DATA 605 02[46835] : Final Project
DATA 605 - Final Project - Fundamentals of Computational Mathematics
DATA 605 02[46835] : Final Project
1 Overview
Your final is due by the end of the last week of class. You should post your solutions to your GitHub account or RPubs. You are also expected to make a short presentation via YouTube and post that recording to the board. This project will show off your ability to understand the elements of the class.
2 PROBLEM 1
Using R, generate a random variable X that has 10,000 random uniform numbers from 1 to N, where N can be any number of your choosing greater than or equal to 6.
Then generate a random variable Y that has 10,000 random normal numbers with a mean of \(\frac{(N+1)}{2}\).
2.1 Answer
set.seed(12345)
N <- 10
n <- 10000
mu <- sigma <- (N + 1)/2
df <- data.frame(X = runif(n, min=1, max=N),
Y = rnorm(n, mean=mu, sd=sigma))
summary(df$X)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.000 3.283 5.541 5.506 7.742 10.000## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -14.664 1.846 5.482 5.500 9.154 26.766
2.2 Question 1 : Probability
Calculate as a minimum the below probabilities a through c. Assume the small letter “x” is estimated as the median of the X variable, and the small letter “y” is estimated as the 1st quartile of the Y variable. Interpret the meaning of all probabilities.
a. P(X>x | X>y)
b. P(X>x, Y>y)
c. P(X<x | X>y)
2.2.1 Answer 1
## [1] 5.540952## [1] 1.8460762.2.1.1 (a) P(X>x | X>y)
Probability that X is greater than its median given that X is greater than the first quartile of Y
\[P(X>x \ | \ X>y) = \frac{P(X>x \ , \ X>y)}{P(X>y)}\]
P_a_and_b <- df %>%
filter(X > x,
X > y) %>%
nrow() / n
P_b <- df %>%
filter(X > y) %>%
nrow() / n
problem_1a <- P_a_and_b / P_b
problem_1a## [1] 0.5512679The probablity of a random number uniformly ranging from 1 to 10 being greater than 5.540952 (median) given that it is greater than 1.8460758 (1st Quartile) is 0.5512679
2.2.1.2 (b) P(X>x, Y>y)
Probability that X is grater than all possible x and Y is greater than all possible y
## [1] 0.3808The probablity of a random number uniformly ranging from 1 to 10 being greater than 5.540952 (median) and a random normally distributed number with a mean and standard deviation of 5.5 being greater than 1.8460758 (1st Quartile) is 0.3808
2.2.1.3 (c) P(X<x | X>y)
Probability of X less than its median given that it is greater than the first quantile of Y
\[P(X<x \ | \ X>y) = \frac{P(X<x \ , \ X>y)}{P(X>y)}\]
P_a_and_b <- df %>%
filter(X < x,
X > y) %>%
nrow() / n
P_b <- df %>%
filter(X > y) %>%
nrow() / n
problem_1c <- P_a_and_b / P_b
problem_1c## [1] 0.4487321The probablity of a random number uniformly ranging from 1 to 10 being less than 5.540952 (median) given that it is greater than 1.8460758 (1st Quartile) is 0.4487321
2.3 Question 2
Investigate whether P(X>x and Y>y)=P(X>x)P(Y>y) by building a table and evaluating the marginal and joint probabilities.
2.3.1 Answer 2
# Create Joint Probabilities
temp <- df %>%
mutate(A = ifelse(X > x, " X greater than x", " X not greater than x"),
B = ifelse(Y > y, " Y greater than y", " Y not greater than y")) %>%
group_by(A, B) %>%
summarise(count = n()) %>%
mutate(probability = count / n)
# Create Marginal Probabilities
temp <- temp %>%
ungroup() %>%
group_by(A) %>%
summarise(count = sum(count),
probability = sum(probability)) %>%
mutate(B = "Total") %>%
bind_rows(temp)
temp <- temp %>%
ungroup() %>%
group_by(B) %>%
summarise(count = sum(count),
probability = sum(probability)) %>%
mutate(A = "Total") %>%
bind_rows(temp)
# Create Table
temp %>%
dplyr::select(-count) %>%
spread(A, probability) %>%
rename(" " = B) %>%
kable() %>%
kable_styling()| X greater than x | X not greater than x | Total | |
|---|---|---|---|
| Y greater than y | 0.3808 | 0.3692 | 0.75 |
| Y not greater than y | 0.1192 | 0.1308 | 0.25 |
| Total | 0.5000 | 0.5000 | 1.00 |
P(X>x and Y>y) is 0.3808. P(X>x)P(Y>y) is 0.5 \(\times\) 0.75 which is 0.375. They are not the same.
2.4 Question 3
Check to see if independence holds by using Fisher’s Exact Test and the Chi Square Test. What is the difference between the two? Which is most appropriate?
2.4.1 Answer 3
count_data <- temp %>%
filter(A != "Total",
B != "Total") %>%
dplyr::select(-probability) %>%
spread(A, count) %>%
as.data.frame()
row.names(count_data) <- count_data$B
count_data <- count_data %>%
dplyr::select(-B) %>%
as.matrix()
fisher.test(count_data)##
## Fisher's Exact Test for Count Data
##
## data: count_data
## p-value = 0.007904
## alternative hypothesis: true odds ratio is not equal to 1
## 95 percent confidence interval:
## 1.032680 1.240419
## sample estimates:
## odds ratio
## 1.131777##
## Pearson's Chi-squared test with Yates' continuity correction
##
## data: count_data
## X-squared = 7.0533, df = 1, p-value = 0.007912\(H_o\): X and Y are independent. \(H_a\): X and Y are not independent.
Since the P-value is less than the significance level (0.05) for both test, we cannot accept the null hypothesis. Thus, we conclude that there is a relationship between X and Y.
Fisher’s Exact Test is for is used when you have small cell sizes (less than 5). The Chi Square Test is used when the cell sizes are large. It would be appropriate in this case. We ran both a fisher and a chi-test. In both of these we state a null hypotheses that the two variables are independent, and a alternative stating that there is dependence.
3 PROBLEM 2
You are to register for Kaggle.com (free) and compete in the House Prices: Advanced Regression Techniques competition. https://www.kaggle.com/c/house-prices-advanced-regression-techniques. I want you to do the following.
Descriptive and Inferential Statistics. Provide univariate descriptive statistics and appropriate plots for the training data set. Provide a scatterplot matrix for at least two of the independent variables and the dependent variable. Derive a correlation matrix for any three quantitative variables in the dataset. Test the hypotheses that the correlations between each pairwise set of variables is 0 and provide an 80% confidence interval. Discuss the meaning of your analysis. Would you be worried about familywise error? Why or why not?
Linear Algebra and Correlation. Invert your correlation matrix from above. (This is known as the precision matrix and contains variance inflation factors on the diagonal.) Multiply the correlation matrix by the precision matrix, and then multiply the precision matrix by the correlation matrix. Conduct LU decomposition on the matrix.
Calculus-Based Probability & Statistics. Many times, it makes sense to fit a closed form distribution to data. Select a variable in the Kaggle.com training dataset that is skewed to the right, shift it so that the minimum value is absolutely above zero if necessary. Then load the MASS package and run fitdistr to fit an exponential probability density function. (See https://stat.ethz.ch/R-manual/R-devel/library/MASS/html/fitdistr.html ). Find the optimal value \(\lambda\) of for this distribution, and then take 1000 samples from this exponential distribution using this value (e.g., rexp(1000, \(\lambda\))). Plot a histogram and compare it with a histogram of your original variable. Using the exponential pdf, find the 5th and 95th percentiles using the cumulative distribution function (CDF). Also generate a 95% confidence interval from the empirical data, assuming normality. Finally, provide the empirical 5th percentile and 95th percentile of the data. Discuss.
Modeling. Build some type of multiple regression model and submit your model to the competition board. Provide your complete model summary and results with analysis. Report your Kaggle.com user name and score.
kaggle <- read.csv("house-prices-advanced-regression-techniques/train.csv") %>%
# Removing outliers per http://jse.amstat.org/v19n3/decock.pdf
filter(GrLivArea < 4000)
DT::datatable(kaggle)fill_holes <- function(df){
df %>%
# Filling in missing values with zeros where it makes sense
mutate(BedroomAbvGr = replace_na(BedroomAbvGr, 0),
BsmtFullBath = replace_na(BsmtFullBath, 0),
BsmtHalfBath = replace_na(BsmtHalfBath, 0),
BsmtUnfSF = replace_na(BsmtUnfSF, 0),
EnclosedPorch = replace_na(EnclosedPorch, 0),
Fireplaces = replace_na(Fireplaces, 0),
GarageArea = replace_na(GarageArea, 0),
GarageCars = replace_na(GarageCars, 0),
HalfBath = replace_na(HalfBath, 0),
KitchenAbvGr = replace_na(KitchenAbvGr, 0),
LotFrontage = replace_na(LotFrontage, 0),
OpenPorchSF = replace_na(OpenPorchSF, 0),
PoolArea = replace_na(PoolArea, 0),
ScreenPorch = replace_na(ScreenPorch, 0),
TotRmsAbvGrd = replace_na(TotRmsAbvGrd, 0),
WoodDeckSF = replace_na(WoodDeckSF, 0))
}
kaggle <- fill_holes(kaggle)
kaggle %>%
dplyr::select(2:11) %>%
pairs.panels(method = "pearson", hist.col = "#f44542")
3.1 Question 1 : Descriptive and Inferential Statistics.
3.1.1 Answer 1
Provide univariate descriptive statistics and appropriate plots for the training data set.
d_table = as.data.frame(matrix(character(),nrow = 0, ncol = 3))
colnames(d_table) <- c("Attribute","Measure","Value")
attribute <- NULL
for (variable in names(kaggle)){
attribute = variable
cat(paste("<h4>", variable, "</h4>"))
d <- kaggle[,names(kaggle) == variable]
if(is.factor(d)){
p <- ggplot(kaggle, aes_string(variable)) +
geom_bar() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
d_table <- kaggle %>%
group_by(.dots = variable) %>%
summarise(count = n()) %>%
kable() %>%
kable_styling()
} else {
p <- ggplot(kaggle, aes_string(variable)) +
geom_density()
q <- quantile(d, na.rm = TRUE)
d_table <- data.frame(Min = min(d, na.rm = TRUE),
First = q[2],
Median = median(d, na.rm = TRUE),
Mean = mean(d, na.rm = TRUE),
Third = q[4],
Max = max(d, na.rm = TRUE)) %>%
rename("First Quartile" = First,
"Third Quartile" = Third) %>%
gather(Measure, Value) %>%
kable() %>%
kable_styling()
d_table <- cbind(attribute, d_table)
DT::datatable(d_table)
}
print(p)
print(d_table)
}## <h4> Id </h4>
## attribute
## [1,] "Id"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 1.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 364.750 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 730.500 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 729.967 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 1094.250 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 1460.000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> MSSubClass </h4>
## attribute
## [1,] "MSSubClass"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 20.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 20.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 50.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 56.88874 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 70.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 190.00000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> MSZoning </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> MSZoning </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> C (all) </td>
## <td style="text-align:right;"> 10 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> FV </td>
## <td style="text-align:right;"> 65 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RH </td>
## <td style="text-align:right;"> 16 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RL </td>
## <td style="text-align:right;"> 1147 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RM </td>
## <td style="text-align:right;"> 218 </td>
## </tr>
## </tbody>
## </table>
## <h4> LotFrontage </h4>
## attribute
## [1,] "LotFrontage"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 42.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 63.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 57.29602 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 79.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 313.00000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> LotArea </h4>
## attribute
## [1,] "LotArea"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 1300.00 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 7538.75 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 9468.50 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 10448.78 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 11588.00 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 215245.00 </td>\n </tr>\n</tbody>\n</table>"
## <h4> Street </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Street </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Grvl </td>
## <td style="text-align:right;"> 6 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Pave </td>
## <td style="text-align:right;"> 1450 </td>
## </tr>
## </tbody>
## </table>
## <h4> Alley </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Alley </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Grvl </td>
## <td style="text-align:right;"> 50 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Pave </td>
## <td style="text-align:right;"> 41 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 1365 </td>
## </tr>
## </tbody>
## </table>
## <h4> LotShape </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> LotShape </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> IR1 </td>
## <td style="text-align:right;"> 481 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> IR2 </td>
## <td style="text-align:right;"> 41 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> IR3 </td>
## <td style="text-align:right;"> 9 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Reg </td>
## <td style="text-align:right;"> 925 </td>
## </tr>
## </tbody>
## </table>
## <h4> LandContour </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> LandContour </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Bnk </td>
## <td style="text-align:right;"> 61 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> HLS </td>
## <td style="text-align:right;"> 50 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Low </td>
## <td style="text-align:right;"> 36 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Lvl </td>
## <td style="text-align:right;"> 1309 </td>
## </tr>
## </tbody>
## </table>
## <h4> Utilities </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Utilities </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> AllPub </td>
## <td style="text-align:right;"> 1455 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NoSeWa </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## </tbody>
## </table>
## <h4> LotConfig </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> LotConfig </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Corner </td>
## <td style="text-align:right;"> 260 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CulDSac </td>
## <td style="text-align:right;"> 94 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> FR2 </td>
## <td style="text-align:right;"> 47 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> FR3 </td>
## <td style="text-align:right;"> 4 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Inside </td>
## <td style="text-align:right;"> 1051 </td>
## </tr>
## </tbody>
## </table>
## <h4> LandSlope </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> LandSlope </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Gtl </td>
## <td style="text-align:right;"> 1378 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Mod </td>
## <td style="text-align:right;"> 65 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Sev </td>
## <td style="text-align:right;"> 13 </td>
## </tr>
## </tbody>
## </table>
## <h4> Neighborhood </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Neighborhood </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Blmngtn </td>
## <td style="text-align:right;"> 17 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Blueste </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BrDale </td>
## <td style="text-align:right;"> 16 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BrkSide </td>
## <td style="text-align:right;"> 58 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> ClearCr </td>
## <td style="text-align:right;"> 28 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CollgCr </td>
## <td style="text-align:right;"> 150 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Crawfor </td>
## <td style="text-align:right;"> 51 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Edwards </td>
## <td style="text-align:right;"> 98 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gilbert </td>
## <td style="text-align:right;"> 79 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> IDOTRR </td>
## <td style="text-align:right;"> 37 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> MeadowV </td>
## <td style="text-align:right;"> 17 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Mitchel </td>
## <td style="text-align:right;"> 49 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NAmes </td>
## <td style="text-align:right;"> 225 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NoRidge </td>
## <td style="text-align:right;"> 39 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NPkVill </td>
## <td style="text-align:right;"> 9 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NridgHt </td>
## <td style="text-align:right;"> 77 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NWAmes </td>
## <td style="text-align:right;"> 73 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> OldTown </td>
## <td style="text-align:right;"> 113 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Sawyer </td>
## <td style="text-align:right;"> 74 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> SawyerW </td>
## <td style="text-align:right;"> 59 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Somerst </td>
## <td style="text-align:right;"> 86 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> StoneBr </td>
## <td style="text-align:right;"> 25 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> SWISU </td>
## <td style="text-align:right;"> 25 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Timber </td>
## <td style="text-align:right;"> 38 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Veenker </td>
## <td style="text-align:right;"> 11 </td>
## </tr>
## </tbody>
## </table>
## <h4> Condition1 </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Condition1 </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Artery </td>
## <td style="text-align:right;"> 48 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Feedr </td>
## <td style="text-align:right;"> 80 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Norm </td>
## <td style="text-align:right;"> 1258 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> PosA </td>
## <td style="text-align:right;"> 8 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> PosN </td>
## <td style="text-align:right;"> 18 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RRAe </td>
## <td style="text-align:right;"> 11 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RRAn </td>
## <td style="text-align:right;"> 26 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RRNe </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RRNn </td>
## <td style="text-align:right;"> 5 </td>
## </tr>
## </tbody>
## </table>
## <h4> Condition2 </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Condition2 </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Artery </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Feedr </td>
## <td style="text-align:right;"> 6 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Norm </td>
## <td style="text-align:right;"> 1442 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> PosA </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> PosN </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RRAe </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RRAn </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RRNn </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## </tbody>
## </table>
## <h4> BldgType </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> BldgType </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> 1Fam </td>
## <td style="text-align:right;"> 1216 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> 2fmCon </td>
## <td style="text-align:right;"> 31 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Duplex </td>
## <td style="text-align:right;"> 52 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Twnhs </td>
## <td style="text-align:right;"> 43 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TwnhsE </td>
## <td style="text-align:right;"> 114 </td>
## </tr>
## </tbody>
## </table>
## <h4> HouseStyle </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> HouseStyle </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> 1.5Fin </td>
## <td style="text-align:right;"> 154 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> 1.5Unf </td>
## <td style="text-align:right;"> 14 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> 1Story </td>
## <td style="text-align:right;"> 726 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> 2.5Fin </td>
## <td style="text-align:right;"> 8 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> 2.5Unf </td>
## <td style="text-align:right;"> 11 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> 2Story </td>
## <td style="text-align:right;"> 441 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> SFoyer </td>
## <td style="text-align:right;"> 37 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> SLvl </td>
## <td style="text-align:right;"> 65 </td>
## </tr>
## </tbody>
## </table>
## <h4> OverallQual </h4>
## attribute
## [1,] "OverallQual"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 1.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 5.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 6.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 6.088599 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 7.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 10.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> OverallCond </h4>
## attribute
## [1,] "OverallCond"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 1.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 5.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 5.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 5.576236 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 6.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 9.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> YearBuilt </h4>
## attribute
## [1,] "YearBuilt"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 1872.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 1954.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 1972.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1971.185 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 2000.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 2010.000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> YearRemodAdd </h4>
## attribute
## [1,] "YearRemodAdd"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 1950.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 1966.750 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 1993.500 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1984.819 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 2004.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 2010.000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> RoofStyle </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> RoofStyle </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Flat </td>
## <td style="text-align:right;"> 13 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gable </td>
## <td style="text-align:right;"> 1140 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gambrel </td>
## <td style="text-align:right;"> 11 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Hip </td>
## <td style="text-align:right;"> 283 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Mansard </td>
## <td style="text-align:right;"> 7 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Shed </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## </tbody>
## </table>
## <h4> RoofMatl </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> RoofMatl </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> CompShg </td>
## <td style="text-align:right;"> 1432 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Membran </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Metal </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Roll </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Tar&Grv </td>
## <td style="text-align:right;"> 11 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> WdShake </td>
## <td style="text-align:right;"> 5 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> WdShngl </td>
## <td style="text-align:right;"> 5 </td>
## </tr>
## </tbody>
## </table>
## <h4> Exterior1st </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Exterior1st </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> AsbShng </td>
## <td style="text-align:right;"> 20 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> AsphShn </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BrkComm </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BrkFace </td>
## <td style="text-align:right;"> 50 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CBlock </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CemntBd </td>
## <td style="text-align:right;"> 60 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> HdBoard </td>
## <td style="text-align:right;"> 221 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> ImStucc </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> MetalSd </td>
## <td style="text-align:right;"> 220 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Plywood </td>
## <td style="text-align:right;"> 108 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Stone </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Stucco </td>
## <td style="text-align:right;"> 24 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> VinylSd </td>
## <td style="text-align:right;"> 515 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Wd Sdng </td>
## <td style="text-align:right;"> 205 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> WdShing </td>
## <td style="text-align:right;"> 26 </td>
## </tr>
## </tbody>
## </table>
## <h4> Exterior2nd </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Exterior2nd </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> AsbShng </td>
## <td style="text-align:right;"> 20 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> AsphShn </td>
## <td style="text-align:right;"> 3 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Brk Cmn </td>
## <td style="text-align:right;"> 7 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BrkFace </td>
## <td style="text-align:right;"> 25 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CBlock </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CmentBd </td>
## <td style="text-align:right;"> 59 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> HdBoard </td>
## <td style="text-align:right;"> 206 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> ImStucc </td>
## <td style="text-align:right;"> 9 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> MetalSd </td>
## <td style="text-align:right;"> 214 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Other </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Plywood </td>
## <td style="text-align:right;"> 142 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Stone </td>
## <td style="text-align:right;"> 5 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Stucco </td>
## <td style="text-align:right;"> 25 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> VinylSd </td>
## <td style="text-align:right;"> 504 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Wd Sdng </td>
## <td style="text-align:right;"> 197 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Wd Shng </td>
## <td style="text-align:right;"> 38 </td>
## </tr>
## </tbody>
## </table>
## <h4> MasVnrType </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> MasVnrType </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> BrkCmn </td>
## <td style="text-align:right;"> 15 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BrkFace </td>
## <td style="text-align:right;"> 444 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> None </td>
## <td style="text-align:right;"> 863 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Stone </td>
## <td style="text-align:right;"> 126 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 8 </td>
## </tr>
## </tbody>
## </table>
## <h4> MasVnrArea </h4>
## attribute
## [1,] "MasVnrArea"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 102.0877 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 164.2500 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 1600.0000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> ExterQual </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> ExterQual </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 49 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 14 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 487 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 906 </td>
## </tr>
## </tbody>
## </table>
## <h4> ExterCond </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> ExterCond </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 3 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 28 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 146 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Po </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 1278 </td>
## </tr>
## </tbody>
## </table>
## <h4> Foundation </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Foundation </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> BrkTil </td>
## <td style="text-align:right;"> 146 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CBlock </td>
## <td style="text-align:right;"> 634 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> PConc </td>
## <td style="text-align:right;"> 643 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Slab </td>
## <td style="text-align:right;"> 24 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Stone </td>
## <td style="text-align:right;"> 6 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Wood </td>
## <td style="text-align:right;"> 3 </td>
## </tr>
## </tbody>
## </table>
## <h4> BsmtQual </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> BsmtQual </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 117 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 35 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 618 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 649 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 37 </td>
## </tr>
## </tbody>
## </table>
## <h4> BsmtCond </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> BsmtCond </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 45 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 65 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Po </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 1307 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 37 </td>
## </tr>
## </tbody>
## </table>
## <h4> BsmtExposure </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> BsmtExposure </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Av </td>
## <td style="text-align:right;"> 220 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 131 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Mn </td>
## <td style="text-align:right;"> 114 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> No </td>
## <td style="text-align:right;"> 953 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 38 </td>
## </tr>
## </tbody>
## </table>
## <h4> BsmtFinType1 </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> BsmtFinType1 </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> ALQ </td>
## <td style="text-align:right;"> 220 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BLQ </td>
## <td style="text-align:right;"> 148 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> GLQ </td>
## <td style="text-align:right;"> 414 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> LwQ </td>
## <td style="text-align:right;"> 74 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Rec </td>
## <td style="text-align:right;"> 133 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Unf </td>
## <td style="text-align:right;"> 430 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 37 </td>
## </tr>
## </tbody>
## </table>
## <h4> BsmtFinSF1 </h4>
## attribute
## [1,] "BsmtFinSF1"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 381.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 436.9911 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 706.5000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 2188.0000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> BsmtFinType2 </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> BsmtFinType2 </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> ALQ </td>
## <td style="text-align:right;"> 19 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BLQ </td>
## <td style="text-align:right;"> 33 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> GLQ </td>
## <td style="text-align:right;"> 14 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> LwQ </td>
## <td style="text-align:right;"> 46 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Rec </td>
## <td style="text-align:right;"> 54 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Unf </td>
## <td style="text-align:right;"> 1252 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 38 </td>
## </tr>
## </tbody>
## </table>
## <h4> BsmtFinSF2 </h4>
## attribute
## [1,] "BsmtFinSF2"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 46.6772 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 1474.0000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> BsmtUnfSF </h4>
## attribute
## [1,] "BsmtUnfSF"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 222.5000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 477.5000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 566.9904 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 808.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 2336.0000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> TotalBsmtSF </h4>
## attribute
## [1,] "TotalBsmtSF"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 795.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 990.500 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1050.659 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 1293.750 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 3206.000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> Heating </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Heating </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Floor </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> GasA </td>
## <td style="text-align:right;"> 1424 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> GasW </td>
## <td style="text-align:right;"> 18 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Grav </td>
## <td style="text-align:right;"> 7 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> OthW </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Wall </td>
## <td style="text-align:right;"> 4 </td>
## </tr>
## </tbody>
## </table>
## <h4> HeatingQC </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> HeatingQC </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 737 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 49 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 241 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Po </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 428 </td>
## </tr>
## </tbody>
## </table>
## <h4> CentralAir </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> CentralAir </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> N </td>
## <td style="text-align:right;"> 95 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Y </td>
## <td style="text-align:right;"> 1361 </td>
## </tr>
## </tbody>
## </table>
## <h4> Electrical </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Electrical </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> FuseA </td>
## <td style="text-align:right;"> 94 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> FuseF </td>
## <td style="text-align:right;"> 27 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> FuseP </td>
## <td style="text-align:right;"> 3 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Mix </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> SBrkr </td>
## <td style="text-align:right;"> 1330 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## </tbody>
## </table>
## <h4> X1stFlrSF </h4>
## attribute
## [1,] "X1stFlrSF"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 334.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 882.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 1086.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1157.109 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 1389.250 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 3228.000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> X2ndFlrSF </h4>
## attribute
## [1,] "X2ndFlrSF"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 343.533 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 728.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 1818.000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> LowQualFinSF </h4>
## attribute
## [1,] "LowQualFinSF"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 5.860577 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 572.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> GrLivArea </h4>
## attribute
## [1,] "GrLivArea"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 334.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 1128.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 1458.500 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1506.502 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 1775.250 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 3627.000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> BsmtFullBath </h4>
## attribute
## [1,] "BsmtFullBath"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 0.4237637 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 1.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 3.0000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> BsmtHalfBath </h4>
## attribute
## [1,] "BsmtHalfBath"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 0.0570055 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 2.0000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> FullBath </h4>
## attribute
## [1,] "FullBath"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 1.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 2.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1.561813 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 2.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 3.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> HalfBath </h4>
## attribute
## [1,] "HalfBath"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 0.3811813 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 1.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 2.0000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> BedroomAbvGr </h4>
## attribute
## [1,] "BedroomAbvGr"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 2.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 3.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 2.864698 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 3.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 8.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> KitchenAbvGr </h4>
## attribute
## [1,] "KitchenAbvGr"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 1.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 1.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1.046703 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 1.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 3.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> KitchenQual </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> KitchenQual </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 96 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 39 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 586 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 735 </td>
## </tr>
## </tbody>
## </table>
## <h4> TotRmsAbvGrd </h4>
## attribute
## [1,] "TotRmsAbvGrd"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 2.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 5.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 6.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 6.506181 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 7.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 14.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> Functional </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Functional </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Maj1 </td>
## <td style="text-align:right;"> 14 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Maj2 </td>
## <td style="text-align:right;"> 5 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Min1 </td>
## <td style="text-align:right;"> 31 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Min2 </td>
## <td style="text-align:right;"> 34 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Mod </td>
## <td style="text-align:right;"> 15 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Sev </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Typ </td>
## <td style="text-align:right;"> 1356 </td>
## </tr>
## </tbody>
## </table>
## <h4> Fireplaces </h4>
## attribute
## [1,] "Fireplaces"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 1.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 0.6092033 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 1.0000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 3.0000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> FireplaceQu </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> FireplaceQu </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 23 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 33 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 378 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Po </td>
## <td style="text-align:right;"> 20 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 312 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 690 </td>
## </tr>
## </tbody>
## </table>
## <h4> GarageType </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> GarageType </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> 2Types </td>
## <td style="text-align:right;"> 6 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Attchd </td>
## <td style="text-align:right;"> 867 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Basment </td>
## <td style="text-align:right;"> 19 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> BuiltIn </td>
## <td style="text-align:right;"> 87 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CarPort </td>
## <td style="text-align:right;"> 9 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Detchd </td>
## <td style="text-align:right;"> 387 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 81 </td>
## </tr>
## </tbody>
## </table>
## <h4> GarageYrBlt </h4>
## attribute
## [1,] "GarageYrBlt"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 1900.00 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 1961.00 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 1980.00 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1978.44 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 2002.00 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 2010.00 </td>\n </tr>\n</tbody>\n</table>"
## <h4> GarageFinish </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> GarageFinish </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Fin </td>
## <td style="text-align:right;"> 348 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> RFn </td>
## <td style="text-align:right;"> 422 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Unf </td>
## <td style="text-align:right;"> 605 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 81 </td>
## </tr>
## </tbody>
## </table>
## <h4> GarageCars </h4>
## attribute
## [1,] "GarageCars"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 1.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 2.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 1.764423 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 2.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 4.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> GarageArea </h4>
## attribute
## [1,] "GarageArea"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 329.5000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 478.5000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 471.5687 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 576.0000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 1390.0000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> GarageQual </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> GarageQual </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 3 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 48 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 14 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Po </td>
## <td style="text-align:right;"> 3 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 1307 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 81 </td>
## </tr>
## </tbody>
## </table>
## <h4> GarageCond </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> GarageCond </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 35 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 9 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Po </td>
## <td style="text-align:right;"> 7 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TA </td>
## <td style="text-align:right;"> 1322 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 81 </td>
## </tr>
## </tbody>
## </table>
## <h4> PavedDrive </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> PavedDrive </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> N </td>
## <td style="text-align:right;"> 90 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> P </td>
## <td style="text-align:right;"> 30 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Y </td>
## <td style="text-align:right;"> 1336 </td>
## </tr>
## </tbody>
## </table>
## <h4> WoodDeckSF </h4>
## attribute
## [1,] "WoodDeckSF"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 93.83379 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 168.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 857.00000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> OpenPorchSF </h4>
## attribute
## [1,] "OpenPorchSF"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 24.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 46.22115 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 68.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 547.00000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> EnclosedPorch </h4>
## attribute
## [1,] "EnclosedPorch"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 22.01442 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 552.00000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> X3SsnPorch </h4>
## attribute
## [1,] "X3SsnPorch"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 3.418956 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 508.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> ScreenPorch </h4>
## attribute
## [1,] "ScreenPorch"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 15.10234 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 480.00000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> PoolArea </h4>
## attribute
## [1,] "PoolArea"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 2.055632 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 0.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 738.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> PoolQC </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> PoolQC </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Ex </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Fa </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Gd </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 1451 </td>
## </tr>
## </tbody>
## </table>
## <h4> Fence </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> Fence </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> GdPrv </td>
## <td style="text-align:right;"> 59 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> GdWo </td>
## <td style="text-align:right;"> 54 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> MnPrv </td>
## <td style="text-align:right;"> 156 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> MnWw </td>
## <td style="text-align:right;"> 11 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 1176 </td>
## </tr>
## </tbody>
## </table>
## <h4> MiscFeature </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> MiscFeature </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Gar2 </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Othr </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Shed </td>
## <td style="text-align:right;"> 49 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> TenC </td>
## <td style="text-align:right;"> 1 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> NA </td>
## <td style="text-align:right;"> 1402 </td>
## </tr>
## </tbody>
## </table>
## <h4> MiscVal </h4>
## attribute
## [1,] "MiscVal"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 43.60852 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 0.00000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 15500.00000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> MoSold </h4>
## attribute
## [1,] "MoSold"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 1.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 5.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 6.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 6.326236 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 8.000000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 12.000000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> YrSold </h4>
## attribute
## [1,] "YrSold"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 2006.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 2007.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 2008.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 2007.817 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 2009.000 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 2010.000 </td>\n </tr>\n</tbody>\n</table>"
## <h4> SaleType </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> SaleType </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> COD </td>
## <td style="text-align:right;"> 43 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Con </td>
## <td style="text-align:right;"> 2 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> ConLD </td>
## <td style="text-align:right;"> 9 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> ConLI </td>
## <td style="text-align:right;"> 5 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> ConLw </td>
## <td style="text-align:right;"> 5 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> CWD </td>
## <td style="text-align:right;"> 4 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> New </td>
## <td style="text-align:right;"> 120 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Oth </td>
## <td style="text-align:right;"> 3 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> WD </td>
## <td style="text-align:right;"> 1265 </td>
## </tr>
## </tbody>
## </table>
## <h4> SaleCondition </h4>
## <table class="table" style="margin-left: auto; margin-right: auto;">
## <thead>
## <tr>
## <th style="text-align:left;"> SaleCondition </th>
## <th style="text-align:right;"> count </th>
## </tr>
## </thead>
## <tbody>
## <tr>
## <td style="text-align:left;"> Abnorml </td>
## <td style="text-align:right;"> 100 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> AdjLand </td>
## <td style="text-align:right;"> 4 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Alloca </td>
## <td style="text-align:right;"> 12 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Family </td>
## <td style="text-align:right;"> 20 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Normal </td>
## <td style="text-align:right;"> 1197 </td>
## </tr>
## <tr>
## <td style="text-align:left;"> Partial </td>
## <td style="text-align:right;"> 123 </td>
## </tr>
## </tbody>
## </table>
## <h4> SalePrice </h4>
## attribute
## [1,] "SalePrice"
## d_table
## [1,] "<table class=\"table\" style=\"margin-left: auto; margin-right: auto;\">\n <thead>\n <tr>\n <th style=\"text-align:left;\"> Measure </th>\n <th style=\"text-align:right;\"> Value </th>\n </tr>\n </thead>\n<tbody>\n <tr>\n <td style=\"text-align:left;\"> Min </td>\n <td style=\"text-align:right;\"> 34900.0 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> First Quartile </td>\n <td style=\"text-align:right;\"> 129900.0 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Median </td>\n <td style=\"text-align:right;\"> 163000.0 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Mean </td>\n <td style=\"text-align:right;\"> 180151.2 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Third Quartile </td>\n <td style=\"text-align:right;\"> 214000.0 </td>\n </tr>\n <tr>\n <td style=\"text-align:left;\"> Max </td>\n <td style=\"text-align:right;\"> 625000.0 </td>\n </tr>\n</tbody>\n</table>"#plot histogram of all numeric variables
kaggle %>%
purrr::keep(is.numeric) %>%
gather() %>%
ggplot(aes(value)) +
facet_wrap(~ key, scales = "free",ncol=4) +
theme( axis.text.x = element_text(angle = 90)) +
geom_histogram()
Provide a scatterplot matrix for at least two of the independent variables and the dependent variable.
kaggle %>%
dplyr::select(c("SalePrice", "LotArea", "TotalBsmtSF")) %>%
pairs.panels(method = "pearson", hist.col = "#c95656")
From this plot we can quickly see that homes without a garage have low sales prices. But we can also that the higher priced homes are not necessarily the ones with the highest lot or garage size.
Here best prices seem to be a moderate size lot, not necessarily very large lots. Over years the prices have gradually increased per lot but not exponentially.
Derive a correlation matrix for any three quantitative variables in the dataset.
correlation_data <- kaggle %>%
dplyr::select(TotalBsmtSF, GrLivArea, YearBuilt)
correlation_matrix <- correlation_data %>%
cor() %>%
as.matrix()
correlation_matrix %>%
kable() %>%
kable_styling()| TotalBsmtSF | GrLivArea | YearBuilt | |
|---|---|---|---|
| TotalBsmtSF | 1.0000000 | 0.3948292 | 0.3998666 |
| GrLivArea | 0.3948292 | 1.0000000 | 0.1926450 |
| YearBuilt | 0.3998666 | 0.1926450 | 1.0000000 |
correlationData<-dplyr::select(kaggle,SalePrice,LotArea,BsmtUnfSF)
correlationMatrix<-round(cor(correlationData),4)
correlationMatrix## SalePrice LotArea BsmtUnfSF
## SalePrice 1.0000 0.2699 0.2207
## LotArea 0.2699 1.0000 -0.0038
## BsmtUnfSF 0.2207 -0.0038 1.0000- The first matrix shows there is good correlation between
BsmtUnfSFandYearBuiltwhereas low correlation betweenGrLivAreaandYearBuilt - The matrix shows that in fact there isn???t a strong correlation between
LotAreaandBsmtUnfSF, with a correlation very close to zero: -0.0038. We do however find some correlation between these two variables and the Sale Price.
Test the hypotheses that the correlations between each pairwise set of variables is 0 and provide an 80% confidence interval.
zero_vars <- 0
test <- 0
variables <- kaggle %>%
dplyr::select(-SalePrice) %>%
names()
df = as.data.frame(matrix(character(),nrow = 0, ncol = 2))
for(variable in variables){
d <- kaggle[,names(kaggle) == variable]
if(is.numeric(d)){
test <- test + 1
results <- cor.test(kaggle$SalePrice, d, conf.level = 0.8)
if(0 > results$conf.int[1] & results$conf.int[2] > 0){
hypothesis_test_results <- "Yes"
zero_vars <- zero_vars + 1
} else {
hypothesis_test_results <- "No"
}
dr = c(variable,hypothesis_test_results)
df <- rbind(df,dr, stringsAsFactors=FALSE)
}
}
colnames(df) = c("Variable","Correlation Equal to Zero")
DT::datatable(df)##
## Pearson's product-moment correlation
##
## data: correlation_data$TotalBsmtSF and correlation_data$GrLivArea
## t = 16.387, df = 1454, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 80 percent confidence interval:
## 0.3660790 0.4228263
## sample estimates:
## cor
## 0.3948292With a very low P value, we are confident the correlation between these two variables is not zero, and we are 80% confident it is between 0.3660790 and 0.4228263
- TotalBsmtSF vs YearBuilt
##
## Pearson's product-moment correlation
##
## data: correlation_data$TotalBsmtSF and correlation_data$YearBuilt
## t = 16.635, df = 1454, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 80 percent confidence interval:
## 0.3712479 0.4277263
## sample estimates:
## cor
## 0.3998666With a very low P value, we are confident the correlation between these two variables is not zero, and we are 80% confident it is between 0.3712479 and 0.4277263
- YearBuilt vs GrLivArea
##
## Pearson's product-moment correlation
##
## data: correlation_data$YearBuilt and correlation_data$GrLivArea
## t = 7.486, df = 1454, p-value = 1.225e-13
## alternative hypothesis: true correlation is not equal to 0
## 80 percent confidence interval:
## 0.1600736 0.2247973
## sample estimates:
## cor
## 0.192645With a low P value, we are confident the correlation between these two variables is not zero, and we are 80% confident it is between 0.1600736 and 0.2247973
- Sale Price vs Lot Area
##
## Pearson's product-moment correlation
##
## data: correlationData$SalePrice and correlationData$LotArea
## t = 10.687, df = 1454, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 80 percent confidence interval:
## 0.2384211 0.3007466
## sample estimates:
## cor
## 0.2698665With a low P value, we are confident the correlation between these two variables is not zero, and we are 80% confident it is between 0.2384211 and 0.3007466. We can conclude that SalePrice and LotArea are significantly correlated with a correlation coefficient of 0.2698665. There is sufficient evidence to conclude there is a significant linear relationship between SalePrice and LotArea because the correlation coefficient is significantly different from zero.
- Sale Price vs Basement Size
##
## Pearson's product-moment correlation
##
## data: correlationData$SalePrice and correlationData$BsmtUnfSF
## t = 8.6274, df = 1454, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 80 percent confidence interval:
## 0.1884678 0.2524136
## sample estimates:
## cor
## 0.2206778With a low P value, we are confident the correlation between these two variables is not zero, and we are 80% confident it is between 0.1884678 and 0.2524136
- Lot Area vs Basement Size
##
## Pearson's product-moment correlation
##
## data: correlationData$LotArea and correlationData$BsmtUnfSF
## t = -0.14391, df = 1454, p-value = 0.8856
## alternative hypothesis: true correlation is not equal to 0
## 80 percent confidence interval:
## -0.03737706 0.02983752
## sample estimates:
## cor
## -0.003774031With a high P value, we are confident the correlation between these two variables is in fact zero, and we are 80% confident it is between -0.03737706 and 0.02983752. It means they have no correlation.
Discuss the meaning of your analysis. Would you be worried about familywise error? Why or why not?
Familywise error is that of making at least one “type I error”, or a false positive, rejection of a true null. Type I error happens when the null is rejected or the P value being smaller than a set threshold.
In our first 5 cases, the P value is extremely small, so any reasonable threshold (0.1, 0.05, etc.) setting will almost certainly be breached. So I would not be worried about committing a type one error, the null hypothesis can very certainly be rejected.
In the last case, now the P value is very large, so again we are far from any reasonable threshold. In this case we can certainly not reject the null hypothesis.
3.2 Question 2 : Linear Algebra and Correlation.
3.2.1 Answer 2
Invert your correlation matrix from above. (This is known as the precision matrix and contains variance inflation factors on the diagonal.)
precision_matrix <- pracma::inv(correlation_matrix)
precision_matrix %>%
kable() %>%
kable_styling()| TotalBsmtSF | GrLivArea | YearBuilt | |
|---|---|---|---|
| TotalBsmtSF | 1.3601385 | -0.4489077 | -0.4573942 |
| GrLivArea | -0.4489077 | 1.1867025 | -0.0491090 |
| YearBuilt | -0.4573942 | -0.0491090 | 1.1923573 |
Multiply the correlation matrix by the precision matrix, and then multiply the precision matrix by the correlation matrix.
| TotalBsmtSF | GrLivArea | YearBuilt | |
|---|---|---|---|
| TotalBsmtSF | 1 | 0 | 0 |
| GrLivArea | 0 | 1 | 0 |
| YearBuilt | 0 | 0 | 1 |
| TotalBsmtSF | GrLivArea | YearBuilt | |
|---|---|---|---|
| TotalBsmtSF | 1 | 0 | 0 |
| GrLivArea | 0 | 1 | 0 |
| YearBuilt | 0 | 0 | 1 |
Conduct LU decomposition on the matrix.
lu_decomposition <- Matrix::expand(Matrix::lu(correlation_matrix))
A <- lu_decomposition$L %*% lu_decomposition$U %>%
as.matrix()
colnames(A) <- colnames(correlation_matrix)
rownames(A) <- rownames(correlation_matrix)
A %>%
kable() %>%
kable_styling()| TotalBsmtSF | GrLivArea | YearBuilt | |
|---|---|---|---|
| TotalBsmtSF | 1.0000000 | 0.3948292 | 0.3998666 |
| GrLivArea | 0.3948292 | 1.0000000 | 0.1926450 |
| YearBuilt | 0.3998666 | 0.1926450 | 1.0000000 |
| TotalBsmtSF | GrLivArea | YearBuilt | |
|---|---|---|---|
| TotalBsmtSF | 1.0000000 | 0.3948292 | 0.3998666 |
| GrLivArea | 0.3948292 | 1.0000000 | 0.1926450 |
| YearBuilt | 0.3998666 | 0.1926450 | 1.0000000 |
Let’s confirm the decomposition by comparing to our original matrix correlationMatrix.
## TotalBsmtSF GrLivArea YearBuilt
## TotalBsmtSF TRUE TRUE TRUE
## GrLivArea TRUE TRUE TRUE
## YearBuilt TRUE TRUE TRUE3.3 Question 3 : Calculus-Based Probability & Statistics.
Many times, it makes sense to fit a closed form distribution to data. Select a variable in the Kaggle.com training dataset that is skewed to the right, shift it so that the minimum value is absolutely above zero if necessary. Then load the MASS package and run fitdistr to fit an exponential probability density function. (See https://stat.ethz.ch/R-manual/R-devel/library/MASS/html/fitdistr.html).
3.3.1 Answer 3
Find the optimal value of \(\lambda\) for this distribution, and then take 1000 samples from this exponential distribution using this value (e.g., rexp(1000, \(\lambda\))).
Using the Square Footage of the Unfinished Basement for this part of the exam. I know it is right skewed because the mean (566.9903846) is larger than the median (477.5) as shown in the figure below:
ggplot(kaggle, aes(BsmtUnfSF)) + geom_density() +
geom_vline(xintercept = mean(kaggle$BsmtUnfSF), color = "red")+
geom_vline(xintercept = median(kaggle$BsmtUnfSF), color = "blue") +
annotate("text", x = 700, y = 0.0005, label = "Mean", color="red") +
annotate("text", x = 300, y = 0.0005, label = "Median", color="blue")
Have loaded the MASS package. The minimum (0) is not smaller than zero so we don’t need to shift the data. Remember that the maximum value is 2336.
library(MASS)
lambda <- fitdistr(kaggle$BsmtUnfSF, densfun = "exponential")$estimate
fit <- fitdistr(kaggle$GrLivArea, "exponential")The optimal value for \(\lambda\) is 0.0017637.
Plot a histogram and compare it with a histogram of your original variable.
histogram_data <- data.frame(Value = samples, Data = c("Sample"))
histogram_data <- data.frame(Value = kaggle$BsmtUnfSF, Data = c("Original")) %>%
rbind(histogram_data) %>%
mutate(Data = as.factor(Data))
ggplot(histogram_data, aes(Value, fill = Data)) + geom_histogram(bins = 50, alpha = 0.5)
sim.df <- data.frame(length = sim)
toFit.df <- data.frame(length = kaggle$GrLivArea)
sim.df$from <- 'sim'
toFit.df$from <- 'toFit'
both.df <- rbind(sim.df,toFit.df)
ggplot(both.df, aes(length, fill = from)) + geom_density(alpha = 0.2)
The original data is not quite exponential, but it’s not a bad approximation. The exponential distribution data has a longer tail than the basement square footage data.
Using the exponential pdf, find the 5th and 95th percentiles using the cumulative distribution function (CDF).
## 5% 95%
## 83.7765 4414.5876
normal.df <- data.frame(length = normal)
normal.df$from <- 'normal'
all.df <- rbind(both.df,normal.df)
ggplot(all.df, aes(length, fill = from)) + geom_density(alpha = 0.2)
From this analysis it appears the selected data GrLivArea was not very right skew. The exponential simulation does not match our data very well, rather, our selected empirical data matches the normal distribution a lot better. This can be seen in the final density plot, but also on the confidence interval where the limits are much closer than for the exponential approximation.
The PDF would be \(f(x;\lambda) = \lambda e^{-\lambda x}\) where \(x \geq 0\) and otherwise zero.
The CDF would be \(F(x;\lambda) = 1 - e^{-\lambda x}\). lambda is 0.0017637. To find the 5th percentile we need to solve for x in:
\[0.05 = 1 - e^{-0.0017637 x}\]
\[-0.95 = - e^{-0.0017637 x}\]
\[-ln(0.95) = 0.0017637 x\]
\[x = \frac{-ln(0.95)}{0.0017637} = 29.0828047\] For the 95th percentile we need to solve for x in:
\[0.95 = 1 - e^{-0.0017637 x}\]
\[-0.05 = - e^{-0.0017637 x}\]
\[-ln(0.05) = 0.0017637 x\]
\[x = \frac{-ln(0.05)}{0.0017637} = 1698.551394\]
So the 5th and 95th percentiles are approximately 29 and 1699, respectively.
Also generate a 95% confidence interval from the empirical data, assuming normality.
mu <- mean(kaggle$BsmtUnfSF)
s <- sd(kaggle$BsmtUnfSF)
n <- nrow(kaggle)
error <- qnorm(0.975) * s / sqrt(n)
ci <- c(mu - error, mu + error)
names(ci) <- c("5%", "95%")
ci 5% 95%
544.2769 589.7038 The 95% confidence interval (assuming normality) is 544 to 590. Although what I think was meant was assume the data is normally distributed. Calculate the 5th and 95th percentile. That is found using \(x = \mu + Z \sigma\). The Z is -1.645 for the 5th percentile, and 1.645 for the 95th. So the percentiles would be -160 and 1294.
Finally, provide the empirical 5th percentile and 95th percentile of the data. Discuss.
5% 95%
0 1468 5% 95%
848.0 2450.5 The actual 5th percentile is 0 and the 95th is 1468. So the findings are summarized in the following table:
| Method | 5% | 95% |
|---|---|---|
| Exponential CDF | 29 | 1699 |
| Normal 95% CI | 544 | 590 |
| Normal Percentiles | -160 | 1294 |
| Emperical Percentiles | 0 | 1468 |
If we model the data as exponentially distributed the 5th percentile is 29. If we model it as normally distributed the 5th is at -160 which in the context of square footage does not make any sense. The actual 5th percentile is 0. The difference is explained to the assumed shape/distibution of the underlying data.
Looking at the 95th percentile we have 393 if the data are exponentially distributed, 1294 if it is normally distributed and 1468 in reality. Again the difference is due to the assumed shape.
I have left out the 95% CI from the discussion because the confidence interval is a way of estimating the mean of the population. We would know if we took 100 estimates that the actual mean falls within the confidence intervals 95% of the time. Within this context it is meaningless.
3.4 Question 4 : Modeling.
Build some type of multiple regression model and submit your model to the competition board. Provide your complete model summary and results with analysis. Report your Kaggle.com user name and score.
3.4.1 Answer 4
Since there are so many variables I will be using a Generalized Linear Model for Model 1 to detect which variables are the most important and will be using them to build the model. First I will drop out the variables that are missing a lot of data or otherwise meaningless and choose only numerical variables.
Next I will be using Linear Model for Model 2 with only significant variables
3.4.1.1 Build Models
# subset training data numerical values
train_int <- kaggle[c(2, 4, 5, 18:21, 27, 35, 37:39, 44:53, 55, 57, 60, 62:63, 67:72, 76:78, 81)]
model1 <- glm(log(SalePrice) ~ log(LotArea) + OverallQual + YearBuilt + GrLivArea, data=train_int)
summary(model1)##
## Call:
## glm(formula = log(SalePrice) ~ log(LotArea) + OverallQual + YearBuilt +
## GrLivArea, data = train_int)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -0.92016 -0.07974 0.01003 0.09551 0.52986
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 2.402e+00 3.386e-01 7.093 2.04e-12 ***
## log(LotArea) 1.525e-01 8.814e-03 17.298 < 2e-16 ***
## OverallQual 1.252e-01 4.603e-03 27.190 < 2e-16 ***
## YearBuilt 3.583e-03 1.726e-04 20.754 < 2e-16 ***
## GrLivArea 2.705e-04 1.127e-05 24.005 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for gaussian family taken to be 0.02541506)
##
## Null deviance: 228.259 on 1455 degrees of freedom
## Residual deviance: 36.877 on 1451 degrees of freedom
## AIC: -1208.1
##
## Number of Fisher Scoring iterations: 2model2 <- dplyr::select(kaggle, GrLivArea, BedroomAbvGr,BsmtFinSF1,BsmtUnfSF,GarageArea,GarageCars,GarageYrBlt,GrLivArea,LotFrontage,LotArea,Fireplaces,YearBuilt,OverallQual)
model2$SalePrice<-log(kaggle$SalePrice)
gather(model2,"VARIABLE","VALUE",-SalePrice) %>%
ggplot(aes(x=VALUE,y=SalePrice)) +
geom_point() + facet_wrap(~VARIABLE,scale="free",ncol=4) +
labs(x="Variables", y="Sale Price") +
theme(axis.text.x=element_text(angle=90))
plotlm<-function(lm) {
print(summary(lm))
plot(fitted(lm),resid(lm))
abline(0, 0)
hist(resid(lm),breaks = 100)
qqnorm(resid(lm))
qqline(resid(lm))
}
lm2<-lm(SalePrice ~ GrLivArea+BsmtFinSF1+GarageCars+GrLivArea+LotArea+Fireplaces+YearBuilt+OverallQual+BedroomAbvGr,data=model2)
plotlm(lm2)##
## Call:
## lm(formula = SalePrice ~ GrLivArea + BsmtFinSF1 + GarageCars +
## GrLivArea + LotArea + Fireplaces + YearBuilt + OverallQual +
## BedroomAbvGr, data = model2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.87601 -0.07637 0.01284 0.08626 0.48649
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 5.641e+00 3.310e-01 17.039 < 2e-16 ***
## GrLivArea 2.777e-04 1.335e-05 20.801 < 2e-16 ***
## BsmtFinSF1 1.417e-04 9.778e-06 14.495 < 2e-16 ***
## GarageCars 6.705e-02 7.163e-03 9.361 < 2e-16 ***
## LotArea 3.340e-06 4.197e-07 7.957 3.52e-15 ***
## Fireplaces 4.134e-02 7.201e-03 5.741 1.15e-08 ***
## YearBuilt 2.589e-03 1.739e-04 14.885 < 2e-16 ***
## OverallQual 1.049e-01 4.553e-03 23.036 < 2e-16 ***
## BedroomAbvGr -6.492e-03 6.150e-03 -1.056 0.291
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.1486 on 1447 degrees of freedom
## Multiple R-squared: 0.86, Adjusted R-squared: 0.8593
## F-statistic: 1111 on 8 and 1447 DF, p-value: < 2.2e-16
correlationData<-dplyr::select(kaggle,GrLivArea,BsmtFinSF1,GarageCars,GrLivArea,LotArea,Fireplaces,YearBuilt,OverallQual,BedroomAbvGr)
correlationMatrix<-round(cor(correlationData),4)
correlationMatrix## GrLivArea BsmtFinSF1 GarageCars LotArea Fireplaces YearBuilt
## GrLivArea 1.0000 0.1215 0.4741 0.2319 0.4517 0.1926
## BsmtFinSF1 0.1215 1.0000 0.2240 0.1734 0.2362 0.2483
## GarageCars 0.4741 0.2240 1.0000 0.1510 0.2977 0.5367
## LotArea 0.2319 0.1734 0.1510 1.0000 0.2597 0.0066
## Fireplaces 0.4517 0.2362 0.2977 0.2597 1.0000 0.1432
## YearBuilt 0.1926 0.2483 0.5367 0.0066 0.1432 1.0000
## OverallQual 0.5835 0.2131 0.5987 0.0887 0.3874 0.5717
## BedroomAbvGr 0.5401 -0.1219 0.0831 0.1190 0.1040 -0.0726
## OverallQual BedroomAbvGr
## GrLivArea 0.5835 0.5401
## BsmtFinSF1 0.2131 -0.1219
## GarageCars 0.5987 0.0831
## LotArea 0.0887 0.1190
## Fireplaces 0.3874 0.1040
## YearBuilt 0.5717 -0.0726
## OverallQual 1.0000 0.0968
## BedroomAbvGr 0.0968 1.0000
- Model 1
Looking at the coefficients for the predictor variables, we can see they all have a positive estimate, though all are very small values. This makes sense, since we can generally assume that the Lot size, Quality, year a property was built, and square footage of the home would have a positive relationships to the price (i.e. large, well-built, new houses on lots of land cost more).
- Model 2
For Model2, we eliminated several variables with high P values and chose model with more features.
The biggest difference for these models are transforming the response variable, since it is also skewed, but because of its simplicity, we’ll use this for predicting the Sale Price of the properties in the Kaggle dataset. Using R’s predict function, we’ll feed it the third reduced model, the test dataset, and store the results in an object.
3.4.1.2 Prediction
test <- read.csv("house-prices-advanced-regression-techniques/test.csv") %>% fill_holes()
# Model 1
predict_price1 <- predict(model1, test, type="response")
submission1 <- data.frame(Id = test$Id, SalePrice = predict_price1)
summary(submission1)## Id SalePrice
## Min. :1461 Min. :11.04
## 1st Qu.:1826 1st Qu.:11.73
## Median :2190 Median :11.97
## Mean :2190 Mean :12.01
## 3rd Qu.:2554 3rd Qu.:12.27
## Max. :2919 Max. :13.84# Model 2
predict_price2<-predict(lm2,test)
test2<-dplyr::select(test,GrLivArea,BsmtFinSF1,GarageCars,GrLivArea,LotArea,Fireplaces,YearBuilt,OverallQual,BedroomAbvGr)Taking this resulting vector, we’ll bind it to the Id column of the test data, then create a .csv from the data.
# Model 1
results <- data.frame(test$Id, exp(predict_price1)) # use exp to transform the log of the response variable back
colnames(results) <- c("Id", "SalePrice")
head(results)# Model 2
test2$SalePrice <- round(exp(predict_price2))
test2$Id<-test$Id
test2$SalePrice[is.na(test2$SalePrice)] <- median(test2$SalePrice, na.rm = TRUE)
tblTable<-tbl_df(test2)
tblTable %>% kable() %>% kable_styling() %>% scroll_box(width = "800px", height = "400px")| GrLivArea | BsmtFinSF1 | GarageCars | LotArea | Fireplaces | YearBuilt | OverallQual | BedroomAbvGr | SalePrice | Id |
|---|---|---|---|---|---|---|---|---|---|
| 896 | 468 | 1 | 11622 | 0 | 1961 | 5 | 2 | 114616 | 1461 |
| 1329 | 923 | 1 | 14267 | 0 | 1958 | 6 | 3 | 152290 | 1462 |
| 1629 | 791 | 2 | 13830 | 1 | 1997 | 5 | 3 | 180078 | 1463 |
| 1604 | 602 | 2 | 9978 | 1 | 1998 | 6 | 3 | 191382 | 1464 |
| 1280 | 263 | 2 | 5005 | 0 | 1992 | 8 | 2 | 192296 | 1465 |
| 1655 | 0 | 2 | 10000 | 1 | 1993 | 6 | 3 | 175958 | 1466 |
| 1187 | 935 | 2 | 7980 | 0 | 1992 | 6 | 3 | 167690 | 1467 |
| 1465 | 0 | 2 | 8402 | 1 | 1998 | 6 | 3 | 168189 | 1468 |
| 1341 | 637 | 2 | 10176 | 1 | 1990 | 7 | 2 | 195886 | 1469 |
| 882 | 804 | 2 | 8400 | 0 | 1970 | 4 | 2 | 116748 | 1470 |
| 1337 | 1051 | 2 | 5858 | 1 | 1999 | 7 | 2 | 209343 | 1471 |
| 987 | 156 | 1 | 1680 | 0 | 1971 | 6 | 2 | 123991 | 1472 |
| 1092 | 300 | 1 | 1680 | 0 | 1971 | 5 | 3 | 116558 | 1473 |
| 1456 | 514 | 2 | 2280 | 1 | 1975 | 6 | 3 | 166576 | 1474 |
| 836 | 0 | 1 | 2280 | 0 | 1975 | 7 | 2 | 130766 | 1475 |
| 2334 | 0 | 3 | 12858 | 1 | 2009 | 9 | 3 | 327500 | 1476 |
| 1544 | 0 | 3 | 12883 | 0 | 2009 | 8 | 3 | 227228 | 1477 |
| 1698 | 110 | 3 | 11520 | 1 | 2005 | 9 | 3 | 274688 | 1478 |
| 1822 | 28 | 3 | 14122 | 1 | 2005 | 8 | 3 | 255252 | 1479 |
| 2696 | 1373 | 3 | 14300 | 2 | 2003 | 9 | 3 | 453610 | 1480 |
| 2250 | 578 | 3 | 13650 | 1 | 2002 | 8 | 3 | 307882 | 1481 |
| 1370 | 24 | 2 | 7132 | 1 | 2006 | 8 | 2 | 207440 | 1482 |
| 1324 | 0 | 2 | 18494 | 0 | 2005 | 6 | 3 | 163435 | 1483 |
| 1145 | 16 | 2 | 3203 | 0 | 2006 | 7 | 2 | 165981 | 1484 |
| 1374 | 326 | 2 | 13300 | 1 | 2004 | 7 | 3 | 196920 | 1485 |
| 1733 | 0 | 2 | 8577 | 1 | 2004 | 7 | 3 | 204489 | 1486 |
| 2475 | 0 | 3 | 17433 | 1 | 1998 | 8 | 4 | 300686 | 1487 |
| 1595 | 0 | 3 | 8987 | 1 | 2005 | 8 | 2 | 236178 | 1488 |
| 1218 | 0 | 2 | 9215 | 0 | 2009 | 7 | 2 | 173768 | 1489 |
| 1468 | 1414 | 2 | 10440 | 1 | 2005 | 6 | 2 | 212246 | 1490 |
| 1659 | 0 | 2 | 11920 | 0 | 2004 | 7 | 3 | 194375 | 1491 |
| 1012 | 0 | 1 | 9800 | 0 | 1920 | 5 | 2 | 99013 | 1492 |
| 1494 | 126 | 2 | 15410 | 2 | 1974 | 6 | 3 | 173057 | 1493 |
| 2349 | 250 | 3 | 13143 | 1 | 1993 | 8 | 4 | 292726 | 1494 |
| 2225 | 1129 | 3 | 11134 | 1 | 1992 | 8 | 4 | 317375 | 1495 |
| 1488 | 1298 | 2 | 4835 | 1 | 2004 | 7 | 2 | 228250 | 1496 |
| 1680 | 0 | 2 | 3515 | 0 | 2004 | 7 | 2 | 191338 | 1497 |
| 1200 | 280 | 2 | 3215 | 0 | 2004 | 7 | 2 | 174065 | 1498 |
| 1200 | 368 | 2 | 2544 | 0 | 2004 | 7 | 2 | 175855 | 1499 |
| 1236 | 376 | 2 | 2544 | 0 | 2005 | 6 | 2 | 160531 | 1500 |
| 1512 | 466 | 2 | 2980 | 0 | 2000 | 6 | 2 | 173539 | 1501 |
| 1080 | 244 | 2 | 2403 | 0 | 2003 | 7 | 2 | 166617 | 1502 |
| 1418 | 1032 | 3 | 12853 | 1 | 2010 | 8 | 1 | 268821 | 1503 |
| 1848 | 484 | 2 | 7379 | 1 | 2000 | 8 | 3 | 247542 | 1504 |
| 1492 | 833 | 2 | 8000 | 1 | 2002 | 7 | 3 | 213694 | 1505 |
| 1829 | 506 | 2 | 10456 | 0 | 1967 | 6 | 4 | 177091 | 1506 |
| 2495 | 1137 | 2 | 10791 | 1 | 1993 | 6 | 4 | 260033 | 1507 |
| 1891 | 687 | 2 | 18837 | 1 | 1978 | 6 | 3 | 205169 | 1508 |
| 1645 | 329 | 2 | 9600 | 0 | 1971 | 6 | 4 | 165335 | 1509 |
| 1232 | 698 | 2 | 9600 | 0 | 1966 | 5 | 3 | 138968 | 1510 |
| 1209 | 1059 | 2 | 9900 | 0 | 1966 | 5 | 3 | 145478 | 1511 |
| 1510 | 1010 | 2 | 9680 | 0 | 1967 | 5 | 3 | 157357 | 1512 |
| 1775 | 0 | 2 | 10600 | 0 | 1964 | 6 | 3 | 162253 | 1513 |
| 1728 | 1500 | 0 | 13260 | 0 | 1962 | 5 | 6 | 153536 | 1514 |
| 2461 | 670 | 2 | 9724 | 2 | 1952 | 5 | 3 | 204063 | 1515 |
| 1556 | 300 | 2 | 17360 | 1 | 1949 | 6 | 3 | 163359 | 1516 |
| 1128 | 944 | 1 | 11380 | 1 | 1966 | 6 | 2 | 153215 | 1517 |
| 1604 | 0 | 2 | 8267 | 0 | 1958 | 5 | 4 | 135228 | 1518 |
| 1480 | 1188 | 2 | 8197 | 0 | 2003 | 7 | 3 | 215602 | 1519 |
| 1143 | 856 | 1 | 8050 | 0 | 1959 | 5 | 3 | 126668 | 1520 |
| 1206 | 936 | 1 | 10725 | 0 | 1959 | 5 | 3 | 131544 | 1521 |
| 1580 | 734 | 2 | 10032 | 2 | 1959 | 6 | 3 | 182524 | 1522 |
| 1337 | 0 | 1 | 8382 | 0 | 1956 | 4 | 3 | 105909 | 1523 |
| 1064 | 339 | 1 | 10950 | 0 | 1952 | 5 | 2 | 114940 | 1524 |
| 972 | 648 | 1 | 10895 | 0 | 1955 | 5 | 3 | 117185 | 1525 |
| 988 | 532 | 1 | 13587 | 0 | 1958 | 5 | 2 | 118511 | 1526 |
| 985 | 0 | 2 | 7898 | 0 | 1920 | 4 | 2 | 94025 | 1527 |
| 1224 | 481 | 1 | 8064 | 0 | 1948 | 6 | 3 | 132605 | 1528 |
| 1175 | 588 | 2 | 7635 | 0 | 1960 | 5 | 3 | 131727 | 1529 |
| 1395 | 717 | 2 | 9760 | 1 | 1963 | 6 | 2 | 168628 | 1530 |
| 1844 | 48 | 1 | 4800 | 2 | 1900 | 4 | 3 | 113969 | 1531 |
| 936 | 579 | 0 | 4485 | 1 | 1920 | 5 | 2 | 100760 | 1532 |
| 1347 | 274 | 2 | 5805 | 0 | 1957 | 5 | 3 | 130335 | 1533 |
| 1251 | 0 | 1 | 6900 | 0 | 1938 | 6 | 3 | 121138 | 1534 |
| 1633 | 780 | 1 | 11851 | 1 | 1948 | 5 | 3 | 147295 | 1535 |
| 1245 | 176 | 1 | 8239 | 0 | 1920 | 5 | 3 | 107039 | 1536 |
| 832 | 0 | 2 | 9656 | 1 | 1923 | 2 | 2 | 77190 | 1537 |
| 1566 | 0 | 1 | 9600 | 0 | 1900 | 8 | 3 | 149132 | 1538 |
| 2268 | 0 | 2 | 9000 | 0 | 1890 | 8 | 3 | 188470 | 1539 |
| 2256 | 0 | 0 | 9045 | 0 | 1910 | 5 | 4 | 125495 | 1540 |
| 1470 | 283 | 2 | 10560 | 0 | 1922 | 6 | 2 | 140079 | 1541 |
| 1612 | 788 | 1 | 5830 | 0 | 1950 | 5 | 3 | 138582 | 1542 |
| 2068 | 474 | 1 | 7793 | 1 | 1922 | 7 | 3 | 181052 | 1543 |
| 765 | 188 | 1 | 5000 | 0 | 1925 | 4 | 2 | 85228 | 1544 |
| 1132 | 452 | 1 | 6000 | 0 | 1939 | 6 | 2 | 125715 | 1545 |
| 1196 | 264 | 2 | 6000 | 2 | 1940 | 6 | 3 | 144168 | 1546 |
| 1453 | 360 | 1 | 6360 | 2 | 1942 | 5 | 3 | 133006 | 1547 |
| 1416 | 300 | 1 | 6000 | 0 | 1948 | 6 | 3 | 135388 | 1548 |
| 1040 | 276 | 2 | 6240 | 0 | 1936 | 5 | 2 | 114288 | 1549 |
| 1536 | 448 | 2 | 6240 | 1 | 1930 | 5 | 4 | 136138 | 1550 |
| 1068 | 960 | 1 | 6120 | 1 | 1923 | 6 | 2 | 132763 | 1551 |
| 1962 | 0 | 2 | 8094 | 1 | 1915 | 4 | 4 | 125330 | 1552 |
| 1560 | 0 | 0 | 12900 | 0 | 1912 | 6 | 3 | 117733 | 1553 |
| 1324 | 0 | 1 | 3068 | 0 | 1920 | 6 | 3 | 116490 | 1554 |
| 1675 | 766 | 1 | 15263 | 2 | 1959 | 5 | 3 | 161310 | 1555 |
| 1224 | 0 | 1 | 10632 | 0 | 1917 | 5 | 3 | 103818 | 1556 |
| 1392 | 1026 | 0 | 9900 | 0 | 1915 | 5 | 3 | 116750 | 1557 |
| 919 | 368 | 1 | 6001 | 0 | 1940 | 6 | 3 | 116636 | 1558 |
| 1884 | 73 | 0 | 6449 | 0 | 1907 | 4 | 4 | 101289 | 1559 |
| 1680 | 736 | 2 | 6048 | 1 | 1910 | 5 | 2 | 141889 | 1560 |
| 1832 | 704 | 0 | 10773 | 0 | 1967 | 4 | 4 | 129377 | 1561 |
| 892 | 240 | 1 | 7800 | 0 | 1966 | 5 | 3 | 110150 | 1562 |
| 864 | 775 | 1 | 7832 | 0 | 1968 | 5 | 2 | 119304 | 1563 |
| 1373 | 1319 | 2 | 7424 | 2 | 1978 | 5 | 3 | 175545 | 1564 |
| 1440 | 267 | 2 | 11227 | 2 | 1968 | 5 | 4 | 151067 | 1565 |
| 1483 | 1092 | 2 | 20062 | 2 | 1977 | 7 | 1 | 227842 | 1566 |
| 756 | 0 | 2 | 9259 | 0 | 1927 | 4 | 2 | 90255 | 1567 |
| 1981 | 964 | 2 | 17082 | 1 | 1978 | 6 | 4 | 216098 | 1568 |
| 1610 | 288 | 1 | 18600 | 1 | 1938 | 3 | 4 | 109585 | 1569 |
| 1074 | 104 | 1 | 11479 | 1 | 1950 | 6 | 3 | 127768 | 1570 |
| 1531 | 192 | 1 | 9350 | 1 | 1947 | 4 | 3 | 117324 | 1571 |
| 1172 | 954 | 1 | 9525 | 0 | 1954 | 5 | 3 | 128444 | 1572 |
| 1508 | 1346 | 2 | 17485 | 2 | 2009 | 7 | 1 | 256166 | 1573 |
| 1298 | 0 | 2 | 11200 | 0 | 1964 | 5 | 3 | 128228 | 1574 |
| 1433 | 1433 | 2 | 11980 | 2 | 1987 | 7 | 1 | 235566 | 1575 |
| 1802 | 860 | 4 | 12361 | 1 | 1993 | 6 | 3 | 238638 | 1576 |
| 1222 | 24 | 2 | 7360 | 0 | 2010 | 7 | 2 | 173926 | 1577 |
| 1445 | 0 | 2 | 14235 | 0 | 1900 | 6 | 3 | 126974 | 1578 |
| 965 | 870 | 2 | 11105 | 0 | 1996 | 5 | 2 | 144554 | 1579 |
| 1692 | 353 | 2 | 9337 | 1 | 1997 | 7 | 3 | 209260 | 1580 |
| 1026 | 198 | 1 | 15240 | 0 | 1977 | 5 | 3 | 119873 | 1581 |
| 876 | 480 | 2 | 7480 | 0 | 1972 | 5 | 3 | 123092 | 1582 |
| 1978 | 1682 | 3 | 10389 | 1 | 2003 | 8 | 3 | 331077 | 1583 |
| 2098 | 0 | 2 | 9375 | 1 | 1997 | 7 | 4 | 221391 | 1584 |
| 848 | 672 | 2 | 4435 | 0 | 2003 | 6 | 1 | 151460 | 1585 |
| 640 | 0 | 1 | 8777 | 0 | 1945 | 3 | 2 | 76974 | 1586 |
| 992 | 0 | 1 | 8842 | 0 | 1954 | 5 | 3 | 106486 | 1587 |
| 1196 | 1070 | 1 | 10044 | 0 | 1968 | 5 | 3 | 136534 | 1588 |
| 1120 | 0 | 2 | 11792 | 0 | 1948 | 4 | 2 | 106329 | 1589 |
| 1096 | 528 | 1 | 6305 | 1 | 1975 | 6 | 3 | 143144 | 1590 |
| 960 | 0 | 0 | 6410 | 0 | 1958 | 4 | 3 | 89070 | 1591 |
| 1296 | 133 | 1 | 4853 | 1 | 1924 | 5 | 2 | 113085 | 1592 |
| 856 | 238 | 2 | 7890 | 1 | 1939 | 6 | 2 | 126691 | 1593 |
| 2650 | 0 | 0 | 7200 | 0 | 1967 | 4 | 6 | 143336 | 1594 |
| 1666 | 0 | 0 | 9839 | 1 | 1931 | 5 | 3 | 118305 | 1595 |
| 2133 | 426 | 1 | 10452 | 2 | 1941 | 7 | 4 | 200928 | 1596 |
| 2177 | 375 | 2 | 15600 | 0 | 1950 | 5 | 5 | 166755 | 1597 |
| 1652 | 343 | 2 | 19645 | 0 | 1994 | 7 | 3 | 203644 | 1598 |
| 1034 | 747 | 2 | 3907 | 1 | 1989 | 8 | 1 | 199482 | 1599 |
| 1191 | 76 | 2 | 3907 | 1 | 1989 | 8 | 2 | 188242 | 1600 |
| 540 | 480 | 1 | 8154 | 0 | 1941 | 2 | 1 | 71729 | 1601 |
| 1107 | 308 | 1 | 9140 | 0 | 1921 | 6 | 2 | 117985 | 1602 |
| 952 | 0 | 1 | 8712 | 0 | 1896 | 4 | 3 | 81569 | 1603 |
| 1646 | 1373 | 2 | 3811 | 1 | 2004 | 8 | 2 | 266778 | 1604 |
| 1916 | 615 | 3 | 11050 | 1 | 1998 | 8 | 3 | 276765 | 1605 |
| 1285 | 679 | 2 | 9620 | 1 | 1977 | 6 | 3 | 167510 | 1606 |
| 2048 | 0 | 2 | 12760 | 0 | 1976 | 6 | 5 | 179516 | 1607 |
| 1346 | 78 | 3 | 11896 | 1 | 2008 | 7 | 3 | 202876 | 1608 |
| 1214 | 0 | 2 | 9803 | 0 | 2009 | 7 | 2 | 173917 | 1609 |
| 1444 | 0 | 2 | 9802 | 0 | 2006 | 5 | 3 | 148177 | 1610 |
| 1264 | 42 | 2 | 15300 | 1 | 1965 | 5 | 2 | 136243 | 1611 |
| 1430 | 0 | 2 | 10114 | 0 | 2004 | 5 | 3 | 146993 | 1612 |
| 1344 | 0 | 2 | 11875 | 1 | 1999 | 5 | 3 | 148529 | 1613 |
| 945 | 915 | 1 | 2394 | 1 | 1973 | 5 | 2 | 129041 | 1614 |
| 1092 | 176 | 0 | 1476 | 0 | 1970 | 4 | 3 | 96121 | 1615 |
| 1092 | 0 | 0 | 1900 | 0 | 1970 | 4 | 3 | 93886 | 1616 |
| 1092 | 294 | 1 | 1890 | 0 | 1972 | 4 | 3 | 105208 | 1617 |
| 874 | 469 | 1 | 6953 | 0 | 1971 | 5 | 3 | 114368 | 1618 |
| 833 | 207 | 2 | 12887 | 0 | 1984 | 5 | 2 | 123707 | 1619 |
| 2432 | 0 | 2 | 7700 | 0 | 1985 | 5 | 4 | 182163 | 1620 |
| 1274 | 458 | 2 | 10475 | 0 | 1991 | 5 | 3 | 145406 | 1621 |
| 1479 | 476 | 1 | 10544 | 0 | 1969 | 5 | 5 | 134592 | 1622 |
| 1803 | 1341 | 2 | 9892 | 2 | 1994 | 8 | 3 | 285646 | 1623 |
| 1797 | 944 | 2 | 12961 | 1 | 1993 | 6 | 3 | 211317 | 1624 |
| 882 | 564 | 1 | 13008 | 0 | 1956 | 6 | 2 | 127470 | 1625 |
| 1434 | 844 | 2 | 10200 | 1 | 1974 | 6 | 4 | 176529 | 1626 |
| 1608 | 847 | 2 | 10179 | 1 | 1997 | 6 | 3 | 197985 | 1627 |
| 2283 | 850 | 3 | 11792 | 1 | 2003 | 8 | 4 | 319680 | 1628 |
| 1628 | 284 | 2 | 8400 | 1 | 1996 | 7 | 3 | 202413 | 1629 |
| 2522 | 1965 | 2 | 7296 | 1 | 2004 | 8 | 1 | 376801 | 1630 |
| 1478 | 341 | 2 | 7380 | 0 | 1998 | 8 | 2 | 210301 | 1631 |
| 1734 | 741 | 2 | 8013 | 0 | 1995 | 8 | 2 | 237620 | 1632 |
| 1382 | 189 | 2 | 8923 | 1 | 1998 | 7 | 3 | 187814 | 1633 |
| 1636 | 476 | 2 | 7500 | 1 | 1998 | 6 | 3 | 188109 | 1634 |
| 1516 | 600 | 2 | 8803 | 1 | 1994 | 6 | 3 | 184062 | 1635 |
| 1190 | 0 | 2 | 7250 | 1 | 1993 | 6 | 3 | 153228 | 1636 |
| 1934 | 400 | 2 | 11900 | 1 | 1977 | 5 | 3 | 174942 | 1637 |
| 2050 | 0 | 2 | 13250 | 1 | 1978 | 7 | 4 | 210684 | 1638 |
| 1671 | 363 | 2 | 10928 | 1 | 1978 | 6 | 3 | 179541 | 1639 |
| 2673 | 602 | 2 | 12388 | 1 | 1980 | 7 | 4 | 273414 | 1640 |
| 1707 | 832 | 2 | 11088 | 1 | 1978 | 6 | 3 | 193913 | 1641 |
| 1884 | 622 | 2 | 7000 | 1 | 2003 | 7 | 3 | 231077 | 1642 |
| 1874 | 0 | 2 | 7500 | 1 | 2000 | 8 | 3 | 232900 | 1643 |
| 1811 | 225 | 2 | 8470 | 1 | 2002 | 8 | 3 | 238274 | 1644 |
| 1621 | 1333 | 2 | 9373 | 2 | 1975 | 5 | 3 | 188198 | 1645 |
| 1116 | 888 | 2 | 10140 | 1 | 1974 | 6 | 3 | 163646 | 1646 |
| 1193 | 636 | 2 | 11050 | 1 | 1975 | 7 | 3 | 180167 | 1647 |
| 1180 | 0 | 2 | 7830 | 0 | 1970 | 5 | 2 | 125438 | 1648 |
| 1050 | 500 | 1 | 8510 | 0 | 1971 | 5 | 3 | 121254 | 1649 |
| 864 | 726 | 2 | 7038 | 0 | 1970 | 4 | 3 | 113627 | 1650 |
| 864 | 240 | 2 | 9000 | 0 | 1971 | 4 | 3 | 107038 | 1651 |
| 987 | 254 | 1 | 1680 | 0 | 1973 | 6 | 2 | 126378 | 1652 |
| 987 | 110 | 1 | 1680 | 0 | 1972 | 6 | 2 | 123504 | 1653 |
| 1548 | 306 | 2 | 2308 | 1 | 1976 | 6 | 3 | 166368 | 1654 |
| 1055 | 435 | 2 | 2280 | 1 | 1975 | 7 | 2 | 164725 | 1655 |
| 1456 | 389 | 2 | 2349 | 1 | 1977 | 6 | 3 | 164538 | 1656 |
| 1548 | 320 | 2 | 2364 | 1 | 1978 | 6 | 3 | 167595 | 1657 |
| 1456 | 279 | 2 | 2364 | 1 | 1978 | 6 | 3 | 162421 | 1658 |
| 836 | 536 | 1 | 2104 | 0 | 1976 | 7 | 2 | 141370 | 1659 |
| 1120 | 644 | 2 | 10710 | 1 | 1966 | 5 | 3 | 139845 | 1660 |
| 2772 | 1360 | 3 | 14257 | 3 | 2007 | 9 | 4 | 483747 | 1661 |
| 2690 | 986 | 3 | 12350 | 1 | 2009 | 9 | 3 | 415050 | 1662 |
| 2020 | 1232 | 3 | 12350 | 1 | 2008 | 9 | 3 | 355888 | 1663 |
| 2674 | 2288 | 3 | 13693 | 2 | 2007 | 10 | 2 | 578548 | 1664 |
| 1736 | 0 | 3 | 11578 | 1 | 2008 | 9 | 3 | 275492 | 1665 |
| 1782 | 1531 | 3 | 16870 | 2 | 2004 | 8 | 3 | 327699 | 1666 |
| 2520 | 1230 | 3 | 23303 | 1 | 2007 | 8 | 5 | 375893 | 1667 |
| 1743 | 1015 | 3 | 10367 | 1 | 2008 | 9 | 3 | 317448 | 1668 |
| 1531 | 1037 | 3 | 10872 | 1 | 2006 | 9 | 2 | 301136 | 1669 |
| 1808 | 1142 | 3 | 13514 | 1 | 2008 | 9 | 3 | 332578 | 1670 |
| 1760 | 1262 | 2 | 12878 | 1 | 2003 | 7 | 3 | 249299 | 1671 |
| 2452 | 1972 | 3 | 15274 | 1 | 2003 | 9 | 3 | 444205 | 1672 |
| 2400 | 0 | 3 | 13262 | 1 | 2003 | 8 | 4 | 294197 | 1673 |
| 1606 | 0 | 3 | 9658 | 1 | 2006 | 8 | 3 | 236507 | 1674 |
| 1358 | 836 | 2 | 6904 | 1 | 2005 | 6 | 2 | 187442 | 1675 |
| 1306 | 881 | 2 | 5122 | 1 | 2005 | 6 | 1 | 186037 | 1676 |
| 1358 | 876 | 2 | 10307 | 1 | 2007 | 7 | 2 | 212846 | 1677 |
| 2492 | 2146 | 3 | 14836 | 1 | 2004 | 10 | 2 | 515204 | 1678 |
| 2200 | 1557 | 3 | 15262 | 1 | 2003 | 8 | 3 | 351623 | 1679 |
| 1884 | 800 | 2 | 7390 | 1 | 2008 | 9 | 2 | 298418 | 1680 |
| 1456 | 0 | 2 | 6472 | 1 | 2008 | 9 | 2 | 235848 | 1681 |
| 1712 | 1196 | 3 | 16770 | 1 | 2002 | 8 | 3 | 292459 | 1682 |
| 1405 | 0 | 2 | 3480 | 1 | 2003 | 7 | 2 | 184253 | 1683 |
| 1456 | 0 | 2 | 10928 | 1 | 2005 | 7 | 3 | 191336 | 1684 |
| 1490 | 0 | 2 | 8918 | 1 | 2005 | 6 | 3 | 172755 | 1685 |
| 1220 | 16 | 2 | 3182 | 1 | 2005 | 7 | 2 | 176158 | 1686 |
| 1374 | 0 | 2 | 9434 | 1 | 2004 | 7 | 3 | 185616 | 1687 |
| 1630 | 0 | 2 | 7984 | 1 | 2004 | 7 | 3 | 198330 | 1688 |
| 1594 | 0 | 2 | 10125 | 1 | 2004 | 7 | 3 | 197766 | 1689 |
| 1489 | 652 | 2 | 8965 | 1 | 2003 | 7 | 3 | 209322 | 1690 |
| 1342 | 494 | 2 | 8174 | 1 | 2003 | 7 | 3 | 195980 | 1691 |
| 2004 | 651 | 3 | 12891 | 1 | 2002 | 8 | 4 | 287931 | 1692 |
| 1374 | 241 | 2 | 9734 | 0 | 2004 | 7 | 3 | 184472 | 1693 |
| 1514 | 683 | 2 | 8433 | 1 | 2000 | 6 | 3 | 188817 | 1694 |
| 1430 | 0 | 2 | 7750 | 1 | 1999 | 7 | 3 | 185057 | 1695 |
| 2312 | 913 | 3 | 15896 | 1 | 1999 | 7 | 4 | 293761 | 1696 |
| 1430 | 0 | 2 | 7848 | 1 | 1999 | 7 | 3 | 185118 | 1697 |
| 2687 | 1173 | 3 | 12720 | 2 | 2000 | 8 | 4 | 388374 | 1698 |
| 2063 | 236 | 3 | 10750 | 2 | 1994 | 8 | 3 | 281536 | 1699 |
| 2061 | 816 | 2 | 9085 | 1 | 1995 | 7 | 3 | 246079 | 1700 |
| 2232 | 624 | 2 | 11692 | 1 | 1993 | 8 | 3 | 279876 | 1701 |
| 1696 | 0 | 3 | 11194 | 0 | 2008 | 8 | 3 | 235082 | 1702 |
| 1658 | 0 | 3 | 10206 | 1 | 2008 | 8 | 3 | 241634 | 1703 |
| 1702 | 1294 | 3 | 10130 | 1 | 2007 | 8 | 3 | 293009 | 1704 |
| 1432 | 379 | 2 | 9139 | 1 | 2006 | 8 | 3 | 221980 | 1705 |
| 2490 | 2158 | 3 | 11128 | 2 | 2005 | 9 | 2 | 479319 | 1706 |
| 1436 | 0 | 2 | 7993 | 0 | 2008 | 7 | 3 | 182199 | 1707 |
| 1402 | 0 | 2 | 8640 | 0 | 2008 | 7 | 3 | 180877 | 1708 |
| 1530 | 0 | 3 | 12606 | 1 | 2007 | 9 | 3 | 260394 | 1709 |
| 1448 | 24 | 2 | 7500 | 1 | 2006 | 8 | 2 | 212243 | 1710 |
| 1795 | 682 | 3 | 10603 | 1 | 2006 | 8 | 3 | 275415 | 1711 |
| 1836 | 0 | 2 | 8125 | 1 | 2008 | 8 | 3 | 235769 | 1712 |
| 1662 | 1430 | 3 | 10625 | 1 | 2006 | 7 | 3 | 265747 | 1713 |
| 1553 | 771 | 2 | 8736 | 0 | 2003 | 7 | 3 | 207764 | 1714 |
| 1653 | 410 | 2 | 8127 | 0 | 2003 | 7 | 3 | 202548 | 1715 |
| 1218 | 0 | 2 | 9605 | 0 | 2007 | 7 | 3 | 171976 | 1716 |
| 1141 | 54 | 2 | 7500 | 0 | 2006 | 7 | 3 | 168007 | 1717 |
| 1158 | 0 | 0 | 7500 | 0 | 2004 | 6 | 3 | 131223 | 1718 |
| 1812 | 0 | 2 | 10628 | 0 | 2004 | 7 | 3 | 201938 | 1719 |
| 1512 | 516 | 3 | 10141 | 0 | 2004 | 8 | 3 | 237010 | 1720 |
| 1114 | 0 | 2 | 13072 | 0 | 2004 | 7 | 3 | 167719 | 1721 |
| 1114 | 0 | 0 | 13072 | 0 | 2004 | 5 | 3 | 118914 | 1722 |
| 1114 | 836 | 2 | 12450 | 0 | 2003 | 5 | 3 | 152373 | 1723 |
| 1450 | 0 | 3 | 7328 | 0 | 2008 | 7 | 2 | 196431 | 1724 |
| 2122 | 637 | 2 | 11492 | 1 | 1996 | 7 | 4 | 245024 | 1725 |
| 1730 | 52 | 2 | 7703 | 0 | 1992 | 6 | 3 | 171887 | 1726 |
| 1332 | 0 | 2 | 7175 | 0 | 1990 | 6 | 2 | 152703 | 1727 |
| 1540 | 36 | 2 | 9109 | 0 | 1994 | 7 | 3 | 182467 | 1728 |
| 1400 | 331 | 2 | 10274 | 0 | 1986 | 6 | 3 | 162032 | 1729 |
| 1882 | 0 | 2 | 8250 | 2 | 1981 | 6 | 4 | 187021 | 1730 |
| 980 | 68 | 2 | 9750 | 0 | 1962 | 5 | 3 | 117345 | 1731 |
| 864 | 660 | 2 | 8499 | 0 | 1961 | 5 | 3 | 122737 | 1732 |
| 864 | 864 | 1 | 9079 | 0 | 1961 | 5 | 2 | 119144 | 1733 |
| 1020 | 544 | 1 | 9316 | 0 | 1965 | 5 | 3 | 119457 | 1734 |
| 912 | 624 | 1 | 7791 | 0 | 1963 | 5 | 3 | 116051 | 1735 |
| 912 | 140 | 1 | 7150 | 0 | 1962 | 5 | 3 | 107846 | 1736 |
| 2014 | 1733 | 3 | 15676 | 2 | 1980 | 8 | 2 | 338840 | 1737 |
| 1755 | 601 | 2 | 11949 | 1 | 1991 | 7 | 3 | 219075 | 1738 |
| 3005 | 0 | 3 | 2880 | 1 | 2004 | 7 | 3 | 305447 | 1739 |
| 1726 | 0 | 2 | 3830 | 1 | 2008 | 6 | 2 | 183952 | 1740 |
| 1256 | 962 | 2 | 4217 | 1 | 2008 | 6 | 1 | 186473 | 1741 |
| 1512 | 507 | 2 | 2998 | 0 | 2000 | 6 | 2 | 174561 | 1742 |
| 1452 | 549 | 2 | 3768 | 0 | 1999 | 7 | 3 | 190556 | 1743 |
| 1694 | 1252 | 2 | 14694 | 1 | 1977 | 8 | 2 | 256993 | 1744 |
| 1740 | 121 | 2 | 15417 | 0 | 1981 | 7 | 2 | 194040 | 1745 |
| 2499 | 0 | 2 | 9600 | 1 | 1976 | 8 | 4 | 260490 | 1746 |
| 2067 | 560 | 2 | 12732 | 2 | 1974 | 7 | 3 | 237507 | 1747 |
| 2640 | 0 | 2 | 10400 | 1 | 1967 | 6 | 5 | 213754 | 1748 |
| 1336 | 553 | 2 | 9600 | 1 | 1969 | 5 | 3 | 147184 | 1749 |
| 1216 | 955 | 1 | 9000 | 0 | 1969 | 6 | 3 | 149878 | 1750 |
| 2288 | 432 | 2 | 13774 | 2 | 1977 | 7 | 4 | 249182 | 1751 |
| 864 | 648 | 1 | 7130 | 0 | 1967 | 5 | 2 | 116599 | 1752 |
| 1568 | 0 | 2 | 9600 | 0 | 1967 | 5 | 3 | 138547 | 1753 |
| 2061 | 698 | 2 | 9600 | 1 | 1974 | 7 | 4 | 228102 | 1754 |
| 1320 | 962 | 2 | 16500 | 1 | 1971 | 6 | 3 | 177384 | 1755 |
| 894 | 734 | 2 | 7436 | 1 | 1960 | 4 | 2 | 117410 | 1756 |
| 864 | 403 | 1 | 8125 | 0 | 1959 | 5 | 3 | 109962 | 1757 |
| 1362 | 775 | 3 | 9450 | 1 | 1957 | 4 | 3 | 142731 | 1758 |
| 1728 | 625 | 2 | 13495 | 1 | 1956 | 5 | 3 | 162406 | 1759 |
| 1313 | 310 | 2 | 9350 | 1 | 1961 | 5 | 3 | 138284 | 1760 |
| 1292 | 998 | 2 | 10500 | 2 | 1964 | 5 | 3 | 159802 | 1761 |
| 2140 | 388 | 2 | 8970 | 1 | 1965 | 5 | 4 | 176376 | 1762 |
| 1576 | 568 | 2 | 11475 | 1 | 1961 | 6 | 4 | 171470 | 1763 |
| 960 | 100 | 1 | 9768 | 0 | 1955 | 5 | 2 | 108362 | 1764 |
| 1691 | 1173 | 2 | 9900 | 0 | 1967 | 6 | 2 | 189427 | 1765 |
| 1453 | 1312 | 2 | 10573 | 1 | 1961 | 6 | 3 | 184782 | 1766 |
| 1567 | 1387 | 2 | 14695 | 2 | 1966 | 6 | 2 | 207682 | 1767 |
| 1144 | 856 | 1 | 8760 | 0 | 1956 | 5 | 3 | 126022 | 1768 |
| 1329 | 544 | 2 | 12285 | 2 | 1960 | 7 | 3 | 185908 | 1769 |
| 988 | 708 | 1 | 9240 | 0 | 1959 | 6 | 3 | 132478 | 1770 |
| 1202 | 435 | 1 | 8750 | 0 | 1956 | 5 | 3 | 120646 | 1771 |
| 1382 | 172 | 1 | 8750 | 0 | 1955 | 5 | 3 | 121873 | 1772 |
| 1200 | 155 | 1 | 10400 | 2 | 1956 | 4 | 3 | 113969 | 1773 |
| 1866 | 0 | 2 | 9482 | 0 | 1958 | 5 | 4 | 146026 | 1774 |
| 1062 | 490 | 1 | 8128 | 0 | 1954 | 6 | 3 | 128948 | 1775 |
| 1112 | 308 | 2 | 13070 | 0 | 1951 | 5 | 2 | 124573 | 1776 |
| 793 | 700 | 1 | 8480 | 0 | 1945 | 5 | 2 | 109284 | 1777 |
| 1031 | 931 | 1 | 7626 | 0 | 1952 | 5 | 2 | 122493 | 1778 |
| 1210 | 0 | 1 | 9533 | 0 | 1953 | 5 | 2 | 113837 | 1779 |
| 1527 | 699 | 2 | 11419 | 1 | 1948 | 7 | 3 | 186216 | 1780 |
| 1200 | 390 | 1 | 9600 | 0 | 1950 | 5 | 3 | 118301 | 1781 |
| 792 | 0 | 1 | 5470 | 0 | 1958 | 3 | 2 | 82128 | 1782 |
| 1352 | 0 | 2 | 10800 | 0 | 1939 | 5 | 4 | 121057 | 1783 |
| 1039 | 0 | 1 | 8146 | 0 | 1900 | 4 | 2 | 84823 | 1784 |
| 1078 | 0 | 1 | 10230 | 0 | 1925 | 5 | 3 | 101643 | 1785 |
| 2377 | 0 | 2 | 10410 | 1 | 1915 | 4 | 3 | 142654 | 1786 |
| 1690 | 0 | 2 | 7200 | 0 | 1910 | 7 | 4 | 150326 | 1787 |
| 599 | 0 | 0 | 5400 | 0 | 1940 | 2 | 2 | 62547 | 1788 |
| 846 | 0 | 2 | 10800 | 0 | 1920 | 5 | 2 | 101448 | 1789 |
| 725 | 0 | 1 | 10800 | 0 | 1890 | 3 | 1 | 69265 | 1790 |
| 2544 | 0 | 3 | 9671 | 0 | 1969 | 6 | 6 | 212752 | 1791 |
| 1380 | 384 | 1 | 10143 | 0 | 1963 | 6 | 3 | 142983 | 1792 |
| 1040 | 872 | 2 | 11500 | 1 | 1967 | 6 | 3 | 157709 | 1793 |
| 951 | 745 | 2 | 8010 | 0 | 1958 | 6 | 2 | 140926 | 1794 |
| 1105 | 546 | 1 | 10454 | 0 | 1957 | 6 | 3 | 133596 | 1795 |
| 1142 | 0 | 1 | 9000 | 1 | 1958 | 6 | 2 | 130749 | 1796 |
| 1133 | 621 | 2 | 8064 | 0 | 1950 | 6 | 3 | 141766 | 1797 |
| 1041 | 0 | 1 | 7350 | 0 | 1958 | 5 | 3 | 108527 | 1798 |
| 732 | 630 | 1 | 7200 | 0 | 1952 | 5 | 2 | 107871 | 1799 |
| 1183 | 433 | 1 | 8000 | 0 | 1959 | 5 | 3 | 120610 | 1800 |
| 1461 | 0 | 1 | 10800 | 0 | 1949 | 4 | 4 | 107821 | 1801 |
| 1495 | 120 | 2 | 8064 | 0 | 1948 | 6 | 3 | 145259 | 1802 |
| 1806 | 0 | 2 | 7570 | 0 | 1964 | 6 | 4 | 160960 | 1803 |
| 941 | 941 | 2 | 8604 | 0 | 1978 | 5 | 2 | 137291 | 1804 |
| 1045 | 826 | 1 | 7936 | 1 | 1963 | 6 | 3 | 143496 | 1805 |
| 1378 | 0 | 1 | 4080 | 0 | 1935 | 6 | 3 | 123348 | 1806 |
| 1944 | 633 | 2 | 10307 | 0 | 1910 | 6 | 4 | 160541 | 1807 |
| 1306 | 0 | 2 | 15660 | 0 | 1910 | 5 | 3 | 113425 | 1808 |
| 1464 | 0 | 0 | 9900 | 0 | 1910 | 5 | 3 | 101664 | 1809 |
| 1558 | 421 | 2 | 6406 | 1 | 1939 | 5 | 3 | 140653 | 1810 |
| 1701 | 0 | 0 | 7627 | 0 | 1920 | 4 | 4 | 98929 | 1811 |
| 1447 | 0 | 0 | 10134 | 0 | 1910 | 5 | 3 | 101264 | 1812 |
| 1328 | 384 | 1 | 6000 | 0 | 1950 | 5 | 3 | 121014 | 1813 |
| 861 | 0 | 2 | 7404 | 0 | 1920 | 4 | 2 | 90693 | 1814 |
| 612 | 0 | 1 | 5925 | 0 | 1940 | 2 | 1 | 67682 | 1815 |
| 792 | 0 | 1 | 8520 | 0 | 1923 | 5 | 2 | 93471 | 1816 |
| 1510 | 0 | 2 | 9600 | 0 | 1910 | 4 | 3 | 105918 | 1817 |
| 2007 | 0 | 1 | 8400 | 0 | 1900 | 6 | 3 | 136116 | 1818 |
| 1288 | 0 | 1 | 3600 | 1 | 1917 | 6 | 3 | 119481 | 1819 |
| 816 | 0 | 0 | 3300 | 1 | 1910 | 4 | 2 | 78463 | 1820 |
| 1480 | 0 | 1 | 5400 | 0 | 1920 | 6 | 3 | 122599 | 1821 |
| 1521 | 0 | 3 | 9720 | 0 | 1910 | 6 | 4 | 139276 | 1822 |
| 797 | 0 | 0 | 9392 | 0 | 1900 | 3 | 2 | 67059 | 1823 |
| 1432 | 0 | 1 | 6615 | 1 | 1923 | 6 | 3 | 127581 | 1824 |
| 1654 | 0 | 1 | 4960 | 1 | 1930 | 5 | 3 | 123730 | 1825 |
| 1142 | 220 | 1 | 6000 | 0 | 1924 | 5 | 3 | 104973 | 1826 |
| 995 | 0 | 1 | 6120 | 0 | 1925 | 5 | 2 | 98611 | 1827 |
| 1582 | 273 | 1 | 6120 | 1 | 1938 | 5 | 3 | 129203 | 1828 |
| 1072 | 134 | 5 | 8635 | 0 | 1925 | 5 | 2 | 135391 | 1829 |
| 1768 | 0 | 2 | 8094 | 0 | 1915 | 6 | 3 | 141458 | 1830 |
| 1944 | 0 | 1 | 9928 | 0 | 1915 | 7 | 3 | 155219 | 1831 |
| 2128 | 0 | 0 | 3000 | 0 | 1922 | 5 | 4 | 122436 | 1832 |
| 1930 | 522 | 1 | 6876 | 0 | 1927 | 6 | 4 | 152082 | 1833 |
| 1427 | 0 | 1 | 5775 | 0 | 1915 | 6 | 3 | 119403 | 1834 |
| 1864 | 169 | 0 | 5852 | 0 | 1902 | 7 | 6 | 136017 | 1835 |
| 1666 | 0 | 1 | 5160 | 0 | 1927 | 6 | 3 | 131353 | 1836 |
| 892 | 749 | 0 | 5160 | 0 | 1923 | 4 | 1 | 89559 | 1837 |
| 1403 | 276 | 1 | 10320 | 0 | 1915 | 6 | 3 | 125228 | 1838 |
| 704 | 0 | 1 | 4280 | 0 | 1946 | 4 | 2 | 85944 | 1839 |
| 1200 | 1200 | 0 | 10800 | 0 | 1987 | 5 | 3 | 137108 | 1840 |
| 1152 | 1152 | 1 | 10547 | 0 | 1978 | 5 | 2 | 141180 | 1841 |
| 1112 | 0 | 1 | 9780 | 0 | 1934 | 5 | 4 | 104189 | 1842 |
| 1052 | 527 | 1 | 11625 | 1 | 1967 | 5 | 3 | 126933 | 1843 |
| 1034 | 456 | 2 | 8014 | 1 | 1978 | 6 | 3 | 150951 | 1844 |
| 1774 | 0 | 1 | 15400 | 1 | 1961 | 5 | 4 | 142601 | 1845 |
| 1138 | 588 | 2 | 15312 | 1 | 1960 | 6 | 3 | 154830 | 1846 |
| 2071 | 0 | 1 | 15584 | 1 | 1956 | 5 | 4 | 152964 | 1847 |
| 660 | 0 | 0 | 9000 | 0 | 1947 | 2 | 2 | 65562 | 1848 |
| 1383 | 0 | 2 | 15635 | 0 | 1954 | 4 | 2 | 117677 | 1849 |
| 1073 | 257 | 1 | 9571 | 0 | 1956 | 5 | 2 | 114553 | 1850 |
| 1639 | 342 | 1 | 9350 | 1 | 1946 | 6 | 3 | 151924 | 1851 |
| 1089 | 173 | 1 | 7440 | 1 | 1954 | 5 | 3 | 116295 | 1852 |
| 1049 | 552 | 1 | 4235 | 0 | 1984 | 5 | 2 | 125317 | 1853 |
| 1061 | 460 | 2 | 10778 | 0 | 1990 | 7 | 1 | 171032 | 1854 |
| 1338 | 70 | 2 | 19255 | 1 | 1983 | 6 | 2 | 164622 | 1855 |
| 1879 | 474 | 2 | 10560 | 1 | 1993 | 7 | 3 | 222825 | 1856 |
| 2016 | 0 | 2 | 26400 | 1 | 1880 | 5 | 4 | 137190 | 1857 |
| 2228 | 0 | 2 | 7018 | 0 | 1979 | 5 | 6 | 166910 | 1858 |
| 1535 | 0 | 2 | 7018 | 0 | 1979 | 5 | 4 | 139490 | 1859 |
| 1229 | 1094 | 2 | 7040 | 2 | 1979 | 5 | 2 | 164649 | 1860 |
| 1513 | 0 | 2 | 7007 | 0 | 1979 | 5 | 4 | 138635 | 1861 |
| 2787 | 820 | 4 | 11855 | 2 | 2000 | 7 | 6 | 359962 | 1862 |
| 2787 | 820 | 4 | 7939 | 2 | 2000 | 7 | 6 | 355284 | 1863 |
| 2787 | 820 | 4 | 7976 | 2 | 2000 | 7 | 6 | 355328 | 1864 |
| 1680 | 1021 | 3 | 10933 | 1 | 2009 | 9 | 1 | 317708 | 1865 |
| 1720 | 1104 | 3 | 10816 | 1 | 2008 | 9 | 3 | 319910 | 1866 |
| 1468 | 0 | 3 | 9178 | 1 | 2008 | 8 | 3 | 228430 | 1867 |
| 1838 | 1359 | 2 | 11422 | 2 | 2007 | 8 | 3 | 300602 | 1868 |
| 1290 | 902 | 2 | 6762 | 1 | 2007 | 7 | 2 | 207168 | 1869 |
| 1254 | 872 | 3 | 10324 | 0 | 2008 | 8 | 2 | 236127 | 1870 |
| 1498 | 24 | 3 | 11645 | 1 | 2005 | 8 | 3 | 231235 | 1871 |
| 1422 | 0 | 2 | 11646 | 1 | 2005 | 6 | 3 | 171075 | 1872 |
| 1759 | 800 | 2 | 16698 | 1 | 1992 | 7 | 3 | 229793 | 1873 |
| 990 | 755 | 1 | 9757 | 0 | 1994 | 5 | 3 | 131772 | 1874 |
| 1463 | 950 | 2 | 14753 | 0 | 1998 | 7 | 3 | 209335 | 1875 |
| 1772 | 606 | 2 | 8750 | 1 | 1998 | 6 | 3 | 199815 | 1876 |
| 1444 | 1259 | 2 | 10739 | 0 | 2002 | 7 | 3 | 216892 | 1877 |
| 1492 | 24 | 2 | 11166 | 1 | 2001 | 7 | 3 | 192072 | 1878 |
| 907 | 625 | 1 | 16269 | 0 | 1978 | 5 | 3 | 123956 | 1879 |
| 914 | 710 | 2 | 6950 | 0 | 1979 | 5 | 2 | 131490 | 1880 |
| 1611 | 1234 | 3 | 11664 | 0 | 2002 | 7 | 3 | 242833 | 1881 |
| 2184 | 0 | 2 | 12334 | 1 | 2003 | 8 | 4 | 258298 | 1882 |
| 1725 | 0 | 2 | 8749 | 0 | 2002 | 7 | 3 | 194873 | 1883 |
| 1870 | 0 | 2 | 11250 | 0 | 2001 | 7 | 3 | 204053 | 1884 |
| 1513 | 1246 | 2 | 15750 | 1 | 1999 | 8 | 2 | 259411 | 1885 |
| 1828 | 1360 | 2 | 12782 | 1 | 2002 | 8 | 3 | 285262 | 1886 |
| 1417 | 1111 | 2 | 8750 | 1 | 1997 | 7 | 3 | 215440 | 1887 |
| 1602 | 1478 | 3 | 10200 | 1 | 2007 | 8 | 3 | 292582 | 1888 |
| 1396 | 0 | 2 | 11069 | 1 | 2007 | 6 | 3 | 170397 | 1889 |
| 1149 | 399 | 1 | 10682 | 0 | 1960 | 4 | 3 | 108305 | 1890 |
| 1072 | 547 | 2 | 3675 | 0 | 2005 | 6 | 2 | 157742 | 1891 |
| 876 | 332 | 1 | 6410 | 0 | 1959 | 4 | 3 | 97787 | 1892 |
| 1368 | 1078 | 1 | 11767 | 0 | 1950 | 5 | 3 | 137639 | 1893 |
| 1678 | 0 | 0 | 10926 | 0 | 1959 | 5 | 6 | 120529 | 1894 |
| 1560 | 546 | 1 | 11767 | 1 | 1956 | 5 | 2 | 143440 | 1895 |
| 1298 | 626 | 1 | 8212 | 2 | 1941 | 5 | 3 | 132774 | 1896 |
| 1268 | 832 | 1 | 6300 | 2 | 1938 | 5 | 3 | 133668 | 1897 |
| 1242 | 0 | 1 | 5707 | 1 | 1935 | 6 | 3 | 124464 | 1898 |
| 1232 | 0 | 2 | 8574 | 1 | 1916 | 6 | 3 | 127573 | 1899 |
| 1228 | 0 | 1 | 7155 | 1 | 1918 | 7 | 3 | 132403 | 1900 |
| 1567 | 728 | 2 | 13680 | 2 | 1940 | 5 | 2 | 158701 | 1901 |
| 1273 | 793 | 1 | 14680 | 0 | 1960 | 5 | 2 | 134285 | 1902 |
| 2480 | 246 | 2 | 8145 | 2 | 1940 | 7 | 5 | 226799 | 1903 |
| 1112 | 154 | 1 | 9100 | 1 | 1954 | 5 | 2 | 118139 | 1904 |
| 1561 | 65 | 2 | 13339 | 1 | 1960 | 6 | 3 | 160626 | 1905 |
| 1523 | 312 | 1 | 15600 | 1 | 1949 | 5 | 3 | 135730 | 1906 |
| 1906 | 784 | 2 | 17500 | 2 | 1954 | 6 | 3 | 203669 | 1907 |
| 1032 | 0 | 2 | 1733 | 1 | 1980 | 6 | 2 | 140115 | 1908 |
| 1229 | 471 | 2 | 1488 | 1 | 1980 | 6 | 2 | 158081 | 1909 |
| 1229 | 0 | 2 | 1612 | 1 | 1980 | 6 | 2 | 147934 | 1910 |
| 1982 | 454 | 2 | 13607 | 1 | 1986 | 6 | 3 | 204246 | 1911 |
| 2365 | 803 | 2 | 17597 | 2 | 1971 | 7 | 3 | 269313 | 1912 |
| 2168 | 0 | 2 | 8660 | 0 | 1900 | 5 | 5 | 135405 | 1913 |
| 572 | 0 | 1 | 10200 | 0 | 1925 | 4 | 2 | 80034 | 1914 |
| 1648 | 1476 | 2 | 3843 | 1 | 2007 | 8 | 2 | 272992 | 1915 |
| 810 | 0 | 1 | 21780 | 0 | 1910 | 2 | 1 | 69763 | 1916 |
| 2052 | 445 | 3 | 10125 | 1 | 2000 | 8 | 3 | 281162 | 1917 |
| 926 | 767 | 1 | 9750 | 1 | 1977 | 6 | 2 | 144560 | 1918 |
| 1287 | 841 | 2 | 9360 | 2 | 1977 | 6 | 2 | 179742 | 1919 |
| 1595 | 55 | 2 | 11070 | 0 | 1991 | 5 | 2 | 151416 | 1920 |
| 2036 | 1758 | 3 | 13438 | 1 | 2008 | 9 | 3 | 386543 | 1921 |
| 1641 | 1115 | 3 | 14463 | 0 | 2008 | 9 | 3 | 304448 | 1922 |
| 2237 | 462 | 2 | 9839 | 1 | 1980 | 6 | 3 | 213397 | 1923 |
| 1479 | 904 | 2 | 14419 | 1 | 1987 | 7 | 3 | 211370 | 1924 |
| 2014 | 0 | 2 | 9157 | 0 | 2003 | 7 | 3 | 211993 | 1925 |
| 1978 | 1640 | 3 | 12633 | 1 | 2007 | 9 | 2 | 374513 | 1926 |
| 1008 | 532 | 1 | 12518 | 0 | 1968 | 5 | 3 | 121071 | 1927 |
| 1404 | 594 | 2 | 13383 | 1 | 1969 | 5 | 3 | 152782 | 1928 |
| 796 | 720 | 1 | 7689 | 0 | 1972 | 5 | 2 | 117316 | 1929 |
| 1091 | 114 | 1 | 7706 | 0 | 1993 | 6 | 2 | 137032 | 1930 |
| 883 | 718 | 2 | 7669 | 1 | 1992 | 5 | 2 | 141013 | 1931 |
| 1287 | 330 | 2 | 10429 | 0 | 1992 | 5 | 3 | 143658 | 1932 |
| 1632 | 496 | 2 | 10457 | 1 | 1969 | 5 | 4 | 157933 | 1933 |
| 1604 | 706 | 2 | 8702 | 1 | 1997 | 6 | 3 | 192898 | 1934 |
| 1470 | 476 | 2 | 8139 | 1 | 1995 | 6 | 3 | 178626 | 1935 |
| 1604 | 851 | 2 | 9535 | 0 | 1998 | 6 | 3 | 189946 | 1936 |
| 1636 | 138 | 2 | 15038 | 1 | 1996 | 6 | 3 | 182933 | 1937 |
| 1384 | 450 | 2 | 14137 | 0 | 1996 | 5 | 3 | 153564 | 1938 |
| 1682 | 656 | 2 | 6264 | 1 | 1997 | 8 | 1 | 242586 | 1939 |
| 1280 | 0 | 2 | 5070 | 0 | 1992 | 8 | 2 | 185301 | 1940 |
| 1633 | 0 | 2 | 11184 | 1 | 1998 | 6 | 3 | 177866 | 1941 |
| 1709 | 504 | 2 | 14067 | 0 | 1991 | 6 | 3 | 185626 | 1942 |
| 1337 | 319 | 2 | 5950 | 1 | 1989 | 8 | 2 | 204289 | 1943 |
| 2500 | 16 | 3 | 13543 | 1 | 2005 | 8 | 5 | 303054 | 1944 |
| 1884 | 1337 | 3 | 15401 | 1 | 2004 | 9 | 2 | 350044 | 1945 |
| 1474 | 0 | 2 | 31220 | 2 | 1952 | 6 | 3 | 168353 | 1946 |
| 1710 | 1034 | 2 | 8118 | 1 | 2007 | 9 | 2 | 293883 | 1947 |
| 1488 | 0 | 2 | 47280 | 1 | 1950 | 6 | 3 | 170216 | 1948 |
| 1688 | 983 | 2 | 12680 | 1 | 1988 | 7 | 2 | 227265 | 1949 |
| 1260 | 747 | 2 | 10825 | 0 | 1983 | 7 | 3 | 182516 | 1950 |
| 2064 | 1206 | 2 | 18559 | 2 | 1978 | 7 | 3 | 267934 | 1951 |
| 1782 | 864 | 2 | 14450 | 1 | 1979 | 7 | 3 | 223962 | 1952 |
| 1211 | 890 | 2 | 13068 | 1 | 1976 | 6 | 3 | 170600 | 1953 |
| 2044 | 0 | 2 | 10400 | 1 | 1980 | 7 | 3 | 210786 | 1954 |
| 1308 | 280 | 2 | 9743 | 0 | 1969 | 5 | 3 | 134875 | 1955 |
| 2840 | 988 | 4 | 12511 | 2 | 1978 | 7 | 4 | 358795 | 1956 |
| 1444 | 0 | 2 | 10400 | 1 | 1976 | 6 | 2 | 160047 | 1957 |
| 2340 | 1023 | 3 | 14311 | 1 | 1996 | 8 | 4 | 329627 | 1958 |
| 1792 | 0 | 2 | 9000 | 0 | 1974 | 5 | 4 | 148865 | 1959 |
| 936 | 252 | 1 | 10295 | 0 | 1969 | 4 | 2 | 102870 | 1960 |
| 864 | 119 | 2 | 7560 | 0 | 1971 | 5 | 3 | 116293 | 1961 |
| 987 | 458 | 1 | 1680 | 0 | 1973 | 6 | 2 | 130085 | 1962 |
| 987 | 483 | 1 | 1890 | 0 | 1972 | 6 | 2 | 130300 | 1963 |
| 1302 | 350 | 1 | 1680 | 0 | 1972 | 5 | 3 | 124759 | 1964 |
| 1456 | 286 | 2 | 2308 | 0 | 1975 | 6 | 4 | 153760 | 1965 |
| 1055 | 378 | 2 | 2529 | 0 | 1977 | 7 | 2 | 157727 | 1966 |
| 1582 | 1012 | 3 | 12704 | 0 | 2007 | 8 | 3 | 263529 | 1967 |
| 2464 | 1728 | 3 | 13693 | 1 | 2007 | 8 | 4 | 387118 | 1968 |
| 1950 | 1375 | 3 | 14418 | 1 | 2007 | 9 | 2 | 360054 | 1969 |
| 2748 | 1420 | 3 | 13418 | 1 | 2006 | 9 | 4 | 443779 | 1970 |
| 2790 | 1082 | 4 | 12539 | 1 | 2005 | 10 | 4 | 505477 | 1971 |
| 2331 | 1249 | 3 | 12151 | 1 | 2005 | 9 | 3 | 385662 | 1972 |
| 2088 | 40 | 3 | 8899 | 1 | 2007 | 8 | 4 | 270172 | 1973 |
| 2332 | 856 | 3 | 10574 | 1 | 2004 | 8 | 4 | 323856 | 1974 |
| 2470 | 2257 | 3 | 12720 | 2 | 2003 | 10 | 1 | 540430 | 1975 |
| 1575 | 1149 | 3 | 10845 | 1 | 2003 | 8 | 2 | 276693 | 1976 |
| 2649 | 1075 | 3 | 16900 | 1 | 2001 | 8 | 4 | 369715 | 1977 |
| 2690 | 0 | 3 | 16451 | 1 | 2003 | 8 | 4 | 322285 | 1978 |
| 1866 | 372 | 3 | 10110 | 1 | 2008 | 9 | 2 | 301561 | 1979 |
| 1367 | 20 | 2 | 12304 | 1 | 2005 | 7 | 2 | 189282 | 1980 |
| 1800 | 1204 | 3 | 8232 | 1 | 2007 | 9 | 2 | 330202 | 1981 |
| 1342 | 846 | 2 | 6240 | 1 | 2006 | 8 | 2 | 230579 | 1982 |
| 1342 | 24 | 2 | 6240 | 1 | 2006 | 8 | 2 | 205221 | 1983 |
| 1626 | 0 | 2 | 2448 | 0 | 2003 | 7 | 2 | 187334 | 1984 |
| 1455 | 1073 | 3 | 3940 | 1 | 2003 | 7 | 2 | 232959 | 1985 |
| 1576 | 1087 | 3 | 3940 | 1 | 2004 | 7 | 2 | 242024 | 1986 |
| 1246 | 0 | 2 | 3710 | 1 | 2007 | 7 | 2 | 178266 | 1987 |
| 1515 | 0 | 2 | 9024 | 1 | 2004 | 6 | 3 | 173570 | 1988 |
| 1720 | 0 | 2 | 8010 | 1 | 2002 | 7 | 3 | 202317 | 1989 |
| 1986 | 0 | 2 | 8396 | 1 | 2003 | 7 | 4 | 217259 | 1990 |
| 1358 | 876 | 2 | 7301 | 1 | 2007 | 7 | 2 | 210720 | 1991 |
| 1892 | 544 | 2 | 8220 | 1 | 2000 | 7 | 3 | 228200 | 1992 |
| 1414 | 0 | 2 | 7750 | 1 | 2002 | 7 | 3 | 185673 | 1993 |
| 2322 | 870 | 2 | 12460 | 1 | 1999 | 7 | 4 | 270676 | 1994 |
| 1651 | 0 | 2 | 8390 | 1 | 1999 | 7 | 3 | 197192 | 1995 |
| 2199 | 0 | 2 | 9660 | 1 | 1997 | 8 | 3 | 254757 | 1996 |
| 2172 | 0 | 3 | 11000 | 1 | 2000 | 9 | 4 | 302023 | 1997 |
| 2006 | 1660 | 3 | 11675 | 1 | 1998 | 8 | 2 | 331906 | 1998 |
| 2125 | 851 | 2 | 10990 | 2 | 1996 | 7 | 4 | 263009 | 1999 |
| 2501 | 0 | 3 | 11929 | 1 | 1995 | 8 | 4 | 295048 | 2000 |
| 2197 | 228 | 3 | 10010 | 1 | 1993 | 7 | 4 | 249275 | 2001 |
| 1578 | 1096 | 3 | 13253 | 1 | 2006 | 7 | 3 | 249799 | 2002 |
| 1861 | 0 | 3 | 9801 | 1 | 2007 | 8 | 3 | 254642 | 2003 |
| 1874 | 729 | 3 | 9428 | 1 | 2007 | 8 | 3 | 283027 | 2004 |
| 1460 | 666 | 2 | 10037 | 1 | 2006 | 8 | 3 | 233700 | 2005 |
| 1372 | 24 | 2 | 8640 | 0 | 2007 | 8 | 3 | 199375 | 2006 |
| 1660 | 0 | 3 | 10625 | 1 | 2007 | 8 | 3 | 241481 | 2007 |
| 1218 | 902 | 2 | 7500 | 0 | 2007 | 7 | 2 | 195324 | 2008 |
| 1696 | 80 | 2 | 10110 | 0 | 2003 | 6 | 3 | 177306 | 2009 |
| 1663 | 0 | 2 | 12774 | 0 | 2003 | 7 | 3 | 194642 | 2010 |
| 1175 | 80 | 0 | 13072 | 0 | 2005 | 6 | 3 | 136205 | 2011 |
| 1162 | 0 | 2 | 9260 | 0 | 2007 | 7 | 3 | 169127 | 2012 |
| 1609 | 362 | 2 | 8453 | 0 | 1995 | 6 | 3 | 175466 | 2013 |
| 1680 | 602 | 2 | 8480 | 0 | 1993 | 6 | 3 | 184212 | 2014 |
| 1657 | 537 | 2 | 14565 | 0 | 1994 | 7 | 3 | 206085 | 2015 |
| 1677 | 472 | 2 | 8450 | 0 | 2001 | 6 | 3 | 184461 | 2016 |
| 1737 | 397 | 2 | 8285 | 0 | 1992 | 7 | 3 | 201243 | 2017 |
| 984 | 53 | 1 | 9100 | 1 | 1963 | 5 | 3 | 114298 | 2018 |
| 864 | 764 | 1 | 8100 | 1 | 1961 | 5 | 3 | 121236 | 2019 |
| 890 | 890 | 1 | 8450 | 0 | 1968 | 5 | 3 | 121603 | 2020 |
| 864 | 489 | 1 | 6360 | 0 | 1963 | 5 | 3 | 111808 | 2021 |
| 1430 | 800 | 2 | 19508 | 2 | 1974 | 6 | 3 | 189627 | 2022 |
| 1641 | 190 | 2 | 10759 | 1 | 1972 | 5 | 4 | 152945 | 2023 |
| 2683 | 704 | 2 | 9205 | 2 | 1990 | 6 | 4 | 265052 | 2024 |
| 2786 | 520 | 2 | 11025 | 1 | 1993 | 9 | 4 | 354115 | 2025 |
| 1245 | 24 | 2 | 3435 | 0 | 2004 | 7 | 1 | 171206 | 2026 |
| 1200 | 390 | 2 | 3180 | 0 | 2005 | 6 | 2 | 159589 | 2027 |
| 1392 | 0 | 2 | 3180 | 0 | 2007 | 7 | 2 | 177809 | 2028 |
| 1549 | 550 | 2 | 2280 | 0 | 1999 | 6 | 3 | 175417 | 2029 |
| 1638 | 1027 | 2 | 4765 | 1 | 2000 | 9 | 2 | 279465 | 2030 |
| 1310 | 1004 | 2 | 4538 | 1 | 2001 | 9 | 1 | 256429 | 2031 |
| 1419 | 964 | 2 | 4385 | 1 | 2001 | 9 | 2 | 260981 | 2032 |
| 1557 | 1141 | 2 | 4109 | 1 | 1999 | 9 | 2 | 276375 | 2033 |
| 1404 | 600 | 2 | 2160 | 0 | 1999 | 7 | 3 | 188382 | 2034 |
| 1789 | 681 | 2 | 10646 | 1 | 2001 | 7 | 3 | 228544 | 2035 |
| 1586 | 612 | 2 | 2645 | 0 | 1999 | 8 | 3 | 220793 | 2036 |
| 1607 | 813 | 2 | 2645 | 0 | 1999 | 8 | 3 | 228502 | 2037 |
| 2393 | 128 | 2 | 3951 | 1 | 1998 | 10 | 2 | 334326 | 2038 |
| 1239 | 560 | 2 | 11064 | 1 | 1995 | 8 | 1 | 213916 | 2039 |
| 2944 | 410 | 3 | 24572 | 1 | 1977 | 9 | 3 | 393579 | 2040 |
| 1671 | 1044 | 2 | 16280 | 1 | 1976 | 8 | 3 | 247003 | 2041 |
| 1812 | 0 | 2 | 7500 | 1 | 2002 | 7 | 3 | 207199 | 2042 |
| 1427 | 828 | 2 | 11104 | 0 | 1969 | 6 | 4 | 167002 | 2043 |
| 1740 | 301 | 2 | 11050 | 1 | 1968 | 6 | 4 | 175705 | 2044 |
| 1620 | 603 | 2 | 15387 | 1 | 1967 | 7 | 4 | 199352 | 2045 |
| 1625 | 0 | 2 | 9750 | 0 | 1965 | 5 | 4 | 139194 | 2046 |
| 1464 | 732 | 2 | 8814 | 0 | 1968 | 5 | 4 | 148346 | 2047 |
| 925 | 260 | 2 | 8125 | 0 | 1965 | 5 | 3 | 119032 | 2048 |
| 1728 | 0 | 2 | 11072 | 0 | 1965 | 5 | 6 | 142011 | 2049 |
| 1670 | 583 | 2 | 13355 | 0 | 1971 | 7 | 4 | 194095 | 2050 |
| 1014 | 0 | 1 | 7785 | 0 | 1956 | 5 | 2 | 108015 | 2051 |
| 1114 | 0 | 2 | 9900 | 0 | 1961 | 5 | 3 | 120374 | 2052 |
| 1118 | 528 | 1 | 11332 | 0 | 1960 | 5 | 3 | 121716 | 2053 |
| 906 | 120 | 1 | 4882 | 0 | 1937 | 4 | 2 | 90515 | 2054 |
| 1496 | 658 | 2 | 9600 | 0 | 1960 | 5 | 3 | 146402 | 2055 |
| 1337 | 32 | 1 | 9600 | 1 | 1950 | 5 | 3 | 121739 | 2056 |
| 1036 | 531 | 1 | 7584 | 0 | 1953 | 5 | 3 | 115435 | 2057 |
| 1988 | 575 | 2 | 14670 | 1 | 1966 | 6 | 4 | 197044 | 2058 |
| 1176 | 621 | 1 | 8856 | 2 | 1957 | 5 | 3 | 133971 | 2059 |
| 1440 | 1053 | 1 | 9840 | 0 | 1959 | 5 | 2 | 143228 | 2060 |
| 1570 | 958 | 2 | 13200 | 1 | 1958 | 6 | 3 | 181726 | 2061 |
| 1104 | 774 | 1 | 10425 | 0 | 1956 | 5 | 3 | 123876 | 2062 |
| 882 | 148 | 1 | 11556 | 0 | 1952 | 5 | 2 | 106573 | 2063 |
| 1152 | 500 | 2 | 9373 | 0 | 1953 | 5 | 3 | 127683 | 2064 |
| 950 | 624 | 2 | 12774 | 0 | 1953 | 5 | 2 | 125071 | 2065 |
| 1790 | 0 | 2 | 14250 | 2 | 1957 | 6 | 3 | 175929 | 2066 |
| 1764 | 0 | 1 | 8838 | 1 | 1957 | 5 | 4 | 137690 | 2067 |
| 1824 | 0 | 2 | 12436 | 0 | 1957 | 5 | 5 | 144446 | 2068 |
| 869 | 0 | 1 | 10122 | 0 | 1948 | 4 | 1 | 92823 | 2069 |
| 1159 | 0 | 1 | 7506 | 0 | 1925 | 5 | 3 | 103014 | 2070 |
| 672 | 0 | 1 | 5400 | 0 | 1940 | 4 | 2 | 84185 | 2071 |
| 1436 | 0 | 4 | 10836 | 1 | 1922 | 5 | 3 | 142258 | 2072 |
| 1044 | 744 | 2 | 10180 | 1 | 1968 | 5 | 3 | 139353 | 2073 |
| 1312 | 637 | 2 | 11355 | 1 | 1958 | 7 | 3 | 178410 | 2074 |
| 1081 | 697 | 1 | 12929 | 0 | 1960 | 6 | 3 | 137771 | 2075 |
| 876 | 432 | 2 | 7200 | 1 | 1951 | 5 | 2 | 121349 | 2076 |
| 1256 | 476 | 1 | 8000 | 0 | 1959 | 5 | 3 | 123832 | 2077 |
| 1027 | 520 | 1 | 8000 | 0 | 1962 | 5 | 3 | 117841 | 2078 |
| 1320 | 315 | 2 | 8064 | 0 | 1948 | 6 | 3 | 142246 | 2079 |
| 984 | 0 | 1 | 6390 | 0 | 1954 | 6 | 2 | 117800 | 2080 |
| 1278 | 673 | 1 | 7200 | 0 | 1954 | 6 | 4 | 139176 | 2081 |
| 1800 | 0 | 0 | 8513 | 0 | 1961 | 5 | 6 | 124324 | 2082 |
| 1588 | 370 | 2 | 7200 | 0 | 1955 | 5 | 3 | 141193 | 2083 |
| 825 | 0 | 1 | 7200 | 0 | 1954 | 5 | 2 | 101763 | 2084 |
| 1117 | 0 | 1 | 7590 | 0 | 1963 | 5 | 3 | 112376 | 2085 |
| 1133 | 96 | 1 | 9836 | 0 | 2008 | 6 | 3 | 143851 | 2086 |
| 1323 | 0 | 2 | 9184 | 0 | 1948 | 5 | 3 | 123051 | 2087 |
| 1360 | 0 | 1 | 4800 | 0 | 1910 | 5 | 2 | 104512 | 2088 |
| 672 | 0 | 1 | 4800 | 0 | 1940 | 5 | 2 | 93308 | 2089 |
| 1456 | 0 | 1 | 6000 | 0 | 1915 | 6 | 4 | 119680 | 2090 |
| 1594 | 0 | 0 | 11426 | 0 | 1910 | 4 | 3 | 95391 | 2091 |
| 1656 | 0 | 2 | 7628 | 0 | 1940 | 4 | 2 | 119196 | 2092 |
| 1740 | 360 | 1 | 7308 | 1 | 1920 | 5 | 2 | 131823 | 2093 |
| 1027 | 0 | 0 | 5400 | 1 | 1920 | 7 | 2 | 117776 | 2094 |
| 1436 | 590 | 2 | 10800 | 2 | 1940 | 6 | 3 | 164000 | 2095 |
| 899 | 0 | 1 | 6756 | 0 | 1910 | 5 | 2 | 92556 | 2096 |
| 1080 | 0 | 0 | 5914 | 0 | 1890 | 5 | 3 | 85623 | 2097 |
| 1499 | 445 | 3 | 9000 | 1 | 1946 | 5 | 3 | 152498 | 2098 |
| 407 | 0 | 1 | 7311 | 0 | 1946 | 2 | 1 | 65239 | 2099 |
| 1588 | 0 | 0 | 12205 | 0 | 1949 | 3 | 5 | 93878 | 2100 |
| 1627 | 0 | 2 | 9142 | 0 | 1900 | 5 | 4 | 117464 | 2101 |
| 1450 | 116 | 1 | 5350 | 0 | 1920 | 7 | 3 | 137242 | 2102 |
| 1017 | 0 | 1 | 9143 | 0 | 1900 | 5 | 2 | 93941 | 2103 |
| 2350 | 234 | 2 | 9600 | 0 | 1920 | 5 | 4 | 156551 | 2104 |
| 1540 | 0 | 0 | 6000 | 0 | 1905 | 5 | 3 | 101171 | 2105 |
| 1086 | 0 | 2 | 11340 | 0 | 1920 | 2 | 2 | 79307 | 2106 |
| 2495 | 0 | 2 | 10800 | 1 | 1890 | 7 | 5 | 187066 | 2107 |
| 984 | 200 | 1 | 9750 | 0 | 1959 | 5 | 2 | 111789 | 2108 |
| 1093 | 0 | 1 | 8516 | 0 | 1958 | 4 | 2 | 100177 | 2109 |
| 1143 | 406 | 1 | 7111 | 1 | 1928 | 5 | 2 | 114691 | 2110 |
| 1668 | 0 | 1 | 7425 | 0 | 1945 | 7 | 3 | 154083 | 2111 |
| 1738 | 175 | 1 | 7010 | 1 | 1935 | 5 | 3 | 132426 | 2112 |
| 1210 | 600 | 1 | 5000 | 0 | 1941 | 5 | 3 | 117579 | 2113 |
| 1290 | 0 | 1 | 5870 | 0 | 1900 | 6 | 3 | 110603 | 2114 |
| 1672 | 521 | 1 | 6000 | 1 | 1940 | 6 | 3 | 153116 | 2115 |
| 949 | 0 | 2 | 6000 | 1 | 1924 | 5 | 2 | 108182 | 2116 |
| 1497 | 201 | 1 | 6000 | 0 | 1937 | 6 | 3 | 132706 | 2117 |
| 1342 | 264 | 1 | 6000 | 1 | 1939 | 6 | 2 | 135237 | 2118 |
| 1013 | 0 | 1 | 5000 | 0 | 1926 | 6 | 3 | 109227 | 2119 |
| 1216 | 68 | 1 | 5520 | 1 | 1920 | 5 | 3 | 107996 | 2120 |
| 896 | NA | 1 | 5940 | 0 | 1946 | 4 | 2 | 157815 | 2121 |
| 1136 | 80 | 1 | 6240 | 0 | 1929 | 4 | 2 | 94400 | 2122 |
| 808 | 0 | 1 | 6120 | 0 | 1945 | 5 | 1 | 99237 | 2123 |
| 2009 | 300 | 2 | 6240 | 1 | 1939 | 7 | 4 | 191928 | 2124 |
| 1902 | 203 | 2 | 6120 | 0 | 1923 | 5 | 4 | 137101 | 2125 |
| 1716 | 0 | 2 | 9144 | 0 | 1915 | 6 | 4 | 139014 | 2126 |
| 1984 | 196 | 1 | 8094 | 0 | 1910 | 6 | 5 | 140721 | 2127 |
| 1609 | 0 | 1 | 4347 | 0 | 1910 | 6 | 3 | 123388 | 2128 |
| 768 | 0 | 2 | 6291 | 0 | 1930 | 6 | 1 | 112179 | 2129 |
| 1536 | 372 | 1 | 10266 | 0 | 1952 | 6 | 4 | 143996 | 2130 |
| 1969 | 0 | 2 | 6876 | 1 | 1938 | 6 | 4 | 163717 | 2131 |
| 1308 | 0 | 2 | 10320 | 0 | 1915 | 5 | 2 | 113670 | 2132 |
| 1040 | 0 | 2 | 7200 | 0 | 1925 | 6 | 2 | 119012 | 2133 |
| 1236 | 121 | 1 | 7006 | 1 | 1925 | 6 | 3 | 123712 | 2134 |
| 759 | 0 | 2 | 10320 | 0 | 1912 | 5 | 1 | 97472 | 2135 |
| 1344 | 0 | 0 | 10320 | 0 | 1915 | 3 | 3 | 80876 | 2136 |
| 1054 | 0 | 1 | 9488 | 0 | 1947 | 5 | 3 | 106620 | 2137 |
| 1075 | 784 | 2 | 11235 | 0 | 1963 | 5 | 3 | 134361 | 2138 |
| 1096 | 528 | 2 | 13014 | 1 | 1978 | 6 | 3 | 157761 | 2139 |
| 992 | 758 | 1 | 10265 | 0 | 1967 | 5 | 3 | 123206 | 2140 |
| 1034 | 450 | 2 | 7703 | 1 | 1978 | 6 | 3 | 150666 | 2141 |
| 1073 | 221 | 1 | 9981 | 0 | 1967 | 5 | 3 | 116663 | 2142 |
| 1126 | 104 | 2 | 7400 | 0 | 1984 | 5 | 2 | 129847 | 2143 |
| 1140 | 1300 | 2 | 12900 | 0 | 1920 | 5 | 3 | 132418 | 2144 |
| 960 | 634 | 1 | 9239 | 0 | 1963 | 5 | 3 | 118346 | 2145 |
| 1188 | 776 | 2 | 14175 | 1 | 1956 | 6 | 1 | 161046 | 2146 |
| 1721 | 988 | 2 | 10532 | 2 | 1960 | 5 | 3 | 177933 | 2147 |
| 1350 | 336 | 3 | 8375 | 0 | 1941 | 5 | 2 | 137063 | 2148 |
| 904 | 704 | 3 | 10200 | 0 | 1970 | 5 | 3 | 137472 | 2149 |
| 1524 | 599 | 2 | 20270 | 2 | 1979 | 7 | 3 | 213375 | 2150 |
| 1079 | 0 | 1 | 5190 | 1 | 1948 | 7 | 2 | 137285 | 2151 |
| 1518 | 1035 | 0 | 19550 | 2 | 1940 | 5 | 2 | 145828 | 2152 |
| 1509 | 870 | 1 | 9571 | 1 | 1956 | 5 | 3 | 146035 | 2153 |
| 864 | 864 | 0 | 9350 | 0 | 1975 | 5 | 2 | 115633 | 2154 |
| 1269 | 324 | 1 | 9360 | 0 | 1962 | 6 | 3 | 136755 | 2155 |
| 2814 | 779 | 2 | 9771 | 1 | 1995 | 6 | 4 | 270542 | 2156 |
| 1626 | 1271 | 2 | 9938 | 1 | 1994 | 7 | 3 | 232665 | 2157 |
| 2200 | 355 | 2 | 14171 | 1 | 1993 | 7 | 4 | 240864 | 2158 |
| 2037 | 0 | 2 | 10541 | 1 | 1996 | 7 | 3 | 219376 | 2159 |
| 1356 | 0 | 2 | 10616 | 1 | 2007 | 7 | 3 | 186867 | 2160 |
| 1615 | 0 | 3 | 9345 | 1 | 2007 | 8 | 3 | 237465 | 2161 |
| 2276 | 2085 | 3 | 11778 | 2 | 2008 | 9 | 3 | 448557 | 2162 |
| 1766 | 1153 | 3 | 11778 | 2 | 2008 | 9 | 3 | 341148 | 2163 |
| 1511 | 770 | 3 | 11454 | 1 | 1995 | 8 | 3 | 251201 | 2164 |
| 1643 | 262 | 2 | 11500 | 1 | 1966 | 6 | 2 | 171684 | 2165 |
| 990 | 722 | 2 | 9750 | 0 | 1994 | 5 | 3 | 140250 | 2166 |
| 1418 | 1308 | 2 | 8696 | 1 | 1997 | 7 | 3 | 221562 | 2167 |
| 1771 | 688 | 2 | 13142 | 0 | 1997 | 6 | 3 | 196267 | 2168 |
| 1652 | 527 | 2 | 8998 | 0 | 2000 | 7 | 3 | 204880 | 2169 |
| 1823 | 663 | 2 | 12192 | 0 | 2000 | 7 | 3 | 221374 | 2170 |
| 1174 | 781 | 2 | 12250 | 0 | 1978 | 5 | 3 | 144000 | 2171 |
| 1076 | 294 | 2 | 9216 | 1 | 1975 | 5 | 3 | 133890 | 2172 |
| 1558 | 88 | 2 | 14330 | 0 | 1975 | 5 | 2 | 146044 | 2173 |
| 2161 | 0 | 2 | 10400 | 1 | 2001 | 7 | 3 | 229911 | 2174 |
| 1947 | 1194 | 3 | 9720 | 1 | 2001 | 9 | 3 | 337665 | 2175 |
| 1786 | 1538 | 3 | 14860 | 1 | 2002 | 8 | 3 | 311365 | 2176 |
| 2327 | 0 | 2 | 10905 | 1 | 2003 | 7 | 4 | 240848 | 2177 |
| 1764 | 0 | 2 | 11690 | 1 | 1999 | 8 | 3 | 228484 | 2178 |
| 848 | 662 | 2 | 4426 | 0 | 2004 | 6 | 1 | 151633 | 2179 |
| 1838 | 1593 | 3 | 10126 | 0 | 1997 | 6 | 2 | 242213 | 2180 |
| 1445 | 24 | 2 | 9750 | 0 | 2004 | 7 | 3 | 182457 | 2181 |
| 1564 | 56 | 3 | 11058 | 0 | 2007 | 7 | 3 | 205056 | 2182 |
| 1361 | 24 | 2 | 9627 | 0 | 2007 | 7 | 3 | 179566 | 2183 |
| 1092 | 609 | 1 | 9825 | 0 | 1966 | 5 | 3 | 123526 | 2184 |
| 1033 | 456 | 2 | 12102 | 0 | 1976 | 5 | 3 | 131489 | 2185 |
| 1127 | 1033 | 2 | 6500 | 1 | 1976 | 6 | 3 | 166389 | 2186 |
| 1117 | 368 | 2 | 9638 | 1 | 1977 | 6 | 3 | 152990 | 2187 |
| 1398 | 288 | 2 | 7200 | 1 | 1976 | 6 | 3 | 161796 | 2188 |
| 3820 | 0 | 2 | 47007 | 2 | 1959 | 5 | 5 | 308130 | 2189 |
| 1152 | 0 | 0 | 6012 | 0 | 1955 | 4 | 2 | 93704 | 2190 |
| 1152 | 0 | 0 | 6845 | 0 | 1955 | 4 | 2 | 93965 | 2191 |
| 784 | 784 | 0 | 6931 | 0 | 1955 | 4 | 2 | 94834 | 2192 |
| 1053 | 0 | 0 | 12180 | 0 | 1938 | 5 | 2 | 98902 | 2193 |
| 1137 | 0 | 0 | 8050 | 0 | 1947 | 5 | 4 | 100884 | 2194 |
| 930 | 767 | 1 | 9520 | 0 | 1953 | 4 | 2 | 105719 | 2195 |
| 1204 | 0 | 1 | 7692 | 0 | 1954 | 4 | 3 | 101307 | 2196 |
| 1292 | 224 | 1 | 5142 | 0 | 1923 | 4 | 3 | 98060 | 2197 |
| 1424 | 0 | 1 | 7290 | 1 | 1921 | 7 | 2 | 141881 | 2198 |
| 1920 | 281 | 2 | 7804 | 2 | 1930 | 6 | 4 | 172103 | 2199 |
| 1316 | 379 | 1 | 8969 | 1 | 1926 | 6 | 2 | 133270 | 2200 |
| 1264 | 0 | 2 | 15564 | 0 | 1914 | 6 | 3 | 125763 | 2201 |
| 1512 | 406 | 1 | 7609 | 1 | 1925 | 8 | 3 | 171878 | 2202 |
| 1603 | 0 | 2 | 9650 | 1 | 1923 | 6 | 4 | 143586 | 2203 |
| 1938 | 606 | 1 | 11700 | 1 | 1937 | 5 | 4 | 150958 | 2204 |
| 1374 | 0 | 1 | 9260 | 0 | 1938 | 5 | 3 | 113758 | 2205 |
| 1091 | 500 | 1 | 7801 | 1 | 1951 | 6 | 2 | 135349 | 2206 |
| 1873 | 210 | 2 | 9670 | 2 | 1935 | 8 | 4 | 211438 | 2207 |
| 2161 | 435 | 2 | 12392 | 2 | 1950 | 7 | 3 | 224825 | 2208 |
| 1898 | 1116 | 2 | 26073 | 2 | 1956 | 5 | 3 | 198393 | 2209 |
| 1032 | 366 | 2 | 1879 | 1 | 1980 | 6 | 2 | 147647 | 2210 |
| 919 | 299 | 1 | 7000 | 0 | 1926 | 6 | 2 | 112491 | 2211 |
| 1090 | 0 | 1 | 6000 | 0 | 1940 | 6 | 3 | 116093 | 2212 |
| 1200 | 0 | 0 | 8155 | 0 | 1930 | 5 | 4 | 98279 | 2213 |
| 1656 | 257 | 1 | 6000 | 1 | 1967 | 5 | 3 | 141789 | 2214 |
| 912 | 0 | 1 | 7392 | 0 | 1930 | 5 | 2 | 98035 | 2215 |
| 1955 | 330 | 1 | 9000 | 0 | 1958 | 5 | 4 | 146438 | 2216 |
| 733 | 0 | 2 | 14584 | 0 | 1952 | 1 | 2 | 71100 | 2217 |
| 1361 | 0 | 1 | 5280 | 0 | 1895 | 4 | 2 | 90692 | 2218 |
| 1049 | 0 | 1 | 5150 | 0 | 1910 | 4 | 2 | 86420 | 2219 |
| 864 | 0 | 1 | 9000 | 0 | 1920 | 4 | 3 | 84783 | 2220 |
| 1648 | 1476 | 2 | 3843 | 1 | 2007 | 8 | 2 | 272992 | 2221 |
| 1646 | 1474 | 2 | 3811 | 1 | 2004 | 7 | 2 | 243676 | 2222 |
| 2032 | 700 | 3 | 23730 | 0 | 1996 | 7 | 3 | 259400 | 2223 |
| 1820 | 0 | 3 | 11050 | 1 | 1996 | 7 | 3 | 221247 | 2224 |
| 1872 | 0 | 2 | 10260 | 0 | 1976 | 5 | 4 | 153645 | 2225 |
| 1689 | 1383 | 2 | 9990 | 1 | 1991 | 4 | 3 | 174288 | 2226 |
| 1501 | 893 | 2 | 4084 | 1 | 1986 | 7 | 2 | 205932 | 2227 |
| 1537 | 1036 | 3 | 11563 | 0 | 2006 | 8 | 3 | 259477 | 2228 |
| 1780 | 770 | 2 | 12852 | 1 | 2007 | 8 | 3 | 262338 | 2229 |
| 1442 | 0 | 2 | 9802 | 0 | 2006 | 5 | 3 | 148095 | 2230 |
| 1612 | 0 | 3 | 12018 | 0 | 2008 | 7 | 3 | 207363 | 2231 |
| 1495 | 0 | 2 | 12890 | 1 | 1989 | 6 | 3 | 168192 | 2232 |
| 1256 | 920 | 2 | 18265 | 1 | 1986 | 6 | 3 | 181148 | 2233 |
| 1440 | 1029 | 2 | 11202 | 1 | 2003 | 8 | 3 | 243729 | 2234 |
| 1675 | 1223 | 2 | 7915 | 0 | 1999 | 6 | 3 | 203641 | 2235 |
| 1728 | 1011 | 2 | 11449 | 1 | 2007 | 8 | 3 | 266311 | 2236 |
| 1964 | 1571 | 3 | 11447 | 1 | 2005 | 8 | 3 | 327484 | 2237 |
| 1344 | 1309 | 4 | 8940 | 0 | 1997 | 7 | 2 | 239934 | 2238 |
| 1092 | 0 | 0 | 9278 | 0 | 2007 | 5 | 2 | 118378 | 2239 |
| 1189 | 864 | 2 | 4500 | 0 | 1997 | 6 | 2 | 167406 | 2240 |
| 1200 | 865 | 3 | 14137 | 0 | 1964 | 4 | 3 | 137162 | 2241 |
| 1040 | 769 | 2 | 4224 | 0 | 1975 | 5 | 3 | 133798 | 2242 |
| 1475 | 318 | 1 | 2665 | 1 | 1976 | 5 | 4 | 136782 | 2243 |
| 988 | 501 | 1 | 1974 | 0 | 1973 | 4 | 2 | 106247 | 2244 |
| 988 | 437 | 1 | 1596 | 1 | 1973 | 4 | 1 | 110307 | 2245 |
| 1160 | 785 | 1 | 17979 | 0 | 1968 | 5 | 3 | 133311 | 2246 |
| 1092 | 358 | 0 | 1477 | 0 | 1970 | 6 | 3 | 121654 | 2247 |
| 816 | 534 | 1 | 6490 | 0 | 1983 | 5 | 2 | 117746 | 2248 |
| 845 | 638 | 1 | 6600 | 0 | 1982 | 5 | 3 | 119416 | 2249 |
| 889 | 647 | 2 | 12395 | 0 | 1984 | 5 | 3 | 132647 | 2250 |
| 1836 | 0 | 1 | 56600 | 0 | 1900 | 5 | 4 | 136405 | 2251 |
| 1587 | 838 | 2 | 10667 | 1 | 1971 | 6 | 3 | 184087 | 2252 |
| 1384 | 0 | 2 | 8872 | 1 | 1997 | 6 | 3 | 164280 | 2253 |
| 1694 | 186 | 2 | 10147 | 1 | 1994 | 6 | 3 | 183188 | 2254 |
| 1714 | 871 | 2 | 8637 | 1 | 1999 | 6 | 3 | 204600 | 2255 |
| 1553 | 414 | 2 | 7875 | 0 | 1996 | 7 | 3 | 193409 | 2256 |
| 2299 | 0 | 2 | 7500 | 1 | 1999 | 6 | 5 | 209198 | 2257 |
| 1187 | 0 | 2 | 9556 | 0 | 1992 | 7 | 3 | 163982 | 2258 |
| 1642 | 0 | 2 | 7655 | 1 | 1993 | 6 | 3 | 173956 | 2259 |
| 1128 | 550 | 2 | 18160 | 1 | 1964 | 6 | 3 | 156652 | 2260 |
| 1179 | 248 | 2 | 4740 | 0 | 1988 | 8 | 2 | 184495 | 2261 |
| 1321 | 926 | 2 | 5118 | 1 | 1990 | 8 | 1 | 223057 | 2262 |
| 2541 | 986 | 3 | 12328 | 1 | 2005 | 8 | 4 | 352557 | 2263 |
| 2338 | 1101 | 3 | 51974 | 2 | 2006 | 9 | 4 | 448708 | 2264 |
| 1424 | 1047 | 3 | 41600 | 0 | 1969 | 5 | 3 | 184698 | 2265 |
| 1612 | 797 | 2 | 8035 | 1 | 2006 | 9 | 2 | 275754 | 2266 |
| 2234 | 1558 | 2 | 14082 | 1 | 2006 | 8 | 1 | 337612 | 2267 |
| 2042 | 1152 | 3 | 13870 | 1 | 2006 | 10 | 3 | 393144 | 2268 |
| 1284 | 256 | 2 | 10960 | 0 | 1984 | 6 | 3 | 154789 | 2269 |
| 1479 | 321 | 2 | 12090 | 1 | 1981 | 7 | 3 | 190123 | 2270 |
| 1664 | 1328 | 2 | 12299 | 1 | 1978 | 7 | 3 | 229224 | 2271 |
| 1930 | 758 | 2 | 11339 | 1 | 1979 | 7 | 4 | 226031 | 2272 |
| 1177 | 781 | 2 | 11850 | 0 | 1984 | 6 | 3 | 162346 | 2273 |
| 1353 | 903 | 2 | 10400 | 1 | 1979 | 6 | 2 | 178743 | 2274 |
| 1220 | 492 | 2 | 13001 | 1 | 1971 | 6 | 2 | 160572 | 2275 |
| 1324 | 624 | 2 | 8991 | 1 | 1976 | 7 | 3 | 185727 | 2276 |
| 1877 | 931 | 2 | 8000 | 1 | 1974 | 6 | 4 | 200635 | 2277 |
| 1422 | 566 | 2 | 9457 | 0 | 1970 | 5 | 3 | 145209 | 2278 |
| 914 | 81 | 1 | 7920 | 0 | 1970 | 5 | 3 | 109528 | 2279 |
| 914 | 314 | 1 | 17199 | 0 | 1961 | 4 | 2 | 103389 | 2280 |
| 1337 | 0 | 2 | 4113 | 1 | 2001 | 6 | 2 | 162304 | 2281 |
| 1337 | 930 | 2 | 10943 | 1 | 1997 | 6 | 2 | 187493 | 2282 |
| 1092 | 312 | 1 | 2205 | 0 | 1973 | 6 | 3 | 130571 | 2283 |
| 1218 | 0 | 1 | 2058 | 0 | 1973 | 6 | 4 | 128471 | 2284 |
| 1055 | 632 | 1 | 2304 | 0 | 1978 | 7 | 2 | 153185 | 2285 |
| 988 | 725 | 1 | 7150 | 0 | 1966 | 5 | 3 | 120913 | 2286 |
| 1816 | 1151 | 3 | 12469 | 1 | 2006 | 9 | 3 | 330863 | 2287 |
| 1694 | 0 | 3 | 11825 | 1 | 2006 | 8 | 3 | 244118 | 2288 |
| 2122 | 1518 | 3 | 14333 | 1 | 2007 | 8 | 2 | 346927 | 2289 |
| 2656 | 1304 | 3 | 13641 | 1 | 2007 | 9 | 3 | 429732 | 2290 |
| 2550 | 0 | 3 | 13440 | 1 | 2006 | 8 | 4 | 309286 | 2291 |
| 2046 | 1430 | 3 | 15431 | 2 | 2005 | 10 | 2 | 430586 | 2292 |
| 2552 | 1812 | 3 | 13891 | 2 | 2007 | 9 | 3 | 467995 | 2293 |
| 2758 | 0 | 3 | 13654 | 1 | 2005 | 9 | 4 | 363233 | 2294 |
| 2290 | 1684 | 3 | 17169 | 1 | 2007 | 10 | 2 | 463379 | 2295 |
| 2152 | 0 | 2 | 16659 | 1 | 2007 | 8 | 3 | 264151 | 2296 |
| 2100 | 778 | 3 | 9709 | 2 | 2007 | 8 | 3 | 316565 | 2297 |
| 1802 | 0 | 3 | 13615 | 1 | 2006 | 9 | 3 | 281044 | 2298 |
| 2956 | 0 | 3 | 13069 | 1 | 2004 | 8 | 5 | 341759 | 2299 |
| 2385 | 938 | 3 | 14277 | 1 | 2003 | 8 | 3 | 337955 | 2300 |
| 1818 | 669 | 3 | 12568 | 1 | 2007 | 8 | 3 | 279213 | 2301 |
| 1614 | 1178 | 3 | 9926 | 0 | 2005 | 7 | 3 | 241588 | 2302 |
| 1721 | 119 | 2 | 9254 | 0 | 2005 | 8 | 3 | 221949 | 2303 |
| 1828 | 0 | 3 | 10732 | 0 | 2006 | 8 | 3 | 242226 | 2304 |
| 1302 | 866 | 2 | 3901 | 1 | 2005 | 6 | 1 | 184681 | 2305 |
| 1302 | 1030 | 2 | 3903 | 1 | 2005 | 6 | 1 | 189026 | 2306 |
| 1362 | 762 | 2 | 6289 | 1 | 2005 | 6 | 2 | 185311 | 2307 |
| 1554 | 24 | 2 | 4590 | 1 | 2006 | 8 | 2 | 216470 | 2308 |
| 1577 | 848 | 2 | 7841 | 1 | 2005 | 9 | 2 | 274179 | 2309 |
| 1324 | 24 | 2 | 6240 | 1 | 2006 | 8 | 2 | 204198 | 2310 |
| 1405 | 1000 | 2 | 3242 | 1 | 2003 | 7 | 2 | 212140 | 2311 |
| 1496 | 0 | 2 | 15810 | 0 | 2007 | 6 | 3 | 170783 | 2312 |
| 1536 | 0 | 2 | 10237 | 1 | 2005 | 6 | 3 | 175748 | 2313 |
| 1458 | 0 | 2 | 13204 | 0 | 2006 | 7 | 3 | 185571 | 2314 |
| 1495 | 0 | 2 | 8857 | 1 | 2006 | 6 | 3 | 173408 | 2315 |
| 1746 | 0 | 3 | 9729 | 1 | 2006 | 6 | 3 | 199400 | 2316 |
| 1326 | 918 | 2 | 12216 | 0 | 2005 | 6 | 3 | 182383 | 2317 |
| 1504 | 0 | 2 | 8229 | 0 | 2007 | 6 | 3 | 166883 | 2318 |
| 1456 | 0 | 2 | 7713 | 0 | 2007 | 7 | 3 | 182569 | 2319 |
| 1258 | 0 | 2 | 7697 | 0 | 2007 | 7 | 3 | 172793 | 2320 |
| 1589 | 1084 | 3 | 3621 | 1 | 2003 | 8 | 2 | 268663 | 2321 |
| 1266 | 0 | 2 | 3710 | 1 | 2007 | 7 | 2 | 179259 | 2322 |
| 1119 | 779 | 2 | 16219 | 0 | 2004 | 7 | 2 | 190774 | 2323 |
| 1374 | 192 | 2 | 11084 | 1 | 2004 | 7 | 3 | 191791 | 2324 |
| 1525 | 0 | 2 | 10936 | 1 | 2006 | 7 | 3 | 195549 | 2325 |
| 1394 | 0 | 2 | 11950 | 1 | 2003 | 7 | 3 | 187739 | 2326 |
| 1948 | 0 | 2 | 7875 | 1 | 2003 | 7 | 4 | 214604 | 2327 |
| 1995 | 574 | 2 | 8740 | 1 | 2002 | 7 | 4 | 235922 | 2328 |
| 1690 | 520 | 2 | 9487 | 1 | 2000 | 6 | 3 | 194430 | 2329 |
| 1644 | 0 | 2 | 9649 | 1 | 1999 | 6 | 3 | 177958 | 2330 |
| 2551 | 1181 | 3 | 12191 | 2 | 1997 | 8 | 4 | 370852 | 2331 |
| 3078 | 672 | 3 | 10557 | 1 | 1998 | 9 | 4 | 424405 | 2332 |
| 2582 | 1048 | 3 | 11002 | 1 | 1998 | 8 | 4 | 351720 | 2333 |
| 2385 | 0 | 3 | 10790 | 1 | 1998 | 7 | 4 | 258268 | 2334 |
| 2202 | 335 | 2 | 11762 | 1 | 1992 | 8 | 4 | 264068 | 2335 |
| 2538 | 1225 | 3 | 9044 | 1 | 1996 | 8 | 4 | 352125 | 2336 |
| 1369 | 0 | 2 | 9910 | 0 | 2007 | 7 | 3 | 179524 | 2337 |
| 1542 | 1220 | 3 | 11830 | 1 | 2007 | 8 | 3 | 278930 | 2338 |
| 1534 | 28 | 2 | 10612 | 1 | 2006 | 8 | 3 | 218347 | 2339 |
| 1966 | 1572 | 3 | 12291 | 1 | 2007 | 10 | 1 | 412773 | 2340 |
| 1528 | 0 | 2 | 9965 | 1 | 2007 | 7 | 3 | 195584 | 2341 |
| 1538 | 769 | 2 | 8847 | 0 | 2005 | 8 | 3 | 230994 | 2342 |
| 1506 | 778 | 2 | 8251 | 1 | 2005 | 7 | 3 | 214700 | 2343 |
| 1977 | 0 | 3 | 9605 | 0 | 2006 | 7 | 3 | 226466 | 2344 |
| 1830 | 0 | 3 | 8778 | 0 | 2006 | 8 | 3 | 240784 | 2345 |
| 1338 | 24 | 2 | 8640 | 0 | 2007 | 8 | 3 | 197502 | 2346 |
| 1335 | 0 | 2 | 9000 | 0 | 2006 | 7 | 3 | 176839 | 2347 |
| 1792 | 350 | 2 | 8640 | 0 | 2007 | 8 | 3 | 234634 | 2348 |
| 1588 | 0 | 2 | 10411 | 0 | 2007 | 5 | 3 | 154937 | 2349 |
| 1880 | 745 | 3 | 12217 | 1 | 2007 | 8 | 3 | 286802 | 2350 |
| 1584 | 0 | 2 | 10440 | 1 | 2007 | 8 | 2 | 222407 | 2351 |
| 1685 | 0 | 3 | 11824 | 1 | 2006 | 8 | 2 | 245094 | 2352 |
| 2443 | 0 | 3 | 10625 | 1 | 2004 | 6 | 4 | 239894 | 2353 |
| 1100 | 0 | 0 | 7500 | 0 | 2006 | 6 | 3 | 129797 | 2354 |
| 1143 | 0 | 0 | 7500 | 0 | 2006 | 7 | 3 | 145883 | 2355 |
| 1094 | 729 | 2 | 12450 | 0 | 2003 | 5 | 3 | 149248 | 2356 |
| 1486 | 0 | 2 | 7441 | 0 | 2006 | 7 | 3 | 183454 | 2357 |
| 1820 | 480 | 2 | 11613 | 0 | 1993 | 6 | 3 | 190212 | 2358 |
| 1266 | 0 | 1 | 8012 | 2 | 1980 | 6 | 2 | 148815 | 2359 |
| 894 | 138 | 1 | 6285 | 0 | 1977 | 5 | 2 | 111928 | 2360 |
| 1040 | 812 | 2 | 7476 | 0 | 1968 | 5 | 3 | 133642 | 2361 |
| 2503 | 727 | 2 | 19522 | 1 | 1990 | 7 | 3 | 280816 | 2362 |
| 1037 | 787 | 2 | 10751 | 0 | 1974 | 5 | 2 | 137517 | 2363 |
| 1055 | 968 | 2 | 12712 | 1 | 1973 | 6 | 2 | 164777 | 2364 |
| 1378 | 851 | 2 | 4379 | 1 | 2004 | 8 | 2 | 230420 | 2365 |
| 1151 | 60 | 2 | 3523 | 0 | 2006 | 8 | 2 | 185998 | 2366 |
| 1565 | 60 | 2 | 3784 | 0 | 2006 | 8 | 2 | 208841 | 2367 |
| 1352 | 937 | 2 | 3606 | 1 | 2006 | 7 | 2 | 209051 | 2368 |
| 1550 | 0 | 2 | 5330 | 0 | 2006 | 8 | 2 | 207279 | 2369 |
| 1501 | 565 | 2 | 2280 | 1 | 1999 | 6 | 3 | 180784 | 2370 |
| 1573 | 417 | 2 | 2117 | 0 | 2000 | 6 | 3 | 173647 | 2371 |
| 1358 | 0 | 2 | 7321 | 0 | 1999 | 7 | 3 | 173799 | 2372 |
| 2048 | 964 | 2 | 8010 | 2 | 2003 | 8 | 3 | 294821 | 2373 |
| 2362 | 901 | 2 | 8413 | 2 | 1998 | 8 | 3 | 315148 | 2374 |
| 1494 | 457 | 2 | 9466 | 1 | 1994 | 8 | 1 | 224499 | 2375 |
| 2362 | 1732 | 2 | 12000 | 1 | 1980 | 7 | 3 | 295886 | 2376 |
| 2497 | 1632 | 2 | 17778 | 2 | 1981 | 8 | 2 | 360647 | 2377 |
| 1152 | 0 | 2 | 11700 | 0 | 1968 | 6 | 3 | 138404 | 2378 |
| 2411 | 915 | 2 | 8000 | 1 | 1970 | 6 | 4 | 229788 | 2379 |
| 1082 | 973 | 2 | 8723 | 0 | 1969 | 6 | 3 | 154669 | 2380 |
| 1295 | 910 | 2 | 11700 | 0 | 1968 | 6 | 3 | 163836 | 2381 |
| 1610 | 346 | 2 | 11358 | 1 | 1972 | 7 | 3 | 192838 | 2382 |
| 1594 | 0 | 2 | 9547 | 1 | 1993 | 7 | 2 | 193093 | 2383 |
| 2075 | 819 | 2 | 10530 | 1 | 1993 | 7 | 3 | 247056 | 2384 |
| 1093 | 792 | 2 | 10738 | 1 | 1966 | 6 | 3 | 157433 | 2385 |
| 1052 | 617 | 1 | 10800 | 0 | 1963 | 6 | 3 | 135213 | 2386 |
| 1107 | 474 | 1 | 8050 | 0 | 1967 | 5 | 3 | 121285 | 2387 |
| 1224 | 0 | 3 | 10899 | 0 | 1964 | 4 | 2 | 121621 | 2388 |
| 1074 | 438 | 2 | 7450 | 1 | 1956 | 5 | 2 | 130097 | 2389 |
| 1187 | 311 | 2 | 14357 | 1 | 1961 | 5 | 2 | 136685 | 2390 |
| 964 | 700 | 2 | 8243 | 1 | 1961 | 5 | 3 | 132154 | 2391 |
| 894 | 0 | 1 | 8680 | 0 | 1960 | 5 | 3 | 105193 | 2392 |
| 1200 | 654 | 2 | 8800 | 1 | 1966 | 7 | 3 | 175488 | 2393 |
| 1042 | 494 | 2 | 9200 | 0 | 1965 | 6 | 3 | 141674 | 2394 |
| 2154 | 414 | 2 | 8800 | 1 | 1964 | 6 | 5 | 195474 | 2395 |
| 1374 | 54 | 1 | 11382 | 1 | 1964 | 6 | 3 | 142930 | 2396 |
| 1652 | 1386 | 2 | 22002 | 1 | 1959 | 6 | 3 | 203959 | 2397 |
| 908 | 130 | 2 | 12172 | 0 | 1940 | 5 | 2 | 111224 | 2398 |
| 666 | 299 | 0 | 5000 | 0 | 1946 | 3 | 2 | 74887 | 2399 |
| 670 | 144 | 0 | 3500 | 0 | 1945 | 3 | 2 | 72786 | 2400 |
| 808 | 150 | 1 | 5175 | 0 | 1958 | 5 | 2 | 103833 | 2401 |
| 1150 | 368 | 1 | 9600 | 0 | 1955 | 5 | 2 | 118589 | 2402 |
| 1560 | 0 | 3 | 8668 | 0 | 1968 | 5 | 4 | 146793 | 2403 |
| 1280 | 602 | 2 | 10050 | 1 | 1966 | 5 | 3 | 145011 | 2404 |
| 1254 | 600 | 2 | 9600 | 1 | 1961 | 6 | 3 | 157551 | 2405 |
| 936 | 873 | 1 | 8760 | 0 | 1957 | 6 | 2 | 133629 | 2406 |
| 1008 | 908 | 1 | 6860 | 0 | 1956 | 5 | 3 | 121475 | 2407 |
| 1053 | 288 | 2 | 8250 | 0 | 1963 | 5 | 3 | 123242 | 2408 |
| 1144 | 0 | 1 | 9100 | 1 | 1960 | 5 | 3 | 117679 | 2409 |
| 1721 | 668 | 2 | 9736 | 3 | 1957 | 6 | 4 | 193517 | 2410 |
| 922 | 512 | 1 | 9770 | 0 | 1957 | 5 | 2 | 114263 | 2411 |
| 1411 | 780 | 1 | 12198 | 1 | 1955 | 5 | 3 | 141184 | 2412 |
| 1216 | 288 | 1 | 10050 | 0 | 1955 | 5 | 3 | 118826 | 2413 |
| 1154 | 408 | 1 | 11556 | 0 | 1953 | 5 | 3 | 118784 | 2414 |
| 1560 | 0 | 2 | 8078 | 0 | 1958 | 5 | 4 | 133502 | 2415 |
| 948 | 441 | 2 | 10950 | 0 | 1952 | 6 | 2 | 134102 | 2416 |
| 1040 | 85 | 1 | 7942 | 0 | 1953 | 6 | 3 | 120625 | 2417 |
| 925 | 114 | 1 | 8540 | 0 | 1956 | 5 | 3 | 106670 | 2418 |
| 1540 | 150 | 1 | 7150 | 0 | 1955 | 4 | 4 | 112958 | 2419 |
| 925 | 793 | 1 | 8400 | 2 | 1955 | 5 | 3 | 127180 | 2420 |
| 1647 | 595 | 1 | 9532 | 1 | 1953 | 4 | 3 | 130374 | 2421 |
| 924 | 292 | 1 | 15783 | 0 | 1952 | 5 | 2 | 111611 | 2422 |
| 1544 | 0 | 0 | 14190 | 0 | 1890 | 4 | 3 | 90157 | 2423 |
| 1728 | 198 | 1 | 12099 | 1 | 1953 | 5 | 3 | 141189 | 2424 |
| 3086 | 0 | 3 | 21281 | 0 | 1935 | 5 | 4 | 214755 | 2425 |
| 1281 | 1030 | 2 | 10284 | 0 | 1925 | 4 | 1 | 121407 | 2426 |
| 1534 | 0 | 0 | 10800 | 0 | 1895 | 5 | 3 | 100012 | 2427 |
| 1651 | 242 | 1 | 10090 | 2 | 1963 | 7 | 4 | 181047 | 2428 |
| 888 | 192 | 1 | 8700 | 0 | 1961 | 5 | 3 | 108201 | 2429 |
| 952 | 952 | 1 | 8300 | 0 | 1968 | 6 | 3 | 138540 | 2430 |
| 1238 | 432 | 1 | 7200 | 1 | 1950 | 5 | 3 | 124345 | 2431 |
| 1040 | 574 | 1 | 7500 | 0 | 1959 | 5 | 3 | 118056 | 2432 |
| 1170 | 625 | 1 | 7315 | 1 | 1958 | 5 | 3 | 128076 | 2433 |
| 1242 | 739 | 1 | 7903 | 0 | 1960 | 5 | 3 | 128326 | 2434 |
| 1377 | 1098 | 1 | 8000 | 2 | 1960 | 5 | 3 | 152316 | 2435 |
| 925 | 0 | 1 | 7000 | 0 | 1961 | 5 | 3 | 105782 | 2436 |
| 864 | 110 | 1 | 6600 | 0 | 1962 | 5 | 2 | 106461 | 2437 |
| 936 | 734 | 1 | 6760 | 1 | 1962 | 5 | 3 | 122927 | 2438 |
| 960 | 0 | 2 | 6978 | 0 | 1926 | 5 | 2 | 105001 | 2439 |
| 1296 | 276 | 2 | 6000 | 0 | 1927 | 6 | 3 | 132173 | 2440 |
| 1022 | 782 | 1 | 4480 | 1 | 1922 | 5 | 2 | 114161 | 2441 |
| 967 | 0 | 1 | 3153 | 1 | 1920 | 5 | 2 | 99673 | 2442 |
| 1072 | 0 | 2 | 7200 | 2 | 1940 | 5 | 2 | 122088 | 2443 |
| 1174 | 130 | 2 | 9000 | 1 | 1900 | 5 | 2 | 111343 | 2444 |
| 1141 | 122 | 1 | 5925 | 0 | 1900 | 4 | 3 | 87555 | 2445 |
| 1798 | 0 | 2 | 9639 | 0 | 1900 | 4 | 4 | 111096 | 2446 |
| 1772 | 0 | 2 | 10337 | 0 | 1910 | 8 | 3 | 173719 | 2447 |
| 1642 | 196 | 1 | 9863 | 1 | 1927 | 6 | 4 | 141113 | 2448 |
| 1232 | 168 | 2 | 4571 | 0 | 1910 | 5 | 3 | 109658 | 2449 |
| 1650 | 259 | 2 | 8398 | 0 | 1910 | 6 | 3 | 140332 | 2450 |
| 1358 | 316 | 1 | 3600 | 1 | 1930 | 5 | 3 | 118647 | 2451 |
| 2454 | 0 | 2 | 13500 | 1 | 1879 | 7 | 3 | 183754 | 2452 |
| 968 | 0 | 1 | 8626 | 0 | 1956 | 4 | 2 | 96295 | 2453 |
| 1382 | 0 | 1 | 11800 | 1 | 1949 | 4 | 1 | 112471 | 2454 |
| 1060 | 317 | 1 | 6854 | 1 | 1925 | 5 | 1 | 110437 | 2455 |
| 1435 | 910 | 1 | 8674 | 0 | 1950 | 5 | 3 | 135517 | 2456 |
| 1274 | 306 | 1 | 6125 | 0 | 1939 | 5 | 3 | 114640 | 2457 |
| 1232 | 276 | 1 | 6000 | 2 | 1939 | 6 | 3 | 136052 | 2458 |
| 884 | 0 | 1 | 6120 | 0 | 1939 | 5 | 2 | 99146 | 2459 |
| 1409 | 52 | 2 | 6240 | 1 | 1938 | 6 | 3 | 141793 | 2460 |
| 1322 | 48 | 1 | 6240 | 0 | 1939 | 5 | 4 | 111325 | 2461 |
| 1426 | 0 | 1 | 6240 | 1 | 1930 | 5 | 3 | 116637 | 2462 |
| 1281 | 351 | 2 | 6120 | 0 | 1926 | 5 | 2 | 120301 | 2463 |
| 2264 | 0 | 1 | 7755 | 0 | 1918 | 6 | 4 | 151840 | 2464 |
| 1376 | 0 | 2 | 8850 | 0 | 1920 | 6 | 3 | 128845 | 2465 |
| 1316 | 0 | 2 | 8550 | 0 | 1926 | 5 | 4 | 115019 | 2466 |
| 1344 | 336 | 2 | 5700 | 1 | 1929 | 7 | 3 | 157017 | 2467 |
| 1173 | 0 | 1 | 5680 | 0 | 1901 | 5 | 3 | 96595 | 2468 |
| 1214 | 0 | 1 | 5680 | 0 | 1901 | 5 | 2 | 98337 | 2469 |
| 2294 | 375 | 2 | 13200 | 1 | 1963 | 6 | 5 | 204565 | 2470 |
| 1952 | 354 | 1 | 9780 | 2 | 1950 | 7 | 4 | 193163 | 2471 |
| 2180 | 375 | 2 | 10320 | 1 | 1915 | 6 | 3 | 175623 | 2472 |
| 1315 | 681 | 2 | 4330 | 0 | 1958 | 4 | 3 | 122938 | 2473 |
| 1484 | 0 | 1 | 10320 | 0 | 1910 | 4 | 3 | 98573 | 2474 |
| 2267 | 288 | 2 | 12888 | 2 | 1937 | 7 | 3 | 219626 | 2475 |
| 1282 | 485 | 1 | 4484 | 0 | 1942 | 5 | 2 | 118886 | 2476 |
| 999 | 925 | 1 | 11235 | 0 | 1963 | 5 | 3 | 125506 | 2477 |
| 1452 | 785 | 2 | 11235 | 1 | 1964 | 5 | 2 | 156928 | 2478 |
| 1005 | 513 | 2 | 14299 | 0 | 1964 | 4 | 3 | 115655 | 2479 |
| 1020 | 68 | 2 | 14149 | 1 | 1964 | 5 | 3 | 126146 | 2480 |
| 1040 | 249 | 1 | 11677 | 0 | 1966 | 5 | 3 | 116416 | 2481 |
| 868 | 748 | 2 | 8425 | 0 | 1971 | 5 | 2 | 128478 | 2482 |
| 897 | 168 | 1 | 8665 | 0 | 1968 | 5 | 3 | 110068 | 2483 |
| 943 | 114 | 2 | 8398 | 0 | 1967 | 5 | 2 | 118662 | 2484 |
| 912 | 216 | 1 | 8169 | 0 | 1966 | 5 | 3 | 110524 | 2485 |
| 1375 | 386 | 1 | 14175 | 1 | 1956 | 5 | 3 | 133409 | 2486 |
| 2654 | 267 | 2 | 16779 | 1 | 1920 | 5 | 4 | 182691 | 2487 |
| 1302 | 258 | 1 | 6960 | 2 | 1940 | 7 | 2 | 155571 | 2488 |
| 1299 | 736 | 2 | 11375 | 1 | 1954 | 6 | 3 | 160666 | 2489 |
| 1176 | 190 | 1 | 13770 | 2 | 1958 | 5 | 3 | 128450 | 2490 |
| 998 | 0 | 2 | 9000 | 0 | 1945 | 4 | 3 | 100392 | 2491 |
| 1522 | 299 | 2 | 11075 | 1 | 1984 | 6 | 3 | 173466 | 2492 |
| 1325 | 300 | 2 | 17541 | 1 | 1948 | 5 | 3 | 137680 | 2493 |
| 1630 | 587 | 2 | 22692 | 1 | 1953 | 5 | 3 | 160847 | 2494 |
| 1242 | 0 | 1 | 17808 | 0 | 1946 | 4 | 2 | 104406 | 2495 |
| 2422 | 353 | 2 | 12671 | 2 | 1954 | 6 | 4 | 216174 | 2496 |
| 1626 | 491 | 1 | 10512 | 0 | 1954 | 6 | 3 | 152039 | 2497 |
| 864 | 453 | 1 | 5400 | 0 | 1958 | 5 | 3 | 109457 | 2498 |
| 943 | 0 | 1 | 11515 | 0 | 1958 | 4 | 3 | 96429 | 2499 |
| 1038 | 283 | 1 | 3869 | 0 | 1984 | 5 | 2 | 120114 | 2500 |
| 1342 | 557 | 1 | 9280 | 0 | 1951 | 5 | 4 | 125382 | 2501 |
| 1480 | 1080 | 1 | 11100 | 1 | 1951 | 5 | 4 | 147117 | 2502 |
| 1362 | 0 | 1 | 7550 | 0 | 1920 | 4 | 4 | 96260 | 2503 |
| 1822 | 0 | 2 | 23920 | 1 | 1984 | 6 | 4 | 187414 | 2504 |
| 1958 | 497 | 2 | 9317 | 1 | 1994 | 7 | 3 | 228155 | 2505 |
| 1651 | 0 | 3 | 9178 | 1 | 2007 | 8 | 3 | 239717 | 2506 |
| 2140 | 0 | 3 | 10481 | 0 | 2006 | 8 | 3 | 263928 | 2507 |
| 1651 | 0 | 3 | 10235 | 1 | 2007 | 8 | 3 | 240565 | 2508 |
| 1546 | 20 | 3 | 11750 | 0 | 2005 | 7 | 3 | 202414 | 2509 |
| 1500 | 36 | 2 | 8760 | 1 | 2006 | 8 | 3 | 215205 | 2510 |
| 1270 | 0 | 2 | 7242 | 0 | 2005 | 7 | 2 | 173334 | 2511 |
| 1795 | 0 | 2 | 9316 | 0 | 2005 | 7 | 3 | 200627 | 2512 |
| 1873 | 608 | 2 | 8883 | 1 | 1988 | 7 | 3 | 222554 | 2513 |
| 1743 | 51 | 2 | 20064 | 2 | 1976 | 8 | 0 | 235595 | 2514 |
| 1022 | 550 | 2 | 14217 | 0 | 1994 | 5 | 3 | 140169 | 2515 |
| 1308 | 539 | 2 | 10021 | 0 | 1997 | 6 | 3 | 167228 | 2516 |
| 990 | 420 | 1 | 8428 | 0 | 1994 | 5 | 3 | 125105 | 2517 |
| 1097 | 549 | 1 | 16561 | 0 | 1996 | 5 | 3 | 135570 | 2518 |
| 1873 | 342 | 2 | 10820 | 1 | 1999 | 7 | 3 | 221941 | 2519 |
| 1753 | 638 | 2 | 12352 | 1 | 1998 | 7 | 3 | 224431 | 2520 |
| 1690 | 0 | 2 | 9543 | 0 | 2001 | 7 | 3 | 193000 | 2521 |
| 1842 | 841 | 2 | 8826 | 1 | 2000 | 7 | 3 | 235205 | 2522 |
| 894 | 663 | 2 | 11800 | 0 | 1974 | 5 | 3 | 129473 | 2523 |
| 1025 | 502 | 2 | 8660 | 1 | 1976 | 5 | 3 | 136056 | 2524 |
| 1009 | 755 | 2 | 9720 | 1 | 1977 | 5 | 3 | 141261 | 2525 |
| 1040 | 539 | 2 | 8982 | 0 | 1977 | 5 | 3 | 132264 | 2526 |
| 907 | 60 | 1 | 16300 | 0 | 1977 | 5 | 3 | 114133 | 2527 |
| 879 | 330 | 2 | 9675 | 0 | 1975 | 5 | 3 | 122438 | 2528 |
| 864 | 671 | 2 | 7200 | 0 | 1972 | 5 | 3 | 125931 | 2529 |
| 875 | 385 | 2 | 7200 | 0 | 1972 | 4 | 3 | 109220 | 2530 |
| 1673 | 1412 | 2 | 11354 | 1 | 2000 | 7 | 3 | 245402 | 2531 |
| 1932 | 654 | 2 | 8749 | 1 | 2003 | 7 | 3 | 236620 | 2532 |
| 1729 | 0 | 2 | 8158 | 0 | 2002 | 7 | 3 | 194705 | 2533 |
| 1592 | 408 | 2 | 11927 | 1 | 1994 | 8 | 3 | 228007 | 2534 |
| 2439 | 1198 | 2 | 12728 | 1 | 2001 | 8 | 4 | 327295 | 2535 |
| 1992 | 762 | 2 | 15295 | 2 | 1996 | 7 | 3 | 255573 | 2536 |
| 1341 | 915 | 2 | 17227 | 1 | 1999 | 8 | 1 | 238689 | 2537 |
| 1476 | 0 | 2 | 8145 | 0 | 2007 | 7 | 3 | 183851 | 2538 |
| 1190 | 709 | 2 | 8769 | 0 | 2005 | 7 | 2 | 188404 | 2539 |
| 1330 | 0 | 2 | 8334 | 1 | 2006 | 6 | 3 | 165352 | 2540 |
| 1491 | 0 | 2 | 8333 | 1 | 2006 | 7 | 3 | 192034 | 2541 |
| 1536 | 0 | 2 | 9045 | 0 | 2005 | 5 | 3 | 151236 | 2542 |
| 936 | 936 | 1 | 9825 | 1 | 1967 | 5 | 2 | 130307 | 2543 |
| 1088 | 132 | 2 | 8308 | 0 | 1963 | 4 | 2 | 110339 | 2544 |
| 1351 | 130 | 2 | 16287 | 1 | 1925 | 5 | 3 | 127018 | 2545 |
| 1179 | 0 | 2 | 8240 | 0 | 1960 | 6 | 2 | 135898 | 2546 |
| 1044 | 504 | 2 | 6285 | 1 | 1976 | 6 | 3 | 150744 | 2547 |
| 2233 | 0 | 2 | 9555 | 0 | 1979 | 5 | 5 | 169662 | 2548 |
| 1408 | 611 | 2 | 7023 | 0 | 2005 | 5 | 3 | 158086 | 2549 |
| 5095 | 4010 | 3 | 39290 | 2 | 2008 | 10 | 2 | 1579681 | 2550 |
| 1072 | 467 | 2 | 3675 | 0 | 2005 | 6 | 2 | 155963 | 2551 |
| 960 | 77 | 1 | 6400 | 0 | 1959 | 5 | 2 | 107913 | 2552 |
| 1152 | 0 | 0 | 6882 | 0 | 1955 | 4 | 2 | 93976 | 2553 |
| 1195 | 0 | 0 | 8741 | 0 | 1946 | 5 | 4 | 102493 | 2554 |
| 865 | 144 | 1 | 10042 | 1 | 1920 | 6 | 2 | 112379 | 2555 |
| 768 | 544 | 1 | 8172 | 1 | 1955 | 4 | 2 | 102126 | 2556 |
| 864 | 682 | 2 | 8172 | 0 | 1955 | 4 | 3 | 109033 | 2557 |
| 2592 | 371 | 0 | 10890 | 0 | 1923 | 5 | 6 | 149155 | 2558 |
| 1422 | 319 | 1 | 7223 | 0 | 1926 | 5 | 3 | 116135 | 2559 |
| 1298 | 113 | 1 | 6821 | 1 | 1921 | 6 | 2 | 125156 | 2560 |
| 1098 | 246 | 1 | 4000 | 1 | 1930 | 7 | 2 | 135861 | 2561 |
| 1436 | 0 | 1 | 6720 | 1 | 1921 | 6 | 3 | 127108 | 2562 |
| 1461 | 0 | 1 | 7155 | 1 | 1926 | 6 | 3 | 129849 | 2563 |
| 1718 | 0 | 2 | 7230 | 1 | 1927 | 7 | 4 | 165014 | 2564 |
| 1226 | 0 | 2 | 13108 | 1 | 1951 | 5 | 2 | 128300 | 2565 |
| 1755 | 189 | 1 | 7810 | 1 | 1930 | 4 | 4 | 118046 | 2566 |
| 1355 | 533 | 2 | 6221 | 0 | 1941 | 5 | 3 | 130192 | 2567 |
| 1560 | 540 | 2 | 25485 | 3 | 1960 | 6 | 3 | 194294 | 2568 |
| 1488 | 813 | 2 | 21579 | 2 | 1968 | 6 | 3 | 191405 | 2569 |
| 1045 | 330 | 2 | 1782 | 1 | 1980 | 6 | 2 | 147379 | 2570 |
| 1680 | 0 | 2 | 17871 | 0 | 1995 | 4 | 4 | 141322 | 2571 |
| 1020 | 577 | 2 | 3907 | 0 | 1988 | 8 | 1 | 185640 | 2572 |
| 1696 | 434 | 2 | 20693 | 2 | 1971 | 7 | 3 | 214463 | 2573 |
| 2726 | 0 | 2 | 18044 | 1 | 1986 | 8 | 2 | 296687 | 2574 |
| 1215 | 375 | 2 | 7000 | 0 | 1940 | 6 | 3 | 135998 | 2575 |
| 1601 | 0 | 0 | 7288 | 0 | 1925 | 5 | 3 | 108834 | 2576 |
| 1828 | 548 | 0 | 9060 | 0 | 1923 | 5 | 3 | 125370 | 2577 |
| 816 | 0 | 1 | 3672 | 0 | 1922 | 5 | 2 | 92345 | 2578 |
| 845 | 0 | 1 | 11067 | 0 | 1939 | 2 | 1 | 73267 | 2579 |
| 1991 | 0 | 0 | 8250 | 0 | 1895 | 5 | 4 | 111853 | 2580 |
| 1073 | 967 | 2 | 6565 | 0 | 1957 | 4 | 3 | 120288 | 2581 |
| 1001 | 737 | 1 | 6060 | 0 | 1930 | 5 | 2 | 111057 | 2582 |
| 1625 | 1573 | 2 | 5568 | 1 | 2006 | 8 | 2 | 275883 | 2583 |
| 1299 | 1001 | 2 | 12150 | 1 | 1979 | 6 | 2 | 179592 | 2584 |
| 1392 | 585 | 3 | 10000 | 1 | 2002 | 5 | 3 | 175139 | 2585 |
| 1409 | 1392 | 2 | 12864 | 1 | 2002 | 7 | 1 | 232748 | 2586 |
| 1478 | 1239 | 2 | 9928 | 1 | 1991 | 7 | 3 | 220559 | 2587 |
| 918 | 224 | 1 | 8750 | 0 | 1975 | 7 | 3 | 140197 | 2588 |
| 1026 | 924 | 2 | 8410 | 1 | 1974 | 6 | 2 | 160537 | 2589 |
| 1501 | 949 | 2 | 4054 | 2 | 1987 | 7 | 2 | 216873 | 2590 |
| 2279 | 0 | 2 | 19958 | 1 | 1958 | 6 | 4 | 196310 | 2591 |
| 1689 | 0 | 2 | 8368 | 0 | 2006 | 7 | 3 | 194695 | 2592 |
| 1564 | 583 | 2 | 8298 | 1 | 2006 | 8 | 2 | 237897 | 2593 |
| 1240 | 215 | 2 | 10331 | 0 | 1985 | 7 | 3 | 168918 | 2594 |
| 1312 | 250 | 2 | 6718 | 0 | 2001 | 8 | 2 | 199358 | 2595 |
| 1922 | 1329 | 3 | 11305 | 1 | 2002 | 8 | 2 | 312227 | 2596 |
| 1491 | 0 | 2 | 7777 | 1 | 1996 | 6 | 3 | 168181 | 2597 |
| 2486 | 766 | 2 | 11800 | 1 | 2003 | 7 | 5 | 279606 | 2598 |
| 1824 | 0 | 3 | 12633 | 1 | 2006 | 10 | 3 | 313009 | 2599 |
| 2034 | 0 | 4 | 43500 | 0 | 1953 | 3 | 2 | 158924 | 2600 |
| 936 | 16 | 2 | 6710 | 0 | 1996 | 6 | 0 | 140858 | 2601 |
| 1092 | 252 | 1 | 1504 | 0 | 1972 | 4 | 3 | 104449 | 2602 |
| 992 | 503 | 1 | 1533 | 0 | 1970 | 4 | 2 | 105416 | 2603 |
| 1092 | 384 | 0 | 1495 | 0 | 1970 | 4 | 3 | 99003 | 2604 |
| 1092 | 0 | 1 | 1890 | 0 | 1976 | 4 | 3 | 101965 | 2605 |
| 1008 | 923 | 2 | 9129 | 1 | 1977 | 5 | 1 | 146226 | 2606 |
| 1356 | 1148 | 2 | 15957 | 1 | 1977 | 6 | 3 | 186493 | 2607 |
| 1676 | 1112 | 2 | 33983 | 2 | 1977 | 5 | 3 | 202111 | 2608 |
| 1432 | 531 | 2 | 8286 | 1 | 1977 | 5 | 3 | 153169 | 2609 |
| 796 | 796 | 0 | 6723 | 0 | 1971 | 5 | 2 | 110253 | 2610 |
| 1608 | 811 | 1 | 27697 | 0 | 1961 | 4 | 3 | 138411 | 2611 |
| 1178 | 1090 | 2 | 11000 | 0 | 1976 | 5 | 3 | 149212 | 2612 |
| 816 | 596 | 1 | 11625 | 0 | 1983 | 5 | 2 | 120840 | 2613 |
| 887 | 516 | 1 | 10447 | 0 | 1984 | 5 | 3 | 120906 | 2614 |
| 1293 | 468 | 2 | 11027 | 0 | 1954 | 6 | 2 | 148959 | 2615 |
| 1024 | 773 | 1 | 10533 | 2 | 1956 | 6 | 2 | 147135 | 2616 |
| 1797 | 1127 | 3 | 11765 | 1 | 1957 | 5 | 3 | 189479 | 2617 |
| 1390 | 1110 | 2 | 39384 | 2 | 1957 | 6 | 1 | 203009 | 2618 |
| 1851 | 0 | 2 | 11727 | 1 | 1969 | 7 | 3 | 195040 | 2619 |
| 1525 | 700 | 2 | 8238 | 1 | 1997 | 6 | 3 | 188260 | 2620 |
| 1671 | 0 | 2 | 13041 | 1 | 1995 | 6 | 3 | 179472 | 2621 |
| 1776 | 0 | 2 | 9783 | 1 | 1996 | 6 | 3 | 183256 | 2622 |
| 2064 | 0 | 2 | 13128 | 1 | 2005 | 8 | 4 | 251796 | 2623 |
| 2212 | 60 | 3 | 13751 | 1 | 2005 | 7 | 3 | 256970 | 2624 |
| 2687 | 0 | 2 | 13108 | 0 | 1994 | 8 | 4 | 279148 | 2625 |
| 1169 | 705 | 2 | 8076 | 1 | 1993 | 6 | 3 | 168810 | 2626 |
| 1204 | 0 | 2 | 3701 | 0 | 1987 | 8 | 2 | 178280 | 2627 |
| 2798 | 1218 | 3 | 16023 | 1 | 2005 | 9 | 3 | 442830 | 2628 |
| 3390 | 0 | 3 | 18062 | 1 | 2006 | 10 | 5 | 486025 | 2629 |
| 2473 | 205 | 3 | 12292 | 1 | 2006 | 9 | 4 | 344810 | 2630 |
| 2698 | 1206 | 3 | 16052 | 1 | 2006 | 10 | 4 | 475704 | 2631 |
| 2795 | 0 | 3 | 15922 | 1 | 2005 | 9 | 4 | 369775 | 2632 |
| 1714 | 1191 | 2 | 8147 | 1 | 2005 | 9 | 2 | 299305 | 2633 |
| 2000 | 1416 | 3 | 18261 | 2 | 2005 | 9 | 3 | 383163 | 2634 |
| 1102 | 850 | 2 | 10464 | 1 | 1980 | 6 | 2 | 165925 | 2635 |
| 1857 | 0 | 2 | 10530 | 1 | 1978 | 7 | 4 | 197883 | 2636 |
| 1083 | 1005 | 2 | 9927 | 1 | 1976 | 7 | 2 | 185113 | 2637 |
| 2318 | 788 | 2 | 9512 | 1 | 2005 | 7 | 3 | 270525 | 2638 |
| 1875 | 548 | 2 | 10530 | 1 | 1975 | 6 | 3 | 193288 | 2639 |
| 1103 | 755 | 2 | 10000 | 0 | 1974 | 6 | 3 | 153459 | 2640 |
| 874 | 20 | 2 | 7200 | 0 | 1971 | 4 | 3 | 103417 | 2641 |
| 1419 | 951 | 2 | 8773 | 0 | 2002 | 6 | 2 | 185646 | 2642 |
| 1092 | 0 | 2 | 2760 | 0 | 1973 | 6 | 3 | 133834 | 2643 |
| 1365 | 402 | 2 | 2160 | 1 | 1973 | 5 | 3 | 143142 | 2644 |
| 1030 | 282 | 1 | 1890 | 0 | 1972 | 6 | 3 | 127333 | 2645 |
| 948 | 276 | 1 | 1680 | 0 | 1972 | 6 | 2 | 125082 | 2646 |
| 1092 | 382 | 1 | 1680 | 0 | 1972 | 6 | 3 | 131301 | 2647 |
| 1069 | 727 | 2 | 4043 | 1 | 1975 | 6 | 2 | 156108 | 2648 |
| 1387 | 373 | 1 | 7514 | 1 | 1967 | 5 | 3 | 134442 | 2649 |
| 1055 | 120 | 1 | 2280 | 0 | 1976 | 7 | 2 | 141716 | 2650 |
| 1456 | 70 | 2 | 2179 | 1 | 1976 | 6 | 3 | 156769 | 2651 |
| 2589 | 1369 | 3 | 16387 | 1 | 2006 | 9 | 4 | 425753 | 2652 |
| 1618 | 0 | 3 | 16163 | 1 | 2004 | 8 | 2 | 242827 | 2653 |
| 1740 | 0 | 3 | 12228 | 0 | 2006 | 7 | 4 | 212523 | 2654 |
| 1868 | 1505 | 3 | 14780 | 1 | 2005 | 9 | 2 | 357073 | 2655 |
| 2206 | 0 | 3 | 13975 | 1 | 2005 | 9 | 4 | 311944 | 2656 |
| 2091 | 1290 | 2 | 9942 | 1 | 2005 | 9 | 3 | 336868 | 2657 |
| 2253 | 0 | 2 | 12867 | 1 | 2005 | 8 | 3 | 266860 | 2658 |
| 2389 | 0 | 3 | 10672 | 1 | 2006 | 8 | 4 | 293041 | 2659 |
| 2358 | 880 | 3 | 11643 | 1 | 2005 | 8 | 4 | 329337 | 2660 |
| 1792 | 1232 | 3 | 13758 | 1 | 2005 | 9 | 2 | 335201 | 2661 |
| 1780 | 1383 | 3 | 14828 | 1 | 2004 | 9 | 2 | 341649 | 2662 |
| 1914 | 994 | 3 | 13215 | 1 | 2004 | 8 | 3 | 298596 | 2663 |
| 1565 | 472 | 2 | 5911 | 1 | 2005 | 9 | 2 | 257421 | 2664 |
| 1686 | 1023 | 3 | 7740 | 1 | 2006 | 9 | 1 | 312515 | 2665 |
| 1666 | 415 | 2 | 6373 | 1 | 2006 | 9 | 2 | 263701 | 2666 |
| 1456 | 0 | 2 | 10237 | 1 | 2005 | 6 | 3 | 171887 | 2667 |
| 1492 | 0 | 2 | 10237 | 0 | 2006 | 7 | 3 | 185484 | 2668 |
| 1326 | 0 | 2 | 11660 | 0 | 2006 | 6 | 3 | 160250 | 2669 |
| 2373 | 0 | 3 | 11631 | 1 | 2004 | 8 | 4 | 291166 | 2670 |
| 1492 | 0 | 2 | 9073 | 0 | 2006 | 7 | 3 | 184764 | 2671 |
| 1364 | 453 | 2 | 3087 | 1 | 2006 | 7 | 2 | 195504 | 2672 |
| 1511 | 1038 | 2 | 2938 | 1 | 2002 | 7 | 2 | 218867 | 2673 |
| 1548 | 1059 | 2 | 3072 | 1 | 2004 | 7 | 2 | 223037 | 2674 |
| 1142 | 16 | 2 | 3010 | 0 | 2005 | 7 | 2 | 165307 | 2675 |
| 1598 | 0 | 2 | 9171 | 1 | 2004 | 7 | 3 | 197356 | 2676 |
| 1889 | 732 | 2 | 8658 | 1 | 2000 | 6 | 3 | 211159 | 2677 |
| 2322 | 0 | 3 | 12104 | 0 | 2006 | 7 | 4 | 249699 | 2678 |
| 1976 | 791 | 3 | 9660 | 1 | 1998 | 8 | 3 | 287187 | 2679 |
| 2234 | 505 | 3 | 9545 | 1 | 2000 | 8 | 3 | 297686 | 2680 |
| 2855 | 1182 | 3 | 9233 | 1 | 2000 | 9 | 4 | 429146 | 2681 |
| 2726 | 527 | 3 | 10019 | 1 | 1995 | 8 | 4 | 336276 | 2682 |
| 3500 | 292 | 3 | 17242 | 1 | 1993 | 9 | 4 | 456416 | 2683 |
| 2494 | 380 | 3 | 10236 | 1 | 1994 | 8 | 4 | 308218 | 2684 |
| 2799 | 247 | 3 | 12585 | 1 | 1993 | 8 | 3 | 333088 | 2685 |
| 1964 | 0 | 2 | 12447 | 1 | 2005 | 8 | 3 | 245935 | 2686 |
| 1670 | 1562 | 3 | 15218 | 1 | 2006 | 8 | 2 | 308030 | 2687 |
| 1504 | 0 | 2 | 10936 | 0 | 2006 | 8 | 3 | 207167 | 2688 |
| 1278 | 24 | 2 | 8640 | 0 | 2006 | 8 | 2 | 194998 | 2689 |
| 2640 | 1836 | 3 | 13162 | 1 | 2006 | 9 | 3 | 459405 | 2690 |
| 1716 | 0 | 2 | 8125 | 0 | 2005 | 6 | 3 | 176028 | 2691 |
| 1142 | 24 | 0 | 7733 | 0 | 2005 | 6 | 3 | 131529 | 2692 |
| 1400 | 0 | 2 | 11024 | 0 | 2005 | 7 | 3 | 180812 | 2693 |
| 1131 | 0 | 0 | 13072 | 0 | 2005 | 6 | 3 | 133034 | 2694 |
| 1686 | 0 | 2 | 7800 | 0 | 2005 | 7 | 3 | 193662 | 2695 |
| 1585 | 0 | 2 | 7632 | 0 | 2005 | 7 | 3 | 188200 | 2696 |
| 1837 | 0 | 2 | 8304 | 0 | 1997 | 6 | 3 | 178419 | 2697 |
| 1731 | 758 | 2 | 9370 | 0 | 1992 | 6 | 3 | 191090 | 2698 |
| 1398 | 904 | 2 | 7175 | 0 | 1990 | 6 | 2 | 176787 | 2699 |
| 1217 | 278 | 2 | 7175 | 0 | 1991 | 6 | 2 | 154246 | 2700 |
| 1320 | 274 | 2 | 9019 | 0 | 1994 | 6 | 3 | 159815 | 2701 |
| 988 | 36 | 2 | 9100 | 0 | 1962 | 5 | 3 | 116820 | 2702 |
| 1654 | 0 | 2 | 8927 | 0 | 1977 | 6 | 4 | 160313 | 2703 |
| 1211 | 612 | 2 | 9240 | 1 | 1962 | 5 | 2 | 141528 | 2704 |
| 984 | 554 | 1 | 9308 | 0 | 1965 | 5 | 3 | 118433 | 2705 |
| 909 | 162 | 1 | 8450 | 0 | 1968 | 5 | 3 | 110262 | 2706 |
| 925 | 181 | 2 | 8638 | 0 | 1963 | 5 | 2 | 118064 | 2707 |
| 1024 | 712 | 1 | 13052 | 0 | 1965 | 5 | 3 | 124009 | 2708 |
| 912 | 644 | 0 | 8020 | 0 | 1964 | 5 | 3 | 109198 | 2709 |
| 941 | 659 | 1 | 8789 | 1 | 1967 | 5 | 3 | 124222 | 2710 |
| 2646 | 1023 | 2 | 14330 | 4 | 1974 | 7 | 3 | 325262 | 2711 |
| 2826 | 1118 | 3 | 11025 | 3 | 1992 | 8 | 3 | 409214 | 2712 |
| 1143 | 0 | 2 | 3628 | 1 | 2004 | 7 | 1 | 172971 | 2713 |
| 1223 | 0 | 2 | 2544 | 0 | 2005 | 7 | 2 | 168423 | 2714 |
| 1524 | 353 | 2 | 2998 | 0 | 2000 | 6 | 2 | 171362 | 2715 |
| 1080 | 0 | 2 | 4447 | 0 | 2003 | 7 | 2 | 162056 | 2716 |
| 1694 | 0 | 1 | 8314 | 1 | 1997 | 7 | 3 | 185607 | 2717 |
| 1568 | 0 | 2 | 7180 | 1 | 2001 | 8 | 3 | 214252 | 2718 |
| 1193 | 962 | 2 | 13110 | 0 | 1972 | 5 | 2 | 147610 | 2719 |
| 1334 | 553 | 2 | 10140 | 0 | 1967 | 7 | 3 | 173502 | 2720 |
| 1051 | 758 | 2 | 9600 | 0 | 1968 | 5 | 3 | 133976 | 2721 |
| 1770 | 361 | 2 | 8640 | 0 | 1968 | 5 | 4 | 153141 | 2722 |
| 976 | 760 | 2 | 9360 | 1 | 1968 | 6 | 2 | 152786 | 2723 |
| 898 | 744 | 1 | 8400 | 0 | 1968 | 5 | 3 | 119358 | 2724 |
| 1051 | 799 | 1 | 9759 | 0 | 1966 | 5 | 3 | 125433 | 2725 |
| 1141 | 602 | 1 | 9600 | 0 | 1967 | 5 | 3 | 125324 | 2726 |
| 1565 | 901 | 1 | 8800 | 2 | 1965 | 6 | 3 | 176047 | 2727 |
| 1488 | 260 | 2 | 10368 | 1 | 1964 | 6 | 3 | 161883 | 2728 |
| 1440 | 360 | 2 | 9350 | 1 | 1964 | 5 | 4 | 144451 | 2729 |
| 1248 | 632 | 1 | 10800 | 0 | 1960 | 5 | 3 | 127837 | 2730 |
| 816 | 574 | 1 | 8550 | 1 | 1934 | 6 | 2 | 121568 | 2731 |
| 1043 | 0 | 1 | 9724 | 1 | 1947 | 5 | 2 | 111591 | 2732 |
| 1433 | 915 | 2 | 9600 | 1 | 1961 | 5 | 3 | 155900 | 2733 |
| 1624 | 40 | 1 | 10858 | 1 | 1952 | 5 | 2 | 134100 | 2734 |
| 1216 | 996 | 1 | 9600 | 0 | 1951 | 5 | 3 | 129820 | 2735 |
| 1728 | 0 | 1 | 9462 | 1 | 1949 | 5 | 3 | 134676 | 2736 |
| 936 | 486 | 1 | 9888 | 0 | 1954 | 5 | 2 | 113447 | 2737 |
| 1584 | 0 | 2 | 8917 | 0 | 1967 | 5 | 4 | 137949 | 2738 |
| 1246 | 939 | 2 | 12700 | 2 | 1964 | 6 | 3 | 175044 | 2739 |
| 1008 | 0 | 2 | 9723 | 0 | 1963 | 6 | 2 | 131254 | 2740 |
| 1364 | 623 | 1 | 8400 | 1 | 1957 | 5 | 3 | 135267 | 2741 |
| 1336 | 203 | 2 | 9610 | 1 | 1958 | 6 | 3 | 151188 | 2742 |
| 1370 | 678 | 1 | 10000 | 1 | 1956 | 5 | 3 | 136930 | 2743 |
| 1124 | 914 | 1 | 10152 | 1 | 1956 | 6 | 3 | 146936 | 2744 |
| 1050 | 824 | 1 | 8092 | 0 | 1954 | 6 | 3 | 134733 | 2745 |
| 1008 | 658 | 1 | 12778 | 0 | 1952 | 5 | 2 | 119126 | 2746 |
| 1575 | 0 | 2 | 10170 | 1 | 1951 | 6 | 2 | 155456 | 2747 |
| 1145 | 271 | 2 | 7700 | 0 | 1956 | 5 | 3 | 123635 | 2748 |
| 1005 | 488 | 1 | 11050 | 1 | 1956 | 5 | 2 | 121654 | 2749 |
| 1056 | 144 | 1 | 13600 | 0 | 1955 | 5 | 3 | 112694 | 2750 |
| 884 | 741 | 1 | 15428 | 0 | 1951 | 5 | 2 | 117187 | 2751 |
| 2039 | 0 | 3 | 21299 | 3 | 1941 | 7 | 3 | 229209 | 2752 |
| 1384 | 494 | 2 | 13300 | 0 | 1956 | 5 | 2 | 139841 | 2753 |
| 2640 | 1018 | 3 | 22136 | 1 | 1925 | 5 | 5 | 221793 | 2754 |
| 1312 | 0 | 2 | 7500 | 0 | 1947 | 6 | 3 | 135128 | 2755 |
| 713 | 0 | 1 | 10410 | 0 | 1930 | 3 | 2 | 75972 | 2756 |
| 715 | 0 | 2 | 10914 | 0 | 1929 | 3 | 2 | 81212 | 2757 |
| 720 | 0 | 1 | 7008 | 0 | 1900 | 4 | 1 | 77841 | 2758 |
| 1595 | 338 | 2 | 7200 | 1 | 1915 | 6 | 3 | 146969 | 2759 |
| 1760 | 0 | 2 | 10818 | 1 | 1910 | 4 | 4 | 118038 | 2760 |
| 1146 | 580 | 1 | 10184 | 1 | 1963 | 6 | 3 | 143595 | 2761 |
| 1207 | 701 | 1 | 9510 | 0 | 1962 | 6 | 3 | 141869 | 2762 |
| 1773 | 913 | 2 | 10800 | 2 | 1961 | 6 | 3 | 199057 | 2763 |
| 1472 | 0 | 2 | 11650 | 1 | 1959 | 7 | 2 | 172139 | 2764 |
| 2448 | 636 | 2 | 18275 | 2 | 1962 | 7 | 3 | 263545 | 2765 |
| 1521 | 455 | 1 | 12144 | 0 | 1950 | 4 | 3 | 118533 | 2766 |
| 1040 | 0 | 2 | 8544 | 0 | 1950 | 3 | 2 | 93108 | 2767 |
| 1556 | 0 | 0 | 8512 | 0 | 1960 | 5 | 4 | 117393 | 2768 |
| 1150 | 781 | 1 | 7000 | 0 | 1961 | 5 | 3 | 125783 | 2769 |
| 1045 | 809 | 2 | 7400 | 0 | 1962 | 7 | 3 | 162409 | 2770 |
| 864 | 468 | 1 | 7000 | 0 | 1962 | 5 | 3 | 111426 | 2771 |
| 1025 | 953 | 0 | 7000 | 0 | 1962 | 5 | 3 | 116717 | 2772 |
| 2014 | 0 | 2 | 9856 | 0 | 1900 | 5 | 5 | 130255 | 2773 |
| 1668 | 276 | 1 | 9600 | 0 | 1948 | 5 | 3 | 131876 | 2774 |
| 1657 | 284 | 1 | 5520 | 1 | 1920 | 4 | 4 | 112594 | 2775 |
| 1416 | 381 | 2 | 9600 | 0 | 1900 | 6 | 3 | 130902 | 2776 |
| 1428 | 208 | 2 | 6451 | 0 | 1900 | 7 | 4 | 139930 | 2777 |
| 1004 | 0 | 1 | 3960 | 1 | 1930 | 7 | 2 | 127808 | 2778 |
| 1951 | 0 | 2 | 7745 | 0 | 1900 | 4 | 4 | 115187 | 2779 |
| 1032 | 143 | 1 | 7741 | 0 | 1924 | 6 | 2 | 113232 | 2780 |
| 844 | 0 | 1 | 5633 | 0 | 1925 | 5 | 2 | 94408 | 2781 |
| 864 | 0 | 1 | 7200 | 0 | 1950 | 4 | 2 | 91674 | 2782 |
| 1376 | 0 | 1 | 7614 | 0 | 1905 | 3 | 2 | 84811 | 2783 |
| 960 | 576 | 2 | 6000 | 0 | 1955 | 5 | 3 | 121622 | 2784 |
| 1566 | 0 | 2 | 6000 | 0 | 1924 | 5 | 5 | 120824 | 2785 |
| 492 | 416 | 1 | 7830 | 0 | 1921 | 3 | 1 | 73886 | 2786 |
| 1182 | 310 | 1 | 9576 | 0 | 1945 | 6 | 3 | 127582 | 2787 |
| 840 | 0 | 1 | 5747 | 0 | 1920 | 3 | 2 | 75503 | 2788 |
| 2104 | 0 | 2 | 6300 | 0 | 1910 | 7 | 5 | 167048 | 2789 |
| 1248 | 0 | 0 | 5976 | 0 | 1920 | 5 | 2 | 97608 | 2790 |
| 960 | 0 | 2 | 9750 | 0 | 1958 | 5 | 3 | 114385 | 2791 |
| 1020 | 0 | 0 | 4761 | 0 | 1918 | 3 | 2 | 73599 | 2792 |
| 1827 | 0 | 1 | 11737 | 1 | 1924 | 6 | 2 | 146150 | 2793 |
| 1162 | 347 | 1 | 6120 | 0 | 1930 | 3 | 3 | 88536 | 2794 |
| 1324 | 0 | 1 | 6120 | 0 | 1930 | 5 | 3 | 108744 | 2795 |
| 816 | 0 | 1 | 11672 | 0 | 1925 | 5 | 2 | 95585 | 2796 |
| 2486 | 0 | 2 | 33120 | 1 | 1962 | 6 | 5 | 218110 | 2797 |
| 1430 | 0 | 2 | 10320 | 0 | 1924 | 4 | 3 | 107672 | 2798 |
| 1330 | 0 | 1 | 7518 | 0 | 1910 | 5 | 3 | 103913 | 2799 |
| 819 | 0 | 0 | 9000 | 0 | 1919 | 5 | 2 | 87299 | 2800 |
| 984 | 343 | 1 | 7200 | 0 | 1930 | 6 | 3 | 115779 | 2801 |
| 1422 | 329 | 1 | 12375 | 1 | 1951 | 5 | 3 | 131556 | 2802 |
| 1921 | 0 | 2 | 11136 | 0 | 1964 | 6 | 4 | 168174 | 2803 |
| 1640 | 0 | 2 | 21370 | 1 | 1950 | 5 | 3 | 146621 | 2804 |
| 1032 | 0 | 1 | 8250 | 1 | 1935 | 5 | 2 | 107318 | 2805 |
| 879 | 0 | 1 | 5220 | 0 | 1936 | 5 | 2 | 97948 | 2806 |
| 1073 | 510 | 1 | 5500 | 0 | 2004 | 7 | 2 | 163585 | 2807 |
| 1064 | 779 | 2 | 11327 | 1 | 1967 | 5 | 3 | 141001 | 2808 |
| 934 | 456 | 1 | 10366 | 0 | 1964 | 6 | 2 | 128882 | 2809 |
| 1059 | 773 | 1 | 9000 | 0 | 1966 | 5 | 3 | 124932 | 2810 |
| 1458 | 194 | 2 | 9535 | 1 | 1967 | 5 | 3 | 143924 | 2811 |
| 1040 | 794 | 2 | 7176 | 1 | 1978 | 6 | 3 | 158179 | 2812 |
| 1967 | 0 | 2 | 9662 | 0 | 1977 | 5 | 6 | 155809 | 2813 |
| 1949 | 483 | 2 | 8235 | 0 | 1977 | 5 | 6 | 165227 | 2814 |
| 872 | 0 | 1 | 17529 | 1 | 1924 | 5 | 2 | 102913 | 2815 |
| 1830 | 810 | 2 | 20355 | 2 | 1967 | 7 | 2 | 233609 | 2816 |
| 1000 | 104 | 2 | 13050 | 2 | 1963 | 5 | 1 | 132298 | 2817 |
| 810 | 535 | 2 | 10820 | 0 | 1971 | 5 | 2 | 123651 | 2818 |
| 1700 | 397 | 1 | 1700 | 0 | 1980 | 7 | 2 | 177793 | 2819 |
| 1350 | 799 | 2 | 9375 | 1 | 1954 | 4 | 3 | 132418 | 2820 |
| 1150 | 230 | 1 | 6488 | 2 | 1942 | 5 | 3 | 120091 | 2821 |
| 2009 | 0 | 3 | 19950 | 2 | 1928 | 6 | 4 | 187809 | 2822 |
| 3672 | 425 | 2 | 19800 | 2 | 1935 | 6 | 5 | 299331 | 2823 |
| 1560 | 612 | 2 | 11679 | 1 | 1962 | 5 | 3 | 156190 | 2824 |
| 1488 | 0 | 2 | 12048 | 1 | 1952 | 5 | 3 | 136959 | 2825 |
| 1057 | 0 | 1 | 10519 | 0 | 1955 | 5 | 3 | 109318 | 2826 |
| 1609 | 468 | 1 | 9525 | 0 | 1953 | 6 | 5 | 148011 | 2827 |
| 2559 | 549 | 2 | 12128 | 1 | 1989 | 6 | 4 | 242101 | 2828 |
| 1440 | 261 | 4 | 9069 | 0 | 1993 | 6 | 2 | 189365 | 2829 |
| 1876 | 0 | 3 | 11003 | 0 | 2005 | 7 | 3 | 220661 | 2830 |
| 1208 | 393 | 2 | 7488 | 0 | 2005 | 7 | 2 | 180282 | 2831 |
| 1846 | 1576 | 2 | 13377 | 1 | 2006 | 6 | 3 | 242641 | 2832 |
| 1590 | 1122 | 3 | 11645 | 0 | 2005 | 8 | 2 | 267670 | 2833 |
| 1809 | 0 | 2 | 10984 | 0 | 2005 | 7 | 3 | 202534 | 2834 |
| 1614 | 56 | 2 | 9316 | 1 | 2005 | 7 | 3 | 200429 | 2835 |
| 1596 | 0 | 2 | 9316 | 0 | 2005 | 7 | 3 | 189841 | 2836 |
| 1388 | 853 | 2 | 12000 | 1 | 1968 | 6 | 3 | 173983 | 2837 |
| 1100 | 0 | 2 | 13015 | 0 | 1996 | 5 | 3 | 132651 | 2838 |
| 1499 | 0 | 2 | 12438 | 1 | 1995 | 6 | 3 | 170757 | 2839 |
| 1425 | 846 | 2 | 8685 | 0 | 1998 | 7 | 3 | 200011 | 2840 |
| 1749 | 500 | 2 | 9272 | 0 | 1999 | 7 | 3 | 209319 | 2841 |
| 1779 | 894 | 2 | 13426 | 1 | 1999 | 7 | 3 | 235863 | 2842 |
| 1388 | 509 | 1 | 8340 | 0 | 1977 | 6 | 3 | 150337 | 2843 |
| 1282 | 595 | 3 | 10385 | 0 | 1978 | 6 | 3 | 170572 | 2844 |
| 864 | 437 | 1 | 7200 | 0 | 1972 | 5 | 3 | 113923 | 2845 |
| 1762 | 456 | 2 | 9930 | 0 | 2002 | 7 | 3 | 210861 | 2846 |
| 1755 | 639 | 2 | 9468 | 1 | 1999 | 6 | 3 | 200805 | 2847 |
| 1358 | 872 | 2 | 11088 | 1 | 2002 | 8 | 1 | 235344 | 2848 |
| 1909 | 0 | 2 | 8726 | 0 | 2002 | 7 | 4 | 203746 | 2849 |
| 2214 | 920 | 3 | 10566 | 1 | 1999 | 8 | 3 | 314230 | 2850 |
| 2049 | 0 | 2 | 21533 | 1 | 1996 | 7 | 4 | 226861 | 2851 |
| 1939 | 796 | 3 | 11250 | 1 | 1998 | 7 | 3 | 257492 | 2852 |
| 1995 | 685 | 2 | 11250 | 1 | 1995 | 7 | 4 | 237341 | 2853 |
| 848 | 717 | 2 | 4435 | 0 | 2003 | 6 | 1 | 152429 | 2854 |
| 1390 | 1000 | 2 | 8810 | 0 | 2003 | 7 | 3 | 205171 | 2855 |
| 1737 | 0 | 2 | 8581 | 0 | 2006 | 7 | 3 | 197448 | 2856 |
| 1611 | 0 | 2 | 8400 | 0 | 2005 | 7 | 3 | 190051 | 2857 |
| 1336 | 996 | 2 | 8772 | 0 | 2005 | 7 | 3 | 203025 | 2858 |
| 1436 | 173 | 2 | 8777 | 0 | 1910 | 4 | 3 | 106047 | 2859 |
| 1012 | 976 | 0 | 7840 | 0 | 1975 | 6 | 4 | 133521 | 2860 |
| 1176 | 847 | 1 | 16133 | 0 | 1969 | 5 | 2 | 135481 | 2861 |
| 1724 | 0 | 2 | 7162 | 1 | 2003 | 7 | 3 | 202492 | 2862 |
| 914 | 475 | 0 | 8050 | 0 | 2002 | 6 | 2 | 131580 | 2863 |
| 2314 | 0 | 2 | 11060 | 1 | 2003 | 7 | 3 | 241668 | 2864 |
| 1072 | 547 | 2 | 3675 | 0 | 2005 | 6 | 2 | 157742 | 2865 |
| 1709 | 0 | 2 | 2522 | 0 | 2004 | 7 | 3 | 191002 | 2866 |
| 936 | 0 | 1 | 6956 | 0 | 1948 | 4 | 3 | 92365 | 2867 |
| 1338 | 0 | 2 | 7822 | 0 | 1915 | 6 | 3 | 125422 | 2868 |
| 1669 | 0 | 1 | 8707 | 0 | 1924 | 4 | 4 | 106328 | 2869 |
| 1482 | 691 | 2 | 16012 | 1 | 1954 | 4 | 3 | 138308 | 2870 |
| 1414 | 0 | 0 | 8248 | 1 | 1922 | 4 | 3 | 96524 | 2871 |
| 498 | 0 | 1 | 8088 | 0 | 1922 | 2 | 1 | 63042 | 2872 |
| 1273 | 0 | 1 | 11388 | 0 | 1910 | 4 | 3 | 93295 | 2873 |
| 1551 | 930 | 1 | 10890 | 0 | 1938 | 5 | 3 | 137069 | 2874 |
| 1340 | 780 | 1 | 6430 | 0 | 1945 | 6 | 3 | 140998 | 2875 |
| 1479 | 424 | 1 | 7000 | 2 | 1926 | 7 | 3 | 160321 | 2876 |
| 1510 | 305 | 1 | 4899 | 0 | 1920 | 6 | 3 | 128870 | 2877 |
| 1636 | 0 | 1 | 9399 | 1 | 1919 | 7 | 4 | 148821 | 2878 |
| 1465 | 646 | 1 | 10164 | 2 | 1939 | 5 | 3 | 139658 | 2879 |
| 1288 | 384 | 1 | 6191 | 0 | 1941 | 5 | 4 | 116238 | 2880 |
| 1550 | 0 | 1 | 21780 | 1 | 1920 | 6 | 3 | 137607 | 2881 |
| 1717 | 602 | 1 | 12400 | 1 | 1940 | 5 | 2 | 145206 | 2882 |
| 1671 | 526 | 2 | 8170 | 1 | 1929 | 7 | 4 | 176947 | 2883 |
| 1609 | 0 | 3 | 12320 | 2 | 1932 | 7 | 3 | 185044 | 2884 |
| 1801 | 0 | 2 | 14210 | 1 | 1930 | 6 | 3 | 157869 | 2885 |
| 2315 | 760 | 1 | 15600 | 3 | 1950 | 5 | 4 | 194977 | 2886 |
| 976 | 305 | 1 | 7288 | 0 | 1942 | 5 | 2 | 107452 | 2887 |
| 1285 | 374 | 2 | 7000 | 0 | 1926 | 6 | 3 | 133714 | 2888 |
| 672 | 0 | 0 | 8534 | 0 | 1925 | 4 | 2 | 76524 | 2889 |
| 641 | 0 | 1 | 7030 | 0 | 1925 | 4 | 2 | 80723 | 2890 |
| 1638 | 0 | 1 | 9060 | 0 | 1957 | 6 | 4 | 141784 | 2891 |
| 729 | 0 | 0 | 12366 | 0 | 1945 | 3 | 2 | 74673 | 2892 |
| 1396 | 0 | 0 | 9000 | 0 | 1951 | 5 | 4 | 109884 | 2893 |
| 936 | 0 | 0 | 8520 | 0 | 1916 | 3 | 2 | 72434 | 2894 |
| 1778 | 1573 | 2 | 5748 | 1 | 2005 | 8 | 2 | 287285 | 2895 |
| 1646 | 1564 | 2 | 3842 | 1 | 2004 | 8 | 2 | 274126 | 2896 |
| 1625 | 776 | 2 | 23580 | 1 | 1979 | 6 | 3 | 196568 | 2897 |
| 1664 | 0 | 2 | 8385 | 0 | 1978 | 6 | 4 | 160884 | 2898 |
| 1491 | 0 | 2 | 9116 | 0 | 2001 | 8 | 3 | 202531 | 2899 |
| 1210 | 576 | 2 | 11080 | 0 | 1975 | 6 | 3 | 155085 | 2900 |
| 1650 | 909 | 2 | 50102 | 2 | 1958 | 6 | 2 | 218953 | 2901 |
| 1403 | 1136 | 2 | 8098 | 0 | 2000 | 6 | 2 | 188328 | 2902 |
| 1960 | 1350 | 3 | 13618 | 2 | 2005 | 8 | 3 | 332820 | 2903 |
| 1838 | 1455 | 3 | 11577 | 1 | 2005 | 9 | 3 | 345618 | 2904 |
| 1600 | 0 | 1 | 31250 | 0 | 1951 | 1 | 3 | 88622 | 2905 |
| 1368 | 1243 | 4 | 7020 | 0 | 1997 | 7 | 2 | 237760 | 2906 |
| 1304 | 0 | 1 | 2665 | 1 | 1977 | 5 | 3 | 125827 | 2907 |
| 874 | 441 | 1 | 10172 | 0 | 1968 | 5 | 3 | 114255 | 2908 |
| 1652 | 149 | 3 | 11836 | 0 | 1970 | 5 | 4 | 156249 | 2909 |
| 630 | 522 | 0 | 1470 | 0 | 1970 | 4 | 1 | 89955 | 2910 |
| 1092 | 252 | 1 | 1484 | 0 | 1972 | 4 | 3 | 104442 | 2911 |
| 1360 | 119 | 1 | 13384 | 1 | 1969 | 5 | 3 | 131950 | 2912 |
| 1092 | 408 | 1 | 1533 | 0 | 1970 | 4 | 3 | 106243 | 2913 |
| 1092 | 0 | 0 | 1526 | 0 | 1970 | 4 | 3 | 93768 | 2914 |
| 1092 | 0 | 0 | 1936 | 0 | 1970 | 4 | 3 | 93897 | 2915 |
| 1092 | 252 | 1 | 1894 | 0 | 1970 | 4 | 3 | 104045 | 2916 |
| 1224 | 1224 | 2 | 20000 | 1 | 1960 | 5 | 4 | 157689 | 2917 |
| 970 | 337 | 0 | 10441 | 0 | 1992 | 5 | 3 | 115160 | 2918 |
| 2000 | 758 | 3 | 9627 | 1 | 1993 | 7 | 3 | 255744 | 2919 |
These seven variables explain 80% of the variability in the sale price. I will use this model to make the Kaggle submission.
write.csv(results, "house-prices-advanced-regression-techniques/submission1.csv", quote = FALSE, row.names = FALSE)
write.csv(dplyr::select(test2, Id, SalePrice), "house-prices-advanced-regression-techniques/submission2.csv", row.names = FALSE)My Kaggle score is 0.15845 and my username is debkabiraj. I am ranked 3487 on the leaderboard.
3.4.1.3 Prediction Submission Scores
3.4.1.3.1 Model 1
Submission1 Score
Submission1 Rank
3.4.1.3.2 Model 2
Submission2 Score
Submission2 Rank
