## Sample data
# Load necessary libraries
library(tidyverse)
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## ✔ purrr 1.0.2
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# Set seed for reproducibility
set.seed(123)
# Generate sample data
n <- 1000 # Number of observations
# Age between 18 and 90
age <- sample(18:90, n, replace = TRUE)
# Introduce errors in age column
age[sample(1:n, 50)] <- "InvalidAge"
# Workclass: Private, Self-emp-not-inc, Self-emp-inc, Federal-gov, Local-gov, State-gov, Without-pay, Never-worked
workclass <- sample(c("Private", "Self-emp-not-inc", "Self-emp-inc", "Federal-gov", "Local-gov", "State-gov", "Without-pay", "Never-worked"), n, replace = TRUE)
# Introduce missing values in workclass column
workclass[sample(1:n, 50)] <- NA
# Education: Bachelors, Some-college, 11th, HS-grad, Prof-school, Assoc-acdm, Assoc-voc, 9th, 7th-8th, 12th, Masters, 1st-4th, 10th, Doctorate, 5th-6th, Preschool
education <- sample(c("Bachelors", "Some-college", "11th", "HS-grad", "Prof-school", "Assoc-acdm", "Assoc-voc", "9th", "7th-8th", "12th", "Masters", "1st-4th", "10th", "Doctorate", "5th-6th", "Preschool"), n, replace = TRUE)
# Introduce inconsistencies in education column
education[sample(1:n, 50)] <- "InvalidEducation"
# Education Number: 1-16
education_num <- sample(1:16, n, replace = TRUE)
# Marital Status: Married-civ-spouse, Divorced, Never-married, Separated, Widowed, Married-spouse-absent, Married-AF-spouse
marital_status <- sample(c("Married-civ-spouse", "Divorced", "Never-married", "Separated", "Widowed", "Married-spouse-absent", "Married-AF-spouse"), n, replace = TRUE)
# Introduce missing values in marital_status column
marital_status[sample(1:n, 50)] <- NA
# Occupation: Tech-support, Craft-repair, Other-service, Sales, Exec-managerial, Prof-specialty, Handlers-cleaners, Machine-op-inspct, Adm-clerical, Farming-fishing, Transport-moving, Priv-house-serv, Protective-serv, Armed-Forces
occupation <- sample(c("Tech-support", "Craft-repair", "Other-service", "Sales", "Exec-managerial", "Prof-specialty", "Handlers-cleaners", "Machine-op-inspct", "Adm-clerical", "Farming-fishing", "Transport-moving", "Priv-house-serv", "Protective-serv", "Armed-Forces"), n, replace = TRUE)
# Introduce errors in occupation column
occupation[sample(1:n, 50)] <- "InvalidOccupation"
# Relationship: Wife, Own-child, Husband, Not-in-family, Other-relative, Unmarried
relationship <- sample(c("Wife", "Own-child", "Husband", "Not-in-family", "Other-relative", "Unmarried"), n, replace = TRUE)
# Introduce missing values in relationship column
relationship[sample(1:n, 50)] <- NA
# Race: White, Asian-Pac-Islander, Amer-Indian-Eskimo, Other, Black
race <- sample(c("White", "Asian-Pac-Islander", "Amer-Indian-Eskimo", "Other", "Black"), n, replace = TRUE)
# Introduce inconsistencies in race column
race[sample(1:n, 50)] <- "InvalidRace"
# Sex: Female, Male
sex <- sample(c("Female", "Male"), n, replace = TRUE)
# Introduce missing values in sex column
sex[sample(1:n, 50)] <- NA
# Capital Gain: 0-99999
capital_gain <- sample(0:99999, n, replace = TRUE)
# Introduce errors in capital_gain column
capital_gain[sample(1:n, 50)] <- -999
# Capital Loss: 0-99999
capital_loss <- sample(0:99999, n, replace = TRUE)
# Introduce errors in capital_loss column
capital_loss[sample(1:n, 50)] <- -999
# Hours per week: 1-99
hours_per_week <- sample(1:99, n, replace = TRUE)
# Introduce missing values in hours_per_week column
hours_per_week[sample(1:n, 50)] <- NA
# Native country: United-States, Cambodia, England, ...
native_country <- sample(c("United-States", "Cambodia", "England", "Puerto-Rico", "Canada", "Germany", "Outlying-US(Guam-USVI-etc)", "India", "Japan", "Greece", "South", "China", "Cuba", "Iran", "Honduras", "Philippines", "Italy", "Poland", "Jamaica", "Vietnam", "Mexico", "Portugal", "Ireland", "France", "Dominican-Republic", "Laos", "Ecuador", "Taiwan", "Haiti", "Columbia", "Hungary", "Guatemala", "Nicaragua", "Scotland", "Thailand", "Yugoslavia", "El-Salvador", "Trinadad&Tobago", "Peru", "Hong", "Holand-Netherlands"), n, replace = TRUE)
# Introduce missing values in native_country column
native_country[sample(1:n, 50)] <- NA
# Income: <=50K, >50K
income <- sample(c("<=50K", ">50K"), n, replace = TRUE, prob = c(0.75, 0.25))
# Create dataframe
sample_dirty_dataset <- data.frame(age, workclass, education, education_num, marital_status, occupation, relationship, race, sex, capital_gain, capital_loss, hours_per_week, native_country, income)
# Print first few rows of the dataset
head(sample_dirty_dataset)
## age workclass education education_num marital_status
## 1 48 Local-gov 7th-8th 1 <NA>
## 2 68 <NA> Prof-school 1 Divorced
## 3 31 State-gov Bachelors 2 Married-spouse-absent
## 4 84 Never-worked 7th-8th 10 Separated
## 5 59 Private 12th 16 Married-civ-spouse
## 6 67 Self-emp-not-inc InvalidEducation 12 Married-spouse-absent
## occupation relationship race sex capital_gain
## 1 Prof-specialty Other-relative Black Male 7826
## 2 Priv-house-serv Unmarried Asian-Pac-Islander Female 84532
## 3 Protective-serv Wife Black Male 35297
## 4 Handlers-cleaners Other-relative Asian-Pac-Islander Male 27074
## 5 Machine-op-inspct Other-relative White Female 73785
## 6 Adm-clerical Husband Black Male 2553
## capital_loss hours_per_week native_country income
## 1 77249 60 Poland >50K
## 2 60981 73 <NA> <=50K
## 3 15093 98 Hungary <=50K
## 4 40203 NA South <=50K
## 5 2056 4 Haiti <=50K
## 6 17031 70 Scotland <=50K
# Remove rows with NA values
sample_dirty_dataset <- sample_dirty_dataset[complete.cases(sample_dirty_dataset), ]
head(sample_dirty_dataset)
## age workclass education education_num marital_status
## 3 31 State-gov Bachelors 2 Married-spouse-absent
## 5 59 Private 12th 16 Married-civ-spouse
## 6 67 Self-emp-not-inc InvalidEducation 12 Married-spouse-absent
## 7 60 Never-worked Prof-school 11 Married-spouse-absent
## 8 31 Self-emp-not-inc 5th-6th 13 Married-AF-spouse
## 9 42 Self-emp-not-inc 10th 10 Married-spouse-absent
## occupation relationship race sex capital_gain
## 3 Protective-serv Wife Black Male 35297
## 5 Machine-op-inspct Other-relative White Female 73785
## 6 Adm-clerical Husband Black Male 2553
## 7 Adm-clerical Other-relative Other Female 19616
## 8 Handlers-cleaners Husband Asian-Pac-Islander Male 91705
## 9 InvalidOccupation Unmarried White Male 53923
## capital_loss hours_per_week native_country income
## 3 15093 98 Hungary <=50K
## 5 2056 4 Haiti <=50K
## 6 17031 70 Scotland <=50K
## 7 51961 15 Cambodia <=50K
## 8 46300 96 Philippines <=50K
## 9 70637 40 Honduras >50K
# Replace negative capital gains with 0
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(capital_gain = ifelse(capital_gain < 0, 0, capital_gain))
# Replace negative capital losses with 0
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(capital_loss = ifelse(capital_loss < 0, 0, capital_loss))
# Function to replace invalid entries with the mode
replace_invalid_with_mode <- function(column, invalid_values) {
mode_value <- as.character(names(which.max(table(column))))
column <- ifelse(column %in% invalid_values, mode_value, column)
return(column)
}
# Define invalid values for each column
invalid_age <- c("InvalidAge")
invalid_education <- c("InvalidEducation")
invalid_occupation <- c("InvalidOccupation")
invalid_race <- c("InvalidRace")
# First, replace invalid values in categorical columns
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
age = replace_invalid_with_mode(age, invalid_age),
education = replace_invalid_with_mode(education, invalid_education),
occupation = replace_invalid_with_mode(occupation, invalid_occupation),
race = replace_invalid_with_mode(race, invalid_race)
)
# Then, recode any remaining invalid values
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
age = na_if(age, "InvalidAge"),
education = case_when(
education %in% c("Bachelors",
"Some-college",
"11th",
"HS-grad",
"Prof-school",
"Assoc-acdm",
"Assoc-voc",
"9th",
"7th-8th",
"12th",
"Masters",
"1st-4th",
"10th",
"Doctorate",
"5th-6th",
"Preschool"
) ~ education, TRUE ~ "InvalidEducation"),
race = case_when(
race %in% c("White", "Asian-Pac-Islander", "Amer-Indian-Eskimo", "Other", "Black") ~ race,
TRUE ~ "InvalidRace"
)
)
library(dlookr)
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library(editrules)
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library(tidyverse)
# Define rules for the dataset
rules <- editset(c(
"age >= 18",
"age <= 90",
"capital_gain >= 0",
"capital_loss >= 0",
"education %in% c('Bachelors', 'Some-college', '11th', 'HS-grad', 'Prof-school', 'Assoc-acdm', 'Assoc-voc', '9th', '7th-8th', '12th', 'Masters', '1st-4th', '10th', 'Doctorate', '5th-6th', 'Preschool')",
"race %in% c('White', 'Asian-Pac-Islander', 'Amer-Indian-Eskimo', 'Other', 'Black')"
))
# Check the dataset against the defined rules
violations <- violatedEdits(rules, sample_dirty_dataset)
# Function to replace invalid entries with the mode
replace_invalid_with_mode <- function(column, invalid_values) {
mode_value <- as.character(names(which.max(table(column))))
column <- ifelse(column %in% invalid_values, mode_value, column)
return(column)
}
# Define invalid values for each column
invalid_education <- c("InvalidEducation")
invalid_occupation <- c("InvalidOccupation")
invalid_race <- c("InvalidRace")
invalid_age <- c("InvalidAge")
# Replace invalid values in categorical columns
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
education = replace_invalid_with_mode(education, invalid_education),
occupation = replace_invalid_with_mode(occupation, invalid_occupation),
race = replace_invalid_with_mode(race, invalid_race),
age = replace_invalid_with_mode(age, invalid_age)
)
# Standardize categorical variables by converting to consistent formats
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
education = case_when(
education %in% c("Bachelors", "Some-college", "11th", "HS-grad", "Prof-school", "Assoc-acdm", "Assoc-voc", "9th", "7th-8th", "12th", "Masters", "1st-4th", "10th", "Doctorate", "5th-6th", "Preschool") ~ education,
TRUE ~ "InvalidEducation"
),
race = case_when(
race %in% c("White", "Asian-Pac-Islander", "Amer-Indian-Eskimo", "Other", "Black") ~ race,
TRUE ~ "InvalidRace"
)
)
library(naniar)
library(mice)
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sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(age = as.numeric(age))
# Impute missing numerical values using median
impute_median <- function(column) {
column[is.na(column)] <- median(column, na.rm = TRUE)
return(column)
}
# Apply imputation to relevant columns
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
age = impute_median(age),
capital_gain = impute_median(capital_gain),
capital_loss = impute_median(capital_loss),
hours_per_week = impute_median(hours_per_week)
)
# Function to replace missing values with the mode
impute_mode <- function(column) {
mode_value <- as.character(names(which.max(table(column, useNA = "no"))))
column[is.na(column)] <- mode_value
return(column)
}
# Apply imputation to relevant columns
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
workclass = impute_mode(workclass),
marital_status = impute_mode(marital_status),
relationship = impute_mode(relationship),
sex = impute_mode(sex),
native_country = impute_mode(native_country)
)
# Remove rows with any remaining missing values
sample_dirty_dataset <- sample_dirty_dataset %>%
drop_na()
# Method 1
boxplot(sample_dirty_dataset$education_num)
boxplot(sample_dirty_dataset$capital_gain)
boxplot(sample_dirty_dataset$capital_loss)
boxplot(sample_dirty_dataset$hours_per_week)
# Method 2
library(ggplot2)
# Define a custom function to create the z-score plot
create_zscore_plot <- function(data, variable_name) {
zscore <- abs(scale(data[[variable_name]]))
# Create a data frame for ggplot
df <- data.frame(index = 1:length(zscore), zscore = zscore)
ggplot(df, aes(x = index, y = zscore)) +
geom_point(alpha = 0.5) + # Use points for better readability
geom_hline(yintercept = 2, col = "red") +
labs(title = paste("Z-score Plot for", variable_name),
x = "Index",
y = "Z-score") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 90, hjust = 1, size = 6)) # Rotate x-axis labels
}
# Apply the function to each variable
create_zscore_plot(sample_dirty_dataset, "education_num")
create_zscore_plot(sample_dirty_dataset, "capital_gain")
create_zscore_plot(sample_dirty_dataset, "capital_loss")
create_zscore_plot(sample_dirty_dataset, "hours_per_week")
# Method 3
library(rrcov)
## Loading required package: robustbase
##
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## education
##
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par(mfrow=c(2,2))
plot(covMcd(sample_dirty_dataset$education_num))
plot(covMcd(sample_dirty_dataset$capital_gain))
plot(covMcd(sample_dirty_dataset$capital_loss))
plot(covMcd(sample_dirty_dataset$hours_per_week))
library(dplyr)
# Convert the variables to numeric (if they are not already) and handle potential conversion issues
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
age = as.numeric(age),
education_num = as.numeric(education_num),
capital_gain = as.numeric(capital_gain),
capital_loss = as.numeric(capital_loss),
hours_per_week = as.numeric(hours_per_week)
)
# Check for NAs introduced by coercion
na_counts <- sample_dirty_dataset %>%
summarise(across(c(age, education_num, capital_gain, capital_loss, hours_per_week), ~ sum(is.na(.))))
# Standardize the numerical variables
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
age_std = scale(age, center = TRUE, scale = TRUE),
education_num_std = scale(education_num, center = TRUE, scale = TRUE),
capital_gain_std = scale(capital_gain, center = TRUE, scale = TRUE),
capital_loss_std = scale(capital_loss, center = TRUE, scale = TRUE),
hours_per_week_std = scale(hours_per_week, center = TRUE, scale = TRUE)
)
# Normalize numerical variables
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
age_norm = (age - min(age, na.rm = TRUE)) / (max(age, na.rm = TRUE) - min(age, na.rm = TRUE)),
education_num_norm = (education_num - min(education_num, na.rm = TRUE)) / (max(education_num, na.rm = TRUE) - min(education_num, na.rm = TRUE)),
capital_gain_norm = (capital_gain - min(capital_gain, na.rm = TRUE)) / (max(capital_gain, na.rm = TRUE) - min(capital_gain, na.rm = TRUE)),
capital_loss_norm = (capital_loss - min(capital_loss, na.rm = TRUE)) / (max(capital_loss, na.rm = TRUE) - min(capital_loss, na.rm = TRUE)),
hours_per_week_norm = (hours_per_week - min(hours_per_week, na.rm = TRUE)) / (max(hours_per_week, na.rm = TRUE) - min(hours_per_week, na.rm = TRUE))
)
# Binning age into categories
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(age_group = cut(age, breaks = c(18, 30, 45, 60, 90), labels = c("18-30", "31-45", "46-60", "61-90"), right = FALSE))
# Binning capital_gain and capital_loss into quartiles
sample_dirty_dataset <- sample_dirty_dataset %>%
mutate(
capital_gain_bin = cut(capital_gain, breaks = quantile(capital_gain, probs = seq(0, 1, 0.25), na.rm = TRUE), include.lowest = TRUE, labels = c("Low", "Medium", "High", "Very High")),
capital_loss_bin = cut(capital_loss, breaks = quantile(capital_loss, probs = seq(0, 1, 0.25), na.rm = TRUE), include.lowest = TRUE, labels = c("Low", "Medium", "High", "Very High"))
)
# Step 10
# 1 Diagnostic Report
# sample_dirty_dataset %>% diagnose_web_report(theme = "blue")
# 2 EDA Report
# sample_dirty_dataset %>% eda_paged_report(theme = "blue")
# 3 Static report
# sample_dirty_dataset %>% transformation_paged_report(theme = "blue")
# Display the updated dataset
print(sample_dirty_dataset)
## age workclass education education_num marital_status
## 1 31 State-gov Bachelors 2 Married-spouse-absent
## 2 59 Private 12th 16 Married-civ-spouse
## 3 67 Self-emp-not-inc 5th-6th 12 Married-spouse-absent
## 4 60 Never-worked Prof-school 11 Married-spouse-absent
## 5 31 Self-emp-not-inc 5th-6th 13 Married-AF-spouse
## 6 42 Self-emp-not-inc 10th 10 Married-spouse-absent
## 7 86 Local-gov Masters 12 Widowed
## 8 74 State-gov Preschool 12 Married-AF-spouse
## 9 26 Local-gov Preschool 16 Divorced
## 10 89 Federal-gov Doctorate 15 Married-AF-spouse
## 11 24 Never-worked 1st-4th 15 Divorced
## 12 26 Private 5th-6th 10 Married-civ-spouse
## 13 60 Self-emp-inc 10th 14 Never-married
## 14 49 Self-emp-inc Doctorate 11 Married-AF-spouse
## 15 26 Private 5th-6th 5 Widowed
## 16 58 Federal-gov 12th 11 Divorced
## 17 40 Federal-gov 10th 7 Married-AF-spouse
## 18 44 Without-pay 1st-4th 5 Separated
## 19 77 Never-worked 7th-8th 4 Married-civ-spouse
## 20 24 Self-emp-inc Doctorate 5 Divorced
## 21 70 Self-emp-inc Preschool 3 Never-married
## 22 55 Private 12th 6 Divorced
## 23 51 Local-gov 10th 1 Never-married
## 24 86 State-gov Doctorate 11 Married-spouse-absent
## 25 89 Federal-gov 9th 15 Divorced
## 26 80 Self-emp-inc Assoc-voc 3 Never-married
## 27 38 Local-gov 10th 14 Divorced
## 28 58 Private 7th-8th 10 Separated
## 29 64 Never-worked Doctorate 5 Married-spouse-absent
## 30 77 State-gov 10th 3 Married-AF-spouse
## 31 23 Private 7th-8th 5 Divorced
## 32 89 Self-emp-inc Prof-school 11 Married-civ-spouse
## 33 56 Local-gov 10th 14 Widowed
## 34 48 State-gov Doctorate 13 Married-civ-spouse
## 35 67 Without-pay Some-college 3 Never-married
## 36 51 State-gov HS-grad 4 Separated
## 37 21 Local-gov Preschool 4 Married-spouse-absent
## 38 30 Self-emp-inc HS-grad 11 Married-AF-spouse
## 39 42 State-gov 9th 1 Divorced
## 40 69 State-gov 5th-6th 4 Married-AF-spouse
## 41 42 Federal-gov Bachelors 9 Married-spouse-absent
## 42 52 Federal-gov Prof-school 14 Married-spouse-absent
## 43 53 Federal-gov Some-college 11 Married-civ-spouse
## 44 47 Self-emp-inc 7th-8th 6 Married-AF-spouse
## 45 29 Never-worked 1st-4th 5 Widowed
## 46 48 Federal-gov Bachelors 14 Divorced
## 47 47 Local-gov 10th 11 Married-spouse-absent
## 48 81 Federal-gov 5th-6th 12 Widowed
## 49 31 State-gov 12th 6 Separated
## 50 88 Self-emp-not-inc 10th 3 Never-married
## 51 84 Federal-gov Bachelors 15 Separated
## 52 40 Self-emp-inc 10th 14 Separated
## 53 54 Private Prof-school 1 Married-spouse-absent
## 54 25 Self-emp-inc Assoc-voc 12 Separated
## 55 68 Never-worked Assoc-acdm 7 Widowed
## 56 67 Local-gov Doctorate 1 Married-AF-spouse
## 57 79 Self-emp-not-inc Assoc-acdm 3 Divorced
## 58 63 Self-emp-inc HS-grad 9 Never-married
## 59 41 Self-emp-not-inc 5th-6th 1 Married-civ-spouse
## 60 24 Federal-gov Assoc-voc 7 Divorced
## 61 43 Self-emp-inc 1st-4th 15 Married-civ-spouse
## 62 49 Never-worked Assoc-voc 4 Divorced
## 63 24 Federal-gov Some-college 2 Separated
## 64 44 Never-worked 7th-8th 10 Divorced
## 65 22 Federal-gov Masters 4 Married-civ-spouse
## 66 87 Federal-gov 5th-6th 4 Never-married
## 67 33 Self-emp-not-inc Some-college 11 Never-married
## 68 41 Private Doctorate 9 Separated
## 69 49 Private 9th 12 Married-AF-spouse
## 70 38 Local-gov 9th 13 Married-spouse-absent
## 71 72 Private Assoc-voc 2 Married-spouse-absent
## 72 56 Federal-gov HS-grad 8 Married-civ-spouse
## 73 71 Private 5th-6th 3 Never-married
## 74 53 Without-pay Some-college 10 Married-spouse-absent
## 75 73 Local-gov Assoc-acdm 15 Divorced
## 76 56 Local-gov 10th 5 Divorced
## 77 85 Private Masters 15 Separated
## 78 18 Without-pay Preschool 2 Widowed
## 79 57 State-gov Masters 4 Separated
## 80 47 Private 12th 10 Married-AF-spouse
## 81 33 Without-pay Prof-school 5 Divorced
## 82 65 Private 10th 15 Widowed
## 83 37 Private HS-grad 13 Separated
## 84 84 Self-emp-inc 7th-8th 15 Married-spouse-absent
## 85 53 Self-emp-inc Preschool 2 Married-spouse-absent
## 86 69 State-gov 11th 2 Married-civ-spouse
## 87 39 Self-emp-not-inc Some-college 10 Divorced
## 88 76 Federal-gov Masters 11 Never-married
## 89 28 Without-pay 9th 9 Divorced
## 90 25 Self-emp-not-inc 12th 9 Married-spouse-absent
## 91 63 Local-gov 11th 1 Widowed
## 92 83 Never-worked Preschool 9 Widowed
## 93 87 State-gov 9th 11 Divorced
## 94 89 Without-pay 5th-6th 16 Married-spouse-absent
## 95 61 Self-emp-inc Bachelors 13 Married-civ-spouse
## 96 49 State-gov 5th-6th 12 Separated
## 97 53 Never-worked HS-grad 6 Widowed
## 98 31 State-gov Some-college 12 Married-spouse-absent
## 99 33 Private 11th 13 Separated
## 100 53 State-gov Assoc-voc 9 Divorced
## 101 57 Local-gov 10th 5 Married-spouse-absent
## 102 89 Private Prof-school 8 Separated
## 103 26 Without-pay 5th-6th 4 Never-married
## 104 75 Private HS-grad 13 Never-married
## 105 41 Local-gov 1st-4th 3 Widowed
## 106 80 Without-pay Assoc-voc 14 Married-AF-spouse
## 107 71 Self-emp-not-inc 10th 14 Married-AF-spouse
## 108 53 State-gov Prof-school 14 Married-AF-spouse
## 109 43 Self-emp-not-inc 5th-6th 15 Married-AF-spouse
## 110 50 Without-pay 5th-6th 15 Never-married
## 111 74 Private 12th 1 Married-spouse-absent
## 112 27 Private 7th-8th 2 Divorced
## 113 70 State-gov 5th-6th 11 Married-spouse-absent
## 114 71 State-gov 12th 5 Never-married
## 115 28 State-gov Doctorate 13 Married-spouse-absent
## 116 42 Never-worked Some-college 2 Separated
## 117 69 Federal-gov Masters 14 Widowed
## 118 43 State-gov 1st-4th 2 Married-civ-spouse
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## 120 42 Federal-gov Masters 6 Separated
## 121 49 State-gov Some-college 6 Married-civ-spouse
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## 123 90 Never-worked Prof-school 3 Married-civ-spouse
## 124 53 Self-emp-inc HS-grad 16 Married-civ-spouse
## 125 23 Without-pay Assoc-voc 7 Divorced
## 126 18 State-gov 11th 7 Married-civ-spouse
## 127 53 Self-emp-inc 5th-6th 3 Married-civ-spouse
## 128 46 Local-gov 1st-4th 10 Married-AF-spouse
## 129 24 Never-worked 12th 4 Divorced
## 130 23 State-gov Assoc-voc 11 Widowed
## 131 48 Never-worked Prof-school 15 Separated
## 132 81 Self-emp-inc Masters 14 Divorced
## 133 74 Never-worked 5th-6th 10 Married-AF-spouse
## 134 37 Without-pay Masters 14 Married-spouse-absent
## 135 52 Self-emp-inc Masters 15 Separated
## 136 50 Never-worked 10th 9 Widowed
## 137 22 State-gov Doctorate 8 Married-AF-spouse
## 138 42 Self-emp-inc 5th-6th 10 Widowed
## 139 25 Federal-gov 11th 3 Married-civ-spouse
## 140 35 Private Preschool 1 Married-spouse-absent
## 141 48 Self-emp-not-inc 1st-4th 10 Separated
## 142 88 Self-emp-not-inc Prof-school 9 Married-AF-spouse
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## 144 65 Self-emp-inc 9th 10 Married-AF-spouse
## 145 62 Self-emp-not-inc 11th 1 Married-spouse-absent
## 146 80 Federal-gov HS-grad 2 Married-spouse-absent
## 147 70 Local-gov 1st-4th 3 Married-AF-spouse
## 148 88 Private Masters 10 Married-spouse-absent
## 149 34 Never-worked 12th 8 Married-civ-spouse
## 150 19 Local-gov 11th 2 Married-civ-spouse
## 151 66 Private Assoc-voc 13 Never-married
## 152 19 Without-pay Prof-school 3 Married-AF-spouse
## 153 30 Private Bachelors 16 Married-spouse-absent
## 154 41 Self-emp-not-inc Preschool 14 Separated
## 155 66 Self-emp-not-inc Doctorate 5 Widowed
## 156 84 Private Prof-school 9 Married-spouse-absent
## 157 53 Self-emp-inc Masters 16 Married-AF-spouse
## 158 54 Private Some-college 10 Widowed
## 159 80 Self-emp-not-inc 10th 10 Widowed
## 160 30 Self-emp-inc Masters 1 Separated
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## 162 87 State-gov Assoc-voc 3 Separated
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## 164 81 Without-pay HS-grad 1 Married-spouse-absent
## 165 52 Without-pay 12th 6 Married-spouse-absent
## 166 65 Federal-gov Bachelors 10 Married-spouse-absent
## 167 83 Never-worked HS-grad 7 Married-spouse-absent
## 168 40 Never-worked 5th-6th 7 Divorced
## 169 26 Private 12th 16 Separated
## 170 53 Local-gov 1st-4th 2 Divorced
## 171 56 Self-emp-not-inc Assoc-voc 13 Married-spouse-absent
## 172 48 Private Preschool 14 Divorced
## 173 53 Without-pay Assoc-voc 4 Widowed
## 174 61 Federal-gov Prof-school 7 Divorced
## 175 58 Without-pay 12th 7 Widowed
## 176 60 Never-worked Masters 12 Divorced
## 177 56 Self-emp-inc Preschool 7 Married-AF-spouse
## 178 54 Self-emp-not-inc 5th-6th 16 Married-civ-spouse
## 179 50 Without-pay Assoc-acdm 7 Never-married
## 180 29 Federal-gov Masters 5 Divorced
## 181 38 Without-pay Prof-school 9 Divorced
## 182 52 Self-emp-inc Prof-school 8 Separated
## 183 67 State-gov 5th-6th 11 Widowed
## 184 64 Self-emp-not-inc Doctorate 15 Divorced
## 185 59 State-gov 5th-6th 2 Married-civ-spouse
## 186 37 Federal-gov 5th-6th 2 Married-AF-spouse
## 187 37 Local-gov 1st-4th 14 Divorced
## 188 53 Local-gov Bachelors 6 Divorced
## 189 25 Local-gov 7th-8th 5 Never-married
## 190 56 Local-gov 5th-6th 10 Married-AF-spouse
## 191 80 State-gov Assoc-acdm 6 Married-spouse-absent
## 192 28 Self-emp-not-inc 5th-6th 16 Divorced
## 193 53 Never-worked 12th 11 Married-spouse-absent
## 194 36 State-gov Assoc-voc 1 Divorced
## 195 30 Self-emp-not-inc Masters 8 Divorced
## 196 48 Without-pay Assoc-voc 13 Married-spouse-absent
## 197 47 State-gov 7th-8th 7 Married-spouse-absent
## 198 33 Local-gov 1st-4th 9 Married-civ-spouse
## 199 53 Self-emp-inc 11th 4 Married-civ-spouse
## 200 67 Never-worked 7th-8th 12 Divorced
## 201 45 Self-emp-not-inc Masters 12 Widowed
## 202 45 Local-gov Masters 12 Divorced
## 203 67 Private 5th-6th 1 Married-civ-spouse
## 204 64 Private 1st-4th 6 Divorced
## 205 68 Self-emp-not-inc 5th-6th 2 Divorced
## 206 23 Self-emp-not-inc 1st-4th 10 Married-spouse-absent
## 207 32 Self-emp-not-inc 5th-6th 10 Married-spouse-absent
## 208 36 Self-emp-inc Bachelors 2 Married-spouse-absent
## 209 76 Without-pay Prof-school 1 Never-married
## 210 20 State-gov Masters 2 Married-civ-spouse
## 211 50 Self-emp-inc Bachelors 8 Divorced
## 212 53 Never-worked Doctorate 8 Married-civ-spouse
## 213 53 Without-pay Bachelors 5 Separated
## 214 26 Local-gov Assoc-voc 8 Married-AF-spouse
## 215 70 Never-worked 11th 13 Married-spouse-absent
## 216 28 Private Assoc-voc 2 Never-married
## 217 25 State-gov 1st-4th 12 Married-AF-spouse
## 218 22 Without-pay Preschool 7 Married-civ-spouse
## 219 46 Self-emp-inc Doctorate 5 Married-AF-spouse
## 220 67 Self-emp-not-inc 1st-4th 14 Separated
## 221 87 Federal-gov Prof-school 4 Never-married
## 222 43 Private Assoc-acdm 9 Divorced
## 223 90 Private Preschool 10 Married-spouse-absent
## 224 28 Self-emp-inc Assoc-acdm 2 Separated
## 225 23 Self-emp-not-inc 11th 12 Married-spouse-absent
## 226 53 Private Assoc-voc 4 Married-civ-spouse
## 227 44 State-gov 12th 13 Separated
## 228 85 Self-emp-not-inc 11th 1 Never-married
## 229 53 Self-emp-inc Prof-school 10 Married-civ-spouse
## 230 57 State-gov 1st-4th 10 Divorced
## 231 23 State-gov 11th 13 Widowed
## 232 53 Without-pay 10th 10 Married-AF-spouse
## 233 72 Never-worked HS-grad 1 Married-spouse-absent
## 234 27 Never-worked 9th 5 Married-spouse-absent
## 235 42 Federal-gov HS-grad 13 Never-married
## 236 55 Federal-gov Bachelors 15 Married-AF-spouse
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## 238 39 Without-pay 7th-8th 12 Never-married
## 239 53 Self-emp-inc 10th 4 Married-spouse-absent
## 240 64 Federal-gov Masters 4 Never-married
## 241 77 Local-gov 10th 7 Married-civ-spouse
## 242 80 Self-emp-inc Doctorate 5 Separated
## 243 54 Without-pay Prof-school 16 Married-AF-spouse
## 244 63 Self-emp-inc 5th-6th 12 Divorced
## 245 64 Self-emp-not-inc Assoc-voc 8 Married-civ-spouse
## 246 33 Self-emp-inc 5th-6th 16 Separated
## 247 36 Federal-gov Prof-school 3 Separated
## 248 89 Private 9th 2 Never-married
## 249 48 Self-emp-inc Assoc-acdm 12 Married-civ-spouse
## 250 65 Never-worked Assoc-acdm 4 Divorced
## 251 79 Without-pay HS-grad 14 Widowed
## 252 47 State-gov Masters 5 Married-civ-spouse
## 253 78 Local-gov 10th 5 Widowed
## 254 51 Never-worked Bachelors 2 Separated
## 255 74 Without-pay 12th 2 Divorced
## 256 55 Never-worked 5th-6th 6 Never-married
## 257 80 Without-pay 5th-6th 3 Separated
## 258 63 State-gov 12th 6 Separated
## 259 53 Self-emp-not-inc 5th-6th 13 Married-civ-spouse
## 260 35 Never-worked 1st-4th 7 Married-AF-spouse
## 261 89 Private 12th 2 Separated
## 262 38 Self-emp-inc 9th 10 Divorced
## 263 74 State-gov Assoc-acdm 2 Married-spouse-absent
## 264 88 Without-pay Doctorate 7 Widowed
## 265 89 Self-emp-inc Masters 2 Never-married
## 266 23 State-gov Assoc-acdm 2 Separated
## 267 57 Self-emp-inc HS-grad 9 Divorced
## 268 66 Self-emp-inc 5th-6th 9 Married-AF-spouse
## 269 86 Private Doctorate 13 Never-married
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## 271 37 Federal-gov Prof-school 14 Married-spouse-absent
## 272 19 Federal-gov 5th-6th 9 Separated
## 273 79 Without-pay HS-grad 7 Married-AF-spouse
## 274 27 Federal-gov Assoc-voc 4 Married-AF-spouse
## 275 76 Private 7th-8th 9 Married-AF-spouse
## 276 66 Self-emp-inc HS-grad 6 Married-civ-spouse
## 277 24 Self-emp-inc Prof-school 9 Married-spouse-absent
## 278 78 Without-pay 1st-4th 2 Divorced
## 279 53 Local-gov Bachelors 9 Separated
## 280 53 Private Some-college 9 Divorced
## 281 21 Private 9th 2 Married-spouse-absent
## 282 46 Self-emp-inc Assoc-voc 9 Married-spouse-absent
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## 284 73 State-gov Prof-school 10 Never-married
## 285 67 Without-pay HS-grad 12 Married-spouse-absent
## 286 65 Self-emp-not-inc Assoc-acdm 10 Widowed
## 287 20 State-gov 5th-6th 2 Never-married
## 288 50 Never-worked Assoc-voc 2 Married-AF-spouse
## 289 51 Local-gov 5th-6th 10 Separated
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## 291 81 Federal-gov HS-grad 10 Married-spouse-absent
## 292 57 Self-emp-inc 5th-6th 2 Married-AF-spouse
## 293 75 Federal-gov 5th-6th 4 Widowed
## 294 37 Self-emp-not-inc Doctorate 6 Widowed
## 295 42 Local-gov 7th-8th 15 Never-married
## 296 88 Federal-gov 1st-4th 4 Widowed
## 297 57 Federal-gov Preschool 4 Widowed
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## 299 39 Federal-gov HS-grad 10 Divorced
## 300 53 Without-pay Assoc-acdm 4 Widowed
## 301 50 Self-emp-inc HS-grad 8 Widowed
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## 304 89 Local-gov Assoc-acdm 2 Married-spouse-absent
## 305 41 Self-emp-inc Some-college 12 Divorced
## 306 77 Local-gov Some-college 16 Married-civ-spouse
## 307 40 State-gov Assoc-voc 14 Separated
## 308 34 Never-worked 5th-6th 1 Separated
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## 310 60 Never-worked 10th 2 Divorced
## 311 40 Federal-gov 9th 9 Married-spouse-absent
## 312 62 Self-emp-inc 7th-8th 6 Divorced
## 313 53 Self-emp-inc Preschool 16 Divorced
## 314 53 State-gov 5th-6th 8 Widowed
## 315 84 Never-worked Doctorate 8 Widowed
## 316 56 Self-emp-not-inc 7th-8th 9 Never-married
## 317 50 Federal-gov 1st-4th 10 Married-spouse-absent
## 318 55 Local-gov 11th 2 Married-spouse-absent
## 319 45 State-gov Some-college 10 Married-AF-spouse
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## 321 27 Never-worked Assoc-voc 14 Married-spouse-absent
## 322 58 Self-emp-not-inc Prof-school 16 Married-spouse-absent
## 323 25 State-gov Some-college 3 Separated
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## 325 83 Self-emp-inc 11th 16 Separated
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## 328 74 State-gov 11th 3 Married-spouse-absent
## 329 90 Local-gov Assoc-acdm 12 Married-AF-spouse
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## 331 57 Never-worked Assoc-acdm 13 Married-civ-spouse
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## 333 90 Federal-gov 5th-6th 2 Married-spouse-absent
## 334 24 Local-gov HS-grad 1 Separated
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## 336 37 State-gov 1st-4th 15 Widowed
## 337 24 Never-worked 10th 14 Married-civ-spouse
## 338 62 Local-gov HS-grad 4 Widowed
## 339 42 Self-emp-not-inc 12th 10 Widowed
## 340 30 Without-pay Assoc-acdm 3 Married-AF-spouse
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## 342 29 Without-pay 9th 5 Married-AF-spouse
## 343 25 Local-gov 5th-6th 4 Married-AF-spouse
## 344 88 Local-gov HS-grad 8 Separated
## 345 32 Never-worked 1st-4th 4 Married-AF-spouse
## 346 66 Self-emp-inc 1st-4th 16 Separated
## 347 56 Local-gov 12th 7 Married-spouse-absent
## 348 52 Never-worked Some-college 1 Married-AF-spouse
## 349 53 Federal-gov 12th 8 Separated
## 350 53 Never-worked Assoc-voc 13 Married-spouse-absent
## 351 25 Self-emp-not-inc Masters 3 Married-AF-spouse
## 352 84 Never-worked 9th 13 Married-AF-spouse
## 353 70 Federal-gov Prof-school 16 Married-civ-spouse
## 354 45 Local-gov 5th-6th 5 Married-AF-spouse
## 355 53 Private 10th 16 Widowed
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## 357 81 Federal-gov Bachelors 3 Widowed
## 358 36 Self-emp-not-inc 5th-6th 12 Separated
## 359 18 State-gov Doctorate 14 Married-AF-spouse
## 360 69 Federal-gov HS-grad 16 Widowed
## 361 36 Self-emp-inc Some-college 9 Never-married
## 362 52 Never-worked 1st-4th 1 Married-civ-spouse
## 363 50 State-gov 7th-8th 16 Widowed
## 364 86 Self-emp-inc Masters 6 Married-AF-spouse
## 365 78 State-gov 5th-6th 5 Married-civ-spouse
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## 367 58 Private Some-college 7 Never-married
## 368 53 Without-pay 9th 16 Widowed
## 369 66 Self-emp-not-inc HS-grad 15 Married-civ-spouse
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## 371 81 State-gov Doctorate 14 Separated
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## 375 82 Federal-gov Assoc-acdm 14 Separated
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## 378 69 Federal-gov Prof-school 4 Married-civ-spouse
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## 380 53 Never-worked Prof-school 10 Never-married
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## 383 41 Self-emp-inc Assoc-acdm 4 Married-civ-spouse
## 384 85 Never-worked Preschool 8 Never-married
## 385 84 Self-emp-not-inc 10th 11 Never-married
## 386 28 Self-emp-not-inc HS-grad 6 Divorced
## 387 22 Never-worked 5th-6th 1 Married-spouse-absent
## 388 28 Never-worked Preschool 7 Divorced
## 389 77 Never-worked 12th 13 Married-AF-spouse
## 390 62 Never-worked Doctorate 3 Never-married
## 391 41 Without-pay 5th-6th 8 Married-AF-spouse
## 392 27 Local-gov Assoc-voc 2 Separated
## 393 81 Local-gov 7th-8th 8 Married-spouse-absent
## 394 89 Private Assoc-acdm 15 Separated
## 395 61 State-gov Prof-school 2 Divorced
## 396 53 Private Prof-school 14 Never-married
## 397 49 Never-worked 11th 4 Never-married
## 398 56 Local-gov 1st-4th 1 Married-spouse-absent
## 399 50 Never-worked 11th 8 Divorced
## 400 19 Private 12th 7 Never-married
## 401 87 Self-emp-inc Masters 15 Widowed
## 402 76 Self-emp-inc 9th 13 Married-civ-spouse
## 403 64 Federal-gov Preschool 10 Widowed
## 404 26 Private 1st-4th 2 Married-civ-spouse
## 405 40 State-gov 12th 5 Never-married
## 406 32 Without-pay 9th 4 Divorced
## 407 89 Without-pay 5th-6th 16 Married-civ-spouse
## 408 38 Local-gov 5th-6th 8 Never-married
## 409 65 Self-emp-inc Some-college 1 Never-married
## 410 90 Without-pay HS-grad 6 Married-AF-spouse
## 411 73 Local-gov Assoc-voc 3 Married-AF-spouse
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## 413 88 Private 5th-6th 11 Married-civ-spouse
## 414 73 Local-gov Some-college 6 Married-civ-spouse
## 415 28 State-gov Bachelors 2 Married-spouse-absent
## 416 77 Private Masters 14 Separated
## 417 84 Without-pay Masters 11 Divorced
## 418 75 Federal-gov 1st-4th 6 Married-spouse-absent
## 419 57 Private 10th 7 Divorced
## 420 30 Never-worked 1st-4th 5 Separated
## 421 25 Private Some-college 1 Divorced
## 422 19 Without-pay 1st-4th 6 Married-spouse-absent
## 423 23 Federal-gov Doctorate 4 Married-spouse-absent
## 424 34 Self-emp-inc 1st-4th 11 Married-spouse-absent
## 425 49 Private Assoc-voc 11 Married-spouse-absent
## 426 88 Self-emp-not-inc 12th 15 Never-married
## 427 89 Local-gov Assoc-voc 14 Divorced
## 428 34 Never-worked 10th 14 Married-AF-spouse
## 429 72 Federal-gov 9th 4 Never-married
## 430 32 Self-emp-not-inc Doctorate 16 Married-civ-spouse
## 431 44 Self-emp-not-inc 5th-6th 10 Separated
## 432 67 Self-emp-inc 11th 6 Divorced
## 433 35 Self-emp-not-inc Assoc-voc 9 Widowed
## 434 70 Private 9th 2 Married-civ-spouse
## 435 80 Private 5th-6th 7 Married-spouse-absent
## 436 53 Without-pay 12th 11 Married-spouse-absent
## 437 48 Never-worked 10th 6 Married-AF-spouse
## 438 35 Never-worked 12th 13 Separated
## 439 61 Self-emp-inc Preschool 14 Widowed
## 440 38 Never-worked Assoc-voc 11 Divorced
## 441 53 Without-pay Masters 13 Widowed
## 442 59 State-gov Some-college 6 Widowed
## 443 86 State-gov 12th 10 Married-civ-spouse
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## 445 79 Federal-gov Preschool 12 Widowed
## 446 81 Private Bachelors 8 Married-spouse-absent
## 447 68 Self-emp-inc Assoc-voc 16 Married-AF-spouse
## 448 35 Without-pay Bachelors 7 Divorced
## 449 27 Never-worked 5th-6th 6 Separated
## 450 89 Without-pay Masters 1 Never-married
## 451 19 Federal-gov HS-grad 2 Married-spouse-absent
## 452 53 Self-emp-not-inc 5th-6th 1 Divorced
## 453 44 Private HS-grad 11 Divorced
## 454 40 Never-worked 7th-8th 8 Divorced
## 455 20 Self-emp-not-inc 1st-4th 9 Married-spouse-absent
## 456 75 Private Preschool 13 Married-spouse-absent
## 457 53 Self-emp-not-inc 5th-6th 14 Divorced
## 458 48 Self-emp-inc Doctorate 11 Married-AF-spouse
## 459 35 State-gov 5th-6th 16 Married-civ-spouse
## 460 63 Private Doctorate 1 Married-AF-spouse
## 461 26 Private Masters 10 Widowed
## 462 34 Private 12th 10 Married-civ-spouse
## 463 24 State-gov 5th-6th 2 Married-civ-spouse
## 464 25 Local-gov Bachelors 14 Married-AF-spouse
## 465 82 State-gov Preschool 12 Widowed
## 466 26 Private 12th 16 Married-AF-spouse
## 467 42 Without-pay Assoc-voc 16 Married-spouse-absent
## 468 19 Private Prof-school 9 Never-married
## 469 28 Without-pay Bachelors 4 Separated
## 470 37 Never-worked Preschool 11 Separated
## 471 28 Self-emp-not-inc Prof-school 12 Married-AF-spouse
## 472 35 State-gov Preschool 11 Widowed
## 473 31 Federal-gov Prof-school 4 Married-civ-spouse
## 474 84 Without-pay Masters 9 Married-AF-spouse
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## 476 40 Without-pay Preschool 12 Married-spouse-absent
## 477 54 Private Assoc-voc 14 Never-married
## 478 77 Local-gov HS-grad 12 Married-AF-spouse
## 479 42 Self-emp-not-inc Some-college 13 Married-spouse-absent
## 480 43 Local-gov 5th-6th 6 Married-AF-spouse
## 481 61 Never-worked Some-college 3 Widowed
## 482 53 Never-worked Bachelors 7 Divorced
## 483 33 Self-emp-inc 7th-8th 11 Married-spouse-absent
## 484 56 Private 11th 12 Widowed
## 485 82 Without-pay HS-grad 8 Divorced
## 486 75 Without-pay Assoc-acdm 4 Married-civ-spouse
## 487 73 Self-emp-not-inc Assoc-acdm 16 Widowed
## 488 60 Local-gov 7th-8th 1 Married-AF-spouse
## 489 84 Without-pay 7th-8th 11 Widowed
## 490 73 Self-emp-inc Masters 1 Married-civ-spouse
## 491 39 Never-worked 11th 9 Married-AF-spouse
## 492 34 Private 7th-8th 4 Married-spouse-absent
## 493 31 Self-emp-not-inc 12th 5 Married-AF-spouse
## 494 41 Federal-gov 5th-6th 3 Married-civ-spouse
## 495 53 State-gov 10th 15 Divorced
## 496 37 Federal-gov 9th 9 Widowed
## 497 67 Self-emp-inc Assoc-acdm 8 Widowed
## 498 34 Federal-gov 1st-4th 13 Never-married
## 499 26 Self-emp-inc 10th 1 Never-married
## 500 52 Never-worked 5th-6th 6 Widowed
## 501 80 Without-pay Assoc-voc 5 Married-civ-spouse
## 502 33 Local-gov 9th 9 Married-civ-spouse
## 503 69 Never-worked Doctorate 10 Separated
## 504 71 State-gov 5th-6th 9 Never-married
## 505 43 Local-gov Prof-school 5 Married-spouse-absent
## 506 30 Local-gov Some-college 1 Never-married
## 507 53 Local-gov Doctorate 4 Separated
## 508 64 State-gov Assoc-acdm 12 Separated
## 509 45 Without-pay Assoc-acdm 15 Divorced
## 510 61 Federal-gov 11th 16 Separated
## 511 71 Self-emp-inc 5th-6th 14 Married-AF-spouse
## 512 42 Local-gov 9th 2 Married-spouse-absent
## 513 46 Private 11th 10 Widowed
## 514 37 Self-emp-inc Some-college 14 Married-spouse-absent
## 515 53 Private Assoc-acdm 5 Separated
## 516 73 Private 1st-4th 13 Married-spouse-absent
## 517 61 Federal-gov HS-grad 15 Married-AF-spouse
## 518 89 Never-worked 1st-4th 6 Married-AF-spouse
## 519 55 Never-worked Bachelors 1 Divorced
## 520 65 Self-emp-inc 9th 7 Never-married
## 521 32 Federal-gov 1st-4th 2 Married-AF-spouse
## 522 82 Never-worked 12th 9 Separated
## 523 27 Self-emp-not-inc 12th 4 Married-civ-spouse
## 524 42 Never-worked Some-college 10 Married-spouse-absent
## 525 69 Never-worked HS-grad 7 Married-spouse-absent
## 526 54 Federal-gov 1st-4th 3 Separated
## 527 44 Never-worked 10th 8 Widowed
## 528 90 Self-emp-not-inc 5th-6th 13 Separated
## 529 51 Self-emp-not-inc Some-college 5 Married-civ-spouse
## 530 53 Self-emp-inc Bachelors 15 Separated
## 531 66 Self-emp-not-inc Prof-school 3 Separated
## 532 52 Never-worked 11th 6 Married-civ-spouse
## 533 46 Federal-gov 5th-6th 7 Married-civ-spouse
## 534 88 Self-emp-inc 10th 12 Separated
## 535 51 Self-emp-not-inc 11th 5 Married-AF-spouse
## 536 90 Private 12th 8 Never-married
## 537 64 Private Masters 16 Never-married
## 538 18 Without-pay 7th-8th 8 Married-spouse-absent
## 539 27 Local-gov 5th-6th 3 Widowed
## 540 58 Self-emp-not-inc 12th 10 Married-spouse-absent
## 541 58 State-gov 5th-6th 1 Widowed
## 542 56 Self-emp-not-inc 11th 4 Married-AF-spouse
## 543 49 Self-emp-inc Assoc-acdm 11 Married-AF-spouse
## 544 78 Federal-gov 5th-6th 15 Never-married
## 545 51 State-gov Some-college 5 Married-civ-spouse
## 546 47 Local-gov 10th 4 Divorced
## 547 87 Self-emp-inc 5th-6th 11 Widowed
## 548 85 Local-gov 9th 1 Divorced
## 549 84 Never-worked Assoc-acdm 13 Married-AF-spouse
## 550 63 Self-emp-inc Some-college 15 Divorced
## 551 76 Self-emp-inc Doctorate 10 Separated
## 552 65 Self-emp-not-inc 1st-4th 16 Widowed
## 553 84 Self-emp-inc 7th-8th 4 Never-married
## 554 18 State-gov Preschool 10 Married-AF-spouse
## 555 61 Never-worked 7th-8th 16 Separated
## 556 63 Local-gov 5th-6th 8 Married-civ-spouse
## 557 67 Self-emp-inc Masters 6 Separated
## 558 43 Self-emp-not-inc 7th-8th 3 Married-civ-spouse
## 559 53 Federal-gov Doctorate 2 Separated
## 560 53 Local-gov 9th 11 Widowed
## 561 74 Private 1st-4th 1 Separated
## 562 28 Self-emp-inc Masters 2 Married-AF-spouse
## 563 68 Local-gov Some-college 8 Divorced
## 564 47 Self-emp-not-inc Some-college 5 Separated
## 565 28 State-gov 1st-4th 11 Never-married
## 566 83 Never-worked Prof-school 15 Widowed
## 567 39 Local-gov 5th-6th 15 Married-spouse-absent
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## 10 Exec-managerial Other-relative Amer-Indian-Eskimo Female 28267
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## 17 Farming-fishing Own-child Black Female 69634
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## 25 Transport-moving Own-child Black Male 81984
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## 35 Prof-specialty Other-relative Amer-Indian-Eskimo Female 45499
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## 38 Armed-Forces Not-in-family Black Male 53753
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## 41 Craft-repair Other-relative Other Female 89400
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## 44 Tech-support Husband Black Male 55035
## 45 Farming-fishing Own-child Amer-Indian-Eskimo Female 93710
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## 53 Craft-repair Own-child Asian-Pac-Islander Female 25093
## 54 Prof-specialty Husband Amer-Indian-Eskimo Female 93550
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## 61 Transport-moving Unmarried Asian-Pac-Islander Male 80429
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## 90 Craft-repair Husband Amer-Indian-Eskimo Female 82708
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## 113 Priv-house-serv Not-in-family Amer-Indian-Eskimo Female 17636
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## 149 Craft-repair Not-in-family Other Female 80924
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## 290 Transport-moving Not-in-family Amer-Indian-Eskimo Female 31710
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## 306 Protective-serv Wife Asian-Pac-Islander Male 83126
## 307 Sales Own-child Asian-Pac-Islander Female 0
## 308 Farming-fishing Own-child Other Female 39044
## 309 Other-service Other-relative Asian-Pac-Islander Female 50668
## 310 Machine-op-inspct Unmarried Asian-Pac-Islander Female 57588
## 311 Handlers-cleaners Own-child Asian-Pac-Islander Male 0
## 312 Adm-clerical Unmarried Black Male 73738
## 313 Prof-specialty Not-in-family White Female 0
## 314 Craft-repair Unmarried Amer-Indian-Eskimo Female 90631
## 315 Armed-Forces Other-relative Asian-Pac-Islander Female 44495
## 316 Handlers-cleaners Wife White Female 43345
## 317 Armed-Forces Husband Asian-Pac-Islander Female 64071
## 318 Prof-specialty Not-in-family Black Male 44399
## 319 Other-service Unmarried White Female 14150
## 320 Armed-Forces Not-in-family Black Male 0
## 321 Craft-repair Unmarried Black Male 51050
## 322 Prof-specialty Other-relative Other Female 85453
## 323 Transport-moving Wife Other Female 92619
## 324 Transport-moving Other-relative Amer-Indian-Eskimo Male 91200
## 325 Priv-house-serv Own-child Asian-Pac-Islander Male 68820
## 326 Tech-support Not-in-family White Female 49230
## 327 Protective-serv Other-relative Asian-Pac-Islander Female 0
## 328 Transport-moving Unmarried Asian-Pac-Islander Female 52072
## 329 Adm-clerical Wife White Male 7723
## 330 Sales Unmarried Other Female 92714
## 331 Armed-Forces Unmarried Asian-Pac-Islander Male 43315
## 332 Machine-op-inspct Unmarried Amer-Indian-Eskimo Female 12025
## 333 Prof-specialty Own-child Asian-Pac-Islander Male 52039
## 334 Adm-clerical Not-in-family Other Female 127
## 335 Tech-support Other-relative Asian-Pac-Islander Female 25723
## 336 Machine-op-inspct Husband Black Female 87065
## 337 Other-service Own-child Black Male 50614
## 338 Armed-Forces Own-child Other Male 5755
## 339 Farming-fishing Not-in-family Amer-Indian-Eskimo Male 60604
## 340 Priv-house-serv Own-child Other Male 76369
## 341 Farming-fishing Other-relative White Male 0
## 342 Armed-Forces Wife Amer-Indian-Eskimo Female 57430
## 343 Tech-support Own-child Asian-Pac-Islander Male 72948
## 344 Priv-house-serv Other-relative Black Female 96526
## 345 Tech-support Wife Amer-Indian-Eskimo Female 37661
## 346 Exec-managerial Unmarried Black Male 71144
## 347 Tech-support Unmarried White Male 93071
## 348 Farming-fishing Other-relative Black Male 51220
## 349 Sales Husband Amer-Indian-Eskimo Female 51520
## 350 Transport-moving Other-relative Black Female 56174
## 351 Tech-support Not-in-family Black Male 71800
## 352 Sales Unmarried Black Male 54500
## 353 Tech-support Own-child Amer-Indian-Eskimo Male 0
## 354 Machine-op-inspct Other-relative Amer-Indian-Eskimo Male 32048
## 355 Other-service Unmarried Asian-Pac-Islander Female 71040
## 356 Transport-moving Unmarried White Female 65392
## 357 Handlers-cleaners Wife Amer-Indian-Eskimo Male 6575
## 358 Exec-managerial Other-relative Asian-Pac-Islander Female 89983
## 359 Exec-managerial Own-child Asian-Pac-Islander Male 36529
## 360 Sales Husband Other Female 74688
## 361 Farming-fishing Husband Asian-Pac-Islander Female 14786
## 362 Craft-repair Not-in-family Other Male 47496
## 363 Machine-op-inspct Unmarried White Male 78806
## 364 Priv-house-serv Other-relative Amer-Indian-Eskimo Female 4008
## 365 Armed-Forces Husband White Female 3428
## 366 Farming-fishing Husband Asian-Pac-Islander Female 81315
## 367 Prof-specialty Not-in-family Amer-Indian-Eskimo Female 75973
## 368 Armed-Forces Unmarried Amer-Indian-Eskimo Female 24356
## 369 Exec-managerial Own-child Amer-Indian-Eskimo Female 5118
## 370 Priv-house-serv Own-child White Female 44637
## 371 Transport-moving Unmarried Amer-Indian-Eskimo Female 419
## 372 Prof-specialty Not-in-family Asian-Pac-Islander Female 82501
## 373 Exec-managerial Not-in-family Asian-Pac-Islander Female 39260
## 374 Machine-op-inspct Husband Amer-Indian-Eskimo Female 39414
## 375 Tech-support Not-in-family White Female 0
## 376 Farming-fishing Unmarried Amer-Indian-Eskimo Male 63341
## 377 Transport-moving Unmarried White Male 79297
## 378 Priv-house-serv Other-relative Amer-Indian-Eskimo Female 87674
## 379 Machine-op-inspct Unmarried Amer-Indian-Eskimo Male 40628
## 380 Tech-support Wife Asian-Pac-Islander Male 26776
## 381 Handlers-cleaners Other-relative Black Male 22147
## 382 Tech-support Wife Asian-Pac-Islander Male 78296
## 383 Armed-Forces Husband Other Male 13339
## 384 Farming-fishing Not-in-family Amer-Indian-Eskimo Male 20054
## 385 Protective-serv Wife Other Female 70882
## 386 Machine-op-inspct Not-in-family White Male 58404
## 387 Transport-moving Unmarried Asian-Pac-Islander Female 71780
## 388 Other-service Other-relative Asian-Pac-Islander Male 34295
## 389 Sales Unmarried Black Male 44316
## 390 Armed-Forces Other-relative Black Male 12756
## 391 Armed-Forces Husband Amer-Indian-Eskimo Female 53024
## 392 Prof-specialty Own-child Asian-Pac-Islander Female 7234
## 393 Tech-support Unmarried White Male 3233
## 394 Machine-op-inspct Not-in-family White Female 31097
## 395 Tech-support Own-child Amer-Indian-Eskimo Male 83657
## 396 Other-service Other-relative Other Female 38616
## 397 Tech-support Wife Asian-Pac-Islander Male 15939
## 398 Tech-support Wife Other Female 30616
## 399 Protective-serv Not-in-family Black Female 72612
## 400 Adm-clerical Other-relative Other Male 61586
## 401 Armed-Forces Not-in-family Amer-Indian-Eskimo Female 0
## 402 Adm-clerical Own-child Other Female 67041
## 403 Adm-clerical Unmarried Amer-Indian-Eskimo Female 65616
## 404 Machine-op-inspct Unmarried Amer-Indian-Eskimo Male 38660
## 405 Machine-op-inspct Wife Asian-Pac-Islander Female 99257
## 406 Priv-house-serv Own-child Other Female 99411
## 407 Craft-repair Other-relative Black Male 90512
## 408 Craft-repair Wife Amer-Indian-Eskimo Male 60624
## 409 Craft-repair Not-in-family Black Female 55796
## 410 Prof-specialty Not-in-family Other Male 47488
## 411 Priv-house-serv Wife Other Female 91877
## 412 Transport-moving Unmarried Asian-Pac-Islander Female 31607
## 413 Tech-support Not-in-family Other Male 5104
## 414 Machine-op-inspct Wife Other Female 5741
## 415 Craft-repair Husband Asian-Pac-Islander Male 70166
## 416 Other-service Wife White Female 56881
## 417 Tech-support Other-relative White Female 93928
## 418 Handlers-cleaners Husband White Female 232
## 419 Tech-support Unmarried Black Male 92127
## 420 Farming-fishing Husband Amer-Indian-Eskimo Male 14436
## 421 Protective-serv Husband Amer-Indian-Eskimo Female 72272
## 422 Exec-managerial Own-child White Male 33108
## 423 Handlers-cleaners Unmarried White Female 58294
## 424 Adm-clerical Other-relative Amer-Indian-Eskimo Male 20696
## 425 Exec-managerial Unmarried Other Female 56791
## 426 Craft-repair Wife Asian-Pac-Islander Male 60255
## 427 Adm-clerical Husband Amer-Indian-Eskimo Female 6757
## 428 Machine-op-inspct Husband White Male 0
## 429 Transport-moving Husband White Male 39129
## 430 Farming-fishing Not-in-family Amer-Indian-Eskimo Male 54826
## 431 Transport-moving Wife Amer-Indian-Eskimo Female 42057
## 432 Priv-house-serv Wife Other Male 58166
## 433 Handlers-cleaners Wife Other Male 38357
## 434 Prof-specialty Not-in-family Other Male 75097
## 435 Sales Not-in-family Asian-Pac-Islander Female 98660
## 436 Sales Husband Black Female 32368
## 437 Tech-support Husband Black Male 98314
## 438 Exec-managerial Own-child Amer-Indian-Eskimo Male 18170
## 439 Tech-support Not-in-family Other Female 29029
## 440 Machine-op-inspct Other-relative Asian-Pac-Islander Female 14210
## 441 Exec-managerial Unmarried Amer-Indian-Eskimo Female 94139
## 442 Protective-serv Wife White Female 94306
## 443 Sales Wife Asian-Pac-Islander Male 3747
## 444 Handlers-cleaners Husband Amer-Indian-Eskimo Male 18353
## 445 Sales Other-relative Amer-Indian-Eskimo Male 97283
## 446 Armed-Forces Husband Amer-Indian-Eskimo Male 44650
## 447 Machine-op-inspct Other-relative Amer-Indian-Eskimo Female 13627
## 448 Farming-fishing Other-relative Black Female 58226
## 449 Armed-Forces Wife Black Female 57692
## 450 Machine-op-inspct Wife Black Female 0
## 451 Sales Other-relative Amer-Indian-Eskimo Female 10908
## 452 Other-service Wife Black Female 61317
## 453 Handlers-cleaners Unmarried Asian-Pac-Islander Female 49788
## 454 Adm-clerical Own-child Black Female 11127
## 455 Tech-support Husband Asian-Pac-Islander Male 0
## 456 Priv-house-serv Unmarried White Male 32341
## 457 Tech-support Other-relative White Female 61253
## 458 Adm-clerical Husband Other Male 91447
## 459 Machine-op-inspct Own-child Amer-Indian-Eskimo Female 16384
## 460 Transport-moving Not-in-family White Male 76304
## 461 Handlers-cleaners Other-relative Asian-Pac-Islander Female 25712
## 462 Sales Unmarried Black Male 89451
## 463 Exec-managerial Husband White Female 33625
## 464 Sales Husband Amer-Indian-Eskimo Male 41270
## 465 Farming-fishing Husband Amer-Indian-Eskimo Female 50287
## 466 Protective-serv Unmarried Other Male 55867
## 467 Other-service Wife Asian-Pac-Islander Female 80793
## 468 Prof-specialty Own-child Asian-Pac-Islander Female 97939
## 469 Sales Husband Black Male 83630
## 470 Adm-clerical Husband Black Male 30881
## 471 Prof-specialty Not-in-family Other Female 75914
## 472 Priv-house-serv Husband Amer-Indian-Eskimo Female 31475
## 473 Other-service Unmarried Other Male 33287
## 474 Armed-Forces Own-child White Female 47221
## 475 Armed-Forces Wife White Male 27637
## 476 Transport-moving Other-relative Other Male 14827
## 477 Sales Unmarried Black Male 75734
## 478 Exec-managerial Husband Other Female 63494
## 479 Machine-op-inspct Own-child Amer-Indian-Eskimo Male 45581
## 480 Adm-clerical Wife Black Female 84893
## 481 Exec-managerial Not-in-family Black Female 65424
## 482 Priv-house-serv Own-child Other Male 71879
## 483 Handlers-cleaners Wife White Female 56881
## 484 Exec-managerial Unmarried Other Male 53290
## 485 Craft-repair Not-in-family Amer-Indian-Eskimo Female 6698
## 486 Farming-fishing Unmarried Other Male 85853
## 487 Other-service Other-relative White Female 68143
## 488 Craft-repair Wife Other Female 12023
## 489 Farming-fishing Husband White Female 9715
## 490 Adm-clerical Other-relative Other Female 81235
## 491 Handlers-cleaners Unmarried Other Male 47691
## 492 Handlers-cleaners Not-in-family White Female 79520
## 493 Machine-op-inspct Not-in-family Other Female 8162
## 494 Farming-fishing Other-relative Other Female 32625
## 495 Farming-fishing Not-in-family Asian-Pac-Islander Male 92103
## 496 Sales Husband White Male 12320
## 497 Exec-managerial Not-in-family Asian-Pac-Islander Female 28240
## 498 Handlers-cleaners Not-in-family Black Female 74645
## 499 Tech-support Unmarried Amer-Indian-Eskimo Female 32140
## 500 Transport-moving Wife Amer-Indian-Eskimo Female 29307
## 501 Exec-managerial Other-relative Black Male 91954
## 502 Farming-fishing Husband Amer-Indian-Eskimo Female 83094
## 503 Protective-serv Other-relative Asian-Pac-Islander Female 29318
## 504 Exec-managerial Own-child Other Female 95583
## 505 Adm-clerical Unmarried Other Male 34472
## 506 Tech-support Other-relative White Male 56632
## 507 Protective-serv Wife Amer-Indian-Eskimo Male 40989
## 508 Exec-managerial Not-in-family Black Female 91581
## 509 Protective-serv Husband Asian-Pac-Islander Male 32957
## 510 Transport-moving Not-in-family Asian-Pac-Islander Male 0
## 511 Tech-support Wife Asian-Pac-Islander Male 96345
## 512 Armed-Forces Wife Black Female 86706
## 513 Machine-op-inspct Other-relative Asian-Pac-Islander Male 9477
## 514 Exec-managerial Wife Other Female 58153
## 515 Tech-support Own-child Black Female 32494
## 516 Adm-clerical Wife Other Female 6423
## 517 Transport-moving Other-relative Asian-Pac-Islander Female 72727
## 518 Handlers-cleaners Other-relative White Female 34884
## 519 Priv-house-serv Own-child Other Female 55510
## 520 Prof-specialty Not-in-family Other Male 54441
## 521 Other-service Husband Amer-Indian-Eskimo Female 50265
## 522 Exec-managerial Unmarried White Female 58114
## 523 Adm-clerical Own-child Other Female 42723
## 524 Exec-managerial Other-relative Other Female 42061
## 525 Prof-specialty Not-in-family Black Male 77590
## 526 Adm-clerical Husband White Female 18098
## 527 Transport-moving Own-child Black Male 20265
## 528 Machine-op-inspct Husband Amer-Indian-Eskimo Female 19665
## 529 Tech-support Not-in-family White Male 31317
## 530 Transport-moving Own-child Asian-Pac-Islander Female 13983
## 531 Handlers-cleaners Husband White Male 66370
## 532 Exec-managerial Not-in-family White Female 64105
## 533 Sales Other-relative Amer-Indian-Eskimo Female 79109
## 534 Other-service Husband Black Female 55484
## 535 Handlers-cleaners Wife Asian-Pac-Islander Female 29201
## 536 Prof-specialty Husband Amer-Indian-Eskimo Male 67648
## 537 Prof-specialty Own-child Amer-Indian-Eskimo Female 28878
## 538 Exec-managerial Own-child Black Male 24261
## 539 Sales Not-in-family Black Female 22871
## 540 Machine-op-inspct Own-child White Male 67696
## 541 Craft-repair Unmarried White Female 47973
## 542 Priv-house-serv Own-child Amer-Indian-Eskimo Female 92226
## 543 Armed-Forces Unmarried White Female 73123
## 544 Adm-clerical Own-child Amer-Indian-Eskimo Female 55333
## 545 Craft-repair Husband Asian-Pac-Islander Male 89357
## 546 Protective-serv Wife Amer-Indian-Eskimo Female 91407
## 547 Machine-op-inspct Own-child Black Female 35016
## 548 Tech-support Husband Asian-Pac-Islander Female 28398
## 549 Adm-clerical Other-relative Asian-Pac-Islander Female 2207
## 550 Adm-clerical Own-child Black Female 72141
## 551 Adm-clerical Not-in-family Black Female 25142
## 552 Exec-managerial Wife Asian-Pac-Islander Male 37653
## 553 Armed-Forces Not-in-family Amer-Indian-Eskimo Female 33953
## 554 Machine-op-inspct Husband Black Male 23819
## 555 Adm-clerical Own-child Other Female 39708
## 556 Machine-op-inspct Not-in-family Asian-Pac-Islander Male 81671
## 557 Transport-moving Husband Asian-Pac-Islander Female 91688
## 558 Armed-Forces Own-child Amer-Indian-Eskimo Female 44690
## 559 Craft-repair Own-child Amer-Indian-Eskimo Female 76187
## 560 Transport-moving Wife White Male 50548
## 561 Tech-support Other-relative Black Male 97555
## 562 Machine-op-inspct Own-child Amer-Indian-Eskimo Male 97091
## 563 Farming-fishing Husband White Male 80294
## 564 Exec-managerial Own-child Black Male 71899
## 565 Tech-support Husband White Female 87107
## 566 Tech-support Husband White Male 72981
## 567 Sales Husband Black Female 94566
## 568 Handlers-cleaners Unmarried White Male 84939
## 569 Priv-house-serv Not-in-family Black Male 45506
## 570 Tech-support Other-relative Asian-Pac-Islander Male 84427
## 571 Exec-managerial Wife Amer-Indian-Eskimo Male 64103
## 572 Priv-house-serv Unmarried White Female 91111
## 573 Prof-specialty Other-relative Black Male 31804
## 574 Tech-support Unmarried Amer-Indian-Eskimo Female 96872
## 575 Other-service Wife White Female 75689
## 576 Craft-repair Wife White Female 56316
## 577 Protective-serv Unmarried White Male 49479
## 578 Sales Other-relative Asian-Pac-Islander Female 5340
## 579 Handlers-cleaners Own-child Amer-Indian-Eskimo Male 0
## 580 Exec-managerial Husband Amer-Indian-Eskimo Male 9210
## 581 Exec-managerial Unmarried Asian-Pac-Islander Male 18098
## 582 Armed-Forces Not-in-family White Male 15014
## 583 Prof-specialty Husband White Female 74966
## 584 Adm-clerical Not-in-family Amer-Indian-Eskimo Female 83593
## 585 Transport-moving Other-relative Amer-Indian-Eskimo Male 28583
## 586 Sales Wife White Male 99839
## 587 Handlers-cleaners Other-relative Amer-Indian-Eskimo Female 50267
## 588 Sales Husband Black Female 48872
## 589 Priv-house-serv Unmarried Other Male 62285
## 590 Armed-Forces Own-child White Male 75805
## 591 Tech-support Not-in-family Black Male 13597
## 592 Tech-support Unmarried Asian-Pac-Islander Female 73768
## 593 Exec-managerial Wife Amer-Indian-Eskimo Male 80204
## 594 Priv-house-serv Not-in-family Amer-Indian-Eskimo Female 0
## 595 Exec-managerial Wife Amer-Indian-Eskimo Female 58973
## 596 Tech-support Own-child Amer-Indian-Eskimo Male 75288
## 597 Armed-Forces Husband Asian-Pac-Islander Female 2995
## 598 Other-service Wife Asian-Pac-Islander Male 12516
## 599 Transport-moving Husband Amer-Indian-Eskimo Male 10477
## 600 Protective-serv Unmarried Asian-Pac-Islander Female 33209
## 601 Machine-op-inspct Unmarried White Male 32573
## 602 Armed-Forces Husband Other Male 9285
## 603 Protective-serv Other-relative Black Female 42459
## 604 Sales Wife Other Male 87728
## 605 Prof-specialty Own-child Other Male 23542
## 606 Handlers-cleaners Husband Amer-Indian-Eskimo Male 47614
## 607 Priv-house-serv Other-relative Amer-Indian-Eskimo Female 20686
## 608 Tech-support Husband Amer-Indian-Eskimo Male 30945
## 609 Priv-house-serv Unmarried Asian-Pac-Islander Male 49799
## 610 Transport-moving Husband Other Female 69076
## 611 Craft-repair Not-in-family Other Male 61163
## 612 Priv-house-serv Other-relative Amer-Indian-Eskimo Female 0
## 613 Tech-support Unmarried Black Male 25638
## 614 Tech-support Husband Amer-Indian-Eskimo Male 32811
## 615 Other-service Husband Black Male 65650
## 616 Priv-house-serv Unmarried Asian-Pac-Islander Female 87875
## 617 Craft-repair Wife Amer-Indian-Eskimo Male 81585
## 618 Tech-support Not-in-family Asian-Pac-Islander Female 79379
## 619 Transport-moving Wife Asian-Pac-Islander Female 30762
## 620 Protective-serv Wife Black Male 75772
## 621 Other-service Unmarried Other Male 10263
## 622 Protective-serv Other-relative Amer-Indian-Eskimo Female 403
## 623 Transport-moving Unmarried Other Female 91557
## 624 Exec-managerial Wife Other Male 47295
## 625 Armed-Forces Other-relative White Male 39778
## 626 Machine-op-inspct Unmarried Asian-Pac-Islander Female 9645
## 627 Protective-serv Own-child Other Female 20953
## 628 Armed-Forces Unmarried Amer-Indian-Eskimo Female 46217
## 629 Sales Wife Asian-Pac-Islander Male 96926
## 630 Tech-support Not-in-family White Male 33785
## 631 Prof-specialty Wife Asian-Pac-Islander Male 34200
## 632 Handlers-cleaners Other-relative Black Female 24361
## 633 Handlers-cleaners Other-relative Asian-Pac-Islander Female 6786
## 634 Machine-op-inspct Unmarried White Male 90540
## 635 Protective-serv Other-relative Amer-Indian-Eskimo Male 37704
## 636 Sales Own-child Amer-Indian-Eskimo Male 33325
## 637 Sales Wife Black Female 73349
## 638 Sales Unmarried Asian-Pac-Islander Female 74691
## 639 Prof-specialty Husband White Male 63253
## 640 Transport-moving Own-child Amer-Indian-Eskimo Female 69280
## 641 Transport-moving Wife White Male 24854
## 642 Farming-fishing Not-in-family Black Female 56576
## 643 Other-service Husband Black Female 18434
## 644 Prof-specialty Own-child Amer-Indian-Eskimo Female 52485
## 645 Exec-managerial Own-child Amer-Indian-Eskimo Male 1569
## 646 Craft-repair Wife Amer-Indian-Eskimo Male 72018
## 647 Prof-specialty Husband White Female 66644
## 648 Armed-Forces Wife Amer-Indian-Eskimo Female 27994
## 649 Prof-specialty Unmarried Other Male 53247
## 650 Exec-managerial Other-relative Asian-Pac-Islander Male 4494
## 651 Transport-moving Unmarried Other Male 24992
## 652 Machine-op-inspct Other-relative Black Male 18557
## 653 Farming-fishing Own-child Amer-Indian-Eskimo Female 40766
## 654 Adm-clerical Own-child Asian-Pac-Islander Female 83041
## 655 Exec-managerial Unmarried Amer-Indian-Eskimo Male 81367
## 656 Tech-support Own-child Other Male 41924
## 657 Protective-serv Other-relative Amer-Indian-Eskimo Male 45219
## 658 Adm-clerical Wife Other Female 16780
## 659 Craft-repair Unmarried Asian-Pac-Islander Female 53570
## 660 Armed-Forces Husband Asian-Pac-Islander Male 71606
## 661 Craft-repair Not-in-family White Male 1536
## 662 Transport-moving Husband Asian-Pac-Islander Male 9275
## 663 Protective-serv Other-relative Black Female 96375
## 664 Machine-op-inspct Not-in-family Asian-Pac-Islander Female 4379
## 665 Machine-op-inspct Wife Other Female 53435
## 666 Other-service Other-relative Other Female 39927
## 667 Tech-support Not-in-family Other Female 4509
## 668 Farming-fishing Not-in-family White Male 21474
## 669 Craft-repair Wife White Female 95518
## 670 Machine-op-inspct Unmarried Amer-Indian-Eskimo Male 41812
## 671 Exec-managerial Wife Black Male 51570
## 672 Exec-managerial Other-relative Amer-Indian-Eskimo Male 85331
## 673 Tech-support Husband Black Female 88852
## 674 Prof-specialty Not-in-family White Female 0
## 675 Tech-support Wife Black Male 49953
## 676 Tech-support Wife Asian-Pac-Islander Male 92271
## 677 Other-service Unmarried White Female 60635
## 678 Adm-clerical Husband Other Male 10909
## 679 Tech-support Wife Amer-Indian-Eskimo Female 55473
## 680 Protective-serv Own-child Black Female 54800
## 681 Craft-repair Not-in-family White Male 29845
## 682 Machine-op-inspct Not-in-family White Male 33685
## 683 Craft-repair Unmarried Other Female 80187
## 684 Craft-repair Wife Black Male 55872
## 685 Tech-support Husband Amer-Indian-Eskimo Female 33419
## 686 Handlers-cleaners Unmarried Amer-Indian-Eskimo Female 29550
## 687 Tech-support Other-relative White Female 36268
## 688 Exec-managerial Wife Black Male 3020
## 689 Craft-repair Other-relative Other Male 93439
## 690 Tech-support Unmarried Other Male 80856
## 691 Sales Not-in-family Asian-Pac-Islander Female 12196
## 692 Armed-Forces Other-relative Asian-Pac-Islander Female 31391
## 693 Tech-support Other-relative White Male 23775
## 694 Armed-Forces Other-relative Other Female 64562
## 695 Protective-serv Wife White Male 16932
## 696 Adm-clerical Other-relative Amer-Indian-Eskimo Male 0
## 697 Machine-op-inspct Husband White Female 0
## 698 Exec-managerial Unmarried Black Female 51941
## 699 Machine-op-inspct Husband Other Female 26542
## 700 Machine-op-inspct Wife Asian-Pac-Islander Male 5268
## 701 Adm-clerical Not-in-family Other Female 67434
## 702 Sales Wife Black Male 10236
## 703 Tech-support Other-relative Black Female 32961
## 704 Machine-op-inspct Not-in-family White Male 0
## 705 Tech-support Wife White Male 14127
## 706 Transport-moving Unmarried Black Female 0
## 707 Adm-clerical Husband Amer-Indian-Eskimo Male 18019
## 708 Prof-specialty Husband Other Male 28237
## 709 Handlers-cleaners Husband Black Male 11999
## 710 Handlers-cleaners Other-relative Asian-Pac-Islander Male 42342
## 711 Protective-serv Own-child Amer-Indian-Eskimo Female 13511
## 712 Armed-Forces Not-in-family Black Female 80618
## 713 Other-service Not-in-family Other Male 72117
## 714 Handlers-cleaners Unmarried White Female 21162
## 715 Handlers-cleaners Not-in-family Other Female 79463
## 716 Other-service Unmarried White Male 97097
## 717 Protective-serv Unmarried White Male 93341
## 718 Adm-clerical Unmarried Asian-Pac-Islander Male 17210
## 719 Other-service Own-child White Female 17621
## 720 Armed-Forces Not-in-family Amer-Indian-Eskimo Male 24999
## 721 Other-service Not-in-family Amer-Indian-Eskimo Female 18123
## 722 Adm-clerical Not-in-family White Female 85388
## 723 Tech-support Wife Black Male 42294
## 724 Craft-repair Wife Other Female 20
## 725 Tech-support Wife Other Female 92879
## 726 Farming-fishing Own-child Amer-Indian-Eskimo Male 86915
## 727 Handlers-cleaners Unmarried White Female 54365
## 728 Armed-Forces Other-relative Amer-Indian-Eskimo Male 86717
## 729 Craft-repair Wife White Female 57902
## 730 Prof-specialty Other-relative Other Male 15650
## 731 Prof-specialty Wife Other Female 68672
## 732 Farming-fishing Not-in-family White Female 50664
## capital_loss hours_per_week native_country income age_std
## 1 15093 98 Hungary <=50K -1.10155350
## 2 2056 4 Haiti <=50K 0.25201008
## 3 17031 70 Scotland <=50K 0.63874253
## 4 51961 15 Cambodia <=50K 0.30035164
## 5 46300 96 Philippines <=50K -1.10155350
## 6 70637 40 Honduras >50K -0.56979638
## 7 52751 11 Thailand <=50K 1.55723210
## 8 75593 35 Holand-Netherlands <=50K 0.97713342
## 9 7469 81 United-States <=50K -1.34326128
## 10 31943 70 El-Salvador <=50K 1.70225677
## 11 89927 88 Italy >50K -1.43994439
## 12 50089 20 Nicaragua <=50K -1.34326128
## 13 95362 2 Haiti <=50K 0.30035164
## 14 31387 70 Mexico >50K -0.23140548
## 15 54995 50 Greece <=50K -1.34326128
## 16 55714 90 Hong <=50K 0.20366852
## 17 85711 16 China <=50K -0.66647949
## 18 7525 61 Hong <=50K -0.47311326
## 19 99095 71 China <=50K 1.12215809
## 20 84470 6 Taiwan <=50K -1.43994439
## 21 95169 99 Yugoslavia <=50K 0.78376720
## 22 10235 87 India >50K 0.05864386
## 23 14809 12 India <=50K -0.13472237
## 24 20845 41 Japan <=50K 1.55723210
## 25 30056 8 Greece >50K 1.70225677
## 26 99847 33 Vietnam >50K 1.26718276
## 27 29258 84 Laos >50K -0.76316260
## 28 49182 40 Ecuador <=50K 0.20366852
## 29 36206 3 Scotland <=50K 0.49371786
## 30 49469 49 Honduras >50K 1.12215809
## 31 78853 74 India <=50K -1.48828595
## 32 28736 7 Ireland >50K 1.70225677
## 33 3780 80 Thailand <=50K 0.10698541
## 34 37719 82 Philippines <=50K -0.27974704
## 35 53845 19 Canada <=50K 0.63874253
## 36 29346 21 Japan <=50K -0.13472237
## 37 3307 94 Columbia <=50K -1.58496906
## 38 91887 9 Poland <=50K -1.14989505
## 39 25911 63 Guatemala <=50K -0.56979638
## 40 70820 3 Poland <=50K 0.73542564
## 41 73542 68 Nicaragua <=50K -0.56979638
## 42 5175 13 Haiti <=50K -0.08638081
## 43 0 65 Japan <=50K -0.03803926
## 44 19377 83 Peru <=50K -0.32808859
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## 500 37733 45 Hong <=50K -0.08638081
## 501 5929 69 Jamaica <=50K 1.26718276
## 502 54620 50 United-States <=50K -1.00487038
## 503 41675 13 Outlying-US(Guam-USVI-etc) <=50K 0.73542564
## 504 92351 52 Puerto-Rico <=50K 0.83210876
## 505 87284 81 Hong <=50K -0.52145482
## 506 65048 1 Jamaica <=50K -1.14989505
## 507 2558 87 Guatemala <=50K -0.03803926
## 508 78571 77 Iran >50K 0.49371786
## 509 72832 67 Ecuador <=50K -0.42477171
## 510 14798 93 Portugal <=50K 0.34869319
## 511 34544 70 Mexico <=50K 0.83210876
## 512 28721 94 Scotland <=50K -0.56979638
## 513 2126 66 Peru <=50K -0.37643015
## 514 39279 75 England <=50K -0.81150416
## 515 92252 29 Haiti >50K -0.03803926
## 516 77573 75 Laos <=50K 0.92879187
## 517 2198 3 Germany >50K 0.34869319
## 518 30236 27 Yugoslavia <=50K 1.70225677
## 519 45139 64 Jamaica <=50K 0.05864386
## 520 97395 30 Portugal <=50K 0.54205942
## 521 57063 45 Honduras <=50K -1.05321194
## 522 4473 64 Canada >50K 1.36386587
## 523 80628 49 Puerto-Rico <=50K -1.29491972
## 524 67088 45 Scotland <=50K -0.56979638
## 525 65654 56 Columbia <=50K 0.73542564
## 526 9209 25 Guatemala <=50K 0.01030230
## 527 26725 62 Ecuador <=50K -0.47311326
## 528 83105 86 Laos >50K 1.75059832
## 529 28885 70 Jamaica >50K -0.13472237
## 530 90703 8 Dominican-Republic <=50K -0.03803926
## 531 75098 8 Portugal <=50K 0.59040097
## 532 0 51 Hungary <=50K -0.08638081
## 533 66701 65 China <=50K -0.37643015
## 534 45066 66 India <=50K 1.65391521
## 535 51534 14 Japan <=50K -0.13472237
## 536 70891 46 Nicaragua <=50K 1.75059832
## 537 19234 11 Japan >50K 0.49371786
## 538 72960 74 England >50K -1.72999373
## 539 96240 36 Vietnam <=50K -1.29491972
## 540 78982 46 South <=50K 0.20366852
## 541 90542 68 Philippines <=50K 0.20366852
## 542 56875 12 El-Salvador <=50K 0.10698541
## 543 1751 23 Hungary <=50K -0.23140548
## 544 5722 24 Peru <=50K 1.17049965
## 545 10566 11 United-States <=50K -0.13472237
## 546 46391 61 Iran <=50K -0.32808859
## 547 23763 46 Honduras <=50K 1.60557366
## 548 74553 75 India <=50K 1.50889054
## 549 43244 5 Guatemala <=50K 1.46054899
## 550 0 74 England <=50K 0.44537631
## 551 41769 72 Guatemala <=50K 1.07381654
## 552 21420 48 Japan <=50K 0.54205942
## 553 10060 13 Cuba >50K 1.46054899
## 554 12592 18 Nicaragua <=50K -1.72999373
## 555 83249 94 India <=50K 0.34869319
## 556 76204 37 Guatemala <=50K 0.44537631
## 557 68236 73 Ecuador <=50K 0.63874253
## 558 5743 54 Hong >50K -0.52145482
## 559 42283 87 Puerto-Rico <=50K -0.03803926
## 560 0 65 Yugoslavia <=50K -0.03803926
## 561 98999 61 Germany <=50K 0.97713342
## 562 68109 89 Hong >50K -1.24657816
## 563 39661 32 El-Salvador <=50K 0.68708409
## 564 33040 35 Ecuador >50K -0.32808859
## 565 67925 56 Holand-Netherlands <=50K -1.24657816
## 566 89054 7 Puerto-Rico <=50K 1.41220743
## 567 16657 52 Thailand <=50K -0.71482105
## 568 16246 17 Dominican-Republic <=50K -0.95652883
## 569 0 51 England <=50K -1.53662750
## 570 44953 17 China <=50K 1.21884121
## 571 38561 94 Germany <=50K -0.08638081
## 572 63222 15 Greece <=50K -0.71482105
## 573 2904 4 Laos <=50K 1.26718276
## 574 25816 92 Ecuador <=50K -0.08638081
## 575 0 66 India <=50K -0.32808859
## 576 27739 39 Puerto-Rico <=50K 1.55723210
## 577 62901 98 France <=50K -1.68165217
## 578 90575 38 Columbia <=50K -0.66647949
## 579 93712 46 Taiwan >50K -0.76316260
## 580 67985 9 South <=50K -0.85984571
## 581 59325 36 South <=50K -1.34326128
## 582 15990 67 Cuba <=50K -0.23140548
## 583 61227 91 Dominican-Republic <=50K 0.54205942
## 584 13091 58 Laos <=50K -0.81150416
## 585 0 32 Ireland <=50K 0.88045031
## 586 10071 97 England <=50K -0.27974704
## 587 97812 23 Philippines <=50K 1.65391521
## 588 37544 28 Laos <=50K 0.97713342
## 589 50037 38 China <=50K -0.08638081
## 590 49143 79 Philippines >50K 0.83210876
## 591 32889 76 Nicaragua <=50K -1.14989505
## 592 23551 75 Vietnam <=50K 1.50889054
## 593 6712 11 Japan <=50K 0.78376720
## 594 80230 26 Hungary <=50K 0.20366852
## 595 46337 90 Cambodia >50K -1.34326128
## 596 0 94 Holand-Netherlands <=50K 0.01030230
## 597 75580 75 Portugal <=50K 0.83210876
## 598 6974 79 Japan <=50K -0.61813793
## 599 75671 3 Canada <=50K -1.10155350
## 600 3255 83 Vietnam <=50K -0.32808859
## 601 45800 83 El-Salvador <=50K 1.21884121
## 602 43561 11 Taiwan <=50K 0.15532697
## 603 97379 81 Thailand <=50K 0.10698541
## 604 8497 56 Taiwan >50K -1.10155350
## 605 0 78 Nicaragua >50K 1.36386587
## 606 11994 65 Philippines <=50K -0.52145482
## 607 4118 48 Puerto-Rico >50K -0.76316260
## 608 81822 13 Haiti <=50K 0.10698541
## 609 78068 15 Guatemala <=50K 1.65391521
## 610 69738 14 Dominican-Republic <=50K 0.39703475
## 611 43706 59 China <=50K -0.95652883
## 612 40228 76 South <=50K -0.27974704
## 613 43674 65 Dominican-Republic <=50K 0.05864386
## 614 8250 37 Laos <=50K 1.70225677
## 615 8676 47 Haiti <=50K -1.53662750
## 616 58129 34 Puerto-Rico >50K 1.26718276
## 617 73428 41 China <=50K 0.20366852
## 618 20912 7 China <=50K 0.44537631
## 619 82802 71 Mexico <=50K -1.00487038
## 620 40825 46 Taiwan >50K -1.48828595
## 621 26557 82 Cambodia >50K 0.73542564
## 622 59559 19 Japan <=50K 1.70225677
## 623 1508 70 Trinadad&Tobago >50K 0.44537631
## 624 0 32 Hungary >50K -1.39160283
## 625 87845 18 Philippines <=50K 0.30035164
## 626 10143 56 United-States <=50K -0.61813793
## 627 19761 48 Dominican-Republic <=50K -1.53662750
## 628 43186 43 Thailand >50K -1.10155350
## 629 22760 88 Peru <=50K -1.58496906
## 630 16575 7 Guatemala <=50K -1.29491972
## 631 60049 51 Dominican-Republic <=50K -0.03803926
## 632 79769 57 Columbia <=50K -1.63331061
## 633 41788 31 Dominican-Republic <=50K -0.52145482
## 634 57609 38 Hong <=50K 1.12215809
## 635 8745 58 Hong <=50K -0.03803926
## 636 15472 62 Laos <=50K -0.95652883
## 637 13495 51 India >50K -1.53662750
## 638 48647 33 Portugal <=50K -0.23140548
## 639 0 49 Hungary <=50K -1.68165217
## 640 70147 88 Hong <=50K 0.59040097
## 641 82366 56 Puerto-Rico <=50K -0.90818727
## 642 32129 96 United-States <=50K -0.52145482
## 643 67359 53 India <=50K -0.32808859
## 644 72790 96 Ecuador <=50K 1.55723210
## 645 32619 38 Guatemala <=50K 0.92879187
## 646 41798 40 Scotland <=50K -1.72999373
## 647 42714 69 Cuba >50K -0.03803926
## 648 70081 5 Holand-Netherlands <=50K 1.55723210
## 649 99912 78 Scotland >50K -1.29491972
## 650 26485 25 Vietnam <=50K -1.39160283
## 651 13901 87 Jamaica <=50K 0.59040097
## 652 11623 54 Scotland <=50K 1.55723210
## 653 83177 24 Canada <=50K 0.10698541
## 654 75938 20 France <=50K -0.71482105
## 655 77395 94 Jamaica <=50K -1.29491972
## 656 23040 16 Guatemala <=50K 1.21884121
## 657 22969 47 China <=50K 1.36386587
## 658 94401 69 Guatemala >50K -1.10155350
## 659 20956 55 India <=50K 1.65391521
## 660 27265 18 Cuba >50K 1.26718276
## 661 44618 56 Thailand >50K -0.13472237
## 662 69416 35 Laos <=50K -0.71482105
## 663 79207 87 Laos <=50K -0.90818727
## 664 98334 73 India <=50K 0.68708409
## 665 58034 42 Dominican-Republic >50K 1.46054899
## 666 79322 85 Hong <=50K 0.73542564
## 667 92047 36 Jamaica <=50K 0.01030230
## 668 19644 72 Thailand >50K 0.20366852
## 669 93352 7 France <=50K 1.36386587
## 670 77561 22 Poland <=50K 0.10698541
## 671 97675 94 Philippines <=50K -1.05321194
## 672 90265 20 Mexico <=50K -0.03803926
## 673 95620 1 Greece <=50K 0.15532697
## 674 3936 47 United-States <=50K -0.03803926
## 675 82400 21 Poland <=50K -0.13472237
## 676 9900 89 Iran <=50K -0.08638081
## 677 15983 11 Poland >50K 1.60557366
## 678 56972 21 Haiti <=50K 0.30035164
## 679 0 52 Poland <=50K 1.75059832
## 680 9842 25 Vietnam >50K -0.81150416
## 681 52757 28 Poland >50K 0.49371786
## 682 37705 20 Canada <=50K 0.20366852
## 683 68300 58 El-Salvador <=50K -1.10155350
## 684 22880 56 Germany <=50K -0.37643015
## 685 89971 86 Italy <=50K 1.12215809
## 686 99089 55 Cambodia <=50K -0.03803926
## 687 42768 24 Nicaragua <=50K 0.68708409
## 688 82859 34 Dominican-Republic <=50K -1.48828595
## 689 7701 68 Cambodia <=50K 1.46054899
## 690 78121 3 El-Salvador <=50K -1.24657816
## 691 90700 64 Columbia <=50K -0.85984571
## 692 6830 24 England >50K -1.24657816
## 693 46556 27 Peru <=50K 1.26718276
## 694 65366 52 Canada <=50K -1.24657816
## 695 87217 96 Iran <=50K -0.47311326
## 696 63909 74 Poland >50K -1.48828595
## 697 63773 22 Jamaica <=50K 0.88045031
## 698 50401 21 Nicaragua <=50K -0.42477171
## 699 53936 49 Honduras <=50K -0.37643015
## 700 0 85 Portugal <=50K 1.50889054
## 701 16572 79 Ecuador <=50K 0.20366852
## 702 79592 25 England >50K -1.53662750
## 703 56467 7 Ireland >50K -1.34326128
## 704 7886 89 India <=50K -0.42477171
## 705 80695 47 Cambodia <=50K -1.05321194
## 706 0 48 Trinadad&Tobago <=50K 1.12215809
## 707 79241 72 Portugal <=50K -0.95652883
## 708 86262 29 Yugoslavia >50K 1.17049965
## 709 304 1 Ecuador <=50K 0.20366852
## 710 61678 40 Hong >50K -0.56979638
## 711 19155 5 Portugal <=50K 1.65391521
## 712 78218 67 Canada <=50K -1.24657816
## 713 1336 75 Holand-Netherlands >50K -1.05321194
## 714 39407 37 Germany <=50K 1.75059832
## 715 33813 83 Scotland <=50K -1.24657816
## 716 44003 91 Guatemala >50K -0.18306393
## 717 71219 56 Ecuador >50K 1.75059832
## 718 51634 82 China <=50K -0.66647949
## 719 14768 81 Dominican-Republic <=50K -0.61813793
## 720 32996 18 Vietnam >50K 1.65391521
## 721 3200 36 France >50K -1.19823661
## 722 56119 97 Iran <=50K -1.63331061
## 723 22259 28 Yugoslavia <=50K -0.27974704
## 724 56498 88 Haiti <=50K 1.21884121
## 725 56597 49 Haiti <=50K -0.13472237
## 726 37109 42 Taiwan <=50K -0.52145482
## 727 99230 77 Hungary <=50K -1.72999373
## 728 73621 52 Peru <=50K 0.25201008
## 729 83857 29 United-States <=50K -0.08638081
## 730 95453 90 France <=50K 0.63874253
## 731 37949 93 Germany >50K -0.18306393
## 732 62382 52 Laos >50K -0.61813793
## education_num_std capital_gain_std capital_loss_std hours_per_week_std
## 1 -1.37334573 -0.415206833 -1.0267071512 1.726693385
## 2 1.61160592 0.909442476 -1.4554359993 -1.590084997
## 3 0.75876259 -1.542163728 -0.9629749653 0.738716845
## 4 0.54555176 -0.954902993 0.1857171161 -1.201951357
## 5 0.97197342 1.526198754 -0.0004479532 1.656123632
## 6 0.33234093 0.225847990 0.7998875516 -0.319829447
## 7 0.75876259 -0.897667185 0.2116966966 -1.343090862
## 8 0.75876259 0.921695000 0.9628683119 -0.496253829
## 9 1.61160592 1.086725489 -1.2774265451 1.126850486
## 10 1.39839509 -0.657159770 -0.4725857206 0.738716845
## 11 1.39839509 -0.012766478 1.4342497117 1.373844621
## 12 0.33234093 0.459024540 0.1241553762 -1.025526975
## 13 1.18518426 -1.430445487 1.6129826479 -1.660654750
## 14 0.54555176 0.515744091 -0.4908700835 0.738716845
## 15 -0.73371323 0.124145155 0.2854918592 0.033019317
## 16 0.54555176 0.942138819 0.3091365659 1.444414373
## 17 -0.30729157 0.766576666 1.2956042546 -1.166666480
## 18 -0.73371323 1.742201120 -1.2755849546 0.421152958
## 19 -0.94692406 -0.242432474 1.7357443868 0.774001722
## 20 -0.73371323 -1.153765592 1.2547932935 -1.519515244
## 21 -1.16013490 -1.380093119 1.6066357377 1.761978261
## 22 -0.52050240 -0.644872829 -1.1864651280 1.338559744
## 23 -1.58655656 -0.488481058 -1.0360466459 -1.307805986
## 24 0.54555176 0.255033778 -0.8375494972 -0.284544570
## 25 1.39839509 1.191629123 -0.5346407437 -1.448945491
## 26 -1.16013490 0.011256729 1.7604743165 -0.566823581
## 27 1.18518426 0.676093840 -0.5608834085 1.232705115
## 28 0.33234093 1.455918825 0.0943281870 -0.319829447
## 29 -0.73371323 0.120634600 -0.3323946429 -1.625369873
## 30 -1.16013490 0.694231706 0.1037663384 -0.002265559
## 31 -0.73371323 -0.481769704 1.0700751881 0.879856351
## 32 0.54555176 -0.394005836 -0.5780496629 -1.484230368
## 33 1.18518426 0.374220552 -1.3987413200 1.091565609
## 34 0.97197342 1.698043848 -0.2826388135 1.162135362
## 35 -1.16013490 -0.064082528 0.2476734826 -1.060811851
## 36 -0.94692406 -0.259365738 -0.5579894805 -0.990242098
## 37 -0.94692406 0.110584777 -1.4142961827 1.585553879
## 38 0.54555176 0.219997065 1.4987053796 -1.413660615
## 39 -1.58655656 1.182990405 -0.6709513271 0.491722711
## 40 -0.94692406 -1.595957816 0.8059056063 -1.625369873
## 41 0.11913010 1.446867101 0.8954200594 0.668147093
## 42 1.18518426 0.178593170 -1.3528659849 -1.272521109
## 43 0.54555176 0.362553120 -1.5230486795 0.562292463
## 44 -0.52050240 0.264119920 -0.8858254771 1.197420239
## 45 -0.73371323 1.595205246 0.3847075480 0.421152958
## 46 1.18518426 1.728916079 -1.1584466438 -1.166666480
## 47 0.54555176 -1.592275176 0.2784872381 -1.343090862
## 48 0.75876259 -1.274466723 0.8089968476 -0.672678211
## 49 -0.52050240 -1.412755045 -0.6586192477 0.879856351
## 50 -1.16013490 0.402890082 -1.1898194536 0.174158823
## 51 1.39839509 -1.013205735 -0.4716320398 1.479699250
## 52 1.18518426 1.763470951 -0.8659626080 -0.213974817
## 53 -1.58655656 -0.766399973 -0.1579697130 1.197420239
## 54 0.75876259 1.589698493 -1.1654183793 -1.201951357
## 55 -0.30729157 -0.635201595 -1.2852861903 0.350583205
## 56 -1.58655656 0.051249519 1.0009497728 1.338559744
## 57 -1.16013490 0.534363798 -0.5410205394 1.020995857
## 58 0.11913010 0.022235817 -0.5245448814 -0.390399199
## 59 -1.58655656 0.574838428 1.0934568104 -0.284544570
## 60 -0.30729157 -0.688169670 0.1567778367 -1.272521109
## 61 1.39839509 1.138110373 -0.0178115209 1.620838755
## 62 -0.94692406 0.335776536 1.6780631411 1.232705115
## 63 -1.37334573 -0.782644892 -0.0728619230 -0.460968952
## 64 0.33234093 0.537392512 -0.4947505778 -1.519515244
## 65 -0.94692406 -0.558795404 1.6333716857 -0.637393334
## 66 -0.94692406 -0.688479425 0.3911531148 -0.954957222
## 67 0.54555176 -0.619645019 0.0192833737 1.585553879
## 68 0.11913010 -0.393455161 -0.1141661673 0.068304194
## 69 0.75876259 0.668315552 -0.5431580998 -0.566823581
## 70 0.97197342 0.287592452 0.6778164092 -1.343090862
## 71 -1.37334573 1.129678158 1.6507023678 -0.319829447
## 72 -0.09408074 0.186990968 1.3704188691 0.138873947
## 73 -1.16013490 -0.700318943 0.8060700341 1.232705115
## 74 0.33234093 -1.630030847 -0.9939531485 1.550269003
## 75 1.39839509 -0.821777252 0.1837768690 -0.778532840
## 76 -0.73371323 -0.538558089 1.4208324094 1.126850486
## 77 1.39839509 -0.570807008 0.6789016321 1.020995857
## 78 -1.37334573 0.868004164 0.1983122798 0.879856351
## 79 -0.94692406 -0.027462624 -0.7591832439 -1.625369873
## 80 0.33234093 0.220272403 1.1496253210 0.103589070
## 81 -0.73371323 -0.618061828 1.2675857704 -0.884387469
## 82 1.39839509 0.804435590 -1.3550364309 -1.554800121
## 83 0.97197342 -1.491708109 0.9677024870 1.162135362
## 84 1.39839509 -0.783780660 -1.2042233222 1.761978261
## 85 -1.37334573 -1.483482397 1.4360584166 -0.072835312
## 86 -1.37334573 -0.058231604 -0.0746048569 -0.531538705
## 87 0.33234093 0.140837499 0.6873861027 -0.531538705
## 88 0.54555176 0.857197162 1.3368427278 -0.178689941
## 89 0.11913010 -1.154935777 -0.6739439116 -0.355114323
## 90 0.11913010 1.216547178 0.8714136117 -0.849102593
## 91 -1.58655656 0.232490510 1.3129678223 -0.531538705
## 92 0.11913010 -1.630030847 0.3369906224 0.421152958
## 93 0.54555176 -0.774763353 0.4619556928 -1.201951357
## 94 1.61160592 0.824638488 1.5960465923 -1.625369873
## 95 0.97197342 -0.547472144 -0.6099157558 0.209443699
## 96 0.75876259 -0.783815077 0.0924865965 1.056280733
## 97 -0.52050240 -0.492645540 0.2216281311 0.668147093
## 98 0.75876259 1.113983913 -1.1538426675 -1.166666480
## 99 0.97197342 0.962789141 0.1992330751 0.809286598
## 100 0.11913010 1.659703084 -0.8810241875 -0.002265559
## 101 -0.73371323 -1.192003105 -0.0555641264 1.197420239
## 102 -0.09408074 0.314024864 -1.5230486795 1.585553879
## 103 -0.94692406 0.191499621 -0.6726942609 1.232705115
## 104 0.97197342 1.131571104 -1.1652210661 0.738716845
## 105 -1.16013490 -1.048242448 1.6895730818 1.303274868
## 106 1.18518426 -0.126756255 -0.8073605671 0.315298329
## 107 1.18518426 -1.443971448 -1.4733586212 1.691408508
## 108 1.18518426 -0.349022552 1.2912633627 1.444414373
## 109 1.39839509 -0.572596702 -0.0402394625 0.738716845
## 110 1.39839509 -1.502067687 -1.5230486795 -0.496253829
## 111 -1.58655656 0.509583412 0.3604051303 -0.037550435
## 112 -1.37334573 0.994108795 -0.6177096300 -1.272521109
## 113 0.54555176 -1.023049055 1.4182673369 -1.519515244
## 114 -0.73371323 0.985814249 -0.9180861966 0.774001722
## 115 0.97197342 -0.325928609 0.2572760617 1.020995857
## 116 -1.37334573 -0.207912019 1.2206909835 -1.695939626
## 117 1.18518426 -0.820262895 -0.2858287114 -1.519515244
## 118 -1.37334573 -0.114021890 -0.7961137107 -1.096096727
## 119 0.33234093 -1.403531234 -1.5230486795 -1.166666480
## 120 -0.52050240 -1.411309522 -0.6804223640 1.267989991
## 121 -0.52050240 1.678013036 -1.1007982837 1.303274868
## 122 -1.58655656 -1.151459640 -0.7294547113 -0.143405065
## 123 -1.16013490 1.776515071 -0.3977711060 0.844571475
## 124 1.61160592 1.712636742 0.9606320948 -0.566823581
## 125 -0.30729157 -0.007294143 1.7363363266 -0.213974817
## 126 -0.30729157 1.105414030 -0.2966480556 1.126850486
## 127 -1.16013490 0.179384766 1.0365648179 -0.849102593
## 128 0.33234093 -0.121008582 -0.2823099581 1.514984126
## 129 -0.94692406 -1.247965477 -1.5230486795 0.950426104
## 130 0.54555176 1.344131750 0.4118381225 -1.625369873
## 131 1.39839509 -1.630030847 0.1511215230 0.597577340
## 132 1.18518426 -0.965709995 -0.5657833546 -1.413660615
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## 679 -1.37334573 0.279194655 -1.5230486795 0.103589070
## 680 -0.52050240 0.256031877 -1.1993891471 -0.849102593
## 681 0.33234093 -0.602849424 0.2118940098 -0.743247963
## 682 -1.58655656 -0.470687364 -0.2830992112 -1.025526975
## 683 -0.09408074 1.129781410 0.7230340333 0.315298329
## 684 -0.09408074 0.292927119 -0.7706274135 0.244728576
## 685 -0.30729157 -0.479842340 1.4356966756 1.303274868
## 686 1.18518426 -0.613002499 1.7355470735 0.209443699
## 687 0.54555176 -0.381787729 -0.1165996976 -0.884387469
## 688 -0.09408074 -1.526090894 1.2018146807 -0.531538705
## 689 0.33234093 1.585878184 -1.2697970987 0.668147093
## 690 1.18518426 1.152806518 1.0460029692 -1.625369873
## 691 1.39839509 -1.210278640 1.4596702378 0.527007587
## 692 0.54555176 -0.549640428 -1.2984404082 -0.884387469
## 693 1.18518426 -0.811761846 0.0079707462 -0.778532840
## 694 1.39839509 0.592012613 0.6265478448 0.103589070
## 695 -1.37334573 -1.047278766 1.3451298851 1.656123632
## 696 -0.30729157 -1.630030847 0.5786336059 0.879856351
## 697 1.39839509 -1.630030847 0.5741611718 -0.954957222
## 698 -0.94692406 0.157633094 0.1344156662 -0.990242098
## 699 -0.30729157 -0.716529445 0.2506660672 -0.002265559
## 700 0.97197342 -1.448721022 -1.5230486795 1.267989991
## 701 1.18518426 0.690858820 -0.9780694304 1.056280733
## 702 -1.58655656 -1.277736357 1.0943776057 -0.849102593
## 703 0.11913010 -0.495605419 0.3338993812 -1.484230368
## 704 0.11913010 -1.630030847 -1.2637132729 1.409129497
## 705 -0.30729157 -1.143819021 1.1306503617 -0.072835312
## 706 -0.94692406 -1.630030847 -1.5230486795 -0.037550435
## 707 -0.30729157 -1.009867267 1.0828347795 0.809286598
## 708 -1.37334573 -0.658192286 1.3137241898 -0.707963087
## 709 0.33234093 -1.217058829 -1.5130514739 -1.695939626
## 710 -0.94692406 -0.172737638 0.5052659554 -0.319829447
## 711 0.97197342 -1.165020018 -0.8931260680 -1.554800121
## 712 -0.94692406 1.144615224 1.0491928671 0.632862216
## 713 0.54555176 0.852034581 -1.4791135916 0.915141227
## 714 -1.58655656 -0.901693998 -0.2271280138 -0.425684076
## 715 1.61160592 1.104863355 -0.4110897517 1.197420239
## 716 -0.30729157 1.711776312 -0.0759860497 1.479699250
## 717 -1.37334573 1.582505298 0.8190269387 0.244728576
## 718 -0.52050240 -1.037710784 0.1749635430 1.162135362
## 719 1.18518426 -1.023565313 -1.0373949532 1.126850486
## 720 -1.58655656 -0.769635190 -0.4379572418 -1.096096727
## 721 0.97197342 -1.006287877 -1.4178149360 -0.460968952
## 722 -0.09408074 1.308785282 0.3224552116 1.691408508
## 723 -0.94692406 -0.174389664 -0.7910493368 -0.743247963
## 724 0.54555176 -1.629342503 0.3349188331 1.373844621
## 725 1.61160592 1.566604550 0.3381745020 -0.002265559
## 726 -1.58655656 1.361340351 -0.3026989959 -0.249259694
## 727 -0.73371323 0.241060394 1.7401839353 0.985710980
## 728 1.18518426 1.354525745 0.8980180174 0.103589070
## 729 0.97197342 0.362794041 1.2346344545 -0.707963087
## 730 0.54555176 -1.091401620 1.6159752325 1.444414373
## 731 0.33234093 0.733467317 -0.2750751382 1.550269003
## 732 -0.94692406 0.113682325 0.5284173789 0.103589070
## age_norm education_num_norm capital_gain_norm capital_loss_norm
## 1 0.18055556 0.06666667 0.3535391981 0.1510145682
## 2 0.56944444 1.00000000 0.7390398542 0.0205715201
## 3 0.68055556 0.73333333 0.0255711696 0.1704054270
## 4 0.58333333 0.66666667 0.1964763269 0.5199011446
## 5 0.18055556 0.80000000 0.9185288314 0.4632594253
## 6 0.33333333 0.60000000 0.5400995603 0.7067657888
## 7 0.94444444 0.73333333 0.2131331444 0.5278055711
## 8 0.77777778 0.73333333 0.7426055950 0.7563535580
## 9 0.11111111 1.00000000 0.7906329190 0.0747318498
## 10 0.98611111 0.93333333 0.2831258326 0.3196089810
## 11 0.08333333 0.93333333 0.4706577590 0.8997738734
## 12 0.11111111 0.60000000 0.6079588137 0.5011706556
## 13 0.58333333 0.86666667 0.0580835145 0.9541543264
## 14 0.43055556 0.66666667 0.6244653893 0.3140458657
## 15 0.11111111 0.26666667 0.5105019081 0.5502581446
## 16 0.55555556 0.66666667 0.7485551738 0.5574521732
## 17 0.30555556 0.40000000 0.6974629153 0.8575902505
## 18 0.36111111 0.26666667 0.9813900380 0.0752921636
## 19 0.81944444 0.20000000 0.4038201504 0.9915052429
## 20 0.08333333 0.26666667 0.1386031511 0.8451732970
## 21 0.72222222 0.13333333 0.0727371067 0.9522232450
## 22 0.51388889 0.33333333 0.2867015896 0.1024073481
## 23 0.45833333 0.00000000 0.3322148659 0.1481729769
## 24 0.94444444 0.66666667 0.5485932351 0.2085667974
## 25 0.98611111 0.93333333 0.8211620709 0.3007284079
## 26 0.86111111 0.13333333 0.4776490149 0.9990294565
## 27 0.27777778 0.86666667 0.6711305201 0.2927439366
## 28 0.55555556 0.60000000 0.8980759022 0.4920955735
## 29 0.63888889 0.26666667 0.5094802632 0.3622628672
## 30 0.81944444 0.13333333 0.6764090185 0.4949671816
## 31 0.06944444 0.26666667 0.3341680105 0.7889718242
## 32 0.98611111 0.66666667 0.3597091317 0.2875210118
## 33 0.52777778 0.86666667 0.5832790793 0.0378211799
## 34 0.41666667 0.80000000 0.9685393484 0.3774013448
## 35 0.68055556 0.13333333 0.4557237152 0.5387517010
## 36 0.45833333 0.20000000 0.3988922165 0.2936244297
## 37 0.04166667 0.20000000 0.5065555544 0.0330885296
## 38 0.16666667 0.66666667 0.5383968189 0.9193848555
## 39 0.33333333 0.00000000 0.8186480233 0.2592551829
## 40 0.70833333 0.20000000 0.0099159647 0.7085968142
## 41 0.33333333 0.53333333 0.8954416611 0.7358320660
## 42 0.47222222 0.86666667 0.5263474193 0.0517789962
## 43 0.48611111 0.66666667 0.5798836126 0.0000000000
## 44 0.40277778 0.33333333 0.5512374924 0.1938785720
## 45 0.15277778 0.26666667 0.9386111640 0.5804450492
## 46 0.41666667 0.86666667 0.9775238133 0.1109321220
## 47 0.40277778 0.66666667 0.0109876902 0.5481269511
## 48 0.87500000 0.73333333 0.1034765973 0.7095373409
## 49 0.18055556 0.33333333 0.0632318032 0.2630072841
## 50 0.97222222 0.13333333 0.5916225122 0.1013867766
## 51 0.91666667 0.93333333 0.1795090095 0.3198991435
## 52 0.30555556 0.86666667 0.9875800038 0.1999219563
## 53 0.50000000 0.00000000 0.2513346488 0.4153325862
## 54 0.09722222 0.73333333 0.9370085838 0.1088109341
## 55 0.69444444 0.40000000 0.2895161210 0.0723405107
## 56 0.68055556 0.00000000 0.4892877533 0.7679400464
## 57 0.84722222 0.13333333 0.6298841134 0.2987873209
## 58 0.62500000 0.53333333 0.4808441591 0.3038001281
## 59 0.31944444 0.00000000 0.6416630776 0.7960858081
## 60 0.08333333 0.40000000 0.2741013031 0.5110962139
## 61 0.34722222 0.93333333 0.8055869951 0.4579764668
## 62 0.43055556 0.20000000 0.5720910666 0.9739554150
## 63 0.08333333 0.06666667 0.2466070373 0.4412270872
## 64 0.36111111 0.60000000 0.6307655325 0.3128652045
## 65 0.05555556 0.20000000 0.3117519206 0.9603578004
## 66 0.95833333 0.20000000 0.2740111580 0.5824061474
## 67 0.20833333 0.66666667 0.2940434099 0.4692627872
## 68 0.31944444 0.53333333 0.3598693897 0.4286600496
## 69 0.43055556 0.73333333 0.6688668757 0.2981369567
## 70 0.27777778 0.80000000 0.5580684903 0.6696249900
## 71 0.75000000 0.06666667 0.8031330442 0.9656307532
## 72 0.52777778 0.46666667 0.5287913541 0.8803529977
## 73 0.73611111 0.13333333 0.2705656106 0.7086468422
## 74 0.48611111 0.60000000 0.0000000000 0.1609801489
## 75 0.76388889 0.93333333 0.2352187021 0.5193108141
## 76 0.52777778 0.26666667 0.3176414027 0.8956915873
## 77 0.93055556 0.93333333 0.3082562926 0.6699551749
## 78 0.00000000 0.06666667 0.7269804385 0.5237332906
## 79 0.54166667 0.20000000 0.4663808732 0.2324101497
## 80 0.40277778 0.60000000 0.5384769479 0.8131753782
## 81 0.20833333 0.26666667 0.2945041517 0.8490654767
## 82 0.65277778 0.93333333 0.7084806539 0.0511186264
## 83 0.26388889 0.80000000 0.0402548102 0.7578243817
## 84 0.91666667 0.93333333 0.2462765052 0.0970043224
## 85 0.48611111 0.06666667 0.0426486643 0.9003241815
## 86 0.70833333 0.06666667 0.4574264566 0.4406967902
## 87 0.29166667 0.60000000 0.5153597292 0.6725366205
## 88 0.80555556 0.66666667 0.7238353750 0.8701372769
## 89 0.13888889 0.53333333 0.1382626028 0.2583446730
## 90 0.09722222 0.53333333 0.8284137461 0.7285279757
## 91 0.62500000 0.00000000 0.5420326726 0.8628732090
## 92 0.90277778 0.53333333 0.0000000000 0.5659269191
## 93 0.95833333 0.66666667 0.2489007302 0.6039482110
## 94 0.98611111 1.00000000 0.7143601198 0.9490014408
## 95 0.59722222 0.80000000 0.3150472260 0.2778255823
## 96 0.43055556 0.73333333 0.2462664890 0.4915352597
## 97 0.48611111 0.33333333 0.3310029147 0.5308272633
## 98 0.18055556 0.73333333 0.7985656908 0.1123329064
## 99 0.20833333 0.80000000 0.7545648494 0.5240134475
## 100 0.48611111 0.53333333 0.9573813840 0.1953393901
## 101 0.54166667 0.26666667 0.1274752351 0.4464900344
## 102 0.98611111 0.46666667 0.5657608750 0.0000000000
## 103 0.11111111 0.20000000 0.5301034666 0.2587248859
## 104 0.79166667 0.80000000 0.8036839311 0.1088709677
## 105 0.31944444 0.13333333 0.1693125933 0.9774573761
## 106 0.86111111 0.86666667 0.4374843498 0.2177519411
## 107 0.73611111 0.86666667 0.0541471770 0.0151184663
## 108 0.48611111 0.86666667 0.3728002083 0.8562695109
## 109 0.34722222 0.93333333 0.3077354541 0.4511526455
## 110 0.44444444 0.93333333 0.0372399563 0.0000000000
## 111 0.77777778 0.00000000 0.6226725027 0.5730509085
## 112 0.12500000 0.06666667 0.7636795240 0.2754542544
## 113 0.72222222 0.66666667 0.1766443975 0.8949111502
## 114 0.73611111 0.26666667 0.7612656377 0.1840630753
## 115 0.13888889 0.80000000 0.3795210289 0.5416733371
## 116 0.33333333 0.06666667 0.4138663248 0.8347974866
## 117 0.70833333 0.86666667 0.2356594117 0.3764308012
## 118 0.34722222 0.06666667 0.4411903164 0.2211738574
## 119 0.08333333 0.60000000 0.0659161250 0.0000000000
## 120 0.33333333 0.33333333 0.0636524805 0.2563735692
## 121 0.43055556 0.33333333 0.9627099630 0.1284719443
## 122 0.77777778 0.00000000 0.1392742315 0.2414552149
## 123 1.00000000 0.13333333 0.9913761155 0.3423717282
## 124 0.48611111 1.00000000 0.9727861858 0.7556731770
## 125 0.06944444 0.40000000 0.4722503230 0.9916853438
## 126 0.00000000 0.40000000 0.7960716754 0.3731389578
## 127 0.48611111 0.13333333 0.5265777902 0.7787761146
## 128 0.38888889 0.60000000 0.4391570428 0.3775014008
## 129 0.08333333 0.20000000 0.1111890143 0.0000000000
## 130 0.06944444 0.66666667 0.8655435251 0.5886996718
## 131 0.41666667 0.93333333 0.0000000000 0.5093752501
## 132 0.87500000 0.86666667 0.1933312633 0.2912531017
## 133 0.77777778 0.60000000 0.8145414117 0.9768770511
## 134 0.26388889 0.86666667 0.5105820371 0.0628251821
## 135 0.47222222 0.93333333 0.5362633840 0.0507784359
## 136 0.44444444 0.53333333 0.5734732920 0.9936064196
## 137 0.05555556 0.46666667 0.0256112341 0.0000000000
## 138 0.33333333 0.60000000 0.5744248240 0.5370507484
## 139 0.09722222 0.13333333 0.4551928605 0.8563895782
## 140 0.23611111 0.00000000 0.5431745110 0.3917894021
## 141 0.41666667 0.60000000 0.5242840974 0.8196690146
## 142 0.97222222 0.53333333 0.3950560402 1.0000000000
## 143 0.83333333 0.13333333 0.8479752401 0.4275694389
## 144 0.65277778 0.60000000 0.1694327868 0.6290022413
## 145 0.61111111 0.00000000 0.6280611785 0.4381053390
## 146 0.86111111 0.06666667 0.3730806599 0.8337969263
## 147 0.72222222 0.13333333 0.3859814301 0.6038181382
## 148 0.97222222 0.60000000 0.4579573113 0.1268110142
## 149 0.22222222 0.46666667 0.8105449774 0.7605258945
## 150 0.01388889 0.06666667 0.0584140466 0.2904726647
## 151 0.66666667 0.80000000 0.9700117189 0.1652225246
## 152 0.01388889 0.13333333 0.5970913170 0.2206235492
## 153 0.16666667 1.00000000 0.9620088342 0.9294004643
## 154 0.31944444 0.86666667 0.6619457326 0.7138797727
## 155 0.66666667 0.26666667 0.1751219463 0.0653265829
## 156 0.91666667 0.53333333 0.5012870722 0.1157448171
## 157 0.48611111 1.00000000 0.0294574265 0.4430781237
## 158 0.50000000 0.60000000 0.0000000000 0.3730589130
## 159 0.86111111 0.60000000 0.6226424544 0.7809273193
## 160 0.16666667 0.00000000 0.4162802111 0.8461538462
## 161 0.83333333 0.53333333 0.7129778944 0.9412771152
## 162 0.95833333 0.13333333 0.9929386312 0.5399623789
## 163 0.51388889 0.20000000 0.7936978535 0.4250980549
## 164 0.87500000 0.00000000 0.4905898497 0.9223565197
## 165 0.47222222 0.33333333 0.0058193692 0.7156807812
## 166 0.65277778 0.60000000 0.5207784533 0.2698611222
## 167 0.90277778 0.40000000 0.1589859674 0.1890658769
## 168 0.30555556 0.40000000 0.1603181122 0.6045385416
## 169 0.11111111 1.00000000 0.4772283376 0.7842591851
## 170 0.48611111 0.06666667 0.8346838410 0.0000000000
## 171 0.52777778 0.80000000 0.3504041507 0.6354058273
## 172 0.41666667 0.86666667 0.2109997095 0.6223785320
## 173 0.48611111 0.20000000 0.5023988622 0.7869306812
## 174 0.59722222 0.40000000 0.9151734292 0.0647162411
## 175 0.55555556 0.40000000 0.4448662346 0.0237533018
## 176 0.58333333 0.73333333 0.8194893779 0.2314896342
## 177 0.52777778 0.40000000 0.2461563117 0.2067557832
## 178 0.50000000 1.00000000 0.8239665862 0.6044384856
## 179 0.44444444 0.40000000 0.2858101543 0.0340590731
## 180 0.15277778 0.26666667 0.3122226785 0.3692667894
## 181 0.27777778 0.53333333 0.3209166758 0.2192327704
## 182 0.47222222 0.46666667 0.0734182033 0.4881833827
## 183 0.68055556 0.66666667 0.3129238073 0.1314736252
## 184 0.63888889 0.93333333 0.1578140807 0.9393360282
## 185 0.56944444 0.06666667 0.2981900860 0.8248619227
## 186 0.26388889 0.06666667 0.5448371879 0.8260425838
## 187 0.26388889 0.86666667 0.2564028085 0.6197870808
## 188 0.48611111 0.33333333 0.8268512305 0.7362623069
## 189 0.09722222 0.26666667 0.8906038722 0.9343532378
## 190 0.52777778 0.60000000 0.2568535342 0.1531257504
## 191 0.86111111 0.33333333 0.7990464648 0.0000000000
## 192 0.13888889 1.00000000 0.2836967518 0.5689986392
## 193 0.48611111 0.66666667 0.1684812548 0.6602597455
## 194 0.25000000 0.00000000 0.8136199281 0.1841731370
## 195 0.16666667 0.46666667 0.6300043069 0.0186804611
## 196 0.41666667 0.80000000 0.9263814742 0.3641739374
## 197 0.40277778 0.40000000 0.3031781168 0.9879432482
## 198 0.20833333 0.53333333 0.8068289947 0.0370607540
## 199 0.48611111 0.20000000 0.7281222769 0.4205354999
## 200 0.68055556 0.73333333 0.0000000000 0.1526054591
## 201 0.37500000 0.73333333 0.9126393494 0.4954974786
## 202 0.37500000 0.73333333 0.6080389427 0.0607940447
## 203 0.68055556 0.00000000 0.0000000000 0.6317637877
## 204 0.63888889 0.33333333 0.0638528030 0.2101776995
## 205 0.69444444 0.06666667 0.1335950881 0.4587268871
## 206 0.06944444 0.60000000 0.8404831779 0.7341211078
## 207 0.19444444 0.60000000 0.7866565170 0.1511546466
## 208 0.25000000 0.06666667 0.3875439458 0.6353958217
## 209 0.80555556 0.00000000 0.9039253198 0.9773973425
## 210 0.02777778 0.06666667 0.4071555204 0.0000000000
## 211 0.44444444 0.46666667 0.5771291780 0.5407127992
## 212 0.48611111 0.46666667 0.0125802542 0.9055371008
## 213 0.48611111 0.26666667 0.5762978395 0.9646001761
## 214 0.11111111 0.46666667 0.6621761035 0.9517629873
## 215 0.72222222 0.80000000 0.5720009215 0.3550888498
## 216 0.13888889 0.06666667 0.5619948116 0.2508104539
## 217 0.09722222 0.73333333 0.8874788409 0.9841010966
## 218 0.05555556 0.40000000 0.2430813610 0.9628491955
## 219 0.38888889 0.26666667 0.4193852102 0.0000000000
## 220 0.68055556 0.86666667 0.3724796923 0.5750020011
## 221 0.95833333 0.20000000 0.3902583159 0.1340750820
## 222 0.34722222 0.53333333 0.5944270275 0.3471343953
## 223 1.00000000 0.60000000 0.0127905929 0.2038841751
## 224 0.13888889 0.06666667 0.2451346668 0.5340990955
## 225 0.06944444 0.73333333 0.5253658390 0.6533258625
## 226 0.48611111 0.20000000 0.1252416390 0.1674037461
## 227 0.36111111 0.80000000 0.9196806859 0.0995057232
## 228 0.93055556 0.00000000 0.0407155520 0.0000000000
## 229 0.48611111 0.60000000 0.7016797043 0.5677479388
## 230 0.54166667 0.60000000 0.3345486233 0.4183142560
## 231 0.06944444 0.80000000 0.6584200563 0.1553269831
## 232 0.48611111 0.60000000 0.8255391180 0.9496518050
## 233 0.75000000 0.00000000 0.9884614229 0.7617065557
## 234 0.12500000 0.26666667 0.4354410601 0.9014548147
## 235 0.33333333 0.80000000 0.8285139074 0.8741495237
## 236 0.51388889 0.93333333 0.7206001663 0.3682962459
## 237 0.33333333 0.20000000 0.2754033995 0.8809633395
## 238 0.29166667 0.73333333 0.8460220956 0.5096554070
## 239 0.48611111 0.20000000 0.6636084095 0.0479568558
## 240 0.63888889 0.20000000 0.6945281904 0.7559833507
## 241 0.81944444 0.40000000 0.2812428009 0.2792763948
## 242 0.86111111 0.26666667 0.0939412454 0.7297786761
## 243 0.50000000 1.00000000 0.0000000000 0.6142839990
## 244 0.62500000 0.73333333 0.8592934625 0.0000000000
## 245 0.63888889 0.46666667 0.1648454011 0.4412070760
## 246 0.20833333 1.00000000 0.5343202556 0.0000000000
## 247 0.25000000 0.13333333 0.4484920722 0.3723685264
## 248 0.98611111 0.06666667 0.2478390208 0.5688885776
## 249 0.41666667 0.73333333 0.6645499254 0.3805631153
## 250 0.65277778 0.20000000 0.6575486533 0.8115844873
## 251 0.84722222 0.86666667 0.3370326225 0.1395781638
## 252 0.40277778 0.26666667 0.7774717295 0.1368566397
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## 254 0.45833333 0.06666667 0.7171646351 0.6002461378
## 255 0.77777778 0.06666667 0.6481334949 0.5366905467
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## 257 0.86111111 0.13333333 0.0772944441 0.1490734811
## 258 0.62500000 0.33333333 0.0417371969 0.1691347154
## 259 0.48611111 0.80000000 0.0227466221 0.9899743857
## 260 0.23611111 0.40000000 0.6846022096 0.9353337869
## 261 0.98611111 0.06666667 0.4189845651 0.4227867606
## 262 0.27777778 0.60000000 0.6739250193 0.1744176739
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## 264 0.97222222 0.40000000 0.6125662316 0.8935403826
## 265 0.98611111 0.06666667 0.6567373471 0.8911790603
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## 267 0.54166667 0.53333333 0.8721842166 0.7469482910
## 268 0.66666667 0.53333333 0.0476467112 0.8381493636
## 269 0.94444444 0.80000000 0.6623263454 0.6135535900
## 270 0.63888889 0.40000000 0.3369024129 0.6707356119
## 271 0.26388889 0.86666667 0.7161830547 0.8946209878
## 272 0.01388889 0.53333333 0.7500175282 0.0000000000
## 273 0.84722222 0.40000000 0.8494676429 0.6319338830
## 274 0.12500000 0.20000000 0.0277446689 0.7473285040
## 275 0.80555556 0.53333333 0.5658009395 0.0000000000
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## 277 0.08333333 0.53333333 0.1784573163 0.0693588410
## 278 0.83333333 0.06666667 0.6242149861 0.4175838470
## 279 0.48611111 0.53333333 0.0665070764 0.8542083567
## 280 0.48611111 0.53333333 0.2492913591 0.6580485072
## 281 0.04166667 0.06666667 0.5853924819 0.0686184263
## 282 0.38888889 0.53333333 0.2848486063 0.2281377571
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## 284 0.76388889 0.60000000 0.9116978335 0.0507284079
## 285 0.68055556 0.73333333 0.3412093470 0.1508144561
## 286 0.65277778 0.60000000 0.4547621671 0.0000000000
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## 288 0.44444444 0.06666667 0.1262232194 0.0400524294
## 289 0.45833333 0.60000000 0.0878514408 0.3367886016
## 290 0.90277778 0.26666667 0.3176113543 0.1836728568
## 291 0.87500000 0.60000000 0.6050140727 0.1543164172
## 292 0.54166667 0.06666667 0.8293552620 0.6589189946
## 293 0.79166667 0.20000000 0.1738298661 0.0000000000
## 294 0.26388889 0.33333333 0.3215677240 0.9465700792
## 295 0.33333333 0.93333333 0.1080840153 0.2078664052
## 296 0.97222222 0.20000000 0.5546329591 0.5531197471
## 297 0.54166667 0.20000000 0.2503230201 0.0237633075
## 298 0.83333333 0.80000000 0.5717204700 0.5503682062
## 299 0.29166667 0.60000000 0.4849107062 0.5937525014
## 300 0.48611111 0.20000000 0.5163813740 0.9690026415
## 301 0.44444444 0.46666667 0.0456535021 0.7468682462
## 302 0.87500000 0.26666667 0.0304590391 0.9465700792
## 303 0.41666667 1.00000000 0.2363405082 0.1411290323
## 304 0.98611111 0.06666667 0.9579022226 0.3871968302
## 305 0.31944444 0.73333333 0.2114304029 0.3185784039
## 306 0.81944444 1.00000000 0.8326004868 0.0630152886
## 307 0.30555556 0.86666667 0.0000000000 0.0709497318
## 308 0.22222222 0.00000000 0.3910696221 0.1322840791
## 309 0.77777778 0.46666667 0.5074970703 0.0007204034
## 310 0.58333333 0.06666667 0.5768086619 0.8681061394
## 311 0.30555556 0.53333333 0.0000000000 0.8307452173
## 312 0.61111111 0.33333333 0.7385690962 0.2063255423
## 313 0.48611111 1.00000000 0.0000000000 0.1945489474
## 314 0.48611111 0.46666667 0.9077715121 0.0542003522
## 315 0.91666667 0.46666667 0.4456675247 0.6197370527
## 316 0.52777778 0.53333333 0.4341489799 0.0670775634
## 317 0.44444444 0.60000000 0.6417432066 0.9028656047
## 318 0.51388889 0.06666667 0.4447059766 0.4886236292
## 319 0.37500000 0.60000000 0.1417281824 0.1879152325
## 320 0.72222222 1.00000000 0.0000000000 0.9953173777
## 321 0.12500000 0.86666667 0.5113232304 0.1417793965
## 322 0.55555556 1.00000000 0.8559080119 0.1812715120
## 323 0.09722222 0.13333333 0.9276835705 0.2564436084
## 324 0.00000000 0.46666667 0.9134706878 0.3148363083
## 325 0.90277778 1.00000000 0.6893097888 0.8623429120
## 326 0.15277778 0.66666667 0.4930938811 0.3245317378
## 327 0.98611111 0.93333333 0.0000000000 0.3933802930
## 328 0.77777778 0.13333333 0.5215597111 0.6322440567
## 329 1.00000000 0.73333333 0.0773545408 0.8425718402
## 330 0.70833333 0.06666667 0.9286351025 0.3414512127
## 331 0.54166667 0.80000000 0.4338484961 0.7286680541
## 332 0.88888889 0.53333333 0.1204439147 0.5764027856
## 333 1.00000000 0.06666667 0.5212291790 0.4820199312
## 334 0.08333333 0.00000000 0.0012720480 0.0882594253
## 335 0.38888889 0.13333333 0.2576448081 0.6099915953
## 336 0.26388889 0.93333333 0.8720540070 0.5529496518
## 337 0.08333333 0.86666667 0.5069561995 0.7299587769
## 338 0.61111111 0.20000000 0.0576428049 0.0182902425
## 339 0.33333333 0.60000000 0.6070172978 0.1304530537
## 340 0.16666667 0.13333333 0.7649215237 0.5104858721
## 341 0.55555556 1.00000000 0.0000000000 0.0000000000
## 342 0.15277778 0.26666667 0.5752261140 0.0204214360
## 343 0.09722222 0.20000000 0.7306563567 0.2600956536
## 344 0.97222222 0.46666667 0.9668165747 0.8166673337
## 345 0.19444444 0.20000000 0.3772173199 0.7625470263
## 346 0.66666667 1.00000000 0.7125872655 0.4319819099
## 347 0.52777778 0.40000000 0.9322108595 0.0613143360
## 348 0.47222222 0.00000000 0.5130259718 0.6705955335
## 349 0.48611111 0.46666667 0.5160308096 0.3756903866
## 350 0.48611111 0.80000000 0.5626458598 0.4111102217
## 351 0.09722222 0.13333333 0.7191578441 0.4867525814
## 352 0.91666667 0.80000000 0.5458788650 0.9040662771
## 353 0.72222222 1.00000000 0.0000000000 0.1748178980
## 354 0.37500000 0.26666667 0.3209968049 0.5650364204
## 355 0.48611111 1.00000000 0.7115455884 0.9186544465
## 356 0.62500000 0.66666667 0.6549745090 0.4546345954
## 357 0.87500000 0.13333333 0.0658560282 0.2719522933
## 358 0.25000000 0.73333333 0.9012810625 0.0810253742
## 359 0.00000000 0.86666667 0.3658790653 0.0000000000
## 360 0.70833333 1.00000000 0.7480844159 0.3022192428
## 361 0.25000000 0.53333333 0.1480984385 0.5295265349
## 362 0.47222222 0.00000000 0.4757259187 0.6784499320
## 363 0.44444444 1.00000000 0.7893308226 0.2458376691
## 364 0.94444444 0.33333333 0.0401446329 0.7022232450
## 365 0.83333333 0.26666667 0.0343352798 0.5621848235
## 366 0.30555556 0.06666667 0.8144612827 0.2064456095
## 367 0.55555556 0.40000000 0.7609551378 0.0226526855
## 368 0.48611111 1.00000000 0.2439527639 0.2559133115
## 369 0.66666667 0.93333333 0.0512625327 0.7136896662
## 370 0.94444444 0.66666667 0.4470898146 0.5384015048
## 371 0.87500000 0.86666667 0.0041967568 0.3031397583
## 372 0.01388889 0.66666667 0.8263404081 0.3742595854
## 373 0.04166667 0.93333333 0.3932331053 0.4909149124
## 374 0.98611111 1.00000000 0.3947755887 0.3752401345
## 375 0.88888889 0.86666667 0.0000000000 0.6151044585
## 376 0.13888889 0.40000000 0.6344314346 0.2219643000
## 377 0.76388889 0.20000000 0.7942487405 0.9908148563
## 378 0.70833333 0.20000000 0.8781538277 0.8932202033
## 379 0.83333333 0.60000000 0.4069351656 0.6678239814
## 380 0.48611111 0.60000000 0.2681917888 0.6715860882
## 381 0.08333333 0.53333333 0.2218271417 0.3519370848
## 382 0.93055556 0.86666667 0.7842225984 0.1606599696
## 383 0.31944444 0.20000000 0.1336051042 0.6273012887
## 384 0.93055556 0.46666667 0.2008633901 0.0095953734
## 385 0.91666667 0.66666667 0.7099630405 0.5186704555
## 386 0.13888889 0.33333333 0.5849818207 0.5429940767
## 387 0.05555556 0.00000000 0.7189575216 0.5706795806
## 388 0.13888889 0.40000000 0.3435030399 0.2535619947
## 389 0.81944444 0.80000000 0.4438746382 0.5547206436
## 390 0.61111111 0.13333333 0.1277657028 0.1385976147
## 391 0.31944444 0.46666667 0.5310950631 0.1587789162
## 392 0.12500000 0.06666667 0.0724566552 0.6499839910
## 393 0.87500000 0.46666667 0.0323821352 0.1049687825
## 394 0.98611111 0.93333333 0.3114714691 0.5952533419
## 395 0.59722222 0.06666667 0.8379190497 0.4810393821
## 396 0.48611111 0.86666667 0.3867827202 0.9876230689
## 397 0.43055556 0.20000000 0.1596470317 0.7335908109
## 398 0.52777778 0.00000000 0.3066537125 0.0000000000
## 399 0.44444444 0.46666667 0.7272909384 0.0384215160
## 400 0.01388889 0.40000000 0.6168531335 0.4424677820
## 401 0.95833333 0.93333333 0.0000000000 0.3794024654
## 402 0.80555556 0.80000000 0.6714911007 0.7954254382
## 403 0.63888889 0.60000000 0.6572181212 0.7661590491
## 404 0.11111111 0.06666667 0.3872234297 0.1951492836
## 405 0.30555556 0.26666667 0.9941706147 0.7487092772
## 406 0.19444444 0.20000000 0.9957130981 0.1913471544
## 407 0.98611111 1.00000000 0.9065795931 0.3130052830
## 408 0.27777778 0.46666667 0.6072176204 0.3733390699
## 409 0.65277778 0.00000000 0.5588597642 0.0351296726
## 410 1.00000000 0.33333333 0.4756457897 0.9404066277
## 411 0.76388889 0.13333333 0.9202516051 0.2620767630
## 412 0.04166667 0.33333333 0.3165796933 0.0000000000
## 413 0.97222222 0.66666667 0.0511223069 0.7782658289
## 414 0.76388889 0.33333333 0.0575025792 0.7306891859
## 415 0.13888889 0.06666667 0.7027914943 0.0875490275
## 416 0.81944444 0.86666667 0.5697272609 0.9000840471
## 417 0.91666667 0.66666667 0.9407946794 0.3088529577
## 418 0.79166667 0.33333333 0.0023237412 0.1735271752
## 419 0.54166667 0.40000000 0.9227556366 0.7134095093
## 420 0.16666667 0.26666667 0.1445927944 0.3033298647
## 421 0.09722222 0.00000000 0.7238854556 0.0652465381
## 422 0.01388889 0.33333333 0.3316138984 0.2027935644
## 423 0.06944444 0.20000000 0.5838800469 0.5564015849
## 424 0.22222222 0.66666667 0.2072937429 0.5669174738
## 425 0.43055556 0.66666667 0.5688258096 0.5367705915
## 426 0.97222222 0.93333333 0.6035216699 0.2567037541
## 427 0.98611111 0.86666667 0.0676789631 0.0259245177
## 428 0.22222222 0.86666667 0.0000000000 0.6945189306
## 429 0.75000000 0.20000000 0.3919209928 0.0072840791
## 430 0.19444444 1.00000000 0.5491441220 0.3331065397
## 431 0.36111111 0.60000000 0.4212482096 0.8792023533
## 432 0.68055556 0.33333333 0.5825979828 0.4307212039
## 433 0.23611111 0.53333333 0.3841885436 0.3939606179
## 434 0.72222222 0.06666667 0.7521810114 0.6401985112
## 435 0.86111111 0.40000000 0.9881909875 0.5665672777
## 436 0.48611111 0.66666667 0.3242019652 0.6424097495
## 437 0.41666667 0.33333333 0.9847254079 0.8806431602
## 438 0.23611111 0.80000000 0.1819930087 0.2479788682
## 439 0.59722222 0.86666667 0.2907581206 0.6312935244
## 440 0.27777778 0.66666667 0.1423291499 0.2460677980
## 441 0.48611111 0.80000000 0.9429080820 0.8973625230
## 442 0.56944444 0.33333333 0.9445807750 0.1089610182
## 443 0.94444444 0.60000000 0.0375304240 0.3650344193
## 444 0.90277778 0.86666667 0.1838259598 0.8768810534
## 445 0.84722222 0.73333333 0.9743987820 0.7571940287
## 446 0.87500000 0.46666667 0.4472200242 0.9866325142
## 447 0.69444444 1.00000000 0.1364897485 0.4490714800
## 448 0.23611111 0.40000000 0.5831989503 0.2866905467
## 449 0.12500000 0.33333333 0.5778503390 0.2623269031
## 450 0.98611111 0.00000000 0.0000000000 0.5497878812
## 451 0.01388889 0.06666667 0.1092559020 0.5021512047
## 452 0.48611111 0.00000000 0.6141587957 0.9766969503
## 453 0.36111111 0.66666667 0.4986828794 0.3414412071
## 454 0.30555556 0.46666667 0.1114494336 0.0670975746
## 455 0.02777778 0.53333333 0.0000000000 0.4224465701
## 456 0.79166667 0.80000000 0.3239315298 0.2971964300
## 457 0.48611111 0.86666667 0.6135177636 0.2759945570
## 458 0.41666667 0.66666667 0.9159446709 0.3715780837
## 459 0.23611111 1.00000000 0.1641042078 0.8734591371
## 460 0.62500000 0.00000000 0.7642704755 0.1295425438
## 461 0.11111111 0.60000000 0.2575346308 0.4022852798
## 462 0.22222222 0.60000000 0.8959524835 0.5678379893
## 463 0.08333333 0.06666667 0.3367922355 0.2604858721
## 464 0.09722222 0.86666667 0.4133655185 0.3383794925
## 465 0.88888889 0.73333333 0.5036809263 0.0000000000
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## 467 0.33333333 1.00000000 0.8092328649 0.3588509565
## 468 0.01388889 0.53333333 0.9809693607 0.6529156328
## 469 0.13888889 0.20000000 0.8376486143 0.0157388137
## 470 0.26388889 0.66666667 0.3093079859 0.6430200913
## 471 0.13888889 0.73333333 0.7603641863 0.9806691747
## 472 0.23611111 0.66666667 0.3152575647 0.7544124710
## 473 0.18055556 0.20000000 0.3334067849 0.2692307692
## 474 0.91666667 0.53333333 0.4729714841 0.3699071480
## 475 0.91666667 0.06666667 0.2768156732 0.1615304571
## 476 0.30555556 0.73333333 0.1485090997 0.3250120067
## 477 0.50000000 0.86666667 0.7585612837 0.7310693989
## 478 0.81944444 0.73333333 0.6359639019 0.7253061715
## 479 0.33333333 0.80000000 0.4565450375 0.1877051149
## 480 0.34722222 0.33333333 0.8502989814 0.4398763307
## 481 0.59722222 0.13333333 0.6552950250 0.8002881614
## 482 0.48611111 0.40000000 0.7199491181 0.9020751621
## 483 0.20833333 0.66666667 0.5697272609 0.0159589370
## 484 0.52777778 0.73333333 0.5337593526 0.9861522453
## 485 0.88888889 0.46666667 0.0670880117 0.7651785000
## 486 0.79166667 0.20000000 0.8599144623 0.6043484351
## 487 0.76388889 1.00000000 0.6825288715 0.2750940527
## 488 0.58333333 0.00000000 0.1204238825 0.5689986392
## 489 0.91666667 0.66666667 0.0973066637 0.3073621228
## 490 0.76388889 0.00000000 0.8136599926 0.1807412151
## 491 0.29166667 0.53333333 0.4776790633 0.3721283919
## 492 0.22222222 0.20000000 0.7964823366 0.0990254543
## 493 0.18055556 0.26666667 0.0817516201 0.3041803410
## 494 0.31944444 0.13333333 0.3267761095 0.6287821180
## 495 0.48611111 0.93333333 0.9225152496 0.2448271032
## 496 0.26388889 0.53333333 0.1233986719 0.0000000000
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## 498 0.22222222 0.80000000 0.7476537225 0.0000000000
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## 500 0.47222222 0.33333333 0.2935426036 0.3775414232
## 501 0.86111111 0.26666667 0.9210228468 0.0593232210
## 502 0.20833333 0.53333333 0.8322799708 0.5465060434
## 503 0.70833333 0.60000000 0.2936527810 0.4169835108
## 504 0.73611111 0.53333333 0.9573713679 0.9240274554
## 505 0.34722222 0.26666667 0.3452758942 0.8733290643
## 506 0.16666667 0.00000000 0.5672332455 0.6508444729
## 507 0.48611111 0.20000000 0.4105509871 0.0255943328
## 508 0.63888889 0.73333333 0.9172868318 0.7861502441
## 509 0.37500000 0.93333333 0.3301014634 0.7287280877
## 510 0.59722222 1.00000000 0.0000000000 0.1480629152
## 511 0.73611111 0.86666667 0.9650036559 0.3456335548
## 512 0.33333333 0.06666667 0.8684582177 0.2873709277
## 513 0.38888889 0.60000000 0.0949228257 0.0212719123
## 514 0.26388889 0.86666667 0.5824677731 0.3930100856
## 515 0.48611111 0.26666667 0.3254639970 0.9230369007
## 516 0.76388889 0.80000000 0.0643335771 0.7761646522
## 517 0.59722222 0.93333333 0.7284427929 0.0219923157
## 518 0.98611111 0.33333333 0.3494025381 0.3025294165
## 519 0.51388889 0.00000000 0.5559951522 0.4516429200
## 520 0.65277778 0.40000000 0.5452879135 0.9744957176
## 521 0.19444444 0.06666667 0.5034605715 0.5709497318
## 522 0.88888889 0.53333333 0.5820771442 0.0447550628
## 523 0.12500000 0.20000000 0.4279189495 0.8067317698
## 524 0.33333333 0.60000000 0.4212882741 0.6712559033
## 525 0.70833333 0.40000000 0.7771512135 0.6569078684
## 526 0.50000000 0.13333333 0.1812718477 0.0921415993
## 527 0.36111111 0.46666667 0.2029767926 0.2673997439
## 528 1.00000000 0.80000000 0.1969671171 0.8315156488
## 529 0.45833333 0.26666667 0.3136750168 0.2890118466
## 530 0.48611111 0.93333333 0.1400554893 0.9075382214
## 531 0.66666667 0.13333333 0.6647702802 0.7514007844
## 532 0.47222222 0.33333333 0.6420837548 0.0000000000
## 533 0.38888889 0.40000000 0.7923657088 0.6673837349
## 534 0.97222222 0.73333333 0.5557347329 0.4509125110
## 535 0.45833333 0.26666667 0.2924808942 0.5156287521
## 536 1.00000000 0.46666667 0.6775708891 0.7093072120
## 537 0.63888889 1.00000000 0.2892456856 0.1924477708
## 538 0.00000000 0.46666667 0.2430012320 0.7300088049
## 539 0.12500000 0.13333333 0.2290788169 0.9629392460
## 540 0.55555556 0.60000000 0.6780516632 0.7902625470
## 541 0.55555556 0.00000000 0.4805036108 0.9059273193
## 542 0.52777778 0.20000000 0.9237472330 0.5690686785
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## 544 0.83333333 0.93333333 0.5542222979 0.0572520612
## 545 0.45833333 0.26666667 0.8950109677 0.1057192028
## 546 0.40277778 0.20000000 0.9155440259 0.4641699352
## 547 0.95833333 0.66666667 0.3507246667 0.2377631474
## 548 0.93055556 0.00000000 0.2844379451 0.7459477307
## 549 0.91666667 0.80000000 0.0221055900 0.4326823021
## 550 0.62500000 0.93333333 0.7225733431 0.0000000000
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## 552 0.65277778 1.00000000 0.3771371909 0.2143200192
## 553 0.91666667 0.20000000 0.3400775248 0.1006563676
## 554 0.00000000 0.60000000 0.2385741043 0.1259905547
## 555 0.59722222 1.00000000 0.3977203297 0.8329564556
## 556 0.62500000 0.46666667 0.8180270235 0.7624669815
## 557 0.68055556 0.33333333 0.9183585573 0.6827423357
## 558 0.34722222 0.13333333 0.4476206693 0.0574621788
## 559 0.48611111 0.06666667 0.7630985887 0.4230669175
## 560 0.48611111 0.66666667 0.5062951352 0.0000000000
## 561 0.77777778 0.00000000 0.9771231683 0.9905447050
## 562 0.13888889 0.06666667 0.9724756859 0.6814716241
## 563 0.69444444 0.46666667 0.8042348181 0.3968322260
## 564 0.40277778 0.26666667 0.7201494406 0.3305851277
## 565 0.13888889 0.66666667 0.8724746842 0.6796305931
## 566 0.90277778 0.93333333 0.7309868889 0.8910389818
## 567 0.29166667 0.93333333 0.9471849678 0.1666633315
## 568 0.22222222 0.40000000 0.8507597232 0.1625510286
## 569 0.05555556 0.06666667 0.4557938281 0.0000000000
## 570 0.84722222 0.93333333 0.8456314667 0.4497818779
## 571 0.47222222 0.26666667 0.6420637226 0.3858260626
## 572 0.29166667 0.53333333 0.9125792526 0.6325742416
## 573 0.86111111 0.93333333 0.3185528701 0.0290562715
## 574 0.47222222 0.53333333 0.9702821543 0.2583046506
## 575 0.40277778 0.46666667 0.7581105580 0.0000000000
## 576 0.94444444 0.66666667 0.5640681497 0.2775454254
## 577 0.01388889 0.60000000 0.4955878965 0.6293624430
## 578 0.30555556 0.93333333 0.0534861126 0.9062575042
## 579 0.27777778 0.40000000 0.0000000000 0.9376450812
## 580 0.25000000 0.73333333 0.0922485201 0.6802309293
## 581 0.11111111 0.00000000 0.1812718477 0.5935824061
## 582 0.43055556 0.06666667 0.1503821152 0.1599895942
## 583 0.65277778 0.86666667 0.7508688989 0.6126130633
## 584 0.26388889 0.80000000 0.8372780176 0.1309833507
## 585 0.75000000 0.13333333 0.2862909284 0.0000000000
## 586 0.41666667 0.06666667 1.0000000000 0.1007664292
## 587 0.97222222 0.60000000 0.5034806038 0.9786680541
## 588 0.77777778 0.53333333 0.4895081081 0.3756503642
## 589 0.47222222 1.00000000 0.6238544056 0.5006503642
## 590 0.73611111 0.46666667 0.7592724286 0.4917053550
## 591 0.16666667 0.20000000 0.1361892647 0.3290742816
## 592 0.93055556 0.66666667 0.7388695800 0.2356419595
## 593 0.72222222 0.20000000 0.8033333667 0.0671576083
## 594 0.55555556 0.60000000 0.0000000000 0.8027495397
## 595 0.11111111 0.20000000 0.5906809964 0.4636296326
## 596 0.50000000 0.86666667 0.7540940915 0.0000000000
## 597 0.73611111 0.00000000 0.0299982973 0.7562234852
## 598 0.31944444 0.26666667 0.1253618326 0.0697790763
## 599 0.18055556 0.66666667 0.1049389517 0.7571339950
## 600 0.40277778 0.86666667 0.3326255271 0.0325682382
## 601 0.84722222 0.13333333 0.3262552710 0.4582566237
## 602 0.54166667 0.20000000 0.0929997296 0.4358540783
## 603 0.52777778 0.86666667 0.4252746923 0.9743356280
## 604 0.18055556 0.00000000 0.8786946985 0.0850176099
## 605 0.88888889 0.86666667 0.2357996374 0.0000000000
## 606 0.34722222 0.86666667 0.4769078216 0.1200072040
## 607 0.27777778 0.53333333 0.2071935817 0.0412030737
## 608 0.52777778 0.66666667 0.3099490179 0.8186784599
## 609 0.97222222 0.66666667 0.4987930568 0.7811174258
## 610 0.61111111 0.13333333 0.6918739170 0.6977707516
## 611 0.22222222 0.73333333 0.6126163123 0.4373048907
## 612 0.41666667 0.86666667 0.0000000000 0.4025054030
## 613 0.51388889 0.53333333 0.2567934374 0.4369847114
## 614 0.98611111 0.13333333 0.3286391090 0.0825462259
## 615 0.05555556 0.46666667 0.6575586695 0.0868086128
## 616 0.86111111 1.00000000 0.8801670690 0.5816157048
## 617 0.55555556 0.00000000 0.8171656367 0.7346914272
## 618 0.62500000 0.66666667 0.7950700628 0.2092371728
## 619 0.20833333 0.00000000 0.3081160669 0.8284839510
## 620 0.06944444 0.93333333 0.7589418965 0.4084787481
## 621 0.70833333 0.40000000 0.1027955008 0.2657188025
## 622 0.98611111 0.80000000 0.0040364988 0.5959237173
## 623 0.62500000 0.86666667 0.9170464448 0.0150884495
## 624 0.09722222 0.33333333 0.4737126774 0.0000000000
## 625 0.58333333 0.40000000 0.3984214585 0.8789422076
## 626 0.31944444 0.93333333 0.0966055349 0.1014868326
## 627 0.05555556 0.66666667 0.2098678873 0.1977207236
## 628 0.18055556 0.86666667 0.4629152936 0.4321019771
## 629 0.04166667 0.93333333 0.9708230251 0.2277275274
## 630 0.12500000 0.46666667 0.3383948157 0.1658428720
## 631 0.48611111 1.00000000 0.3425515079 0.6008264628
## 632 0.02777778 0.00000000 0.2440028446 0.7981369567
## 633 0.34722222 0.00000000 0.0679694308 0.4181141439
## 634 0.81944444 0.60000000 0.9068600447 0.5764127912
## 635 0.48611111 0.46666667 0.3776480133 0.0874989994
## 636 0.22222222 0.20000000 0.3337873977 0.1548066917
## 637 0.05555556 0.46666667 0.7346728232 0.1350256143
## 638 0.43055556 0.26666667 0.7481144643 0.4867425758
## 639 0.01388889 0.86666667 0.6335500155 0.0000000000
## 640 0.66666667 0.66666667 0.6939172067 0.7018630433
## 641 0.23611111 0.86666667 0.2489407947 0.8241215080
## 642 0.34722222 0.60000000 0.5666723425 0.3214700232
## 643 0.40277778 0.00000000 0.1846372660 0.6739674218
## 644 0.94444444 0.93333333 0.5256963712 0.7283078524
## 645 0.76388889 0.80000000 0.0157153016 0.3263727688
## 646 0.00000000 0.20000000 0.7213413596 0.4182142000
## 647 0.48611111 0.86666667 0.6675146987 0.4273793324
## 648 0.94444444 0.26666667 0.2803914302 0.7012026735
## 649 0.12500000 1.00000000 0.5333286591 0.9996798207
## 650 0.09722222 0.53333333 0.0450124701 0.2649983991
## 651 0.66666667 0.46666667 0.2503230201 0.1390878892
## 652 0.94444444 0.93333333 0.1858692495 0.1162951253
## 653 0.52777778 0.80000000 0.4083173910 0.8322360522
## 654 0.29166667 0.26666667 0.8317491161 0.7598054911
## 655 0.12500000 0.66666667 0.8149821212 0.7743836548
## 656 0.84722222 0.06666667 0.4199160649 0.2305290963
## 657 0.88888889 0.86666667 0.4529191999 0.2298186985
## 658 0.18055556 0.66666667 0.1680705937 0.9445389418
## 659 0.97222222 0.73333333 0.5365638678 0.2096774194
## 660 0.86111111 0.60000000 0.7172147157 0.2728027696
## 661 0.45833333 0.80000000 0.0153847695 0.4464300008
## 662 0.29166667 0.06666667 0.0928995683 0.6945489474
## 663 0.23611111 0.06666667 0.9653041397 0.7925138077
## 664 0.69444444 0.93333333 0.0438606156 0.9838909789
## 665 0.91666667 0.86666667 0.5352116908 0.5806651725
## 666 0.70833333 0.20000000 0.3999138613 0.7936644521
## 667 0.50000000 0.93333333 0.0451627120 0.9209857520
## 668 0.55555556 0.20000000 0.2150862889 0.1965500680
## 669 0.88888889 0.73333333 0.9567203197 0.9340430641
## 670 0.52777778 0.80000000 0.4187942588 0.7760445850
## 671 0.19444444 0.06666667 0.5165316159 0.9772972865
## 672 0.48611111 0.66666667 0.8546860445 0.9031557672
## 673 0.54166667 0.40000000 0.8899528240 0.9567357720
## 674 0.48611111 0.66666667 0.0000000000 0.0393820540
## 675 0.45833333 0.86666667 0.5003355402 0.8244616986
## 676 0.47222222 0.73333333 0.9241979587 0.0990554711
## 677 0.95833333 1.00000000 0.6073277978 0.1599195550
## 678 0.58333333 1.00000000 0.1092659181 0.5700392220
## 679 1.00000000 0.06666667 0.5556245555 0.0000000000
## 680 0.26388889 0.33333333 0.5488837028 0.0984751461
## 681 0.63888889 0.60000000 0.2989312794 0.5278656047
## 682 0.55555556 0.00000000 0.3373932031 0.3772612663
## 683 0.18055556 0.46666667 0.8031630926 0.6833826943
## 684 0.38888889 0.46666667 0.5596209898 0.2289281998
## 685 0.81944444 0.40000000 0.3347289136 0.9002141199
## 686 0.48611111 0.86666667 0.2959765222 0.9914452093
## 687 0.69444444 0.66666667 0.3632648564 0.4279196350
## 688 0.06944444 0.46666667 0.0302487004 0.8290542704
## 689 0.91666667 0.60000000 0.9358967938 0.0770531498
## 690 0.13888889 0.86666667 0.8098638808 0.7816477227
## 691 0.25000000 0.93333333 0.1221566722 0.9075082046
## 692 0.13888889 0.66666667 0.3144162101 0.0683382694
## 693 0.86111111 0.86666667 0.2381333948 0.4658208597
## 694 0.13888889 0.93333333 0.6466611244 0.6540262547
## 695 0.36111111 0.06666667 0.1695930448 0.8726586889
## 696 0.06944444 0.40000000 0.0000000000 0.6394480909
## 697 0.75000000 0.93333333 0.0000000000 0.6380873289
## 698 0.37500000 0.20000000 0.5202475986 0.5042924037
## 699 0.38888889 0.40000000 0.2658480153 0.5396622108
## 700 0.93055556 0.80000000 0.0527649516 0.0000000000
## 701 0.55555556 0.86666667 0.6754274382 0.1658128552
## 702 0.05555556 0.00000000 0.1025250654 0.7963659649
## 703 0.11111111 0.53333333 0.3301415279 0.5649863924
## 704 0.37500000 0.53333333 0.0000000000 0.0789041863
## 705 0.19444444 0.40000000 0.1414978115 0.8074021452
## 706 0.81944444 0.20000000 0.0000000000 0.0000000000
## 707 0.22222222 0.40000000 0.1804805737 0.7928539982
## 708 0.83333333 0.06666667 0.2828253488 0.8631033379
## 709 0.55555556 0.60000000 0.1201834954 0.0030417034
## 710 0.33333333 0.20000000 0.4241028055 0.6171255903
## 711 0.97222222 0.80000000 0.1353278779 0.1916573281
## 712 0.13888889 0.20000000 0.8074800429 0.7826182662
## 713 0.19444444 0.66666667 0.7223329561 0.0133674858
## 714 1.00000000 0.00000000 0.2119612576 0.3942908028
## 715 0.13888889 1.00000000 0.7959114174 0.3383194589
## 716 0.44444444 0.40000000 0.9725357826 0.4402765549
## 717 1.00000000 0.06666667 0.9349152135 0.7125890499
## 718 0.30555556 0.33333333 0.1723775278 0.5166293124
## 719 0.31944444 0.86666667 0.1764941556 0.1477627471
## 720 0.97222222 0.00000000 0.2503931329 0.3301448811
## 721 0.15277778 0.80000000 0.1815222508 0.0320179300
## 722 0.02777778 0.46666667 0.8552569637 0.5615044425
## 723 0.41666667 0.20000000 0.4236220315 0.2227147202
## 724 0.84722222 0.66666667 0.0002003225 0.5652965661
## 725 0.45833333 1.00000000 0.9302877633 0.5662871208
## 726 0.34722222 0.00000000 0.8705515881 0.3712979268
## 727 0.00000000 0.26666667 0.5445266880 0.9928559994
## 728 0.56944444 0.86666667 0.8685683951 0.7366225086
## 729 0.47222222 0.80000000 0.5799537255 0.8390398623
## 730 0.68055556 0.66666667 0.1567523713 0.9550648363
## 731 0.44444444 0.60000000 0.6878274021 0.3797026335
## 732 0.31944444 0.20000000 0.5074570058 0.6241695349
## hours_per_week_norm age_group capital_gain_bin capital_loss_bin
## 1 0.98979592 31-45 Medium Low
## 2 0.03061224 46-60 Very High Low
## 3 0.70408163 61-90 Low Low
## 4 0.14285714 61-90 Low High
## 5 0.96938776 31-45 Very High High
## 6 0.39795918 31-45 High High
## 7 0.10204082 61-90 Low High
## 8 0.34693878 61-90 Very High Very High
## 9 0.81632653 18-30 Very High Low
## 10 0.70408163 61-90 Medium Medium
## 11 0.88775510 18-30 Medium Very High
## 12 0.19387755 18-30 High High
## 13 0.01020408 61-90 Low Very High
## 14 0.70408163 46-60 High Medium
## 15 0.50000000 18-30 High High
## 16 0.90816327 46-60 Very High High
## 17 0.15306122 31-45 High Very High
## 18 0.61224490 31-45 Very High Low
## 19 0.71428571 61-90 Medium Very High
## 20 0.05102041 18-30 Low Very High
## 21 1.00000000 61-90 Low Very High
## 22 0.87755102 46-60 Medium Low
## 23 0.11224490 46-60 Medium Low
## 24 0.40816327 61-90 High Medium
## 25 0.07142857 61-90 Very High Medium
## 26 0.32653061 61-90 Medium Very High
## 27 0.84693878 31-45 High Medium
## 28 0.39795918 46-60 Very High High
## 29 0.02040816 61-90 High Medium
## 30 0.48979592 61-90 High High
## 31 0.74489796 18-30 Medium Very High
## 32 0.06122449 61-90 Medium Medium
## 33 0.80612245 46-60 High Low
## 34 0.82653061 46-60 Very High Medium
## 35 0.18367347 61-90 Medium High
## 36 0.20408163 46-60 Medium Medium
## 37 0.94897959 18-30 High Low
## 38 0.08163265 31-45 High Very High
## 39 0.63265306 31-45 Very High Medium
## 40 0.02040816 61-90 Low High
## 41 0.68367347 31-45 Very High Very High
## 42 0.12244898 46-60 High Low
## 43 0.65306122 46-60 High Low
## 44 0.83673469 46-60 High Medium
## 45 0.61224490 18-30 Very High High
## 46 0.15306122 46-60 Very High Low
## 47 0.10204082 46-60 Low High
## 48 0.29591837 61-90 Low High
## 49 0.74489796 31-45 Low Medium
## 50 0.54081633 61-90 High Low
## 51 0.91836735 61-90 Low Medium
## 52 0.42857143 31-45 Very High Medium
## 53 0.83673469 46-60 Medium Medium
## 54 0.14285714 18-30 Very High Low
## 55 0.59183673 61-90 Medium Low
## 56 0.87755102 61-90 High Very High
## 57 0.78571429 61-90 High Medium
## 58 0.37755102 61-90 High Medium
## 59 0.40816327 31-45 High Very High
## 60 0.12244898 18-30 Medium High
## 61 0.95918367 31-45 Very High High
## 62 0.84693878 46-60 High Very High
## 63 0.35714286 18-30 Medium Medium
## 64 0.05102041 31-45 High Medium
## 65 0.30612245 18-30 Medium Very High
## 66 0.21428571 61-90 Medium High
## 67 0.94897959 31-45 Medium High
## 68 0.51020408 31-45 Medium Medium
## 69 0.32653061 46-60 High Medium
## 70 0.10204082 31-45 High High
## 71 0.39795918 61-90 Very High Very High
## 72 0.53061224 46-60 High Very High
## 73 0.84693878 61-90 Medium High
## 74 0.93877551 46-60 Low Low
## 75 0.26530612 61-90 Low High
## 76 0.81632653 46-60 Medium Very High
## 77 0.78571429 61-90 Medium High
## 78 0.74489796 18-30 Very High High
## 79 0.02040816 46-60 Medium Medium
## 80 0.52040816 46-60 High Very High
## 81 0.23469388 31-45 Medium Very High
## 82 0.04081633 61-90 High Low
## 83 0.82653061 31-45 Low Very High
## 84 1.00000000 61-90 Medium Low
## 85 0.46938776 46-60 Low Very High
## 86 0.33673469 61-90 Medium Medium
## 87 0.33673469 31-45 High High
## 88 0.43877551 61-90 Very High Very High
## 89 0.38775510 18-30 Low Medium
## 90 0.24489796 18-30 Very High High
## 91 0.33673469 61-90 High Very High
## 92 0.61224490 61-90 Low High
## 93 0.14285714 61-90 Medium High
## 94 0.02040816 61-90 High Very High
## 95 0.55102041 61-90 Medium Medium
## 96 0.79591837 46-60 Medium High
## 97 0.68367347 46-60 Medium High
## 98 0.15306122 31-45 Very High Low
## 99 0.72448980 31-45 Very High High
## 100 0.48979592 46-60 Very High Medium
## 101 0.83673469 46-60 Low Medium
## 102 0.94897959 61-90 High Low
## 103 0.84693878 18-30 High Medium
## 104 0.70408163 61-90 Very High Low
## 105 0.86734694 31-45 Low Very High
## 106 0.58163265 61-90 Medium Medium
## 107 0.97959184 61-90 Low Low
## 108 0.90816327 46-60 Medium Very High
## 109 0.70408163 31-45 Medium High
## 110 0.34693878 46-60 Low Low
## 111 0.47959184 61-90 High High
## 112 0.12244898 18-30 Very High Medium
## 113 0.05102041 61-90 Low Very High
## 114 0.71428571 61-90 Very High Low
## 115 0.78571429 18-30 Medium High
## 116 0.00000000 31-45 Medium Very High
## 117 0.05102041 61-90 Low Medium
## 118 0.17346939 31-45 Medium Medium
## 119 0.15306122 18-30 Low Low
## 120 0.85714286 31-45 Low Medium
## 121 0.86734694 46-60 Very High Low
## 122 0.44897959 61-90 Low Medium
## 123 0.73469388 <NA> Very High Medium
## 124 0.32653061 46-60 Very High Very High
## 125 0.42857143 18-30 Medium Very High
## 126 0.81632653 18-30 Very High Medium
## 127 0.24489796 46-60 High Very High
## 128 0.92857143 46-60 Medium Medium
## 129 0.76530612 18-30 Low Low
## 130 0.02040816 18-30 Very High High
## 131 0.66326531 46-60 Low High
## 132 0.08163265 61-90 Low Medium
## 133 0.29591837 61-90 Very High Very High
## 134 0.96938776 31-45 High Low
## 135 0.80612245 46-60 High Low
## 136 0.01020408 46-60 High Very High
## 137 0.31632653 18-30 Low Low
## 138 0.93877551 31-45 High High
## 139 0.31632653 18-30 Medium Very High
## 140 0.38775510 31-45 High Medium
## 141 0.19387755 46-60 High Very High
## 142 0.73469388 61-90 Medium Very High
## 143 0.59183673 61-90 Very High Medium
## 144 0.66326531 61-90 Low High
## 145 0.82653061 61-90 High Medium
## 146 0.35714286 61-90 Medium Very High
## 147 0.62244898 61-90 Medium High
## 148 0.44897959 61-90 Medium Low
## 149 0.18367347 31-45 Very High Very High
## 150 0.28571429 18-30 Low Medium
## 151 0.67346939 61-90 Very High Low
## 152 0.92857143 18-30 High Medium
## 153 0.63265306 31-45 Very High Very High
## 154 0.95918367 31-45 High High
## 155 0.70408163 61-90 Low Low
## 156 0.23469388 61-90 High Low
## 157 0.62244898 46-60 Low Medium
## 158 0.38775510 46-60 Low Medium
## 159 0.63265306 61-90 High Very High
## 160 0.73469388 31-45 Medium Very High
## 161 0.71428571 61-90 High Very High
## 162 0.78571429 61-90 Very High High
## 163 0.55102041 46-60 Very High Medium
## 164 0.39795918 61-90 High Very High
## 165 0.69387755 46-60 Low High
## 166 0.34693878 61-90 High Medium
## 167 0.12244898 61-90 Low Low
## 168 0.44897959 31-45 Low High
## 169 0.21428571 18-30 Medium Very High
## 170 0.96938776 46-60 Very High Low
## 171 0.70408163 46-60 Medium High
## 172 0.52040816 46-60 Low High
## 173 0.13265306 46-60 High Very High
## 174 0.48979592 61-90 Very High Low
## 175 0.20408163 46-60 Medium Low
## 176 0.67346939 61-90 Very High Medium
## 177 0.46938776 46-60 Medium Medium
## 178 0.82653061 46-60 Very High High
## 179 0.61224490 46-60 Medium Low
## 180 0.68367347 18-30 Medium Medium
## 181 0.47959184 31-45 Medium Medium
## 182 0.71428571 46-60 Low High
## 183 0.15306122 61-90 Medium Low
## 184 0.10204082 61-90 Low Very High
## 185 0.60204082 46-60 Medium Very High
## 186 0.61224490 31-45 High Very High
## 187 0.27551020 31-45 Medium High
## 188 0.41836735 46-60 Very High Very High
## 189 0.19387755 18-30 Very High Very High
## 190 0.16326531 46-60 Medium Low
## 191 0.38775510 61-90 Very High Low
## 192 0.91836735 18-30 Medium High
## 193 0.74489796 46-60 Low High
## 194 0.74489796 31-45 Very High Low
## 195 0.94897959 31-45 High Low
## 196 0.79591837 46-60 Very High Medium
## 197 0.44897959 46-60 Medium Very High
## 198 0.40816327 31-45 Very High Low
## 199 0.69387755 46-60 Very High Medium
## 200 0.94897959 61-90 Low Low
## 201 0.05102041 46-60 Very High High
## 202 0.38775510 46-60 High Low
## 203 0.51020408 61-90 Low High
## 204 0.53061224 61-90 Low Medium
## 205 0.15306122 61-90 Low High
## 206 0.92857143 18-30 Very High Very High
## 207 0.40816327 31-45 Very High Low
## 208 0.03061224 31-45 Medium High
## 209 0.68367347 61-90 Very High Very High
## 210 0.10204082 18-30 Medium Low
## 211 0.91836735 46-60 High High
## 212 0.61224490 46-60 Low Very High
## 213 0.11224490 46-60 High Very High
## 214 0.37755102 18-30 High Very High
## 215 0.28571429 61-90 High Medium
## 216 0.08163265 18-30 High Medium
## 217 0.80612245 18-30 Very High Very High
## 218 0.46938776 18-30 Low Very High
## 219 0.76530612 46-60 Medium Low
## 220 0.81632653 61-90 Medium High
## 221 0.71428571 61-90 Medium Low
## 222 0.17346939 31-45 High Medium
## 223 0.65306122 <NA> Low Medium
## 224 1.00000000 18-30 Medium High
## 225 0.33673469 18-30 High High
## 226 0.54081633 46-60 Low Low
## 227 0.06122449 31-45 Very High Low
## 228 0.66326531 61-90 Low Low
## 229 0.36734694 46-60 High High
## 230 0.22448980 46-60 Medium Medium
## 231 0.32653061 18-30 High Low
## 232 1.00000000 46-60 Very High Very High
## 233 0.67346939 61-90 Very High Very High
## 234 0.45918367 18-30 Medium Very High
## 235 0.38775510 31-45 Very High Very High
## 236 0.36734694 46-60 High Medium
## 237 0.37755102 31-45 Medium Very High
## 238 0.30612245 31-45 Very High High
## 239 0.19387755 46-60 High Low
## 240 0.87755102 61-90 High Very High
## 241 0.62244898 61-90 Medium Medium
## 242 0.00000000 61-90 Low High
## 243 0.74489796 46-60 Low High
## 244 0.89795918 61-90 Very High Low
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