
## 6186 Bad
## 6189 Bad
## 6190 Good
## 6191 Good
## 6192 Very Bad
## 6193 Good
## 6194 Bad
## 6195 Bad
## 6196 Good
## 6197 Good
## 6200 Good
## 6201 Good
## 6202 Bad
## 6203 Bad
## 6204 Bad
## 6205 Bad
## 6206 Very Bad
## 6207 Bad
## 6208 Bad
## 6209 Bad
## 6210 Good
## 6212 Good
## 6213 Good
## 6214 Good
## 6216 Good
## 6217 Good
## 6219 Bad
## 6221 Bad
## 6222 Very Good
## 6223 Good
## 6224 Good
## 6225 Good
## 6226 Good
## 6227 Bad
## 6228 Good
## 6229 Good
## 6230 Bad
## 6231 Good
## 6232 Bad
## 6234 Good
## 6235 Bad
## 6236 Bad
## 6237 Bad
## 6238 Good
## 6239 Good
## 6240 Good
## 6241 Good
## 6242 Good
## 6243 Bad
## 6244 Good
## 6245 Bad
## 6246 Bad
## 6247 Bad
## 6248 Bad
## 6249 Bad
## 6250 Good
## 6251 Bad
## 6252 Bad
## 6253 Bad
## 6254 Bad
## 6255 Bad
## 6256 Good
## 6257 Bad
## 6258 Good
## 6259 Bad
## 6260 Bad
## 6261 Good
## 6262 Very Bad
## 6263 Good
## 6264 Bad
## 6265 Bad
## 6267 Good
## 6268 Very Bad
## 6272 Bad
## 6274 Bad
## 6275 Bad
## 6277 Good
## 6278 Good
## 6279 Good
## 6280 Bad
## 6281 Bad
## 6282 Bad
## 6283 Bad
## 6284 Bad
## 6285 Bad
## 6286 Bad
## 6287 Bad
## 6288 Bad
## 6289 Good
## 6290 Bad
## 6291 Bad
## 6292 Bad
## 6293 Bad
## 6294 Good
## 6295 Bad
## 6296 Bad
## 6297 Very Good
## 6298 Good
## 6299 Bad
## 6300 Bad
## 6301 Good
## 6303 Good
## 6304 Very Good
## 6305 Good
## 6306 Good
## 6308 Good
## 6310 Good
## 6311 Good
## 6312 Bad
## 6313 Bad
## 6314 Bad
## 6315 Bad
## 6316 Very Good
## 6317 Bad
## 6318 Bad
## 6319 Bad
## 6320 Bad
## 6321 Good
## 6322 Very Bad
## 6323 Good
## 6324 Good
## 6326 Bad
## 6327 Bad
## 6328 Bad
## 6329 Bad
## 6330 Good
## 6331 Good
## 6332 Very Good
## 6335 Bad
## 6337 Bad
## 6338 Good
## 6339 Very Good
## 6340 Good
## 6341 Bad
## 6342 Bad
## 6343 Good
## 6344 Good
## 6345 Bad
## 6346 Bad
## 6347 Bad
## 6348 Very Good
## 6349 Very Good
## 6350 Very Good
## 6351 Very Good
## 6352 Bad
## 6353 Good
## 6354 Good
## 6355 Good
## 6356 Bad
## 6357 Bad
## 6358 Very Good
## 6360 Very Bad
## 6361 Good
## 6362 Good
## 6363 Bad
## 6364 Bad
## 6365 Very Good
## 6367 Very Good
## 6369 Bad
## 6370 Bad
## 6371 Good
## 6372 Bad
## 6377 Very Bad
## 6378 Bad
## 6379 Very Bad
## 6380 Bad
## 6382 Bad
## 6383 Very Bad
## 6384 Bad
## 6385 Bad
## 6386 Bad
## 6387 Bad
## 6388 Good
## 6389 Good
## 6390 Bad
## 6391 Bad
## 6392 Bad
## 6393 Very Good
## 6394 Good
## 6395 Bad
## 6396 Good
## 6397 Good
## 6398 Good
## 6399 Bad
## 6400 Bad
## 6401 Bad
## 6402 Good
## 6403 Good
## 6404 Very Bad
## 6405 Good
## 6406 Good
## 6408 Bad
## 6409 Good
## 6410 Bad
## 6411 Good
## 6412 Good
## 6413 Good
## 6414 Good
## 6416 Good
## 6417 Bad
## 6418 Bad
## 6419 Good
## 6420 Very Bad
## 6422 Bad
## 6423 Good
## 6424 Bad
## 6425 Good
## 6426 Good
## 6427 Good
## 6428 Good
## 6429 Good
## 6430 Bad
## 6431 Good
## 6432 Bad
## 6433 Very Good
## 6434 Good
## 6435 Good
## 6436 Good
## 6437 Bad
## 6438 Bad
## 6439 Good
## 6440 Very Good
## 6441 Good
## 6442 Good
## 6443 Very Good
## 6444 Good
## 6445 Bad
## 6446 Bad
## 6447 Bad
## 6448 Very Good
## 6449 Bad
## 6450 Bad
## 6451 Good
## 6452 Bad
## 6453 Good
## 6454 Very Good
## 6455 Bad
## 6456 Good
## 6458 Bad
## 6459 Bad
## 6460 Bad
## 6461 Bad
## 6462 Bad
## 6463 Bad
## 6464 Good
## 6466 Bad
## 6467 Bad
## 6468 Good
## 6470 Good
## 6471 Bad
## 6472 Good
## 6474 Good
## 6475 Good
## 6476 Good
## 6477 Good
## 6478 Bad
## 6479 Good
## 6480 Bad
## 6481 Bad
## 6482 Bad
## 6483 Very Good
## 6484 Good
## 6485 Good
## 6486 Good
## 6487 Good
## 6488 Bad
## 6489 Good
## 6490 Good
## 6491 Good
## 6492 Good
## 6493 Bad
## 6494 Good
## 6495 Good
## 6496 Bad
## 6497 Good
##
## $subset
## NULL
##
## $outlierMethod
## [1] "none"
##
## attr(,"class")
## [1] "mvn"pred_vars <- df_final %>% dplyr::select(-quality_label) %>% names()
par(mfrow = c(3, 4))
for (var in pred_vars) {
qqnorm(df_final[[var]], main = paste('Q-Q Plot:', var), cex.main = 0.9)
qqline(df_final[[var]], col = 'red')
}
par(mfrow = c(1, 1))
As expected, the Henze-Zirkler test formally rejects multivariate normality (HZ = 4.935, p < 0.001. Nevertheless, visual inspection of Q-Q plots reveales that all predictors follow the theoretical normal line closely through the central distribution, with only minor tail deviations. This pattern is only indicates a slight skewness rather than a major distributional violation. This rejection is therefore due to the high statistical strength at n ≈ 5,970, which is sensitive to even the slightest deviation, and the assumption of normality is considered to be satisfied well enough for the LDA to proceed.
However, as stated earlier, there is a slight chance that the estimated probabilities assigned to each group may be unreliable. Given the mild tail deviations observed in the Q-Q plots, this effect is expected to be minor rather than severe, though results near the decision boundary between adjacent quality tiers should be interpreted cautiously.
3.2.2 Homogenity of Variance
LDA pools covariance matrices from all groups into a single matrix of `\(S_{pooled}\)`, which serves as a shared variance structure for constructing the linear decision boundaries. This pooling will only produces a valid boundary if all groups share the same underlying covariance structure. We use Box’s M rather than Bartlett because Box’s M evaluates the entire ‘\(p \times p\)’ covariance matrix simultaneously, while the latter only checks univariate variances and ignores covariances entirely.
If this assumption fails substantially, `\(S_{pooled}\)` becomes a distorted representation of each group’s true spread, causing the linear boundary to be misaligned and misclassification rates to increase. The best expected outcome is a non-significant Box’s M (p > 0.05), though at n ≈ 5,970 rejection is almost certain due to high statistical power detecting even trivially small differences
boxM_result <- boxM(
data = df_final %>% dplyr::select(-quality_label),
grouping = df_final$quality_label
)
print(boxM_result)##
## Box's M-test for Homogeneity of Covariance Matrices
##
## data: df_final %>% dplyr::select(-quality_label)
## Chi-Sq (approx.) = 2266.6, df = 165, p-value < 2.2e-16pred_vars <- df_final %>% dplyr::select(-quality_label) %>% names()
plot_list <- lapply(levels(df_final$quality_label), function(grp) {
cor_mat <- df_final %>%
filter(quality_label == grp) %>%
dplyr::select(all_of(pred_vars)) %>%
cor()
ggcorrplot(cor_mat,
method = 'square',
type = 'lower',
lab = FALSE,
tl.cex = 7,
colors = c('#2980b9', 'white', '#922b21'),
title = paste('Correlation Structure:', grp),
ggtheme = theme_minimal())
})## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## ℹ The deprecated feature was likely used in the ggcorrplot package.
## Please report the issue at <https://github.com/kassambara/ggcorrplot/issues>.
## This warning is displayed once per session.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
4 Ordinal Logistic
4.1 Model Summary
model_final <- vglm(
quality_label ~ fixed.acidity + volatile.acidity + citric.acid +
residual.sugar + free.sulfur.dioxide + total.sulfur.dioxide +
sulphates + alcohol + chlorides + pH,
family = cumulative(parallel = FALSE ~ free.sulfur.dioxide + alcohol +
chlorides + pH,
reverse = FALSE),
data = df_final
)
summary(model_final)##
## Call:
## vglm(formula = quality_label ~ fixed.acidity + volatile.acidity +
## citric.acid + residual.sugar + free.sulfur.dioxide + total.sulfur.dioxide +
## sulphates + alcohol + chlorides + pH, family = cumulative(parallel = FALSE ~
## free.sulfur.dioxide + alcohol + chlorides + pH, reverse = FALSE),
## data = df_final)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept):1 4.146e+00 1.828e+00 2.268 0.023299 *
## (Intercept):2 1.200e+01 9.273e-01 12.939 < 2e-16 ***
## (Intercept):3 1.375e+01 1.030e+00 13.355 < 2e-16 ***
## fixed.acidity -8.539e-02 3.132e-02 -2.726 0.006403 **
## volatile.acidity 4.043e+00 2.467e-01 16.386 < 2e-16 ***
## citric.acid 5.678e-01 2.537e-01 2.238 0.025239 *
## residual.sugar -6.622e-02 6.985e-03 -9.481 < 2e-16 ***
## free.sulfur.dioxide:1 -5.248e-02 6.212e-03 -8.449 < 2e-16 ***
## free.sulfur.dioxide:2 -2.160e-02 2.649e-03 -8.155 3.49e-16 ***
## free.sulfur.dioxide:3 -1.504e-02 2.890e-03 -5.203 1.96e-07 ***
## total.sulfur.dioxide 6.804e-03 8.073e-04 8.428 < 2e-16 ***
## sulphates -2.234e+00 2.349e-01 -9.514 < 2e-16 ***
## alcohol:1 -4.653e-01 8.041e-02 -5.787 7.16e-09 ***
## alcohol:2 -9.685e-01 3.780e-02 -25.620 < 2e-16 ***
## alcohol:3 -9.030e-01 3.767e-02 -23.972 < 2e-16 ***
## chlorides:1 -1.581e+01 4.300e+00 -3.677 0.000236 ***
## chlorides:2 3.385e+00 1.976e+00 1.713 0.086686 .
## chlorides:3 1.249e+01 2.592e+00 4.816 1.46e-06 ***
## pH:1 -2.767e-01 5.179e-01 -0.534 0.593167
## pH:2 -7.159e-01 2.325e-01 -3.079 0.002078 **
## pH:3 -8.659e-01 2.594e-01 -3.338 0.000843 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Names of linear predictors: logitlink(P[Y<=1]), logitlink(P[Y<=2]),
## logitlink(P[Y<=3])
##
## Residual deviance: 11570.2 on 17889 degrees of freedom
##
## Log-likelihood: -5785.101 on 17889 degrees of freedom
##
## Number of Fisher scoring iterations: 8
##
##
## Exponentiated coefficients:
## fixed.acidity volatile.acidity citric.acid
## 9.181517e-01 5.699160e+01 1.764351e+00
## residual.sugar free.sulfur.dioxide:1 free.sulfur.dioxide:2
## 9.359254e-01 9.488703e-01 9.786293e-01
## free.sulfur.dioxide:3 total.sulfur.dioxide sulphates
## 9.850741e-01 1.006827e+00 1.070458e-01
## alcohol:1 alcohol:2 alcohol:3
## 6.279229e-01 3.796532e-01 4.053672e-01
## chlorides:1 chlorides:2 chlorides:3
## 1.361739e-07 2.952763e+01 2.643803e+05
## pH:1 pH:2 pH:3
## 7.582817e-01 4.887437e-01 4.206928e-01The three intercepts run 4.15, 12.00, and 13.75, increasing monotonically across the cutpoints, confirming the model is internally consistent. Alcohol and volatile acidity dominate by z-value (25.6 and 16.4 respectively), with sulphates and residual sugar close behind. The weak predictors are pH:1 (z = -0.53, p = 0.59) and chlorides:2 (z = 1.71, p = 0.087). Citric acid clears the 0.05 threshold at p = 0.025, borderline but significant. Residual deviance is 11,570.2, which serves as a baseline for any subsequent model comparisons involving pH:1 or chlorides:2.
4.2 Simultaneous Test (G-Statistic)
model_null <- vglm(quality_label ~ 1,
family = cumulative(parallel = TRUE, reverse = FALSE),
data = df_final)
G_stat <- deviance(model_null) - deviance(model_final)
df_G <- df.residual(model_null) - df.residual(model_final)
p_G <- pchisq(G_stat, df = df_G, lower.tail = FALSE)
cat("G statistic :", round(G_stat, 4), "\n")## G statistic : 2305.58## Degrees of freedom: 18## P-value : 0if (p_G < 0.05) {
cat("Decision: Reject H0, at least one predictor significantly influences wine quality.\n")
} else {
cat("Decision: Fail to reject H0.\n")
}## Decision: Reject H0, at least one predictor significantly influences wine quality.The G-statistic tests whether the predictors as a group do anything useful compared to a model with no predictors at all. With G = 2305.58, df = 18, and p < 0.05, we reject the null hypothesis. The chemical predictors collectively explain a significant portion of the variation in quality tier.
The size of the statistic is worth noting. A G of 2305.58 on 18 degrees of freedom is very large, which tells us the model is not just barely significant. The physicochemical variables carry real and substantial information about quality.
4.3 Partial Test (Wald Test)
coef_table <- coef(summary(model_final))
wald_table <- as.data.frame(coef_table)
colnames(wald_table) <- c("Value", "Std.Error", "z")
wald_table$W2 <- wald_table$z^2
wald_table$p_value <- pchisq(wald_table$W2, df = 1, lower.tail = FALSE)
print(round(wald_table, 4))## Value Std.Error z <NA> W2 p_value
## (Intercept):1 4.1464 1.8278 2.2685 0.0233 5.1460 0.0233
## (Intercept):2 11.9982 0.9273 12.9392 0.0000 167.4228 0.0000
## (Intercept):3 13.7508 1.0297 13.3546 0.0000 178.3444 0.0000
## fixed.acidity -0.0854 0.0313 -2.7264 0.0064 7.4333 0.0064
## volatile.acidity 4.0429 0.2467 16.3860 0.0000 268.5015 0.0000
## citric.acid 0.5678 0.2537 2.2377 0.0252 5.0074 0.0252
## residual.sugar -0.0662 0.0070 -9.4807 0.0000 89.8846 0.0000
## free.sulfur.dioxide:1 -0.0525 0.0062 -8.4486 0.0000 71.3787 0.0000
## free.sulfur.dioxide:2 -0.0216 0.0026 -8.1550 0.0000 66.5036 0.0000
## free.sulfur.dioxide:3 -0.0150 0.0029 -5.2027 0.0000 27.0680 0.0000
## total.sulfur.dioxide 0.0068 0.0008 8.4282 0.0000 71.0346 0.0000
## sulphates -2.2345 0.2349 -9.5143 0.0000 90.5226 0.0000
## alcohol:1 -0.4653 0.0804 -5.7872 0.0000 33.4919 0.0000
## alcohol:2 -0.9685 0.0378 -25.6201 0.0000 656.3871 0.0000
## alcohol:3 -0.9030 0.0377 -23.9720 0.0000 574.6550 0.0000
## chlorides:1 -15.8093 4.3001 -3.6765 0.0002 13.5168 0.0002
## chlorides:2 3.3853 1.9761 1.7131 0.0867 2.9349 0.0867
## chlorides:3 12.4851 2.5923 4.8163 0.0000 23.1966 0.0000
## pH:1 -0.2767 0.5179 -0.5343 0.5932 0.2854 0.5932
## pH:2 -0.7159 0.2325 -3.0789 0.0021 9.4797 0.0021
## pH:3 -0.8659 0.2594 -3.3383 0.0008 11.1442 0.0008# Filter to predictor rows only (exclude intercepts)
coef_predictors <- wald_table[!grepl("\\(Intercept\\)", rownames(wald_table)), ]
coef_predictors$Variable <- rownames(coef_predictors)
coef_predictors$Significant <- coef_predictors$p_value < 0.05
coef_predictors$Lower <- coef_predictors$Value - 1.96 * coef_predictors$Std.Error
coef_predictors$Upper <- coef_predictors$Value + 1.96 * coef_predictors$Std.Error
ggplot(coef_predictors, aes(x = reorder(Variable, Value), y = Value, color = Significant)) +
geom_point(size = 3) +
geom_errorbar(aes(ymin = Lower, ymax = Upper), width = 0.3) +
geom_hline(yintercept = 0, linetype = "dashed", color = "gray50") +
coord_flip() +
scale_color_manual(values = c("FALSE" = "#bdc3c7", "TRUE" = "#c0392b"),
labels = c("Not significant", "Significant (p < 0.05)")) +
theme_minimal() +
labs(title = "Predictor Coefficients with 95% Confidence Intervals",
subtitle = "Red points are statistically significant in the Wald test",
x = "Predictor", y = "Coefficient Estimate", color = "Significance")
Most predictors are significant at the 0.05 level. Among the non-parallel terms, pH:1 does not reach significance (W² = 0.29, p = 0.593), and chlorides:2 is marginal (W² = 2.93, p = 0.087). All other predictor rows clear the threshold, including citric acid (W² = 5.01, p = 0.025). The three intercept rows at the bottom correspond to the quality cutpoints and confirm that the boundaries between tiers are statistically real, which is expected given the sample size.
4.4 Odds Ratios
coefs <- coef(model_final)
se_coefs <- sqrt(diag(vcov(model_final)))
# Exclude intercept rows
pred_idx <- !grepl("\\(Intercept\\)", names(coefs))
OR_table <- data.frame(
OR = exp(coefs[pred_idx]),
Lower_95 = exp(coefs[pred_idx] - 1.96 * se_coefs[pred_idx]),
Upper_95 = exp(coefs[pred_idx] + 1.96 * se_coefs[pred_idx])
)
print(round(OR_table, 4))## OR Lower_95 Upper_95
## fixed.acidity 0.9182 0.8635 9.763000e-01
## volatile.acidity 56.9916 35.1391 9.243380e+01
## citric.acid 1.7644 1.0730 2.901100e+00
## residual.sugar 0.9359 0.9232 9.488000e-01
## free.sulfur.dioxide:1 0.9489 0.9374 9.605000e-01
## free.sulfur.dioxide:2 0.9786 0.9736 9.837000e-01
## free.sulfur.dioxide:3 0.9851 0.9795 9.907000e-01
## total.sulfur.dioxide 1.0068 1.0052 1.008400e+00
## sulphates 0.1070 0.0676 1.696000e-01
## alcohol:1 0.6279 0.5364 7.351000e-01
## alcohol:2 0.3797 0.3525 4.089000e-01
## alcohol:3 0.4054 0.3765 4.364000e-01
## chlorides:1 0.0000 0.0000 6.000000e-04
## chlorides:2 29.5276 0.6140 1.420070e+03
## chlorides:3 264380.2817 1643.0042 4.254215e+07
## pH:1 0.7583 0.2748 2.092600e+00
## pH:2 0.4887 0.3099 7.709000e-01
## pH:3 0.4207 0.2530 6.994000e-01or_df <- OR_table
or_df$Variable <- rownames(or_df)
ggplot(or_df, aes(x = reorder(Variable, OR), y = OR)) +
geom_point(size = 3, color = "#2980b9") +
geom_errorbar(aes(ymin = Lower_95, ymax = Upper_95), width = 0.3, color = "#2980b9") +
geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
coord_flip() +
theme_minimal() +
labs(title = "Odds Ratios with 95% Confidence Intervals",
subtitle = "OR > 1 increases the odds of a higher quality tier; OR < 1 decreases it",
x = "Predictor", y = "Odds Ratio")
Volatile acidity carries the largest effect among the parallel terms (OR = 56.99), where each one-unit increase is associated with substantially higher odds of falling into a lower quality tier. Sulphates moves in the opposite direction (OR = 0.107), as does alcohol across all three cutpoints (ORs ranging from 0.38 to 0.63).
Among the non-parallel terms, chlorides shows the widest spread: chlorides:1 approaches zero while chlorides:3 reaches 264,380, both with confidence intervals too wide to interpret reliably. The two rows whose confidence intervals actually cross 1.0 are pH:1 (OR = 0.758, 95% CI: 0.275 to 2.093) and chlorides:2 (OR = 29.53, 95% CI: 0.614 to 1,420). The threshold rows are not predictor odds ratios and should not be interpreted as such.
4.5 Predicted Probabilities and Confusion Matrix
pred_probs <- predict(model_final, type = "response")
pred_class <- factor(
levels(df_final$quality_label)[apply(pred_probs, 1, which.max)],
levels = levels(df_final$quality_label)
)
conf_matrix <- table(Predicted = pred_class, Actual = df_final$quality_label)
print(conf_matrix)## Actual
## Predicted Very Bad Bad Good Very Good
## Very Bad 0 0 0 0
## Bad 114 1155 572 88
## Good 80 771 1775 731
## Very Good 5 22 280 377accuracy <- sum(diag(conf_matrix)) / sum(conf_matrix)
cat("Overall Accuracy:", round(accuracy * 100, 2), "%\n")## Overall Accuracy: 55.39 %conf_df <- as.data.frame(conf_matrix)
ggplot(conf_df, aes(x = Actual, y = Predicted, fill = Freq)) +
geom_tile(color = "white") +
geom_text(aes(label = Freq), size = 5) +
scale_fill_gradient(low = "#f9ebea", high = "#922b21") +
theme_minimal() +
labs(title = "Confusion Matrix: Partial Proportional Odds Model",
subtitle = paste("Overall accuracy:", round(accuracy * 100, 2), "%"),
x = "Actual Quality Tier", y = "Predicted Quality Tier", fill = "Count")
The model reaches 55.39% overall accuracy on the training data. Performance is strongest on the Good tier (1,775 correct) and completely absent on Very Bad, where the model predicts zero instances across all 199 actual cases. This is a direct consequence of class imbalance: with Very Bad representing a small fraction of the data, the model has no incentive to predict it.
The largest source of misclassification falls between Bad and Good, with 771 Bad cases predicted as Good and 572 Good cases predicted as Bad. Good and Very Good also bleed into each other (731 and 280 misclassified respectively), consistent with cutpoints 2 and 3 sitting only 1.75 apart on the log-odds scale compared to the 7.85 gap separating cutpoint 1 from cutpoint 2.
4.6 Pseudo R-Squared
loglik_full <- logLik(model_final)
loglik_null <- logLik(model_null)
n <- nrow(df_final)
mcfadden <- 1 - as.numeric(loglik_full) / as.numeric(loglik_null)
coxsnell <- 1 - exp((2 / n) * (as.numeric(loglik_null) - as.numeric(loglik_full)))
nagelkerke <- coxsnell / (1 - exp((2 / n) * as.numeric(loglik_null)))
cat("McFadden :", round(mcfadden, 4), "\n")## McFadden : 0.1662## CoxSnell : 0.3204## Nagelkerke: 0.3551Ordinal logistic regression has no single R-squared equivalent, so three pseudo-R² measures are reported here. McFadden’s R² is 0.166, Cox-Snell is 0.320, and Nagelkerke is 0.355. McFadden values between 0.1 and 0.4 are generally considered acceptable for logistic models, so 0.166 clears that bar without indicating strong fit.
Cox-Snell and Nagelkerke both suggest the predictors account for roughly 32 to 36% of the variability in quality tier. The remaining variance reflects factors the chemical measurements do not capture, including the subjective nature of sensory evaluation scores used to define quality in the original data.
5 Discriminant Analysis
5.1 Model Summary
## Length Class Mode
## prior 4 -none- numeric
## counts 4 -none- numeric
## means 40 -none- numeric
## scaling 30 -none- numeric
## lev 4 -none- character
## svd 3 -none- numeric
## N 1 -none- numeric
## call 3 -none- call
## terms 3 terms call
## xlevels 0 -none- listUnlike OLR where the summary output of the model can produces such summary, in LDA the output from the model itself is just a preview of each aspects of the model.
The prior and counts output reveals that the model structure is a system that classify data into four groups. It utilizing ten predictor variables based on the forty entries in the group means matrix and the absence of categorical data in the xlevels list.
The classification operates within a three dimensional space, evidenced by the svd length of three and the scaling matrix of thirty. The model is founded on a single total observation count stored in N, while the call and terms entries retain the specific formula and code parameters used to generate the classification object.
However, to understand the output more clearly, we need to deep dive to some most important aspects which we choose to be: prior, means, and scaling,
## === Prior Probabilities ===## Very Bad Bad Good Very Good
## 0.0333 0.3263 0.4400 0.2003##
## === Group Means (Class Centroids) ===## fixed.acidity volatile.acidity citric.acid residual.sugar chlorides
## Very Bad 7.2291 0.4149 0.2695 4.3040 0.0549
## Bad 7.2492 0.3770 0.2969 5.8624 0.0588
## Good 7.0952 0.3064 0.3138 5.5273 0.0505
## Very Good 7.0238 0.2837 0.3304 4.9363 0.0432
## free.sulfur.dioxide total.sulfur.dioxide pH sulphates alcohol
## Very Bad 19.5503 103.8894 3.2275 0.4889 10.1902
## Bad 29.9548 120.9410 3.2152 0.5145 9.8377
## Good 31.4922 117.1011 3.2179 0.5230 10.5810
## Very Good 30.9268 111.2525 3.2237 0.5251 11.4107##
## === Linear Discriminant Coefficients ===## LD1 LD2 LD3
## fixed.acidity 0.0733 0.0532 0.0250
## volatile.acidity -3.7422 4.2659 6.4846
## citric.acid -0.6280 0.6903 4.2654
## residual.sugar 0.0606 -0.0173 0.0361
## chlorides -4.1171 -20.7287 8.2649
## free.sulfur.dioxide 0.0166 -0.0546 0.0337
## total.sulfur.dioxide -0.0057 0.0088 0.0042
## pH 0.6291 0.4056 0.0699
## sulphates 1.8908 -2.2380 0.1264
## alcohol 0.8887 0.2219 0.4161The result from prior that our data is heavily imbalanced where 76.6% of wines fall into the “Bad” or “Good” categories, creating a bias that favors middle-tier classifications. Group means then shows that higher quality wines are chemically characterized by increased alcohol and citric acid levels alongside lower volatile acidity. The LD1 coefficients indicate that volatile acidity and chlorides are the primary negative influences that distinguish lower quality tiers. On the other hands, sulphates and alcohol are the strongest positive contributors on the first discriminant axis for identifying high-quality samples. These coefficients represent the specific weights used to transform the physicochemical data into the three dimensions that maximize separation between quality groups.
5.2 Proportion of Trace
prop_trace <- lda_model$svd^2 / sum(lda_model$svd^2)
names(prop_trace) <- paste0("LD", seq_along(prop_trace))
cat("=== Proportion of Trace ===\n")## === Proportion of Trace ===## LD1 LD2 LD3
## 0.9292 0.0600 0.0108prop_df <- data.frame(
LD = names(prop_trace),
Proportion = as.numeric(prop_trace),
Cumulative = cumsum(as.numeric(prop_trace))
)
ggplot(prop_df, aes(x = LD)) +
geom_bar(aes(y = Proportion), stat = "identity", fill = "#922b21", alpha = 0.8) +
geom_line(aes(y = Cumulative, group = 1), color = "#2c3e50", linewidth = 1.1) +
geom_point(aes(y = Cumulative), color = "#2c3e50", size = 3) +
scale_y_continuous(labels = scales::percent_format()) +
theme_minimal() +
labs(
title = "Proportion of Trace per Discriminant Axis",
subtitle = "Bars = individual variance explained; Line = cumulative",
x = "Linear Discriminant",
y = "Proportion of Trace"
)
The results show that LD1 dominates heavily that itself alone is already contributing 88.3% of the total between-group variance. When combined with the 10.5% from LD2, nearly 99% of the chemical signal is explained, making the third axis statistically redundant. This high concentration indicates that the ten original chemical variables can be effectively split into two dimensions without losing significant information. As a result, the chart proves that the hierarchical progression of wine quality is driven by a highly consistent and linear chemical transition.
5.3 Discriminant Space Visualization
lda_scores <- predict(lda_model)$x
lda_plot_df <- data.frame(
LD1 = lda_scores[, 1],
LD2 = if (ncol(lda_scores) >= 2) lda_scores[, 2] else 0,
Group = df_final$quality_label
)
ggplot(lda_plot_df, aes(x = LD1, y = LD2, color = Group, fill = Group)) +
geom_point(alpha = 0.25, size = 1.2) +
stat_ellipse(geom = "polygon", alpha = 0.10, level = 0.95) +
stat_ellipse(level = 0.95, linewidth = 0.9) +
scale_color_brewer(palette = "RdYlGn") +
scale_fill_brewer(palette = "RdYlGn") +
theme_minimal() +
labs(
title = "Discriminant Space: LD1 vs LD2",
subtitle = "Each ellipse covers 95% of its group's projected observations",
x = paste0("LD1 (", round(prop_trace[1] * 100, 1), "% of trace)"),
y = paste0("LD2 (", round(prop_trace[2] * 100, 1), "% of trace)"),
color = "Quality Tier",
fill = "Quality Tier"
)
The discriminant space plot demonstrate a clear chemical progression along the LD1 axis, where wine quality shifts from “Very Bad” on the left to “Very Good” on the right. This horizontal progress confirms that LD1 is the primary quality tiebreaker by capturing 92.9% of the trace. Significant overlap between the 95% ellipses, especially among the “Bad,” “Good,” and “Very Good” categories, explains why the model often struggles to find perfect boundaries between nearby tiers. Meanwhile, LD2 provides only a minor vertical adjustment with 6% of the trace, helping to refine the separation between the more common middle tier wines.
In the end, the visualization shows that while wine quality follows a predictable chemical DNA, the transitions between levels are continuous and often blurred.
5.4 Classification & Confusion Matrix
lda_pred <- predict(lda_model)
pred_class_lda <- lda_pred$class
conf_lda <- table(Predicted = pred_class_lda, Actual = df_final$quality_label)
precision <- diag(conf_lda) / rowSums(conf_lda)
recall <- diag(conf_lda) / colSums(conf_lda)
f1_score <- 2 * (precision * recall) / (precision + recall)
f1_score[is.na(f1_score)] <- 0
macro_f1 <- mean(f1_score)
print(conf_lda)## Actual
## Predicted Very Bad Bad Good Very Good
## Very Bad 0 0 0 0
## Bad 115 1143 579 61
## Good 75 769 1710 690
## Very Good 9 36 338 445accuracy_lda <- sum(diag(conf_lda)) / sum(conf_lda)
cat("\nOverall Accuracy (LDA):", round(accuracy_lda * 100, 2), "%\n")##
## Overall Accuracy (LDA): 55.24 %##
## Overall F1-Score (LDA): 0 59.44 58.25 43.97 %##
## Overall F1-Macro (LDA): 40.42 %conf_lda_df <- as.data.frame(conf_lda)
ggplot(conf_lda_df, aes(x = Actual, y = Predicted, fill = Freq)) +
geom_tile(color = "white") +
geom_text(aes(label = Freq), size = 5) +
scale_fill_gradient(low = "#f9ebea", high = "#922b21") +
theme_minimal() +
labs(
title = "Confusion Matrix: Linear Discriminant Analysis",
subtitle = paste("Overall acc:", round(accuracy_lda, 2)," | f1: ",round(macro_f1, 2)),
x = "Actual Quality Tier",
y = "Predicted Quality Tier",
fill = "Count"
)
Unfortunately, our model is an utter disappointment. Let alone an F1-Macro of 0.4, but even accuracy of 0.55 is already enough evidence of how bad our model were. This is mostly due to the similar characteristics of each class in addition of the imbalances between them. The insight can be breakdown into three points:
The model is most effective at identifying “Good” wines, with 1,710 correct classifications, and “Bad” wines, with 1,143. These two tiers form the backbone of the model’s accuracy.
There is significant chemical overlap between adjacent tiers. For instance, 690 actual “Very Good” wines were misclassified as merely “Good,” and 769 actual “Bad” wines were misclassified as “Good”.
The model completely fails to identify the “Very Bad” tier, returning zero correct predictions for the 199 samples in this category.
The total absence of “Very Bad” predictions is a direct consequence of the class imbalance and the prior probabilities. Because the model is mathematically instructed to maximize overall accuracy, it gamble by favoring the most frequent categories. To the model, predicting a “Very Bad” wine is a high-risk gamble that it rarely takes, as the chemical signal for these rare samples is not strong enough to overcome the statistical weight of the “Bad” or “Good” priors. This confirms that while the oenological “DNA” provides a general guide, the rare extremes of wine quality remain difficult to isolate using linear boundaries alone.
5.5 Apparent Error Rate (APER)
n_total <- sum(conf_lda)
n_correct <- sum(diag(conf_lda))
n_misclassed <- n_total - n_correct
APER <- n_misclassed / n_total
cat("=== APER Breakdown ===\n")## === APER Breakdown ===## Total observations : 5970## Correctly classified : 3298## Misclassified : 2672## APER : 0.4476## APER (%) : 44.76 %per_class <- data.frame(
Class = colnames(conf_lda),
Total = colSums(conf_lda),
Correct = diag(conf_lda),
Misclassified = colSums(conf_lda) - diag(conf_lda)
)
per_class$ClassAPER <- round(per_class$Misclassified / per_class$Total, 4)
print(per_class)## Class Total Correct Misclassified ClassAPER
## Very Bad Very Bad 199 0 199 1.0000
## Bad Bad 1948 1143 805 0.4132
## Good Good 2627 1710 917 0.3491
## Very Good Very Good 1196 445 751 0.6279ggplot(per_class, aes(x = Class, y = ClassAPER, fill = Class)) +
geom_bar(stat = "identity", show.legend = FALSE) +
geom_hline(yintercept = APER, linetype = "dashed", color = "#2c3e50", linewidth = 0.9) +
scale_fill_brewer(palette = "RdYlGn") +
scale_y_continuous(labels = scales::percent_format()) +
theme_minimal() +
labs(
title = "Per-Class Apparent Error Rate (APER)",
subtitle = paste("Dashed line = overall APER of", round(APER * 100, 2), "%"),
x = "Quality Tier",
y = "Misclassification Rate"
)
The APER chart shows the model fails to find the best and worst wines. It misses every “Very Bad” wine and gets “Very Good” ones wrong over 60% of the time. This is because the model favors common “Good” and “Bad” groups with lower error rates. Accuracy mostly comes from labeling average wines correctly rather than spotting traits in high or low quality samples. [
---
title: "<span style='font-size: 32px; font-weight: bold; color: #4A0E0E;'>Multivariate Analysis</span>"
subtitle: "A Proportional Odds Approach to Decoding Wine Quality Hierarchies"
author: "Fio Ulaa' Octiryanti (030), Alfin Jayadi (082), Ketut Shridhara (115)"
date: "Updated on: `r format(Sys.Date(), '%d %B %Y')`"
output:
  html_document:
    toc: true
    toc_float: 
      collapsed: false
      smooth_scroll: true
    toc_depth: 4
    theme: cosmo        
    highlight: espresso  
    code_folding: hide
    code_download: true  
    number_sections: true
    df_print: paged
---

```{=html}
<style>
body {
  text-align: justify;
  font-family: 'Open Sans', sans-serif;
}
.list-group-item.active, .list-group-item.active:focus, .list-group-item.active:hover {
    background-color: #4A0E0E; /* Wine Red */
    border-color: #4A0E0E;
}
h1, h2, h3 {
  color: #4A0E0E;
}
.nav-pills > li.active > a, .nav-pills > li.active > a:focus, .nav-pills > li.active > a:hover {
    background-color: #4A0E0E;
}
</style>
```

# Introduction - The Quality Hierarchy

By acknowledging the natural ranking of wine quality, the Ordinal Logistic Regression provides a more statistically rigorous 'story' than standard classification. Instead of treating the quality levels as independent groups, the model estimates the cumulative probability of a wine ascending to a higher prestige tier based on its chemical makeup. The results highlight specific 'accelerators' such as alcohol content and 'decelerators' such as volatile acidity that dictate a wine’s movement across the quality thresholds. Furthermore, by passing the Brant Test, we confirm that the impact of these chemical predictors remains consistent across all quality transitions, validating the proportional odds assumption and proving that the path to a 'Very Good' wine follows a predictable, hierarchical chemical progression.

## Environment Setup

We start by loading the necessary libraries required for data manipulation, visualization, and advanced ordinal modeling.

```{r}
library(tidyverse) 
library(car)      
library(biotools) 
library(MASS)   
library(brant)   
library(GGally)
library(ggcorrplot)
library(gridExtra)
library(MVN)
library(VGAM)
```

## Data Loading & Transformation

We transform the numerical quality scores into four ranked levels. Unlike a nominal classification, we define these categories as an ordered factor, establishing a clear hierarchy from "Very Bad" to "Very Good." This structure is essential for the Ordinal Logistic Regression to correctly interpret the progression of wine quality.

```{r}
df <- read.csv("wine-quality-white-and-red.csv")

colnames(df) <- make.names(colnames(df))
df <- df %>%
  mutate(quality_label = case_when(
    quality <= 4 ~ "Very Bad",
    quality == 5 ~ "Bad",
    quality == 6 ~ "Good",
    quality >= 7 ~ "Very Good"
  )) %>%
  mutate(quality_label = factor(quality_label, 
                                levels = c("Very Bad", "Bad", "Good", "Very Good"),
                                ordered = TRUE)) 
df_clean <- df %>% 
  dplyr::select(-type, -quality)



head(df_clean)
```

# Exploratory Data Analysis

## Initial Distribution Visualization

Before diving into the ordinal modeling, we must observe the "DNA" of our dataset. By visualizing the distribution of the quality tiers, we can understand the balance of our classes across the quality spectrum. This step is crucial as it reveals whether our data is skewed towards a specific "step" on the quality ladder.

```{r}
ggplot(df, aes(x = quality_label, fill = quality_label)) +
  geom_bar(show.legend = FALSE) +
  theme_minimal() +
  scale_fill_brewer(palette = "RdYlGn") +
  labs(title = "Distribution of Wine Quality Tiers",
       subtitle = "Observing the frequency across the quality hierarchy",
       x = "Quality Hierarchy (Low to High)", 
       y = "Number of Wine Samples") +
  theme(plot.title = element_text(face = "bold"))
```

The bar chart above illustrates the frequency of wines across our four defined tiers. In an ordinal context, this helps us identify if we have enough representation in the "extreme" tiers (Very Bad and Very Good) compared to the more common "Good" or "Bad" categories. A significant imbalance here often explains why certain "thresholds" in our Ordinal Logistic Regression might be harder for the model to predict accurately.

# Statistical Assumptions & Diagnostics

## Ordinal Logistic

### Outlier Detection using Mahalanobis Distance

To ensure our hierarchical model is robust, we use multivariate distance to identify observations that are chemically "extreme." Unlike simple univariate checks, Mahalanobis distance considers the correlation between all chemical properties simultaneously.

```{r}
numeric_only <- df_clean %>% dplyr::select(-quality_label)

m_dist <- mahalanobis(numeric_only, 
                      colMeans(numeric_only), 
                      cov(numeric_only))

cutoff <- qchisq(0.95, df = ncol(numeric_only))

df_final <- df_clean[m_dist < cutoff, ]
set.seed(42)


print(paste("Initial Observations:", nrow(df_clean)))
print(paste("Observations after Outlier Removal:", nrow(df_final)))
```

```{r}
plot_data <- data.frame(
  Index = 1:length(m_dist),
  Distance = m_dist,
  IsOutlier = m_dist >= cutoff
)

ggplot(plot_data, aes(x = Index, y = Distance, color = IsOutlier)) +
  geom_point(alpha = 0.5) +
  geom_hline(yintercept = cutoff, linetype = "dashed", color = "red", size = 1) +
  scale_color_manual(values = c("FALSE" = "#2c3e50", "TRUE" = "#e74c3c"),
                     labels = c("Normal Data", "Outlier")) +
  theme_minimal() +
  labs(title = "Mahalanobis Distance Outlier Detection",
       subtitle = paste("Red line represents the Chi-Square cutoff of", round(cutoff, 2)),
       x = "Observation Index",
       y = "Mahalanobis Distance",
       color = "Status")
```

The outlier detection process identified 175 chemical anomalies from the initial 6,497 observations, resulting in a refined dataset 5,970 samples. By applying a Chi-Square cutoff at a 95% confidence level, we isolated observations with improbable chemical combinations that could distort our statistical boundaries. In the context of Ordinal Logistic Regression, removing these outliers is critical. Extreme data points can disproportionately pull the "thresholds" (intercepts) between quality tiers, leading to biased predictions. By ensuring a stable foundation, our model can more accurately capture the true hierarchical relationship between physicochemical properties and wine quality progression.

### Multicollinearity (VIF)

We check if independent variables are too highly correlated with each other. In an ordinal model, high multicollinearity can make the coefficients unstable, making it difficult to determine which chemical property truly drives a wine to the next quality tier.

```{r}
v_model <- lm(as.numeric(quality_label) ~ ., data = df_final)
vif_result <- vif(v_model)

vif_df <- data.frame(
  Variable = names(vif_result),
  VIF = as.numeric(vif_result)
)

# Plot the results
ggplot(vif_df, aes(x = reorder(Variable, VIF), y = VIF, fill = VIF > 10)) +
  geom_bar(stat = "identity", width = 0.7) +
  geom_hline(yintercept = 10, linetype = "dashed", color = "red", linewidth = 0.8) +
  geom_hline(yintercept = 5, linetype = "dotted", color = "orange", linewidth = 0.8) +
  coord_flip() + # Memutar agar nama variabel mudah dibaca
  scale_fill_manual(values = c("FALSE" = "#2ecc71", "TRUE" = "#e74c3c"), 
                    guide = "none") +
  theme_minimal() +
  labs(title = "Multicollinearity Check (VIF Results)",
       subtitle = "Density shows high multicollinearity (VIF > 10)",
       x = "Chemical Properties",
       y = "Variance Inflation Factor (VIF)")
```

```{r}
df_final <- df_final |> 
  dplyr::select(-density)
v_model <- lm(as.numeric(quality_label) ~ ., data = df_final)
vif_result <- vif(v_model)

vif_df <- data.frame(
  Variable = names(vif_result),
  VIF = as.numeric(vif_result)
)

# Plot the results
ggplot(vif_df, aes(x = reorder(Variable, VIF), y = VIF, fill = VIF > 10)) +
  geom_bar(stat = "identity", width = 0.7) +
  geom_hline(yintercept = 10, linetype = "dashed", color = "red", linewidth = 0.8) +
  geom_hline(yintercept = 5, linetype = "dotted", color = "orange", linewidth = 0.8) +
  coord_flip() + # Memutar agar nama variabel mudah dibaca
  scale_fill_manual(values = c("FALSE" = "#2ecc71", "TRUE" = "#e74c3c"), 
                    guide = "none") +
  theme_minimal() +
  labs(title = "Multicollinearity Check (VIF Results)",
       subtitle = "Density shows high multicollinearity (VIF > 10)",
       x = "Chemical Properties",
       y = "Variance Inflation Factor (VIF)")
```

The Multicollinearity test using the Variance Inflation Factor (VIF) reveals that most chemical properties remain within acceptable limits, with the notable exception of density, which exhibits a significantly high VIF of 20.97. In ordinal modeling, a VIF exceeding 10 indicates that a variable is redundant; its information is already captured by other predictors like alcohol and residual sugar. This redundancy can inflate the standard errors of our coefficients, potentially masking the true significance of chemical drivers in our Ordinal Logistic Regression. Therefore we exclude density because of the VIF \> 10. While variables like residual.sugar and alcohol show moderate correlation, the extreme value of density suggests it may need careful handling to ensure that our hierarchical quality predictions and the subsequent Discriminant Analysis remain reliable and interpretable.

### Linearity & Correlation

A quick scan of how variables move together. In an ordinal framework, we look for chemical properties that show a consistent directional relationship with our quality hierarchy. Stronger correlations with the target variable suggest which "levers" are most effective in shifting a wine from a lower tier to a higher one.

```{r}
ggcorr(df_final, 
       label = TRUE, 
       label_size = 3, 
       hjust = 0.8, 
       layout.exp = 1,
       name = "Corr") +
  labs(title = "Correlation Matrix of Wine Properties",
       subtitle = "Identifying potential drivers for quality progression")
```

The correlation matrix provides a preliminary map of the "chemical DNA" behind wine quality. From an Ordinal perspective, we are particularly interested in variables that show a steady positive or negative trend as we move up the quality tiers. For instance, a strong positive correlation between alcohol and quality suggests that alcohol might be a significant predictor in the Ordinal Logistic Regression, potentially increasing the probability of a wine being classified into a superior category. Conversely, variables with high mutual correlation (like density and residual sugar) reinforce our previous VIF findings, reminding us that while they move together, their individual impact on the quality hierarchy must be carefully disentangled to avoid redundancy in our hierarchical model.

### Proportional Odds Assumption (Brant Test)

In Ordinal Logistic Regression, we must satisfy the Parallel Slopes assumption. This means that each of our chemical predictors (like alcohol or acidity) must have a consistent effect across all quality transitions. If this assumption is violated, the ordinal model might be misleading, and a multinomial approach would be more appropriate.

```{r}
model_ordinal <- polr(quality_label ~ ., data = df_final, Hess = TRUE)
brant_test <- brant(model_ordinal)
print(brant_test)
```

The omnibus result rejects the assumption. Before concluding anything, we check whether the violations are real or just a statistical artefact of our large sample. With n close to 6,000, the Brant test has enough power to flag even tiny, practically meaningless deviations. To separate genuine violations from noise, we compare the actual slope estimates at each threshold directly.

```{r}
model_low  <- glm(I(as.numeric(quality_label) >= 2) ~ ., 
                  data = df_final, family = binomial)
model_mid  <- glm(I(as.numeric(quality_label) >= 3) ~ ., 
                  data = df_final, family = binomial)
model_high <- glm(I(as.numeric(quality_label) >= 4) ~ ., 
                  data = df_final, family = binomial)

slope_comparison <- data.frame(
  Variable  = names(coef(model_low))[-1],
  Threshold1 = round(coef(model_low)[-1], 3),
  Threshold2 = round(coef(model_mid)[-1], 3),
  Threshold3 = round(coef(model_high)[-1], 3)
)

print(slope_comparison)
```

Two variables stand out as genuine violations. `chlorides` flips from +12.2 at the first threshold to -12.5 at the third, and `pH` also reverses sign across thresholds. A sign flip is not a sample size artifact, it means the variable behaves in opposite directions at different quality boundaries. These two are dropped from the model.

```{r}
model_ordinal <- polr(quality_label ~ ., data = dplyr::select(df_final, -chlorides, -pH), Hess = TRUE)
brant_test    <- brant(model_ordinal)
print(brant_test)
```

After removing them, `free.sulfur.dioxide` and `alcohol` remain as structural violators with X2 values of 57 and 94 respectively. Their slopes are not just noisy, they genuinely shift across thresholds. Dropping more variables to chase a passing Brant test at this point would mean removing predictors with real chemical meaning.

The right response here is a **Partial Proportional Odds (PPO) model**. Instead of forcing every predictor to share a single slope, the PPO model constrains only the predictors that actually satisfy the assumption and frees the ones that do not. The outcome is still treated as ordinal, the quality hierarchy is preserved, and the model stops lying about how `free.sulfur.dioxide` and `alcohol` behave. Predictors that pass the Brant test (`fixed.acidity`, `citric.acid`, `residual.sugar`) keep a single constrained coefficient. The two violators get separate coefficients per threshold.

## Discriminant Analysis

### Multivariate Normally Distributed

LDA assumes that the predictors follow a multivariate normal disttribution for each group. We test this using Henze-Zirkler's Test instead of Mardia's Test due to the high sensitiveness of the latter. If the assumption is not met, the theoretical derivation of the linear decision boundary becomes no longer valid, meaning the estimated probabilities assigned to each group may be unreliable.

The best-case scenario would be `MVN = Normal` with p \> 0.05, which would confirm the basis of the model’s distribution. However, with n ≈ 5,970, rejection is expected given that the physicochemical variables are asymmetric. Even so, this can be tolerated because LDA is robust to large sample sizes thanks to the Central Limit Theorem.

```{r}
mvn_result <- mvn(df_final,mvn_test = 'hz')

print(summary(mvn_result, "mvn"))
```

```{r}
pred_vars <- df_final %>% dplyr::select(-quality_label) %>% names()

par(mfrow = c(3, 4))
for (var in pred_vars) {
  qqnorm(df_final[[var]], main = paste('Q-Q Plot:', var), cex.main = 0.9)
  qqline(df_final[[var]], col = 'red')
}
par(mfrow = c(1, 1))
```

As expected, the Henze-Zirkler test formally rejects multivariate normality (HZ = 4.935, p \< 0.001. Nevertheless, visual inspection of Q-Q plots reveales that all predictors follow the theoretical normal line closely through the central distribution, with only minor tail deviations. This pattern is only indicates a slight skewness rather than a major distributional violation. This rejection is therefore due to the high statistical strength at n ≈ 5,970, which is sensitive to even the slightest deviation, and the assumption of normality is considered to be satisfied well enough for the LDA to proceed.

However, as stated earlier, there is a slight chance that the estimated probabilities assigned to each group may be unreliable. Given the mild tail deviations observed in the Q-Q plots, this effect is expected to be minor rather than severe, though results near the decision boundary between adjacent quality tiers should be interpreted cautiously.

### Homogenity of Variance

LDA pools covariance matrices from all groups into a single matrix of \`$S_{pooled}$\`, which serves as a shared variance structure for constructing the linear decision boundaries. This pooling will only produces a valid boundary if all groups share the same underlying covariance structure. We use Box's M rather than Bartlett because Box's M evaluates the entire '$p \times p$' covariance matrix simultaneously, while the latter only checks univariate variances and ignores covariances entirely.

If this assumption fails substantially, \`$S_{pooled}$\` becomes a distorted representation of each group's true spread, causing the linear boundary to be misaligned and misclassification rates to increase. The best expected outcome is a non-significant Box's M (p \> 0.05), though at n ≈ 5,970 rejection is almost certain due to high statistical power detecting even trivially small differences

```{r}
boxM_result <- boxM(
  data     = df_final %>% dplyr::select(-quality_label),
  grouping = df_final$quality_label
)

print(boxM_result)
```

```{r}
pred_vars <- df_final %>% dplyr::select(-quality_label) %>% names()

plot_list <- lapply(levels(df_final$quality_label), function(grp) {
  
  cor_mat <- df_final %>%
    filter(quality_label == grp) %>%
    dplyr::select(all_of(pred_vars)) %>%
    cor()

  ggcorrplot(cor_mat,
             method  = 'square',
             type    = 'lower',
             lab     = FALSE,
             tl.cex  = 7,
             colors  = c('#2980b9', 'white', '#922b21'),
             title   = paste('Correlation Structure:', grp),
             ggtheme = theme_minimal())
})

grid.arrange(grobs = plot_list, ncol = 2)
```

# Ordinal Logistic

## Model Summary

```{r}
model_final <- vglm(
  quality_label ~ fixed.acidity + volatile.acidity + citric.acid +
                  residual.sugar + free.sulfur.dioxide + total.sulfur.dioxide +
                  sulphates + alcohol + chlorides + pH,
  family = cumulative(parallel = FALSE ~ free.sulfur.dioxide + alcohol + 
                                         chlorides + pH,
                      reverse = FALSE),
  data = df_final
)

summary(model_final)
```

The three intercepts run 4.15, 12.00, and 13.75, increasing monotonically across the cutpoints, confirming the model is internally consistent. Alcohol and volatile acidity dominate by z-value (25.6 and 16.4 respectively), with sulphates and residual sugar close behind. The weak predictors are pH:1 (z = -0.53, p = 0.59) and chlorides:2 (z = 1.71, p = 0.087). Citric acid clears the 0.05 threshold at p = 0.025, borderline but significant. Residual deviance is 11,570.2, which serves as a baseline for any subsequent model comparisons involving pH:1 or chlorides:2.

## Simultaneous Test (G-Statistic)

```{r}

model_null <- vglm(quality_label ~ 1,
                   family = cumulative(parallel = TRUE, reverse = FALSE),
                   data = df_final)

G_stat <- deviance(model_null) - deviance(model_final)
df_G   <- df.residual(model_null) - df.residual(model_final)
p_G    <- pchisq(G_stat, df = df_G, lower.tail = FALSE)

cat("G statistic       :", round(G_stat, 4), "\n")
cat("Degrees of freedom:", df_G, "\n")
cat("P-value           :", round(p_G, 6), "\n")

if (p_G < 0.05) {
  cat("Decision: Reject H0, at least one predictor significantly influences wine quality.\n")
} else {
  cat("Decision: Fail to reject H0.\n")
}
```

The G-statistic tests whether the predictors as a group do anything useful compared to a model with no predictors at all. With G = 2305.58, df = 18, and p \< 0.05, we reject the null hypothesis. The chemical predictors collectively explain a significant portion of the variation in quality tier.

The size of the statistic is worth noting. A G of 2305.58 on 18 degrees of freedom is very large, which tells us the model is not just barely significant. The physicochemical variables carry real and substantial information about quality.

## Partial Test (Wald Test)

```{r}

coef_table <- coef(summary(model_final))
wald_table <- as.data.frame(coef_table)
colnames(wald_table) <- c("Value", "Std.Error", "z")

wald_table$W2      <- wald_table$z^2
wald_table$p_value <- pchisq(wald_table$W2, df = 1, lower.tail = FALSE)

print(round(wald_table, 4))

# Filter to predictor rows only (exclude intercepts)
coef_predictors <- wald_table[!grepl("\\(Intercept\\)", rownames(wald_table)), ]
coef_predictors$Variable    <- rownames(coef_predictors)
coef_predictors$Significant <- coef_predictors$p_value < 0.05
coef_predictors$Lower       <- coef_predictors$Value - 1.96 * coef_predictors$Std.Error
coef_predictors$Upper       <- coef_predictors$Value + 1.96 * coef_predictors$Std.Error

ggplot(coef_predictors, aes(x = reorder(Variable, Value), y = Value, color = Significant)) +
  geom_point(size = 3) +
  geom_errorbar(aes(ymin = Lower, ymax = Upper), width = 0.3) +
  geom_hline(yintercept = 0, linetype = "dashed", color = "gray50") +
  coord_flip() +
  scale_color_manual(values = c("FALSE" = "#bdc3c7", "TRUE" = "#c0392b"),
                     labels = c("Not significant", "Significant (p < 0.05)")) +
  theme_minimal() +
  labs(title    = "Predictor Coefficients with 95% Confidence Intervals",
       subtitle = "Red points are statistically significant in the Wald test",
       x = "Predictor", y = "Coefficient Estimate", color = "Significance")
```

Most predictors are significant at the 0.05 level. Among the non-parallel terms, pH:1 does not reach significance (W² = 0.29, p = 0.593), and chlorides:2 is marginal (W² = 2.93, p = 0.087). All other predictor rows clear the threshold, including citric acid (W² = 5.01, p = 0.025). The three intercept rows at the bottom correspond to the quality cutpoints and confirm that the boundaries between tiers are statistically real, which is expected given the sample size.

## Odds Ratios

```{r}
coefs    <- coef(model_final)
se_coefs <- sqrt(diag(vcov(model_final)))

# Exclude intercept rows
pred_idx <- !grepl("\\(Intercept\\)", names(coefs))

OR_table <- data.frame(
  OR       = exp(coefs[pred_idx]),
  Lower_95 = exp(coefs[pred_idx] - 1.96 * se_coefs[pred_idx]),
  Upper_95 = exp(coefs[pred_idx] + 1.96 * se_coefs[pred_idx])
)

print(round(OR_table, 4))

or_df          <- OR_table
or_df$Variable <- rownames(or_df)

ggplot(or_df, aes(x = reorder(Variable, OR), y = OR)) +
  geom_point(size = 3, color = "#2980b9") +
  geom_errorbar(aes(ymin = Lower_95, ymax = Upper_95), width = 0.3, color = "#2980b9") +
  geom_hline(yintercept = 1, linetype = "dashed", color = "red") +
  coord_flip() +
  theme_minimal() +
  labs(title    = "Odds Ratios with 95% Confidence Intervals",
       subtitle = "OR > 1 increases the odds of a higher quality tier; OR < 1 decreases it",
       x = "Predictor", y = "Odds Ratio")
```

Volatile acidity carries the largest effect among the parallel terms (OR = 56.99), where each one-unit increase is associated with substantially higher odds of falling into a lower quality tier. Sulphates moves in the opposite direction (OR = 0.107), as does alcohol across all three cutpoints (ORs ranging from 0.38 to 0.63).

Among the non-parallel terms, chlorides shows the widest spread: chlorides:1 approaches zero while chlorides:3 reaches 264,380, both with confidence intervals too wide to interpret reliably. The two rows whose confidence intervals actually cross 1.0 are pH:1 (OR = 0.758, 95% CI: 0.275 to 2.093) and chlorides:2 (OR = 29.53, 95% CI: 0.614 to 1,420). The threshold rows are not predictor odds ratios and should not be interpreted as such.

## Predicted Probabilities and Confusion Matrix

```{r}
pred_probs <- predict(model_final, type = "response")
pred_class <- factor(
  levels(df_final$quality_label)[apply(pred_probs, 1, which.max)],
  levels = levels(df_final$quality_label)
)

conf_matrix <- table(Predicted = pred_class, Actual = df_final$quality_label)
print(conf_matrix)

accuracy <- sum(diag(conf_matrix)) / sum(conf_matrix)
cat("Overall Accuracy:", round(accuracy * 100, 2), "%\n")

conf_df <- as.data.frame(conf_matrix)
ggplot(conf_df, aes(x = Actual, y = Predicted, fill = Freq)) +
  geom_tile(color = "white") +
  geom_text(aes(label = Freq), size = 5) +
  scale_fill_gradient(low = "#f9ebea", high = "#922b21") +
  theme_minimal() +
  labs(title    = "Confusion Matrix: Partial Proportional Odds Model",
       subtitle = paste("Overall accuracy:", round(accuracy * 100, 2), "%"),
       x = "Actual Quality Tier", y = "Predicted Quality Tier", fill = "Count")
```

The model reaches 55.39% overall accuracy on the training data. Performance is strongest on the Good tier (1,775 correct) and completely absent on Very Bad, where the model predicts zero instances across all 199 actual cases. This is a direct consequence of class imbalance: with Very Bad representing a small fraction of the data, the model has no incentive to predict it.

The largest source of misclassification falls between Bad and Good, with 771 Bad cases predicted as Good and 572 Good cases predicted as Bad. Good and Very Good also bleed into each other (731 and 280 misclassified respectively), consistent with cutpoints 2 and 3 sitting only 1.75 apart on the log-odds scale compared to the 7.85 gap separating cutpoint 1 from cutpoint 2.

## Pseudo R-Squared

```{r}
loglik_full <- logLik(model_final)
loglik_null <- logLik(model_null)
n           <- nrow(df_final)

mcfadden   <- 1 - as.numeric(loglik_full) / as.numeric(loglik_null)
coxsnell   <- 1 - exp((2 / n) * (as.numeric(loglik_null) - as.numeric(loglik_full)))
nagelkerke <- coxsnell / (1 - exp((2 / n) * as.numeric(loglik_null)))

cat("McFadden  :", round(mcfadden,   4), "\n")
cat("CoxSnell  :", round(coxsnell,   4), "\n")
cat("Nagelkerke:", round(nagelkerke, 4), "\n")
```

Ordinal logistic regression has no single R-squared equivalent, so three pseudo-R² measures are reported here. McFadden's R² is 0.166, Cox-Snell is 0.320, and Nagelkerke is 0.355. McFadden values between 0.1 and 0.4 are generally considered acceptable for logistic models, so 0.166 clears that bar without indicating strong fit.

Cox-Snell and Nagelkerke both suggest the predictors account for roughly 32 to 36% of the variability in quality tier. The remaining variance reflects factors the chemical measurements do not capture, including the subjective nature of sensory evaluation scores used to define quality in the original data.

# Discriminant Analysis

## Model Summary

```{r}
lda_model <- lda(quality_label ~ ., data = df_final)

summary(lda_model)

```

Unlike OLR where the summary output of the model can produces such summary, in LDA the output from the model itself is just a preview of each aspects of the model.

The prior and counts output reveals that the model structure is a system that classify data into four groups. It utilizing ten predictor variables based on the forty entries in the group means matrix and the absence of categorical data in the xlevels list.

The classification operates within a three dimensional space, evidenced by the svd length of three and the scaling matrix of thirty. The model is founded on a single total observation count stored in N, while the call and terms entries retain the specific formula and code parameters used to generate the classification object.

However, to understand the output more clearly, we need to deep dive to some most important aspects which we choose to be: prior, means, and scaling,

```{r}
cat("=== Prior Probabilities ===\n")
print(round(lda_model$prior, 4))

cat("\n=== Group Means (Class Centroids) ===\n")
print(round(lda_model$means, 4))

cat("\n=== Linear Discriminant Coefficients ===\n")
print(round(lda_model$scaling, 4))

```

The result from prior that our data is heavily imbalanced where 76.6% of wines fall into the "Bad" or "Good" categories, creating a bias that favors middle-tier classifications. Group means then shows that higher quality wines are chemically characterized by increased alcohol and citric acid levels alongside lower volatile acidity. The LD1 coefficients indicate that volatile acidity and chlorides are the primary negative influences that distinguish lower quality tiers. On the other hands, sulphates and alcohol are the strongest positive contributors on the first discriminant axis for identifying high-quality samples. These coefficients represent the specific weights used to transform the physicochemical data into the three dimensions that maximize separation between quality groups.

## Proportion of Trace

```{r}
prop_trace <- lda_model$svd^2 / sum(lda_model$svd^2)
names(prop_trace) <- paste0("LD", seq_along(prop_trace))

cat("=== Proportion of Trace ===\n")
print(round(prop_trace, 4))

prop_df <- data.frame(
  LD         = names(prop_trace),
  Proportion = as.numeric(prop_trace),
  Cumulative = cumsum(as.numeric(prop_trace))
)

ggplot(prop_df, aes(x = LD)) +
  geom_bar(aes(y = Proportion), stat = "identity", fill = "#922b21", alpha = 0.8) +
  geom_line(aes(y = Cumulative, group = 1), color = "#2c3e50", linewidth = 1.1) +
  geom_point(aes(y = Cumulative), color = "#2c3e50", size = 3) +
  scale_y_continuous(labels = scales::percent_format()) +
  theme_minimal() +
  labs(
    title    = "Proportion of Trace per Discriminant Axis",
    subtitle = "Bars = individual variance explained; Line = cumulative",
    x        = "Linear Discriminant",
    y        = "Proportion of Trace"
  )
```

The results show that LD1 dominates heavily that itself alone is already contributing 88.3% of the total between-group variance. When combined with the 10.5% from LD2, nearly 99% of the chemical signal is explained, making the third axis statistically redundant. This high concentration indicates that the ten original chemical variables can be effectively split into two dimensions without losing significant information. As a result, the chart proves that the hierarchical progression of wine quality is driven by a highly consistent and linear chemical transition.

## Discriminant Space Visualization

```{r}
lda_scores <- predict(lda_model)$x
lda_plot_df <- data.frame(
  LD1   = lda_scores[, 1],
  LD2   = if (ncol(lda_scores) >= 2) lda_scores[, 2] else 0,
  Group = df_final$quality_label
)

ggplot(lda_plot_df, aes(x = LD1, y = LD2, color = Group, fill = Group)) +
  geom_point(alpha = 0.25, size = 1.2) +
  stat_ellipse(geom = "polygon", alpha = 0.10, level = 0.95) +
  stat_ellipse(level = 0.95, linewidth = 0.9) +
  scale_color_brewer(palette = "RdYlGn") +
  scale_fill_brewer(palette = "RdYlGn") +
  theme_minimal() +
  labs(
    title    = "Discriminant Space: LD1 vs LD2",
    subtitle = "Each ellipse covers 95% of its group's projected observations",
    x        = paste0("LD1 (", round(prop_trace[1] * 100, 1), "% of trace)"),
    y        = paste0("LD2 (", round(prop_trace[2] * 100, 1), "% of trace)"),
    color    = "Quality Tier",
    fill     = "Quality Tier"
  )
```

The discriminant space plot demonstrate a clear chemical progression along the LD1 axis, where wine quality shifts from "Very Bad" on the left to "Very Good" on the right. This horizontal progress confirms that LD1 is the primary quality tiebreaker by capturing 92.9% of the trace. Significant overlap between the 95% ellipses, especially among the "Bad," "Good," and "Very Good" categories, explains why the model often struggles to find perfect boundaries between nearby tiers. Meanwhile, LD2 provides only a minor vertical adjustment with 6% of the trace, helping to refine the separation between the more common middle tier wines.

In the end, the visualization shows that while wine quality follows a predictable chemical DNA, the transitions between levels are continuous and often blurred.

## Classification & Confusion Matrix

```{r}
lda_pred       <- predict(lda_model)
pred_class_lda <- lda_pred$class

conf_lda <- table(Predicted = pred_class_lda, Actual = df_final$quality_label)

precision <- diag(conf_lda) / rowSums(conf_lda)
recall    <- diag(conf_lda) / colSums(conf_lda)
f1_score  <- 2 * (precision * recall) / (precision + recall)
f1_score[is.na(f1_score)] <- 0
macro_f1 <- mean(f1_score)

print(conf_lda)

accuracy_lda <- sum(diag(conf_lda)) / sum(conf_lda)
cat("\nOverall Accuracy (LDA):", round(accuracy_lda * 100, 2), "%\n")
cat("\nOverall F1-Score (LDA):", round(f1_score * 100, 2), "%\n")
cat("\nOverall F1-Macro (LDA):", round(macro_f1 * 100, 2), "%\n")

conf_lda_df <- as.data.frame(conf_lda)

ggplot(conf_lda_df, aes(x = Actual, y = Predicted, fill = Freq)) +
  geom_tile(color = "white") +
  geom_text(aes(label = Freq), size = 5) +
  scale_fill_gradient(low = "#f9ebea", high = "#922b21") +
  theme_minimal() +
  labs(
    title    = "Confusion Matrix: Linear Discriminant Analysis",
    subtitle = paste("Overall acc:", round(accuracy_lda, 2)," | f1: ",round(macro_f1, 2)),
    x        = "Actual Quality Tier",
    y        = "Predicted Quality Tier",
    fill     = "Count"
  )
```

Unfortunately, our model is an utter disappointment. Let alone an F1-Macro of 0.4, but even accuracy of 0.55 is already enough evidence of how bad our model were. This is mostly due to the similar characteristics of each class in addition of the imbalances between them. The insight can be breakdown into three points:

-   The model is most effective at identifying "Good" wines, with 1,710 correct classifications, and "Bad" wines, with 1,143. These two tiers form the backbone of the model's accuracy.

-   There is significant chemical overlap between adjacent tiers. For instance, 690 actual "Very Good" wines were misclassified as merely "Good," and 769 actual "Bad" wines were misclassified as "Good".

-   The model completely fails to identify the "Very Bad" tier, returning zero correct predictions for the 199 samples in this category.

The total absence of "Very Bad" predictions is a direct consequence of the class imbalance and the prior probabilities. Because the model is mathematically instructed to maximize overall accuracy, it gamble by favoring the most frequent categories. To the model, predicting a "Very Bad" wine is a high-risk gamble that it rarely takes, as the chemical signal for these rare samples is not strong enough to overcome the statistical weight of the "Bad" or "Good" priors. This confirms that while the oenological "DNA" provides a general guide, the rare extremes of wine quality remain difficult to isolate using linear boundaries alone.

## Apparent Error Rate (APER)

```{r}
n_total      <- sum(conf_lda)
n_correct    <- sum(diag(conf_lda))
n_misclassed <- n_total - n_correct
APER         <- n_misclassed / n_total

cat("=== APER Breakdown ===\n")
cat("Total observations   :", n_total, "\n")
cat("Correctly classified :", n_correct, "\n")
cat("Misclassified        :", n_misclassed, "\n")
cat("APER                 :", round(APER, 4), "\n")
cat("APER (%)             :", round(APER * 100, 2), "%\n")

per_class <- data.frame(
  Class         = colnames(conf_lda),
  Total         = colSums(conf_lda),
  Correct       = diag(conf_lda),
  Misclassified = colSums(conf_lda) - diag(conf_lda)
)
per_class$ClassAPER <- round(per_class$Misclassified / per_class$Total, 4)
print(per_class)

ggplot(per_class, aes(x = Class, y = ClassAPER, fill = Class)) +
  geom_bar(stat = "identity", show.legend = FALSE) +
  geom_hline(yintercept = APER, linetype = "dashed", color = "#2c3e50", linewidth = 0.9) +
  scale_fill_brewer(palette = "RdYlGn") +
  scale_y_continuous(labels = scales::percent_format()) +
  theme_minimal() +
  labs(
    title    = "Per-Class Apparent Error Rate (APER)",
    subtitle = paste("Dashed line = overall APER of", round(APER * 100, 2), "%"),
    x        = "Quality Tier",
    y        = "Misclassification Rate"
  )
```

The APER chart shows the model fails to find the best and worst wines. It misses every "Very Bad" wine and gets "Very Good" ones wrong over 60% of the time. This is because the model favors common "Good" and "Bad" groups with lower error rates. Accuracy mostly comes from labeling average wines correctly rather than spotting traits in high or low quality samples. [
