assignment1
How many variables are included in this dataset?
data = read.csv("C:\\Users\\ky925\\Downloads\\fastfood_survey.csv")
length(names(data))#bames()all variable in df## [1] 21subset the data to only include the first eleven columns of data. Call this data_cluster.For the first two sections of this assignment, we will only work with this reduced dataset.How many variables does data_cluster have?
data_cluster = data[,1:11]
length(names(data_cluster))## [1] 11Cluster analysis is particularly sensitive to missing values. Let us see if this dataset has any missing values. How many missing values are there for the variable cleanliness?
sum(is.na(data$cleanliness))## [1] 23How many rows of data would be left if rows corresponding to missing values on any of the eleven variables were removed? (Hint: You can use na.omit() but don’t overwrite the original data)
df=na.omit(data_cluster)#remove all the missing value
nrow(df)## [1] 556What is the imputed value of observation 10 for the variable cleanliness?
#install.packages("mice")
library(mice)##
## 载入程辑包：'mice'## The following object is masked from 'package:stats':
##
## filter## The following objects are masked from 'package:base':
##
## cbind, rbindset.seed(1706)
data_clusters = complete(mice(data_cluster, use.matcher=T))##
## iter imp variable
## 1 1 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 1 2 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 1 3 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 1 4 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 1 5 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 2 1 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 2 2 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 2 3 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 2 4 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 2 5 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 3 1 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 3 2 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 3 3 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 3 4 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 3 5 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 4 1 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 4 2 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 4 3 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 4 4 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 4 5 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 5 1 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 5 2 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 5 3 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 5 4 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgers
## 5 5 speed_of_service variety popularity_with_children cleanliness convenience taste price drive_through friendliness quality_of_fries taste_burgersdata_cluster[1:10,]#answer is 6## speed_of_service variety popularity_with_children cleanliness convenience
## 1 6 5 1 6 6
## 2 5 3 3 6 6
## 3 5 6 1 6 6
## 4 6 3 3 6 6
## 5 NA NA NA 6 6
## 6 6 4 1 6 6
## 7 5 3 1 6 6
## 8 4 4 NA 6 3
## 9 6 6 1 6 6
## 10 NA NA NA NA NA
## taste price drive_through friendliness quality_of_fries taste_burgers
## 1 6 6 1 6 5 6
## 2 6 5 3 5 6 6
## 3 6 6 3 5 3 6
## 4 6 6 6 6 6 6
## 5 6 6 4 6 6 6
## 6 6 6 1 3 3 6
## 7 6 5 2 5 6 6
## 8 NA 3 1 3 6 6
## 9 6 6 1 6 3 6
## 10 NA NA NA NA NA NA##What is the value of observation 10 for the variable cleanliness?
data_cluster=scale(data_clusters)
data_cluster[10,4]## cleanliness
## 0.3479976Compute the Euclidean distance between all observations in data_cluster. How many elements are in the distance matrix?
d = dist(x = data_cluster,method = 'euclidean')
length(d)## [1] 193131Conduct a Hierarchical cluster analysis using the method, ‘ward.D2’. Plot the dendrogram from this process. Let us see how well the dendrogram matches true distances. What is the Cophenetic correlation coefficient?
clusters = hclust(d = d,method='ward.D2')
plot(clusters)#The height represents the dissimilarity between elements that are joined
cor(cophenetic(clusters),d)## [1] 0.7903926#Cophenetic correlation coefficient (CPC) is a goodness of fit statistic for hierarchical clustering which assesses how well a dendrogram matches the true distance metric. It is interpreted similar to a correlation coefficient. CPC> 0.7 indicates relatively strong fit, 0.3<CPC<0.7 indicates moderate fit.Based on the distances shown in the dendrogram alone, which is the best cluster solution?
#install.packages("dendextnd")
library(dendextend)##
## ---------------------
## Welcome to dendextend version 1.17.1
## Type citation('dendextend') for how to cite the package.
##
## Type browseVignettes(package = 'dendextend') for the package vignette.
## The github page is: https://github.com/talgalili/dendextend/
##
## Suggestions and bug-reports can be submitted at: https://github.com/talgalili/dendextend/issues
## You may ask questions at stackoverflow, use the r and dendextend tags:
## https://stackoverflow.com/questions/tagged/dendextend
##
## To suppress this message use: suppressPackageStartupMessages(library(dendextend))
## ---------------------##
## 载入程辑包：'dendextend'## The following object is masked from 'package:stats':
##
## cutreeplot(cut(as.dendrogram(clusters),h=5)$upper)
plot(clusters)
rect.hclust(clusters, k = 2, border = 'tomato')#change k to any #>2 and check the part of different rectangular 
plot(clusters)
rect.hclust(clusters, k = 4, border = 'tomato')
plot(clusters)
rect.hclust(clusters, k = 5, border = 'tomato')
plot(clusters)
rect.hclust(clusters, k = 6, border = 'tomato')
## with a two-cluster solution, how many observations would be in the
smaller of the two clusters?
h_segments_2 = cutree(tree = clusters,k=2)
table(h_segments_2)## h_segments_2
## 1 2
## 581 41with a three-cluster solution, how many observations would be in the smallest of the three clusters?
h_segments_3 = cutree(tree = clusters,k=3)
table(h_segments_3)## h_segments_3
## 1 2 3
## 338 243 41Conduct k-means clustering to generate a two-cluster solution. use a seed of 1706. Set max iterations to 100. Do not set nstart. (Save the cluster memberships in an object as you will need it in a later question). How many observations are in the smaller cluster?
set.seed(1706)
km_2 = kmeans(x = data_cluster,centers = 2,iter.max=100)
k_segments_2 = km_2$cluster
table(k_segments_2)## k_segments_2
## 1 2
## 43 579#Here are the number of observations in the resulting clustersthis time to generate a three-cluster solution. As above, use a seed of 1706 and set max iterations to 100. Do not set nstart. How many observations are in the smallest cluster?
set.seed(1706)
km_3 = kmeans(x = data_cluster, centers = 3,iter.max=100)
table(km_3$cluster)##
## 1 2 3
## 255 326 41Compute the total within cluster sum of squares for cluster solutions from 1 to 10. Use a seed of 1706. Do not set nstart. What is the total within cluster sum of squares for a three-cluster solution?
library(ggplot2)
within_ss = sapply(1:10,FUN = function(x){
set.seed(1706)
kmeans(x = data_cluster,centers = x,iter.max = 100)$tot.withinss})
ggplot(data=data.frame(cluster = 1:10,within_ss),aes(x=cluster,y=within_ss))+
geom_line(col='steelblue',size=1.2)+
geom_point()+
scale_x_continuous(breaks=seq(1,10,1))## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
within_ss[3]# sum of squares for a three-cluster solution## [1] 3801.308For the three-cluster solution, what is the ratio of between sum of squares and total sum of squares? (Express as a decimal.)
ratio_ss = sapply(1:10,FUN = function(x) {
set.seed(617)
km = kmeans(x = data_cluster,centers = x,iter.max = 100)
km$betweenss/km$totss} )
ggplot(data=data.frame(cluster = 1:10,ratio_ss),aes(x=cluster,y=ratio_ss))+
geom_line(col='steelblue',size=1.2)+
geom_point()+
scale_x_continuous(breaks=seq(1,10,1))
ratio_ss[3]## [1] 0.4435209Construct a line graph of clusters (on x-axis) against total within cluster sum of squares (on y-axis). Based on this chart, which of the following are good cluster solutions?
#answer is 2 and 3
ggplot(data = data.frame(cluster = 1:10, within_ss), aes(x = cluster, y = within_ss)) +
geom_line(col = 'steelblue', size = 1.2) +
geom_point() +
scale_x_continuous(breaks = seq(1, 10, 1))
#在某一个点之后，总组内平方和的下降速度会急剧变缓，形成一个类似于手肘的形状，这个点就被称为“肘点”（Elbow Point）。在聚类分析中，我们通常会选择肘点对应的聚类数目作为最终的聚类数目，因为在这个点之后，总组内平方和的下降速度减缓，增加聚类数目不再带来显著的收益The elbow point is used to determine the optimal number of clusters to use in clustering analysis. It is the number of clusters where the total within-cluster sum of squares begins to level off, indicating that additional clusters are not improving the clustering solution substantially.What is the average silhouette width for a 2 cluster solution? Use pam() from library(cluster) to compute silhouette width.
library(cluster)
pam(data_cluster,k = 2)$silinfo$avg.width## [1] 0.5869224What is the average silhouette width for a 3 cluster solution?
pam(data_cluster,k = 3)$silinfo$avg.width## [1] 0.1722077Examine average silhouette width for other cluster solutions. Based on this criterion, which is the best cluster solution?
#answer is 2
library(cluster)
silhoette_width = sapply(2:7,
FUN = function(x) pam(x = data_cluster,k = x)$silinfo$avg.width)
ggplot(data=data.frame(cluster = 2:7,silhoette_width),aes(x=cluster,y=silhoette_width))+
geom_line(col='steelblue',size=1.2)+
geom_point()+
scale_x_continuous(breaks=seq(2,7,1))
## Use Mclust() from library(mclust) to cluster the data. How many
clusters has the model decided to group the data into?
#install.packages("mclust")
library(mclust)## Package 'mclust' version 6.0.0
## Type 'citation("mclust")' for citing this R package in publications.clusters_mclust = Mclust(data_cluster)
summary(clusters_mclust)## ----------------------------------------------------
## Gaussian finite mixture model fitted by EM algorithm
## ----------------------------------------------------
##
## Mclust VEV (ellipsoidal, equal shape) model with 3 components:
##
## log-likelihood n df BIC ICL
## -6003.55 622 213 -13377.32 -13391.27
##
## Clustering table:
## 1 2 3
## 342 121 159#clustering table list 3 cluster so the answer is 3use model-based clustering to force a two-cluster solution. (Save the cluster memberships in an object as you will need it in a later question). How many observations are in the smaller cluster?
clusters_mclust_2= Mclust(data_cluster,G=2)
summary(clusters_mclust_2)## ----------------------------------------------------
## Gaussian finite mixture model fitted by EM algorithm
## ----------------------------------------------------
##
## Mclust VEV (ellipsoidal, equal shape) model with 2 components:
##
## log-likelihood n df BIC ICL
## -6603.417 622 145 -14139.61 -14145.26
##
## Clustering table:
## 1 2
## 451 171# the answer is 171 bc cluster 2 shows 171Now, let us compare the two-cluster solutions obtained from hierarchical cluster to k-means. Specifically, compare the cluster assignments for hierarchical cluster analysis to k-means for the two-cluster solution. For how many observations do the cluster assignments differ?
h_segments_compare = cutree(tree = clusters,k=2)
table(h_segments_compare)## h_segments_compare
## 1 2
## 581 41set.seed(1706)
km_compare = kmeans(x = data_cluster,centers = 2,iter.max=100)
k_segments_compare = km_compare$cluster
table(k_segments_compare)## k_segments_compare
## 1 2
## 43 579#answer is 4compare the two-cluster solutions for k-means to Model-based clustering. Specifically, compare the cluster assignments for k-means to Model-based clustering. For how many observations do the cluster assignments differ?
table(k_segments_compare)## k_segments_compare
## 1 2
## 43 579m_clusters_2 = Mclust(data = data_cluster,G = 2)
m_segments_compare = m_clusters_2$classification
table(m_segments_compare)## m_segments_compare
## 1 2
## 451 171#The number of cases that differ will be the minimum of a) the number of cases that match with the original labels and b) the number of cases that do not match with the original labels.so the answer is 579-451=128We will use k-means clustering with three clusters. Use a seed of 1706 and set maximum iterations to 100. Do not set nstart.Compared to other clusters, Cluster 1 has the lowest value for:
#install.packages("tidyverse")
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.1 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ lubridate 1.9.2 ✔ tibble 3.2.1
## ✔ purrr 1.0.1 ✔ tidyr 1.3.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks mice::filter(), stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ✖ purrr::map() masks mclust::map()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsset.seed(1706)
km = kmeans(x = data_cluster,centers = 3,iter.max=100)
k_segments = km$cluster
m_clusters = Mclust(data = data_cluster,G = 3)
m_segments = m_clusters$classification
h_segments = cutree(tree = clusters,k=3)
data2 = cbind(data,h_segments, k_segments,m_segments)
data2 %>%
select(speed_of_service:taste_burgers,k_segments)%>%
group_by(k_segments)%>%
summarize_all(function(x) round(mean(x,na.rm=T),2))%>%
data.frame()## k_segments speed_of_service variety popularity_with_children cleanliness
## 1 1 4.93 3.65 2.40 5.72
## 2 2 5.59 4.84 4.22 5.97
## 3 3 2.68 2.84 3.03 1.74
## convenience taste price drive_through friendliness quality_of_fries
## 1 5.13 5.71 4.66 1.77 4.28 4.20
## 2 5.79 5.97 5.71 3.00 5.51 5.57
## 3 2.00 1.24 2.00 4.31 2.26 2.34
## taste_burgers
## 1 5.41
## 2 5.89
## 3 1.76library(dplyr); library(ggplot2); library(tidyr)
data2 %>%
select(speed_of_service:taste_burgers,k_segments)%>%#change the variable name speed:taste
group_by(k_segments)%>%
summarize_all(function(x) round(mean(x,na.rm=T),2))%>%
gather(key = var,value = value,speed_of_service:taste_burgers)%>%
ggplot(aes(x=var,y=value,fill=factor(k_segments)))+
geom_col(position='dodge')+
coord_flip()
#answer is popularity with children & drive through demographic makeup of the customers that belong to each cluster or market segment. To examine distributions of factor demographic variables, Compared to other clusters, Cluster 1:
#not sufficient to answer the question
round(prop.table(table(data2$k_segments,data2[,18]),1), 2) * 100##
## 1.managerial 2.skilled trade 3.laborer 4.office worker 5.technical
## 1 14 5 3 11 6
## 2 9 6 5 12 3
## 3 11 5 5 16 3
##
## 6.professional 7.stay at home mom 8.student 9.retired
## 1 23 23 12 4
## 2 16 33 8 8
## 3 29 21 5 5data2## speed_of_service variety popularity_with_children cleanliness convenience
## 1 6 5 1 6 6
## 2 5 3 3 6 6
## 3 5 6 1 6 6
## 4 6 3 3 6 6
## 5 NA NA NA 6 6
## 6 6 4 1 6 6
## 7 5 3 1 6 6
## 8 4 4 NA 6 3
## 9 6 6 1 6 6
## 10 NA NA NA NA NA
## 11 6 6 6 6 5
## 12 5 4 1 6 5
## 13 6 3 6 6 6
## 14 5 2 3 6 6
## 15 5 5 5 6 6
## 16 6 4 4 6 6
## 17 6 3 6 6 6
## 18 NA NA NA 6 NA
## 19 5 5 3 6 6
## 20 5 2 3 6 4
## 21 6 6 5 6 5
## 22 6 1 5 4 4
## 23 3 5 1 6 5
## 24 5 6 6 6 6
## 25 6 6 6 6 6
## 26 6 6 6 6 6
## 27 6 3 1 6 6
## 28 6 4 6 6 6
## 29 6 3 5 5 6
## 30 6 6 NA 6 6
## 31 6 6 3 6 6
## 32 6 6 3 6 6
## 33 6 4 1 6 6
## 34 6 6 1 6 6
## 35 5 4 NA 6 NA
## 36 4 4 4 6 6
## 37 6 4 6 6 4
## 38 6 6 4 6 6
## 39 4 3 4 5 1
## 40 5 5 4 6 5
## 41 6 5 5 6 5
## 42 6 1 6 6 6
## 43 NA NA NA NA NA
## 44 3 6 NA 6 3
## 45 5 5 1 6 5
## 46 NA NA NA NA NA
## 47 3 4 3 6 5
## 48 4 4 6 5 5
## 49 5 6 4 6 6
## 50 6 6 1 6 6
## 51 6 6 6 6 6
## 52 6 4 1 6 6
## 53 5 6 6 6 6
## 54 6 5 4 5 4
## 55 6 6 6 6 6
## 56 6 3 1 6 6
## 57 5 6 1 6 6
## 58 6 6 4 6 6
## 59 4 3 6 6 5
## 60 6 6 6 6 6
## 61 6 4 6 6 6
## 62 4 3 1 6 6
## 63 6 5 4 5 5
## 64 6 6 6 6 6
## 65 4 3 6 6 6
## 66 6 6 1 6 6
## 67 6 3 5 6 6
## 68 3 5 1 5 5
## 69 5 2 6 6 6
## 70 2 3 5 1 1
## 71 NA 4 4 6 5
## 72 5 3 4 6 5
## 73 6 5 1 6 6
## 74 4 4 4 6 4
## 75 5 5 5 6 6
## 76 6 3 2 6 5
## 77 6 4 2 6 5
## 78 3 5 2 1 2
## 79 3 5 4 6 4
## 80 6 3 1 6 6
## 81 5 2 2 6 6
## 82 4 2 3 6 6
## 83 6 4 1 6 5
## 84 6 6 6 6 6
## 85 6 6 1 6 6
## 86 6 6 2 6 6
## 87 5 4 3 6 4
## 88 3 4 1 6 4
## 89 6 1 6 6 6
## 90 5 4 1 6 6
## 91 6 NA NA 6 NA
## 92 6 3 2 6 6
## 93 4 4 NA 6 4
## 94 4 4 3 5 5
## 95 6 6 6 6 6
## 96 NA NA NA NA NA
## 97 2 1 1 6 2
## 98 6 6 6 6 6
## 99 6 6 6 6 6
## 100 5 4 2 6 4
## 101 6 4 1 6 6
## 102 5 4 6 6 5
## 103 6 6 1 6 6
## 104 4 6 1 6 6
## 105 6 6 6 6 6
## 106 5 5 5 6 6
## 107 6 6 6 6 6
## 108 6 4 3 6 6
## 109 2 2 NA 2 1
## 110 3 4 4 6 6
## 111 6 4 1 6 4
## 112 6 3 3 6 6
## 113 6 3 6 6 6
## 114 6 4 1 6 6
## 115 6 3 2 6 6
## 116 6 6 6 6 6
## 117 2 3 NA 6 3
## 118 6 6 4 6 6
## 119 6 6 1 6 6
## 120 5 5 5 6 6
## 121 6 6 1 6 6
## 122 6 5 2 6 5
## 123 6 6 1 6 6
## 124 6 4 4 6 6
## 125 6 4 1 6 6
## 126 6 6 2 6 6
## 127 6 2 6 1 1
## 128 5 4 1 6 5
## 129 5 3 4 6 5
## 130 6 5 1 6 6
## 131 5 4 1 6 5
## 132 2 4 4 1 1
## 133 6 4 4 6 6
## 134 6 5 2 6 6
## 135 6 5 5 6 5
## 136 6 6 3 6 6
## 137 6 5 6 6 6
## 138 4 2 6 6 6
## 139 6 6 6 6 6
## 140 6 1 1 6 6
## 141 4 3 6 6 6
## 142 4 2 5 6 6
## 143 4 4 4 6 6
## 144 5 5 1 3 6
## 145 6 4 1 6 4
## 146 5 4 5 6 6
## 147 6 3 3 5 6
## 148 6 4 3 6 6
## 149 3 2 5 6 6
## 150 6 6 4 6 6
## 151 5 3 3 6 6
## 152 1 3 3 1 1
## 153 NA NA NA 6 NA
## 154 5 4 1 6 5
## 155 5 2 3 6 6
## 156 6 6 6 6 6
## 157 6 5 6 6 6
## 158 6 1 1 5 5
## 159 6 4 6 6 6
## 160 2 5 6 6 6
## 161 6 4 1 6 6
## 162 6 5 4 6 4
## 163 6 6 1 6 6
## 164 6 4 1 6 6
## 165 6 3 4 6 6
## 166 6 6 6 6 4
## 167 1 1 1 1 1
## 168 6 3 3 6 6
## 169 4 3 2 6 6
## 170 5 2 2 6 6
## 171 1 1 1 2 2
## 172 6 6 1 6 3
## 173 6 6 2 6 6
## 174 4 5 1 6 4
## 175 6 4 6 6 6
## 176 4 2 1 6 4
## 177 6 5 6 6 6
## 178 6 4 6 6 6
## 179 4 6 6 6 5
## 180 5 4 3 6 5
## 181 6 6 6 6 6
## 182 6 5 6 6 6
## 183 2 1 1 6 6
## 184 6 4 6 6 2
## 185 3 1 1 6 6
## 186 6 3 1 6 4
## 187 6 5 6 6 6
## 188 6 6 6 6 6
## 189 6 5 2 6 6
## 190 5 6 3 6 6
## 191 6 2 2 6 6
## 192 4 2 2 6 3
## 193 4 4 4 6 4
## 194 6 1 6 6 6
## 195 6 6 1 6 6
## 196 4 5 1 6 3
## 197 6 2 6 6 6
## 198 5 1 6 6 4
## 199 6 6 6 6 6
## 200 6 4 6 6 6
## 201 5 6 5 6 5
## 202 5 6 4 6 6
## 203 5 3 5 6 5
## 204 6 3 6 6 6
## 205 6 6 6 6 6
## 206 6 2 1 6 6
## 207 5 1 4 5 5
## 208 5 5 2 6 6
## 209 4 4 4 6 6
## 210 6 5 1 6 6
## 211 6 1 3 6 6
## 212 6 4 1 6 6
## 213 5 4 1 6 5
## 214 5 4 3 6 5
## 215 5 4 1 6 4
## 216 4 2 1 6 4
## 217 6 6 6 6 6
## 218 4 4 4 6 5
## 219 4 6 6 6 6
## 220 6 5 5 6 2
## 221 6 6 6 6 6
## 222 6 5 4 6 6
## 223 6 5 6 6 6
## 224 5 5 2 6 5
## 225 5 5 3 6 5
## 226 6 3 1 6 6
## 227 6 6 6 6 6
## 228 3 3 1 6 3
## 229 6 6 4 6 6
## 230 5 5 1 6 5
## 231 6 6 6 6 6
## 232 6 5 5 6 6
## 233 5 4 6 5 5
## 234 6 4 5 6 6
## 235 5 4 1 6 6
## 236 6 4 1 6 6
## 237 6 6 1 4 5
## 238 1 NA NA NA NA
## 239 3 2 6 6 6
## 240 6 6 6 6 3
## 241 6 4 6 6 6
## 242 4 6 1 5 4
## 243 5 4 6 6 6
## 244 NA NA NA NA NA
## 245 6 4 3 6 6
## 246 NA NA NA NA NA
## 247 6 5 1 6 6
## 248 6 3 6 NA 6
## 249 5 4 4 6 6
## 250 NA NA NA NA NA
## 251 6 5 5 6 6
## 252 4 4 5 6 4
## 253 6 6 6 6 6
## 254 NA NA NA NA NA
## 255 4 4 4 6 4
## 256 3 1 1 6 6
## 257 4 5 5 6 6
## 258 4 3 1 6 6
## 259 4 3 1 6 5
## 260 4 4 5 6 6
## 261 6 3 6 6 6
## 262 5 4 6 6 6
## 263 6 1 1 6 NA
## 264 6 1 6 6 6
## 265 5 6 6 6 6
## 266 5 1 1 6 6
## 267 6 4 5 6 6
## 268 6 4 6 6 6
## 269 4 4 1 6 5
## 270 6 6 6 6 6
## 271 6 6 6 6 6
## 272 6 6 4 6 4
## 273 4 1 1 6 5
## 274 4 2 1 6 5
## 275 6 6 5 6 6
## 276 6 6 1 6 6
## 277 4 5 1 6 6
## 278 NA NA NA NA NA
## 279 6 NA NA 6 6
## 280 5 5 2 6 6
## 281 6 6 6 6 6
## 282 6 3 3 6 5
## 283 4 3 3 6 5
## 284 6 6 3 6 6
## 285 2 1 1 1 2
## 286 6 6 6 6 6
## 287 6 2 3 5 6
## 288 6 2 1 6 6
## 289 6 4 3 6 6
## 290 6 4 4 6 6
## 291 4 3 2 5 5
## 292 4 6 3 6 5
## 293 6 3 6 6 6
## 294 5 2 5 6 6
## 295 6 6 6 6 6
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## 519 6 5 1 6 6 6
## 520 6 5 1 3 6 6
## 521 5 6 3 5 5 5
## 522 6 4 3 6 4 6
## 523 6 4 1 6 3 5
## 524 6 6 1 2 6 6
## 525 6 6 5 6 6 6
## 526 6 4 1 4 6 6
## 527 6 6 1 6 6 6
## 528 6 3 1 6 6 6
## 529 6 6 5 4 3 5
## 530 3 3 3 3 3 3
## 531 5 6 1 3 5 5
## 532 6 6 1 6 6 6
## 533 6 6 3 3 5 6
## 534 5 6 1 4 5 5
## 535 5 NA 5 4 4 5
## 536 6 6 1 6 6 6
## 537 5 5 1 5 5 5
## 538 6 6 3 5 4 6
## 539 6 6 2 6 6 6
## 540 6 6 3 6 6 6
## 541 5 5 1 3 6 5
## 542 6 6 1 5 3 5
## 543 6 4 2 4 5 6
## 544 6 6 1 5 5 5
## 545 1 3 6 3 3 1
## 546 5 5 3 4 3 4
## 547 5 3 3 5 5 5
## 548 5 5 4 5 4 5
## 549 1 1 NA NA 1 1
## 550 1 1 3 1 3 1
## 551 6 6 1 4 6 6
## 552 6 4 1 4 3 5
## 553 NA NA NA NA NA NA
## 554 4 6 1 1 3 6
## 555 6 5 4 6 2 4
## 556 6 5 4 5 5 5
## 557 6 3 1 6 6 6
## 558 6 5 2 4 2 6
## 559 6 6 1 6 3 6
## 560 6 5 2 5 6 6
## 561 6 6 2 6 6 6
## 562 6 4 1 3 6 6
## 563 6 NA NA 6 2 6
## 564 1 NA NA NA 1 6
## 565 6 4 1 6 6 6
## 566 6 3 1 5 6 6
## 567 6 6 2 5 5 5
## 568 6 6 3 6 6 6
## 569 6 6 4 6 4 5
## 570 6 4 1 4 4 6
## 571 6 6 3 5 5 6
## 572 1 1 3 1 1 1
## 573 6 6 1 6 6 6
## 574 6 6 2 5 3 6
## 575 6 3 1 3 3 5
## 576 6 6 1 6 6 6
## 577 6 6 4 5 6 6
## 578 6 6 1 6 6 6
## 579 6 6 1 6 6 6
## 580 3 5 2 5 4 4
## 581 2 2 6 5 5 2
## 582 6 6 4 4 4 6
## 583 6 4 4 6 2 6
## 584 6 6 1 6 5 5
## 585 6 4 2 6 3 5
## 586 6 5 1 6 1 6
## 587 6 6 3 4 6 6
## 588 6 6 6 5 6 6
## 589 6 6 3 6 5 6
## 590 6 6 3 6 6 6
## 591 6 6 1 6 6 6
## 592 6 5 2 6 5 6
## 593 1 1 1 1 1 6
## 594 3 6 4 4 2 2
## 595 6 6 5 5 2 4
## 596 3 2 NA 5 6 6
## 597 6 6 1 6 5 6
## 598 6 6 5 6 6 6
## 599 6 4 3 4 6 6
## 600 6 6 4 6 6 6
## 601 NA NA 6 NA 1 1
## 602 6 6 1 1 6 6
## 603 6 6 1 5 5 6
## 604 5 4 3 4 4 3
## 605 NA 5 1 5 4 5
## 606 6 5 3 6 6 6
## 607 6 5 1 2 6 6
## 608 1 3 6 1 4 1
## 609 6 6 2 5 6 6
## 610 6 NA 3 3 NA 6
## 611 6 4 1 6 6 6
## 612 6 6 1 6 6 6
## 613 6 6 5 6 6 6
## 614 4 3 1 3 1 6
## 615 6 2 1 3 1 6
## 616 6 4 4 5 1 6
## 617 6 6 3 4 6 6
## 618 6 6 3 6 3 6
## 619 6 5 2 5 5 5
## 620 6 6 4 6 6 6
## 621 6 6 6 1 4 6
## 622 6 5 1 5 5 6
## dollars_avg_meal marital_status gender number_children own_rent dwelling
## 1 2.$10-$15 2.married 2.female NA 2.own 2.apt
## 2 2.$10-$15 2.married 2.female 0 1.rent 1.house
## 3 1.Less than $10 1.single 2.female 0 1.rent 2.apt
## 4 3.$15.01-$20 2.married 2.female 2 2.own 1.house
## 5 4.Over $20 2.married 2.female NA 2.own 1.house
## 6 4.Over $20 2.married <NA> NA 2.own 1.house
## 7 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 8 1.Less than $10 <NA> 2.female 0 2.own 1.house
## 9 2.$10-$15 2.married 2.female NA 2.own 1.house
## 10 <NA> <NA> <NA> NA <NA> <NA>
## 11 4.Over $20 2.married 2.female 1 2.own 1.house
## 12 2.$10-$15 2.married 1.male 0 2.own 1.house
## 13 4.Over $20 <NA> <NA> NA <NA> <NA>
## 14 1.Less than $10 2.married 2.female 1 2.own 1.house
## 15 3.$15.01-$20 2.married <NA> 1 2.own 1.house
## 16 4.Over $20 2.married 2.female 3 2.own 1.house
## 17 3.$15.01-$20 2.married 1.male 3 2.own 1.house
## 18 3.$15.01-$20 2.married 1.male 3 2.own 1.house
## 19 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 20 1.Less than $10 2.married <NA> 2 2.own 1.house
## 21 2.$10-$15 2.married 2.female 4 2.own 1.house
## 22 <NA> 2.married 1.male 3 2.own 1.house
## 23 1.Less than $10 1.single 2.female 0 1.rent 2.apt
## 24 2.$10-$15 2.married 2.female 1 2.own 1.house
## 25 3.$15.01-$20 2.married 1.male NA 2.own 1.house
## 26 3.$15.01-$20 2.married 2.female 0 2.own 1.house
## 27 4.Over $20 2.married 2.female 0 2.own 1.house
## 28 3.$15.01-$20 2.married <NA> 0 1.rent 2.apt
## 29 3.$15.01-$20 2.married 1.male 1 2.own 1.house
## 30 <NA> 2.married 2.female 0 1.rent 2.apt
## 31 1.Less than $10 2.married 1.male 2 1.rent 2.apt
## 32 1.Less than $10 3.other 2.female 0 2.own 1.house
## 33 1.Less than $10 2.married 2.female 0 2.own 1.house
## 34 1.Less than $10 1.single 1.male NA 1.rent 1.house
## 35 2.$10-$15 2.married 2.female 0 <NA> <NA>
## 36 4.Over $20 2.married <NA> 0 2.own 1.house
## 37 1.Less than $10 2.married 2.female 2 2.own 1.house
## 38 2.$10-$15 2.married 2.female 2 2.own 1.house
## 39 2.$10-$15 2.married <NA> 2 2.own 1.house
## 40 4.Over $20 2.married 2.female 2 1.rent 2.apt
## 41 1.Less than $10 2.married 1.male 1 1.rent 2.apt
## 42 2.$10-$15 1.single <NA> 0 1.rent 2.apt
## 43 <NA> 2.married 2.female 0 <NA> 1.house
## 44 4.Over $20 1.single 1.male 0 1.rent 2.apt
## 45 1.Less than $10 2.married 1.male 0 2.own 1.house
## 46 <NA> <NA> <NA> NA <NA> <NA>
## 47 4.Over $20 2.married 1.male 1 2.own 1.house
## 48 1.Less than $10 2.married 2.female 3 2.own 1.house
## 49 4.Over $20 2.married 2.female 1 2.own 1.house
## 50 4.Over $20 2.married 1.male 0 2.own 1.house
## 51 2.$10-$15 3.other 2.female 0 2.own 1.house
## 52 1.Less than $10 2.married <NA> 0 2.own 1.house
## 53 2.$10-$15 2.married 2.female 2 2.own 1.house
## 54 2.$10-$15 2.married 1.male 3 2.own 1.house
## 55 3.$15.01-$20 2.married 2.female 0 2.own 1.house
## 56 4.Over $20 2.married 1.male 0 1.rent 2.apt
## 57 1.Less than $10 2.married 1.male 2 1.rent 2.apt
## 58 1.Less than $10 2.married 2.female 3 2.own 1.house
## 59 4.Over $20 2.married <NA> 4 2.own 1.house
## 60 3.$15.01-$20 3.other 2.female 1 2.own 1.house
## 61 1.Less than $10 2.married 2.female 1 2.own 1.house
## 62 2.$10-$15 1.single 2.female 1 2.own 1.house
## 63 2.$10-$15 2.married 2.female 2 1.rent 1.house
## 64 1.Less than $10 3.other 2.female 0 1.rent 2.apt
## 65 <NA> 3.other 2.female NA 2.own 1.house
## 66 4.Over $20 2.married 1.male 1 2.own 1.house
## 67 3.$15.01-$20 2.married 2.female 2 2.own 1.house
## 68 1.Less than $10 1.single 1.male 0 2.own 1.house
## 69 <NA> 2.married 2.female 2 2.own 1.house
## 70 1.Less than $10 2.married 2.female 1 1.rent 2.apt
## 71 3.$15.01-$20 2.married 2.female 0 2.own <NA>
## 72 4.Over $20 2.married <NA> 0 2.own 1.house
## 73 2.$10-$15 1.single 2.female 1 1.rent 2.apt
## 74 1.Less than $10 2.married 2.female 0 2.own 1.house
## 75 1.Less than $10 2.married 2.female 2 2.own 1.house
## 76 1.Less than $10 1.single 2.female NA 1.rent 2.apt
## 77 <NA> 2.married 2.female 0 1.rent 2.apt
## 78 2.$10-$15 3.other <NA> 1 2.own 1.house
## 79 <NA> 2.married 2.female 0 2.own 1.house
## 80 4.Over $20 2.married <NA> 1 2.own 1.house
## 81 2.$10-$15 3.other 2.female 0 2.own 1.house
## 82 2.$10-$15 2.married 2.female 2 2.own 1.house
## 83 1.Less than $10 2.married 2.female 0 1.rent 2.apt
## 84 2.$10-$15 2.married 1.male 1 2.own 1.house
## 85 2.$10-$15 3.other 2.female 2 2.own <NA>
## 86 1.Less than $10 2.married 2.female 2 2.own 1.house
## 87 1.Less than $10 1.single 1.male NA <NA> 1.house
## 88 1.Less than $10 1.single <NA> 0 <NA> 1.house
## 89 4.Over $20 2.married 2.female 3 2.own 1.house
## 90 2.$10-$15 1.single <NA> 0 2.own 3.duplex
## 91 1.Less than $10 3.other 2.female 0 1.rent 2.apt
## 92 2.$10-$15 3.other 2.female 0 2.own 1.house
## 93 3.$15.01-$20 2.married 1.male 0 2.own 1.house
## 94 1.Less than $10 2.married 1.male 1 2.own 1.house
## 95 2.$10-$15 2.married 2.female 0 2.own 1.house
## 96 2.$10-$15 2.married 1.male 0 1.rent 2.apt
## 97 <NA> 2.married 1.male 0 2.own 1.house
## 98 2.$10-$15 2.married <NA> 2 2.own 1.house
## 99 2.$10-$15 2.married 2.female 0 1.rent 2.apt
## 100 2.$10-$15 1.single 1.male 1 2.own 1.house
## 101 2.$10-$15 2.married 1.male 1 2.own 1.house
## 102 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 103 1.Less than $10 3.other <NA> 0 2.own 1.house
## 104 1.Less than $10 2.married 2.female 1 2.own 1.house
## 105 4.Over $20 2.married 2.female 2 2.own 1.house
## 106 <NA> 2.married <NA> 3 2.own 1.house
## 107 4.Over $20 2.married 1.male 3 <NA> 1.house
## 108 1.Less than $10 2.married 2.female 3 2.own 1.house
## 109 3.$15.01-$20 3.other 2.female 2 2.own 1.house
## 110 2.$10-$15 2.married 2.female 0 1.rent 1.house
## 111 4.Over $20 2.married <NA> 0 2.own 1.house
## 112 4.Over $20 2.married 2.female 2 2.own 1.house
## 113 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 114 3.$15.01-$20 2.married 2.female 0 2.own 2.apt
## 115 3.$15.01-$20 2.married 1.male 0 2.own 1.house
## 116 4.Over $20 2.married 2.female 4 2.own 1.house
## 117 2.$10-$15 2.married 1.male 0 2.own 1.house
## 118 2.$10-$15 3.other <NA> 1 1.rent 2.apt
## 119 1.Less than $10 2.married 2.female 4 2.own 1.house
## 120 4.Over $20 2.married 1.male 4 2.own 1.house
## 121 3.$15.01-$20 2.married 2.female 0 2.own 1.house
## 122 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 123 1.Less than $10 1.single 2.female 0 1.rent 1.house
## 124 4.Over $20 2.married 1.male 2 2.own 1.house
## 125 1.Less than $10 2.married 2.female 0 1.rent 2.apt
## 126 2.$10-$15 2.married <NA> 1 2.own 1.house
## 127 4.Over $20 1.single 2.female 0 2.own 1.house
## 128 4.Over $20 2.married 2.female 0 2.own 1.house
## 129 2.$10-$15 2.married 1.male 1 2.own 1.house
## 130 2.$10-$15 2.married 1.male 0 2.own 1.house
## 131 2.$10-$15 2.married 2.female 0 2.own 1.house
## 132 3.$15.01-$20 <NA> 2.female 1 2.own 1.house
## 133 1.Less than $10 2.married 2.female NA 2.own 1.house
## 134 3.$15.01-$20 3.other 2.female 2 2.own 1.house
## 135 1.Less than $10 2.married 2.female 2 1.rent 1.house
## 136 1.Less than $10 2.married 2.female 0 1.rent 2.apt
## 137 3.$15.01-$20 2.married 1.male 0 2.own 1.house
## 138 <NA> 2.married <NA> 1 2.own 1.house
## 139 <NA> 2.married 2.female 0 2.own 1.house
## 140 4.Over $20 2.married 2.female 0 2.own 1.house
## 141 3.$15.01-$20 2.married 1.male 2 2.own 1.house
## 142 4.Over $20 3.other 2.female 7 2.own 1.house
## 143 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 144 1.Less than $10 1.single <NA> 0 1.rent 2.apt
## 145 1.Less than $10 3.other 2.female 0 2.own 1.house
## 146 4.Over $20 2.married 2.female 2 2.own 1.house
## 147 1.Less than $10 2.married 1.male 2 1.rent 2.apt
## 148 4.Over $20 2.married <NA> 0 1.rent <NA>
## 149 3.$15.01-$20 2.married 1.male NA 2.own 1.house
## 150 4.Over $20 2.married 2.female 1 2.own 1.house
## 151 2.$10-$15 2.married 2.female 0 1.rent 2.apt
## 152 4.Over $20 2.married 2.female 0 2.own 1.house
## 153 3.$15.01-$20 3.other 2.female 0 1.rent 2.apt
## 154 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 155 1.Less than $10 2.married 1.male 2 2.own 1.house
## 156 1.Less than $10 2.married <NA> 2 2.own 1.house
## 157 1.Less than $10 2.married <NA> 1 2.own 1.house
## 158 2.$10-$15 1.single 1.male 0 1.rent 2.apt
## 159 4.Over $20 2.married 2.female 3 2.own 1.house
## 160 4.Over $20 1.single 2.female 0 1.rent 2.apt
## 161 1.Less than $10 1.single 2.female 0 1.rent 2.apt
## 162 2.$10-$15 3.other <NA> 2 2.own 1.house
## 163 1.Less than $10 1.single 2.female 4 2.own 1.house
## 164 1.Less than $10 3.other <NA> 0 1.rent 2.apt
## 165 4.Over $20 2.married 1.male 1 2.own 1.house
## 166 4.Over $20 2.married 2.female 2 2.own 1.house
## 167 4.Over $20 2.married 2.female 4 2.own 1.house
## 168 2.$10-$15 2.married 2.female 0 2.own 1.house
## 169 3.$15.01-$20 2.married 1.male 1 1.rent 3.duplex
## 170 4.Over $20 2.married 2.female 2 2.own 1.house
## 171 1.Less than $10 2.married 1.male 1 <NA> 1.house
## 172 1.Less than $10 1.single <NA> 0 <NA> 1.house
## 173 1.Less than $10 2.married <NA> 0 2.own 1.house
## 174 <NA> 1.single 2.female 0 1.rent 2.apt
## 175 2.$10-$15 2.married 2.female 1 2.own 1.house
## 176 1.Less than $10 1.single 2.female 0 1.rent 2.apt
## 177 3.$15.01-$20 3.other 2.female 2 2.own 1.house
## 178 3.$15.01-$20 2.married 2.female 5 2.own 1.house
## 179 1.Less than $10 3.other <NA> 3 1.rent 1.house
## 180 4.Over $20 2.married 2.female 1 2.own 1.house
## 181 4.Over $20 2.married 2.female 5 2.own 1.house
## 182 4.Over $20 2.married 2.female 2 2.own 1.house
## 183 3.$15.01-$20 2.married 2.female 0 2.own 1.house
## 184 2.$10-$15 2.married 2.female 2 2.own 1.house
## 185 2.$10-$15 2.married 2.female 0 1.rent 2.apt
## 186 3.$15.01-$20 2.married 2.female 3 2.own 1.house
## 187 3.$15.01-$20 2.married 2.female 2 2.own 1.house
## 188 1.Less than $10 3.other <NA> 3 2.own 1.house
## 189 1.Less than $10 1.single 2.female 0 2.own 1.house
## 190 4.Over $20 3.other 2.female 2 1.rent 2.apt
## 191 4.Over $20 2.married 2.female 1 2.own 1.house
## 192 4.Over $20 1.single <NA> 0 1.rent 1.house
## 193 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 194 4.Over $20 2.married 2.female 2 1.rent 2.apt
## 195 1.Less than $10 1.single 2.female NA 2.own 1.house
## 196 1.Less than $10 2.married 1.male NA 2.own 1.house
## 197 <NA> 2.married 1.male 3 1.rent 2.apt
## 198 4.Over $20 2.married 1.male 3 2.own 1.house
## 199 3.$15.01-$20 3.other 2.female 1 2.own 1.house
## 200 2.$10-$15 2.married <NA> 0 2.own 1.house
## 201 2.$10-$15 2.married <NA> 2 2.own 1.house
## 202 2.$10-$15 1.single 2.female 0 1.rent 2.apt
## 203 1.Less than $10 3.other <NA> 0 1.rent 3.duplex
## 204 <NA> 1.single <NA> NA 2.own 1.house
## 205 1.Less than $10 1.single 1.male 0 2.own 1.house
## 206 1.Less than $10 1.single 2.female NA <NA> 1.house
## 207 1.Less than $10 1.single 1.male 2 2.own 1.house
## 208 1.Less than $10 2.married 1.male 0 1.rent 1.house
## 209 2.$10-$15 2.married 2.female 0 2.own 1.house
## 210 3.$15.01-$20 2.married 1.male 0 2.own 1.house
## 211 4.Over $20 3.other <NA> 0 2.own 1.house
## 212 1.Less than $10 2.married 2.female 0 2.own 1.house
## 213 2.$10-$15 2.married 2.female 0 2.own 1.house
## 214 2.$10-$15 2.married 1.male NA 2.own 1.house
## 215 4.Over $20 2.married 1.male 0 2.own 1.house
## 216 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 217 1.Less than $10 2.married 2.female 1 2.own 1.house
## 218 3.$15.01-$20 2.married 1.male 1 2.own 1.house
## 219 2.$10-$15 2.married <NA> 3 2.own 1.house
## 220 4.Over $20 2.married <NA> 4 2.own 1.house
## 221 4.Over $20 2.married 2.female 2 2.own 1.house
## 222 4.Over $20 2.married 1.male 3 2.own 1.house
## 223 2.$10-$15 2.married 2.female 2 2.own 1.house
## 224 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 225 1.Less than $10 2.married 2.female 0 1.rent 2.apt
## 226 2.$10-$15 2.married 2.female 0 2.own 1.house
## 227 <NA> 2.married <NA> 0 1.rent 2.apt
## 228 2.$10-$15 2.married 2.female 1 2.own 1.house
## 229 3.$15.01-$20 2.married 1.male 1 1.rent 2.apt
## 230 3.$15.01-$20 2.married <NA> 0 2.own 1.house
## 231 2.$10-$15 2.married 2.female NA 2.own 1.house
## 232 <NA> 2.married 2.female 1 2.own 1.house
## 233 1.Less than $10 2.married 2.female NA 2.own 1.house
## 234 3.$15.01-$20 2.married 2.female 1 1.rent 2.apt
## 235 2.$10-$15 2.married 1.male 0 1.rent 2.apt
## 236 <NA> 2.married 1.male 0 2.own 1.house
## 237 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 238 4.Over $20 2.married 1.male 6 2.own 1.house
## 239 4.Over $20 2.married 1.male 2 2.own 1.house
## 240 2.$10-$15 2.married 1.male 3 2.own 1.house
## 241 4.Over $20 2.married 1.male 4 2.own 1.house
## 242 2.$10-$15 2.married 1.male 0 1.rent 2.apt
## 243 4.Over $20 2.married 1.male 2 2.own 1.house
## 244 <NA> 3.other 1.male 0 1.rent 2.apt
## 245 1.Less than $10 2.married 1.male 1 2.own 1.house
## 246 4.Over $20 1.single <NA> 0 1.rent 2.apt
## 247 1.Less than $10 1.single 2.female NA 1.rent 2.apt
## 248 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 249 4.Over $20 2.married 2.female 2 2.own 1.house
## 250 <NA> 2.married 2.female 2 2.own 1.house
## 251 3.$15.01-$20 2.married 2.female 0 2.own 1.house
## 252 3.$15.01-$20 2.married 1.male 2 2.own 1.house
## 253 1.Less than $10 2.married 1.male 4 <NA> 1.house
## 254 <NA> <NA> <NA> NA <NA> <NA>
## 255 2.$10-$15 2.married <NA> 0 1.rent 2.apt
## 256 <NA> 2.married 1.male 0 1.rent 2.apt
## 257 3.$15.01-$20 2.married 1.male 2 2.own 1.house
## 258 2.$10-$15 1.single 1.male 3 2.own 1.house
## 259 2.$10-$15 2.married 1.male 0 2.own 1.house
## 260 2.$10-$15 2.married 2.female 1 2.own 1.house
## 261 4.Over $20 2.married 2.female 1 2.own 1.house
## 262 4.Over $20 2.married 2.female 4 1.rent 1.house
## 263 1.Less than $10 2.married 2.female NA 2.own 1.house
## 264 3.$15.01-$20 3.other 2.female 1 2.own 1.house
## 265 1.Less than $10 2.married 2.female 3 2.own 1.house
## 266 4.Over $20 2.married 1.male 0 2.own 1.house
## 267 4.Over $20 2.married 2.female 2 2.own 1.house
## 268 1.Less than $10 2.married 2.female 1 2.own 1.house
## 269 3.$15.01-$20 2.married 2.female 0 2.own 3.duplex
## 270 3.$15.01-$20 2.married <NA> 1 2.own 1.house
## 271 1.Less than $10 2.married <NA> NA 1.rent 1.house
## 272 4.Over $20 2.married 2.female 3 1.rent <NA>
## 273 1.Less than $10 2.married 2.female 1 2.own 1.house
## 274 2.$10-$15 3.other 2.female NA 2.own 1.house
## 275 4.Over $20 2.married 2.female 2 2.own 1.house
## 276 2.$10-$15 2.married 2.female 0 2.own 1.house
## 277 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 278 <NA> 3.other 2.female NA 2.own 2.apt
## 279 4.Over $20 2.married 2.female 2 2.own 1.house
## 280 2.$10-$15 2.married 1.male 1 2.own 1.house
## 281 4.Over $20 3.other 2.female 1 1.rent 2.apt
## 282 2.$10-$15 2.married 1.male 2 2.own 1.house
## 283 1.Less than $10 2.married 2.female 0 2.own 1.house
## 284 4.Over $20 2.married 1.male 0 2.own 1.house
## 285 4.Over $20 2.married 2.female 2 2.own 1.house
## 286 3.$15.01-$20 1.single 1.male 2 1.rent 2.apt
## 287 3.$15.01-$20 2.married 1.male 5 2.own 1.house
## 288 1.Less than $10 3.other <NA> 0 1.rent 2.apt
## 289 1.Less than $10 1.single 1.male 2 <NA> 1.house
## 290 3.$15.01-$20 2.married 1.male 2 2.own 1.house
## 291 4.Over $20 2.married 1.male 0 1.rent 2.apt
## 292 3.$15.01-$20 2.married 1.male 0 1.rent 2.apt
## 293 4.Over $20 2.married 2.female 1 2.own 1.house
## 294 4.Over $20 2.married 2.female 3 2.own 1.house
## 295 4.Over $20 2.married 2.female 0 2.own 1.house
## 296 4.Over $20 2.married 2.female 4 2.own 1.house
## 297 1.Less than $10 2.married 1.male 1 2.own 1.house
## 298 1.Less than $10 1.single 2.female 1 2.own 1.house
## 299 2.$10-$15 2.married 1.male 0 2.own 1.house
## 300 1.Less than $10 1.single 2.female 3 2.own 1.house
## 301 2.$10-$15 2.married 1.male 2 1.rent 1.house
## 302 1.Less than $10 1.single 1.male 1 2.own 1.house
## 303 2.$10-$15 3.other 2.female 0 1.rent 2.apt
## 304 2.$10-$15 2.married 2.female 2 2.own 1.house
## 305 2.$10-$15 1.single 1.male 0 1.rent 2.apt
## 306 1.Less than $10 2.married 2.female 3 2.own 1.house
## 307 4.Over $20 2.married <NA> 0 2.own 1.house
## 308 1.Less than $10 2.married 2.female 1 <NA> 3.duplex
## 309 1.Less than $10 2.married <NA> 4 2.own 1.house
## 310 3.$15.01-$20 2.married 1.male 0 1.rent 2.apt
## 311 4.Over $20 2.married 2.female 3 2.own 1.house
## 312 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 313 2.$10-$15 2.married 1.male 0 2.own <NA>
## 314 1.Less than $10 2.married 1.male 0 1.rent 1.house
## 315 1.Less than $10 1.single <NA> 0 1.rent 2.apt
## 316 4.Over $20 2.married <NA> 0 1.rent 3.duplex
## 317 1.Less than $10 1.single <NA> 3 1.rent 2.apt
## 318 1.Less than $10 1.single 2.female NA <NA> 1.house
## 319 1.Less than $10 2.married 1.male 1 2.own 1.house
## 320 1.Less than $10 2.married 2.female 3 1.rent 2.apt
## 321 2.$10-$15 2.married 2.female 4 1.rent 1.house
## 322 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 323 3.$15.01-$20 2.married 2.female 0 1.rent 1.house
## 324 1.Less than $10 3.other 2.female 0 2.own 1.house
## 325 4.Over $20 2.married 2.female 2 2.own 1.house
## 326 2.$10-$15 1.single <NA> 0 1.rent 1.house
## 327 3.$15.01-$20 3.other <NA> 1 1.rent 2.apt
## 328 4.Over $20 2.married 2.female 0 2.own 1.house
## 329 1.Less than $10 1.single 1.male 2 1.rent 1.house
## 330 1.Less than $10 1.single 2.female 3 2.own 1.house
## 331 2.$10-$15 1.single 1.male 0 1.rent 3.duplex
## 332 3.$15.01-$20 2.married 1.male 0 1.rent 2.apt
## 333 4.Over $20 2.married 2.female 3 2.own 1.house
## 334 1.Less than $10 1.single 2.female 0 1.rent 1.house
## 335 2.$10-$15 2.married <NA> 0 2.own 1.house
## 336 2.$10-$15 2.married 1.male 0 2.own 1.house
## 337 2.$10-$15 2.married 1.male 0 1.rent 2.apt
## 338 1.Less than $10 2.married 1.male 2 2.own 1.house
## 339 <NA> <NA> <NA> NA <NA> <NA>
## 340 1.Less than $10 1.single <NA> 2 2.own 1.house
## 341 4.Over $20 2.married 2.female 2 2.own 1.house
## 342 <NA> 3.other 2.female NA <NA> <NA>
## 343 1.Less than $10 3.other 2.female 0 2.own 1.house
## 344 1.Less than $10 2.married 2.female 0 2.own 1.house
## 345 4.Over $20 2.married 2.female 2 2.own 1.house
## 346 4.Over $20 2.married 2.female 3 2.own 1.house
## 347 1.Less than $10 2.married 1.male 0 2.own 1.house
## 348 4.Over $20 2.married 1.male 1 2.own 1.house
## 349 1.Less than $10 1.single 2.female 0 1.rent 2.apt
## 350 2.$10-$15 2.married 2.female 1 2.own 1.house
## 351 4.Over $20 2.married 2.female 2 2.own 1.house
## 352 1.Less than $10 1.single 1.male 0 1.rent 1.house
## 353 4.Over $20 2.married <NA> 4 2.own 1.house
## 354 2.$10-$15 2.married 2.female 1 2.own 1.house
## 355 <NA> 2.married 2.female 1 2.own 1.house
## 356 1.Less than $10 2.married 2.female 2 1.rent 1.house
## 357 1.Less than $10 1.single 2.female 5 <NA> 1.house
## 358 1.Less than $10 1.single 1.male 0 1.rent 1.house
## 359 3.$15.01-$20 2.married 2.female 3 <NA> 1.house
## 360 4.Over $20 1.single 2.female 3 2.own 1.house
## 361 1.Less than $10 2.married 2.female NA 2.own 1.house
## 362 3.$15.01-$20 2.married 2.female 0 1.rent 2.apt
## 363 2.$10-$15 1.single <NA> NA 1.rent 2.apt
## 364 3.$15.01-$20 2.married 2.female 0 1.rent 2.apt
## 365 1.Less than $10 2.married 1.male 0 2.own 1.house
## 366 <NA> 2.married 2.female 1 2.own 1.house
## 367 4.Over $20 2.married <NA> NA 2.own 1.house
## 368 4.Over $20 1.single 2.female 0 1.rent 2.apt
## 369 2.$10-$15 2.married 2.female NA 2.own 1.house
## 370 4.Over $20 2.married 2.female 0 2.own 1.house
## 371 4.Over $20 2.married 2.female 2 1.rent 3.duplex
## 372 1.Less than $10 2.married 1.male 0 1.rent 2.apt
## 373 2.$10-$15 2.married 2.female 0 1.rent 2.apt
## 374 1.Less than $10 2.married 2.female 1 2.own 1.house
## 375 2.$10-$15 2.married 1.male 0 1.rent 3.duplex
## 376 1.Less than $10 2.married 2.female 5 2.own 1.house
## 377 1.Less than $10 1.single 1.male 1 2.own 1.house
## 378 1.Less than $10 1.single 1.male 0 1.rent 1.house
## 379 <NA> 3.other 1.male 0 <NA> 1.house
## 380 3.$15.01-$20 2.married 1.male 0 2.own 1.house
## 381 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 382 3.$15.01-$20 2.married 1.male 1 2.own 1.house
## 383 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 384 3.$15.01-$20 3.other 2.female 0 1.rent 3.duplex
## 385 4.Over $20 2.married 1.male 0 2.own 1.house
## 386 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 387 3.$15.01-$20 2.married 1.male 0 2.own 1.house
## 388 4.Over $20 2.married 2.female 2 2.own 1.house
## 389 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 390 3.$15.01-$20 3.other 2.female 3 2.own 3.duplex
## 391 3.$15.01-$20 2.married 1.male 1 2.own 1.house
## 392 2.$10-$15 1.single 1.male 0 1.rent 1.house
## 393 2.$10-$15 1.single 1.male 0 1.rent 1.house
## 394 <NA> 3.other 2.female 0 2.own <NA>
## 395 3.$15.01-$20 1.single 2.female 0 1.rent 2.apt
## 396 1.Less than $10 2.married 2.female 3 2.own 1.house
## 397 2.$10-$15 2.married 2.female 2 2.own 1.house
## 398 2.$10-$15 2.married 2.female 4 2.own 1.house
## 399 1.Less than $10 1.single 2.female 0 2.own 1.house
## 400 2.$10-$15 1.single 2.female NA 1.rent 2.apt
## 401 1.Less than $10 <NA> 2.female 0 2.own 1.house
## 402 4.Over $20 2.married <NA> 1 2.own 1.house
## 403 4.Over $20 1.single <NA> 0 1.rent 1.house
## 404 1.Less than $10 2.married <NA> 2 2.own 1.house
## 405 4.Over $20 2.married 2.female 2 2.own 1.house
## 406 3.$15.01-$20 <NA> <NA> 0 2.own 1.house
## 407 4.Over $20 2.married 1.male 0 <NA> <NA>
## 408 1.Less than $10 1.single 2.female 0 1.rent 2.apt
## 409 1.Less than $10 1.single 1.male 2 2.own 1.house
## 410 4.Over $20 2.married 1.male 3 2.own 1.house
## 411 2.$10-$15 2.married 1.male 0 1.rent 2.apt
## 412 2.$10-$15 2.married 1.male 1 2.own 1.house
## 413 2.$10-$15 2.married 1.male 3 2.own 1.house
## 414 4.Over $20 2.married 1.male NA 2.own 1.house
## 415 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 416 4.Over $20 3.other 1.male 0 2.own 1.house
## 417 <NA> 2.married 1.male 0 2.own 1.house
## 418 2.$10-$15 2.married 1.male 2 2.own 1.house
## 419 2.$10-$15 1.single 1.male 0 1.rent 1.house
## 420 2.$10-$15 2.married 1.male 0 1.rent 2.apt
## 421 3.$15.01-$20 2.married 1.male 1 2.own 1.house
## 422 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 423 2.$10-$15 1.single 1.male 5 2.own 1.house
## 424 3.$15.01-$20 2.married 1.male 1 1.rent 2.apt
## 425 2.$10-$15 2.married 1.male 3 2.own 1.house
## 426 2.$10-$15 2.married 1.male 3 2.own 1.house
## 427 <NA> 1.single <NA> 0 2.own 1.house
## 428 1.Less than $10 1.single 1.male 0 2.own 3.duplex
## 429 <NA> 1.single 2.female 0 1.rent 1.house
## 430 <NA> 2.married 2.female NA <NA> <NA>
## 431 2.$10-$15 2.married 2.female 0 2.own 1.house
## 432 3.$15.01-$20 2.married <NA> 0 2.own 1.house
## 433 3.$15.01-$20 3.other 2.female 1 2.own 1.house
## 434 1.Less than $10 1.single 1.male 1 2.own 1.house
## 435 3.$15.01-$20 3.other <NA> NA 1.rent 2.apt
## 436 2.$10-$15 3.other 2.female 1 1.rent 2.apt
## 437 1.Less than $10 2.married 2.female 0 2.own 1.house
## 438 2.$10-$15 2.married <NA> 1 2.own 1.house
## 439 2.$10-$15 2.married 2.female 1 1.rent 3.duplex
## 440 2.$10-$15 1.single 1.male 0 1.rent 2.apt
## 441 3.$15.01-$20 2.married <NA> 0 2.own 2.apt
## 442 3.$15.01-$20 2.married <NA> 0 2.own 2.apt
## 443 4.Over $20 2.married 2.female 0 2.own 1.house
## 444 2.$10-$15 2.married 2.female 0 2.own <NA>
## 445 1.Less than $10 2.married 1.male 4 2.own 1.house
## 446 1.Less than $10 2.married <NA> 3 2.own 1.house
## 447 4.Over $20 2.married 2.female 0 2.own 2.apt
## 448 4.Over $20 2.married 1.male 1 2.own 1.house
## 449 1.Less than $10 2.married 1.male 0 1.rent 1.house
## 450 3.$15.01-$20 2.married 2.female 0 2.own 1.house
## 451 4.Over $20 2.married 1.male 0 <NA> 1.house
## 452 1.Less than $10 2.married 2.female 1 1.rent 2.apt
## 453 1.Less than $10 2.married <NA> 3 2.own 1.house
## 454 3.$15.01-$20 1.single 2.female 1 1.rent 2.apt
## 455 3.$15.01-$20 1.single 1.male 0 1.rent 2.apt
## 456 1.Less than $10 2.married 1.male 1 2.own 1.house
## 457 <NA> 2.married 2.female 0 1.rent 2.apt
## 458 1.Less than $10 2.married <NA> 1 2.own 1.house
## 459 3.$15.01-$20 3.other <NA> 3 2.own 1.house
## 460 1.Less than $10 2.married 2.female 0 2.own 1.house
## 461 1.Less than $10 1.single 2.female 0 1.rent 2.apt
## 462 <NA> 2.married 2.female 0 2.own 1.house
## 463 2.$10-$15 2.married <NA> 1 2.own 1.house
## 464 <NA> 3.other 2.female NA 2.own 1.house
## 465 1.Less than $10 2.married 2.female 1 2.own 1.house
## 466 1.Less than $10 3.other 1.male 0 2.own 2.apt
## 467 4.Over $20 1.single 1.male 2 2.own 1.house
## 468 3.$15.01-$20 3.other <NA> 0 1.rent 2.apt
## 469 3.$15.01-$20 1.single 2.female 2 1.rent 2.apt
## 470 4.Over $20 2.married 2.female 3 2.own 1.house
## 471 4.Over $20 2.married 1.male NA 2.own 1.house
## 472 3.$15.01-$20 2.married <NA> 0 2.own 1.house
## 473 <NA> 1.single <NA> 2 2.own 1.house
## 474 2.$10-$15 2.married 1.male 0 1.rent 2.apt
## 475 3.$15.01-$20 2.married 2.female 0 1.rent 2.apt
## 476 3.$15.01-$20 2.married 1.male 1 1.rent 2.apt
## 477 1.Less than $10 2.married 2.female 0 2.own 1.house
## 478 4.Over $20 3.other <NA> 2 1.rent 2.apt
## 479 2.$10-$15 2.married 2.female 0 2.own 1.house
## 480 3.$15.01-$20 1.single 1.male 0 1.rent 1.house
## 481 <NA> 3.other 1.male 0 1.rent 3.duplex
## 482 1.Less than $10 1.single 2.female 1 <NA> 1.house
## 483 2.$10-$15 2.married 2.female 3 2.own 1.house
## 484 1.Less than $10 2.married 2.female 1 2.own 1.house
## 485 4.Over $20 2.married 2.female 0 1.rent 2.apt
## 486 2.$10-$15 2.married 2.female 0 1.rent 2.apt
## 487 4.Over $20 2.married 1.male 0 2.own 1.house
## 488 1.Less than $10 2.married 2.female 1 2.own 1.house
## 489 1.Less than $10 1.single 2.female 4 2.own 1.house
## 490 2.$10-$15 2.married 1.male 2 2.own 1.house
## 491 <NA> 2.married 2.female 0 2.own 1.house
## 492 1.Less than $10 2.married 1.male 0 2.own 1.house
## 493 2.$10-$15 3.other <NA> 1 1.rent 2.apt
## 494 4.Over $20 2.married 2.female 0 2.own 1.house
## 495 1.Less than $10 2.married 1.male 2 2.own 1.house
## 496 4.Over $20 2.married 1.male 2 2.own 1.house
## 497 2.$10-$15 2.married <NA> NA 2.own 1.house
## 498 4.Over $20 2.married 1.male 2 2.own 1.house
## 499 2.$10-$15 2.married 1.male 0 2.own 1.house
## 500 <NA> 2.married 2.female 0 2.own 1.house
## 501 1.Less than $10 2.married 2.female 0 2.own 1.house
## 502 3.$15.01-$20 2.married <NA> 3 1.rent 3.duplex
## 503 <NA> 2.married 2.female 0 2.own 1.house
## 504 2.$10-$15 1.single 2.female 0 1.rent 2.apt
## 505 1.Less than $10 2.married 2.female 2 2.own 1.house
## 506 2.$10-$15 2.married 1.male 0 2.own 1.house
## 507 4.Over $20 2.married <NA> NA 2.own 1.house
## 508 <NA> 2.married 2.female 5 2.own 1.house
## 509 3.$15.01-$20 2.married 1.male 0 1.rent 1.house
## 510 4.Over $20 2.married 2.female 0 2.own 1.house
## 511 1.Less than $10 2.married 2.female 1 2.own 1.house
## 512 1.Less than $10 2.married 2.female 0 1.rent 2.apt
## 513 4.Over $20 2.married 2.female 0 2.own 1.house
## 514 4.Over $20 1.single <NA> 0 1.rent 2.apt
## 515 3.$15.01-$20 2.married <NA> NA 2.own 1.house
## 516 1.Less than $10 2.married 1.male 3 2.own 1.house
## 517 3.$15.01-$20 2.married 1.male 1 2.own 1.house
## 518 1.Less than $10 1.single <NA> 0 1.rent 2.apt
## 519 1.Less than $10 2.married 1.male 2 2.own 1.house
## 520 3.$15.01-$20 2.married 2.female 0 2.own 1.house
## 521 4.Over $20 2.married <NA> 1 2.own 1.house
## 522 1.Less than $10 2.married 2.female 4 2.own 1.house
## 523 2.$10-$15 2.married 1.male 5 2.own 1.house
## 524 1.Less than $10 2.married 2.female 1 1.rent 1.house
## 525 1.Less than $10 2.married <NA> 3 2.own 1.house
## 526 4.Over $20 3.other 2.female 0 1.rent 2.apt
## 527 1.Less than $10 1.single <NA> 3 2.own 1.house
## 528 4.Over $20 2.married 1.male 3 2.own 1.house
## 529 2.$10-$15 2.married 2.female 0 2.own 1.house
## 530 2.$10-$15 2.married <NA> 0 1.rent 2.apt
## 531 2.$10-$15 2.married 1.male 3 2.own 1.house
## 532 2.$10-$15 2.married 1.male 1 1.rent 2.apt
## 533 3.$15.01-$20 2.married 2.female 0 2.own 1.house
## 534 1.Less than $10 2.married 1.male 2 1.rent 2.apt
## 535 4.Over $20 2.married 2.female 1 2.own 1.house
## 536 1.Less than $10 1.single 2.female 0 1.rent 2.apt
## 537 <NA> 1.single 2.female 1 2.own 1.house
## 538 1.Less than $10 2.married 1.male 0 1.rent 2.apt
## 539 4.Over $20 2.married 1.male 1 2.own 1.house
## 540 2.$10-$15 2.married <NA> 0 2.own 1.house
## 541 2.$10-$15 2.married 1.male 1 1.rent 2.apt
## 542 2.$10-$15 1.single 1.male 0 1.rent 2.apt
## 543 4.Over $20 2.married 2.female 2 1.rent 2.apt
## 544 4.Over $20 2.married 2.female 2 2.own 1.house
## 545 <NA> 2.married 2.female 2 2.own 1.house
## 546 1.Less than $10 2.married 2.female 2 1.rent 2.apt
## 547 1.Less than $10 2.married 2.female 2 2.own 1.house
## 548 2.$10-$15 2.married 2.female 1 2.own 2.apt
## 549 4.Over $20 1.single 1.male 0 1.rent 2.apt
## 550 3.$15.01-$20 2.married 2.female 2 2.own 1.house
## 551 2.$10-$15 1.single 2.female 3 2.own 1.house
## 552 1.Less than $10 2.married 1.male 2 1.rent 1.house
## 553 <NA> 2.married 1.male 0 2.own 1.house
## 554 4.Over $20 2.married <NA> 3 2.own 1.house
## 555 2.$10-$15 2.married 1.male 2 2.own 1.house
## 556 2.$10-$15 3.other 2.female 1 1.rent 1.house
## 557 4.Over $20 2.married 1.male 0 2.own 2.apt
## 558 4.Over $20 2.married 2.female 0 2.own 1.house
## 559 4.Over $20 2.married 2.female 1 2.own 1.house
## 560 4.Over $20 2.married <NA> 2 2.own 1.house
## 561 2.$10-$15 2.married 2.female 3 2.own <NA>
## 562 1.Less than $10 2.married 1.male 0 1.rent 2.apt
## 563 2.$10-$15 3.other 2.female 0 2.own 3.duplex
## 564 3.$15.01-$20 1.single 1.male 0 2.own 1.house
## 565 4.Over $20 2.married 1.male 0 2.own 1.house
## 566 1.Less than $10 2.married 1.male 1 2.own 1.house
## 567 4.Over $20 2.married 2.female 0 1.rent 2.apt
## 568 2.$10-$15 1.single 2.female 0 1.rent 2.apt
## 569 3.$15.01-$20 1.single 1.male 0 1.rent 2.apt
## 570 2.$10-$15 2.married 1.male 0 2.own 1.house
## 571 2.$10-$15 1.single 1.male 0 1.rent <NA>
## 572 4.Over $20 2.married 2.female 3 2.own 1.house
## 573 1.Less than $10 2.married 2.female 0 2.own 1.house
## 574 <NA> 1.single 2.female 0 1.rent 2.apt
## 575 1.Less than $10 2.married 2.female 5 1.rent 1.house
## 576 2.$10-$15 2.married <NA> 0 2.own 1.house
## 577 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 578 4.Over $20 2.married 2.female 3 2.own 1.house
## 579 4.Over $20 2.married 2.female 2 2.own 1.house
## 580 1.Less than $10 2.married 1.male 0 1.rent 1.house
## 581 3.$15.01-$20 2.married 1.male 0 1.rent 2.apt
## 582 2.$10-$15 2.married 2.female NA <NA> 3.duplex
## 583 3.$15.01-$20 2.married <NA> 0 2.own 1.house
## 584 3.$15.01-$20 2.married 2.female 2 2.own 1.house
## 585 4.Over $20 3.other <NA> 2 2.own 1.house
## 586 4.Over $20 2.married 2.female NA 1.rent 2.apt
## 587 <NA> 2.married 1.male 0 1.rent 1.house
## 588 2.$10-$15 1.single 1.male NA 2.own 1.house
## 589 4.Over $20 2.married 1.male 2 2.own 1.house
## 590 2.$10-$15 2.married 2.female 0 2.own 1.house
## 591 1.Less than $10 2.married 1.male 0 2.own 1.house
## 592 1.Less than $10 1.single 2.female 0 2.own 1.house
## 593 2.$10-$15 2.married 2.female 0 2.own 1.house
## 594 4.Over $20 2.married 2.female 3 2.own 1.house
## 595 1.Less than $10 2.married 2.female 5 2.own 1.house
## 596 3.$15.01-$20 2.married <NA> 2 1.rent 2.apt
## 597 4.Over $20 2.married 2.female 2 2.own 1.house
## 598 3.$15.01-$20 2.married 2.female NA 2.own 2.apt
## 599 4.Over $20 2.married <NA> 2 2.own 1.house
## 600 1.Less than $10 2.married 2.female 1 2.own 1.house
## 601 4.Over $20 1.single 1.male 0 1.rent 1.house
## 602 1.Less than $10 2.married 2.female 2 2.own 1.house
## 603 1.Less than $10 3.other 1.male 0 1.rent 1.house
## 604 1.Less than $10 1.single 1.male 0 1.rent 2.apt
## 605 1.Less than $10 2.married <NA> 2 2.own 1.house
## 606 3.$15.01-$20 2.married 2.female 3 2.own 1.house
## 607 4.Over $20 2.married 2.female 3 2.own 1.house
## 608 3.$15.01-$20 3.other 1.male 0 1.rent 1.house
## 609 3.$15.01-$20 2.married 2.female 1 2.own 1.house
## 610 2.$10-$15 2.married 2.female 1 2.own 1.house
## 611 3.$15.01-$20 2.married 2.female 5 1.rent 1.house
## 612 3.$15.01-$20 2.married <NA> 1 2.own 1.house
## 613 1.Less than $10 2.married 2.female 1 2.own 1.house
## 614 <NA> 1.single 2.female 0 1.rent 1.house
## 615 2.$10-$15 2.married 2.female 0 2.own 1.house
## 616 4.Over $20 2.married 2.female 1 2.own 1.house
## 617 1.Less than $10 2.married 2.female 1 1.rent 2.apt
## 618 2.$10-$15 <NA> 2.female 0 2.own 1.house
## 619 2.$10-$15 2.married 2.female 1 <NA> <NA>
## 620 2.$10-$15 2.married 2.female 2 <NA> <NA>
## 621 1.Less than $10 2.married 2.female 1 <NA> <NA>
## 622 2.$10-$15 2.married 2.female 0 1.rent 2.apt
## occupation education age income
## 1 9.retired 2.Some college 60 and over <NA>
## 2 7.stay at home mom 2.Some college 30 and under $60,000 - $79,999
## 3 8.student 2.Some college 30 and under $40,000 or less
## 4 7.stay at home mom 2.Some college 40-49 $80,000 and over
## 5 9.retired 1.High School or less 60 and over $40,001 - $59,999
## 6 7.stay at home mom 2.Some college 50-59 $80,000 and over
## 7 8.student 2.Some college 30 and under $80,000 and over
## 8 7.stay at home mom 1.High School or less 60 and over $40,001 - $59,999
## 9 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 10 <NA> <NA> <NA> <NA>
## 11 7.stay at home mom 1.High School or less 31-39 $80,000 and over
## 12 6.professional 4.Graduate degree 30 and under $80,000 and over
## 13 <NA> <NA> <NA> <NA>
## 14 3.laborer 1.High School or less 30 and under $40,001 - $59,999
## 15 7.stay at home mom 2.Some college 40-49 $80,000 and over
## 16 7.stay at home mom 1.High School or less 31-39 $40,001 - $59,999
## 17 6.professional 4.Graduate degree 31-39 $80,000 and over
## 18 2.skilled trade 1.High School or less 40-49 $60,000 - $79,999
## 19 6.professional 3.College graduate 30 and under $40,001 - $59,999
## 20 5.technical 2.Some college 30 and under $60,000 - $79,999
## 21 7.stay at home mom 1.High School or less 31-39 $40,001 - $59,999
## 22 6.professional 4.Graduate degree 40-49 $80,000 and over
## 23 8.student 3.College graduate 30 and under $40,000 or less
## 24 4.office worker 2.Some college 30 and under $80,000 and over
## 25 9.retired <NA> 60 and over $40,000 or less
## 26 7.stay at home mom 1.High School or less 60 and over $40,001 - $59,999
## 27 6.professional 2.Some college 50-59 $60,000 - $79,999
## 28 9.retired 3.College graduate 60 and over $40,001 - $59,999
## 29 6.professional 4.Graduate degree 30 and under $60,000 - $79,999
## 30 <NA> 1.High School or less 60 and over $40,001 - $59,999
## 31 6.professional 2.Some college 31-39 $80,000 and over
## 32 7.stay at home mom <NA> 50-59 <NA>
## 33 <NA> 3.College graduate 30 and under $60,000 - $79,999
## 34 8.student 2.Some college 30 and under $40,000 or less
## 35 3.laborer 1.High School or less 50-59 $40,001 - $59,999
## 36 4.office worker 2.Some college 50-59 $80,000 and over
## 37 4.office worker 1.High School or less 30 and under $80,000 and over
## 38 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 39 1.managerial 4.Graduate degree 30 and under $60,000 - $79,999
## 40 7.stay at home mom 2.Some college 30 and under $60,000 - $79,999
## 41 8.student 4.Graduate degree 31-39 $40,000 or less
## 42 6.professional 3.College graduate 60 and over $40,001 - $59,999
## 43 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 44 9.retired 2.Some college 60 and over $40,001 - $59,999
## 45 6.professional 4.Graduate degree 40-49 <NA>
## 46 <NA> <NA> <NA> <NA>
## 47 4.office worker 1.High School or less 31-39 $80,000 and over
## 48 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 49 7.stay at home mom 1.High School or less 30 and under $60,000 - $79,999
## 50 5.technical 1.High School or less 50-59 <NA>
## 51 <NA> 4.Graduate degree 60 and over $40,000 or less
## 52 <NA> 1.High School or less 40-49 $60,000 - $79,999
## 53 <NA> 2.Some college 31-39 $80,000 and over
## 54 2.skilled trade 1.High School or less 30 and under $60,000 - $79,999
## 55 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 56 1.managerial 2.Some college 30 and under $60,000 - $79,999
## 57 6.professional 3.College graduate 30 and under $60,000 - $79,999
## 58 7.stay at home mom 1.High School or less 40-49 $80,000 and over
## 59 6.professional 2.Some college 31-39 $80,000 and over
## 60 3.laborer 1.High School or less 40-49 $40,000 or less
## 61 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 62 8.student 1.High School or less 30 and under $80,000 and over
## 63 7.stay at home mom 1.High School or less 30 and under $60,000 - $79,999
## 64 9.retired 2.Some college 60 and over $40,000 or less
## 65 7.stay at home mom 1.High School or less 60 and over $60,000 - $79,999
## 66 3.laborer 1.High School or less 50-59 $80,000 and over
## 67 8.student 2.Some college 30 and under $60,000 - $79,999
## 68 3.laborer 1.High School or less 40-49 $40,001 - $59,999
## 69 7.stay at home mom 3.College graduate 30 and under $80,000 and over
## 70 7.stay at home mom 4.Graduate degree 30 and under $60,000 - $79,999
## 71 9.retired 1.High School or less 60 and over $40,001 - $59,999
## 72 6.professional 3.College graduate 60 and over $40,001 - $59,999
## 73 6.professional 2.Some college 60 and over $40,001 - $59,999
## 74 6.professional 3.College graduate 30 and under $80,000 and over
## 75 6.professional 3.College graduate 30 and under $80,000 and over
## 76 6.professional 3.College graduate 31-39 $60,000 - $79,999
## 77 5.technical 2.Some college 30 and under $40,001 - $59,999
## 78 7.stay at home mom 3.College graduate 40-49 $80,000 and over
## 79 7.stay at home mom 3.College graduate 50-59 $80,000 and over
## 80 7.stay at home mom 1.High School or less 31-39 $80,000 and over
## 81 4.office worker 1.High School or less 50-59 $40,001 - $59,999
## 82 7.stay at home mom 2.Some college 31-39 $60,000 - $79,999
## 83 4.office worker 2.Some college 31-39 $40,000 or less
## 84 1.managerial 1.High School or less 31-39 $60,000 - $79,999
## 85 1.managerial 1.High School or less 40-49 $40,001 - $59,999
## 86 6.professional 4.Graduate degree 31-39 $60,000 - $79,999
## 87 8.student 1.High School or less 30 and under $40,000 or less
## 88 8.student 1.High School or less 30 and under $40,000 or less
## 89 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 90 4.office worker 1.High School or less 30 and under $40,001 - $59,999
## 91 9.retired 1.High School or less 60 and over $40,000 or less
## 92 4.office worker 2.Some college 40-49 $40,001 - $59,999
## 93 9.retired 3.College graduate 60 and over $60,000 - $79,999
## 94 6.professional 4.Graduate degree 31-39 $80,000 and over
## 95 7.stay at home mom 1.High School or less 40-49 $80,000 and over
## 96 2.skilled trade 1.High School or less 60 and over $60,000 - $79,999
## 97 9.retired 4.Graduate degree 60 and over $40,001 - $59,999
## 98 6.professional 4.Graduate degree 31-39 $80,000 and over
## 99 7.stay at home mom 1.High School or less 60 and over <NA>
## 100 8.student 2.Some college 30 and under $80,000 and over
## 101 5.technical 1.High School or less 31-39 $60,000 - $79,999
## 102 7.stay at home mom 3.College graduate 31-39 $40,001 - $59,999
## 103 2.skilled trade 1.High School or less 50-59 $40,001 - $59,999
## 104 <NA> 2.Some college 30 and under $60,000 - $79,999
## 105 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 106 6.professional 3.College graduate 31-39 $60,000 - $79,999
## 107 2.skilled trade 1.High School or less 50-59 $60,000 - $79,999
## 108 6.professional 1.High School or less 31-39 $60,000 - $79,999
## 109 2.skilled trade 2.Some college 31-39 $60,000 - $79,999
## 110 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 111 4.office worker 2.Some college 40-49 $80,000 and over
## 112 7.stay at home mom 2.Some college 50-59 $80,000 and over
## 113 6.professional 3.College graduate 40-49 $80,000 and over
## 114 5.technical 2.Some college 30 and under $40,001 - $59,999
## 115 3.laborer 1.High School or less 30 and under $80,000 and over
## 116 7.stay at home mom 1.High School or less 30 and under $40,001 - $59,999
## 117 6.professional 4.Graduate degree 60 and over $60,000 - $79,999
## 118 1.managerial 2.Some college 31-39 $80,000 and over
## 119 3.laborer 1.High School or less 40-49 <NA>
## 120 6.professional 3.College graduate 40-49 $80,000 and over
## 121 7.stay at home mom 4.Graduate degree 60 and over $80,000 and over
## 122 8.student 3.College graduate 30 and under $80,000 and over
## 123 4.office worker 1.High School or less 30 and under $40,000 or less
## 124 1.managerial 2.Some college 31-39 $60,000 - $79,999
## 125 6.professional 3.College graduate 30 and under $40,001 - $59,999
## 126 1.managerial 1.High School or less 40-49 $60,000 - $79,999
## 127 6.professional 4.Graduate degree 50-59 $80,000 and over
## 128 4.office worker 1.High School or less 30 and under $80,000 and over
## 129 5.technical 3.College graduate 31-39 $60,000 - $79,999
## 130 6.professional 3.College graduate 50-59 $80,000 and over
## 131 7.stay at home mom 3.College graduate 40-49 $80,000 and over
## 132 6.professional 2.Some college 40-49 $60,000 - $79,999
## 133 7.stay at home mom 3.College graduate 40-49 $60,000 - $79,999
## 134 4.office worker 2.Some college 40-49 $60,000 - $79,999
## 135 <NA> 3.College graduate 31-39 $80,000 and over
## 136 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 137 4.office worker 1.High School or less 60 and over $60,000 - $79,999
## 138 7.stay at home mom 4.Graduate degree 40-49 $60,000 - $79,999
## 139 7.stay at home mom 1.High School or less 60 and over <NA>
## 140 1.managerial 2.Some college 40-49 $80,000 and over
## 141 6.professional 3.College graduate 31-39 $60,000 - $79,999
## 142 6.professional 3.College graduate 40-49 $60,000 - $79,999
## 143 6.professional 2.Some college 30 and under $40,001 - $59,999
## 144 2.skilled trade 3.College graduate 30 and under $40,000 or less
## 145 6.professional 1.High School or less 50-59 $60,000 - $79,999
## 146 7.stay at home mom 2.Some college 31-39 $80,000 and over
## 147 1.managerial 3.College graduate 30 and under $80,000 and over
## 148 1.managerial 3.College graduate 30 and under $40,001 - $59,999
## 149 1.managerial 2.Some college 50-59 $60,000 - $79,999
## 150 7.stay at home mom 3.College graduate 40-49 $80,000 and over
## 151 7.stay at home mom 2.Some college 30 and under $80,000 and over
## 152 7.stay at home mom 1.High School or less 50-59 $80,000 and over
## 153 9.retired 1.High School or less 60 and over $40,001 - $59,999
## 154 8.student 2.Some college 30 and under $40,000 or less
## 155 6.professional 2.Some college 30 and under $60,000 - $79,999
## 156 7.stay at home mom 2.Some college 31-39 $60,000 - $79,999
## 157 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 158 6.professional 3.College graduate 30 and under $40,001 - $59,999
## 159 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 160 3.laborer 1.High School or less 30 and under $40,000 or less
## 161 8.student 4.Graduate degree 30 and under $40,000 or less
## 162 7.stay at home mom 2.Some college 50-59 $40,001 - $59,999
## 163 8.student 1.High School or less 30 and under $80,000 and over
## 164 4.office worker <NA> 40-49 $40,001 - $59,999
## 165 2.skilled trade 1.High School or less 30 and under $60,000 - $79,999
## 166 6.professional 3.College graduate 40-49 $80,000 and over
## 167 7.stay at home mom 1.High School or less 31-39 <NA>
## 168 7.stay at home mom 1.High School or less 40-49 <NA>
## 169 1.managerial 3.College graduate 30 and under $40,001 - $59,999
## 170 <NA> 3.College graduate 31-39 $80,000 and over
## 171 <NA> 1.High School or less 60 and over <NA>
## 172 8.student 2.Some college 30 and under $80,000 and over
## 173 7.stay at home mom 2.Some college 60 and over $80,000 and over
## 174 6.professional 4.Graduate degree 30 and under $40,001 - $59,999
## 175 7.stay at home mom 3.College graduate 30 and under $60,000 - $79,999
## 176 6.professional 3.College graduate 30 and under $40,001 - $59,999
## 177 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 178 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 179 1.managerial 1.High School or less 31-39 $40,001 - $59,999
## 180 2.skilled trade 1.High School or less 40-49 $80,000 and over
## 181 7.stay at home mom 1.High School or less 30 and under $60,000 - $79,999
## 182 7.stay at home mom 3.College graduate 30 and under $60,000 - $79,999
## 183 9.retired 2.Some college 60 and over $40,000 or less
## 184 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 185 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 186 7.stay at home mom 2.Some college 31-39 $40,001 - $59,999
## 187 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 188 6.professional 3.College graduate 50-59 $60,000 - $79,999
## 189 6.professional 1.High School or less 30 and under $40,001 - $59,999
## 190 7.stay at home mom 1.High School or less 30 and under $40,000 or less
## 191 1.managerial 1.High School or less 40-49 $80,000 and over
## 192 2.skilled trade 1.High School or less 30 and under $80,000 and over
## 193 <NA> 3.College graduate 30 and under $60,000 - $79,999
## 194 7.stay at home mom 1.High School or less 40-49 $80,000 and over
## 195 8.student 1.High School or less 30 and under $40,001 - $59,999
## 196 5.technical 2.Some college 31-39 $40,001 - $59,999
## 197 1.managerial 2.Some college 31-39 $60,000 - $79,999
## 198 1.managerial 3.College graduate 50-59 $80,000 and over
## 199 6.professional 2.Some college 40-49 $60,000 - $79,999
## 200 9.retired 2.Some college 60 and over $40,000 or less
## 201 4.office worker 2.Some college 31-39 $60,000 - $79,999
## 202 4.office worker 1.High School or less 30 and under $40,001 - $59,999
## 203 4.office worker 1.High School or less 50-59 $40,001 - $59,999
## 204 1.managerial 1.High School or less 40-49 $80,000 and over
## 205 4.office worker 1.High School or less 50-59 $60,000 - $79,999
## 206 4.office worker 2.Some college 30 and under $40,001 - $59,999
## 207 6.professional 3.College graduate 30 and under $60,000 - $79,999
## 208 8.student 3.College graduate 30 and under $60,000 - $79,999
## 209 3.laborer 1.High School or less 50-59 $80,000 and over
## 210 6.professional 4.Graduate degree 60 and over $80,000 and over
## 211 <NA> 1.High School or less 60 and over <NA>
## 212 7.stay at home mom 2.Some college 40-49 $80,000 and over
## 213 6.professional 4.Graduate degree 31-39 $80,000 and over
## 214 <NA> 4.Graduate degree 60 and over $40,001 - $59,999
## 215 1.managerial 2.Some college 31-39 $80,000 and over
## 216 5.technical 3.College graduate 40-49 $60,000 - $79,999
## 217 7.stay at home mom 2.Some college 31-39 $40,001 - $59,999
## 218 1.managerial 1.High School or less 31-39 $60,000 - $79,999
## 219 7.stay at home mom 3.College graduate 31-39 $60,000 - $79,999
## 220 6.professional 4.Graduate degree 31-39 $80,000 and over
## 221 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 222 2.skilled trade 2.Some college 31-39 $80,000 and over
## 223 4.office worker 1.High School or less 40-49 $80,000 and over
## 224 8.student 4.Graduate degree 30 and under $40,000 or less
## 225 7.stay at home mom 2.Some college 30 and under $60,000 - $79,999
## 226 6.professional 1.High School or less 40-49 $80,000 and over
## 227 4.office worker 1.High School or less 30 and under $40,001 - $59,999
## 228 7.stay at home mom 4.Graduate degree 50-59 $60,000 - $79,999
## 229 2.skilled trade 1.High School or less 30 and under $40,000 or less
## 230 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 231 7.stay at home mom 1.High School or less 60 and over $80,000 and over
## 232 7.stay at home mom 2.Some college 50-59 $60,000 - $79,999
## 233 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 234 7.stay at home mom 1.High School or less 30 and under $40,001 - $59,999
## 235 8.student 2.Some college 30 and under $40,001 - $59,999
## 236 6.professional 3.College graduate 31-39 $80,000 and over
## 237 <NA> 1.High School or less 40-49 <NA>
## 238 3.laborer 1.High School or less 40-49 $80,000 and over
## 239 1.managerial 2.Some college 31-39 $80,000 and over
## 240 2.skilled trade 1.High School or less 40-49 $60,000 - $79,999
## 241 6.professional 1.High School or less 40-49 $80,000 and over
## 242 5.technical 4.Graduate degree 30 and under $80,000 and over
## 243 1.managerial 4.Graduate degree 31-39 $80,000 and over
## 244 9.retired 1.High School or less 60 and over $40,000 or less
## 245 1.managerial 3.College graduate 31-39 <NA>
## 246 5.technical 2.Some college 40-49 $60,000 - $79,999
## 247 4.office worker 2.Some college 30 and under $40,001 - $59,999
## 248 4.office worker 2.Some college 40-49 $80,000 and over
## 249 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 250 7.stay at home mom 4.Graduate degree 31-39 $60,000 - $79,999
## 251 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 252 1.managerial 1.High School or less 40-49 $80,000 and over
## 253 3.laborer 1.High School or less 50-59 $60,000 - $79,999
## 254 <NA> <NA> <NA> <NA>
## 255 9.retired 1.High School or less 60 and over $40,000 or less
## 256 1.managerial 4.Graduate degree 50-59 $80,000 and over
## 257 1.managerial 3.College graduate 31-39 $80,000 and over
## 258 8.student 1.High School or less 30 and under $60,000 - $79,999
## 259 6.professional 3.College graduate 30 and under $80,000 and over
## 260 4.office worker 1.High School or less 40-49 $80,000 and over
## 261 7.stay at home mom 3.College graduate 50-59 $40,001 - $59,999
## 262 7.stay at home mom 3.College graduate 40-49 $80,000 and over
## 263 7.stay at home mom 1.High School or less 60 and over $40,001 - $59,999
## 264 7.stay at home mom 1.High School or less 50-59 $40,000 or less
## 265 6.professional 3.College graduate 31-39 $40,001 - $59,999
## 266 2.skilled trade 3.College graduate 40-49 $80,000 and over
## 267 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 268 4.office worker 1.High School or less 40-49 $60,000 - $79,999
## 269 7.stay at home mom 1.High School or less 31-39 $40,001 - $59,999
## 270 6.professional 3.College graduate 31-39 $60,000 - $79,999
## 271 2.skilled trade 1.High School or less 30 and under $40,001 - $59,999
## 272 3.laborer 2.Some college 40-49 <NA>
## 273 7.stay at home mom 2.Some college 50-59 $80,000 and over
## 274 <NA> 1.High School or less 60 and over $40,000 or less
## 275 7.stay at home mom 1.High School or less 40-49 $40,001 - $59,999
## 276 7.stay at home mom 2.Some college 50-59 $80,000 and over
## 277 7.stay at home mom 2.Some college 40-49 $80,000 and over
## 278 9.retired <NA> 60 and over <NA>
## 279 7.stay at home mom 1.High School or less 40-49 $40,001 - $59,999
## 280 2.skilled trade 1.High School or less 30 and under $60,000 - $79,999
## 281 4.office worker 2.Some college 31-39 $40,000 or less
## 282 1.managerial 2.Some college 30 and under $80,000 and over
## 283 7.stay at home mom 2.Some college 50-59 $60,000 - $79,999
## 284 1.managerial 2.Some college 50-59 <NA>
## 285 6.professional 3.College graduate 31-39 $60,000 - $79,999
## 286 2.skilled trade 2.Some college 30 and under $60,000 - $79,999
## 287 6.professional 4.Graduate degree 40-49 $80,000 and over
## 288 6.professional 4.Graduate degree 40-49 $80,000 and over
## 289 8.student 1.High School or less 30 and under $40,001 - $59,999
## 290 6.professional 3.College graduate 31-39 $80,000 and over
## 291 8.student 2.Some college 30 and under $60,000 - $79,999
## 292 6.professional 4.Graduate degree 30 and under $40,001 - $59,999
## 293 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 294 6.professional 3.College graduate 31-39 $80,000 and over
## 295 9.retired 1.High School or less 60 and over <NA>
## 296 7.stay at home mom 4.Graduate degree 31-39 $80,000 and over
## 297 6.professional 4.Graduate degree 31-39 $60,000 - $79,999
## 298 8.student 1.High School or less 30 and under <NA>
## 299 9.retired 2.Some college 60 and over $40,001 - $59,999
## 300 8.student 1.High School or less 30 and under $40,000 or less
## 301 6.professional 2.Some college 40-49 $60,000 - $79,999
## 302 8.student 1.High School or less 30 and under $40,001 - $59,999
## 303 4.office worker 3.College graduate 50-59 $60,000 - $79,999
## 304 7.stay at home mom 2.Some college 31-39 $60,000 - $79,999
## 305 <NA> 1.High School or less 30 and under $60,000 - $79,999
## 306 7.stay at home mom 2.Some college 30 and under $80,000 and over
## 307 1.managerial 3.College graduate 50-59 $80,000 and over
## 308 4.office worker 2.Some college <NA> <NA>
## 309 7.stay at home mom 2.Some college 40-49 $80,000 and over
## 310 1.managerial 3.College graduate 30 and under $60,000 - $79,999
## 311 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 312 1.managerial 3.College graduate 30 and under $40,001 - $59,999
## 313 3.laborer 2.Some college 30 and under $40,001 - $59,999
## 314 8.student 3.College graduate 30 and under $40,000 or less
## 315 4.office worker 1.High School or less 50-59 $40,001 - $59,999
## 316 6.professional 4.Graduate degree 30 and under $60,000 - $79,999
## 317 8.student 2.Some college 30 and under $60,000 - $79,999
## 318 8.student 1.High School or less 30 and under $40,000 or less
## 319 2.skilled trade 1.High School or less 40-49 $40,001 - $59,999
## 320 7.stay at home mom 1.High School or less 31-39 $40,001 - $59,999
## 321 7.stay at home mom 2.Some college 31-39 $60,000 - $79,999
## 322 4.office worker 3.College graduate 30 and under $40,001 - $59,999
## 323 4.office worker 1.High School or less 50-59 $80,000 and over
## 324 6.professional 1.High School or less 50-59 $40,000 or less
## 325 1.managerial 1.High School or less 31-39 $80,000 and over
## 326 8.student 3.College graduate 30 and under $60,000 - $79,999
## 327 2.skilled trade 1.High School or less 50-59 $40,001 - $59,999
## 328 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 329 4.office worker 2.Some college 30 and under $40,001 - $59,999
## 330 8.student 1.High School or less 30 and under $60,000 - $79,999
## 331 6.professional 3.College graduate 30 and under $60,000 - $79,999
## 332 8.student 2.Some college 30 and under $40,001 - $59,999
## 333 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 334 8.student 4.Graduate degree 30 and under $40,001 - $59,999
## 335 9.retired 1.High School or less 50-59 $60,000 - $79,999
## 336 2.skilled trade 2.Some college 50-59 $80,000 and over
## 337 6.professional 3.College graduate 30 and under $80,000 and over
## 338 6.professional 3.College graduate 31-39 $80,000 and over
## 339 <NA> <NA> <NA> <NA>
## 340 1.managerial 3.College graduate 40-49 $80,000 and over
## 341 7.stay at home mom 1.High School or less 30 and under $40,001 - $59,999
## 342 <NA> <NA> 50-59 $40,001 - $59,999
## 343 7.stay at home mom 2.Some college 60 and over $40,001 - $59,999
## 344 4.office worker 1.High School or less 30 and under $60,000 - $79,999
## 345 7.stay at home mom 1.High School or less 30 and under $60,000 - $79,999
## 346 7.stay at home mom 1.High School or less 30 and under $80,000 and over
## 347 2.skilled trade 1.High School or less 40-49 <NA>
## 348 <NA> 3.College graduate 40-49 $80,000 and over
## 349 4.office worker 2.Some college 30 and under $40,001 - $59,999
## 350 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 351 4.office worker 1.High School or less 40-49 $60,000 - $79,999
## 352 5.technical 3.College graduate 30 and under $40,001 - $59,999
## 353 7.stay at home mom 1.High School or less 31-39 $80,000 and over
## 354 7.stay at home mom 1.High School or less 30 and under $40,001 - $59,999
## 355 7.stay at home mom 1.High School or less 30 and under $60,000 - $79,999
## 356 4.office worker 1.High School or less 30 and under $40,001 - $59,999
## 357 8.student 1.High School or less 30 and under <NA>
## 358 8.student 3.College graduate 30 and under $40,000 or less
## 359 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 360 6.professional 4.Graduate degree 40-49 <NA>
## 361 1.managerial 3.College graduate 30 and under $80,000 and over
## 362 8.student 2.Some college 30 and under $60,000 - $79,999
## 363 4.office worker 2.Some college 30 and under $40,001 - $59,999
## 364 4.office worker 3.College graduate 30 and under $40,001 - $59,999
## 365 1.managerial 1.High School or less 31-39 $60,000 - $79,999
## 366 7.stay at home mom 3.College graduate 30 and under $60,000 - $79,999
## 367 1.managerial 2.Some college 50-59 $80,000 and over
## 368 8.student 2.Some college 30 and under $80,000 and over
## 369 9.retired 2.Some college 60 and over $40,001 - $59,999
## 370 7.stay at home mom 1.High School or less 40-49 $80,000 and over
## 371 7.stay at home mom 1.High School or less 31-39 $80,000 and over
## 372 6.professional 3.College graduate 30 and under $80,000 and over
## 373 6.professional 3.College graduate 31-39 $60,000 - $79,999
## 374 7.stay at home mom 1.High School or less 50-59 $80,000 and over
## 375 5.technical 3.College graduate 30 and under $60,000 - $79,999
## 376 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 377 <NA> 1.High School or less 30 and under $80,000 and over
## 378 8.student 2.Some college 30 and under $80,000 and over
## 379 9.retired 3.College graduate 60 and over $60,000 - $79,999
## 380 5.technical 1.High School or less 60 and over $80,000 and over
## 381 8.student 2.Some college 30 and under $40,000 or less
## 382 6.professional 4.Graduate degree 40-49 $60,000 - $79,999
## 383 5.technical 2.Some college 50-59 $80,000 and over
## 384 5.technical 2.Some college 31-39 $80,000 and over
## 385 9.retired 4.Graduate degree 60 and over $80,000 and over
## 386 2.skilled trade 2.Some college 30 and under $40,001 - $59,999
## 387 6.professional 4.Graduate degree 50-59 $80,000 and over
## 388 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 389 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 390 3.laborer 1.High School or less 40-49 $40,001 - $59,999
## 391 1.managerial 3.College graduate 31-39 $80,000 and over
## 392 2.skilled trade 2.Some college 30 and under $40,001 - $59,999
## 393 8.student 2.Some college 30 and under $40,000 or less
## 394 <NA> 1.High School or less 60 and over $40,000 or less
## 395 4.office worker 2.Some college 31-39 $40,001 - $59,999
## 396 7.stay at home mom 1.High School or less 31-39 $80,000 and over
## 397 7.stay at home mom 1.High School or less 30 and under $40,001 - $59,999
## 398 1.managerial 1.High School or less 31-39 $40,001 - $59,999
## 399 1.managerial 3.College graduate 30 and under $40,001 - $59,999
## 400 9.retired 2.Some college 50-59 $40,001 - $59,999
## 401 9.retired 3.College graduate 60 and over $40,001 - $59,999
## 402 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 403 1.managerial 2.Some college 30 and under $40,001 - $59,999
## 404 4.office worker 2.Some college 30 and under $60,000 - $79,999
## 405 7.stay at home mom 1.High School or less 40-49 $80,000 and over
## 406 7.stay at home mom 1.High School or less 40-49 <NA>
## 407 6.professional 2.Some college 30 and under $80,000 and over
## 408 6.professional 3.College graduate 30 and under $40,001 - $59,999
## 409 8.student 1.High School or less 30 and under $60,000 - $79,999
## 410 6.professional 4.Graduate degree 31-39 $80,000 and over
## 411 6.professional 4.Graduate degree 30 and under $80,000 and over
## 412 <NA> 2.Some college 50-59 $60,000 - $79,999
## 413 5.technical 3.College graduate 31-39 $80,000 and over
## 414 6.professional 4.Graduate degree 30 and under $60,000 - $79,999
## 415 <NA> 2.Some college 30 and under $40,001 - $59,999
## 416 4.office worker 2.Some college 50-59 $60,000 - $79,999
## 417 1.managerial 1.High School or less 60 and over <NA>
## 418 1.managerial 3.College graduate 31-39 $80,000 and over
## 419 5.technical 2.Some college 30 and under $40,001 - $59,999
## 420 6.professional 3.College graduate 30 and under $60,000 - $79,999
## 421 1.managerial 3.College graduate 31-39 $60,000 - $79,999
## 422 1.managerial 3.College graduate 30 and under $60,000 - $79,999
## 423 <NA> 2.Some college 30 and under $80,000 and over
## 424 5.technical 3.College graduate 30 and under $60,000 - $79,999
## 425 1.managerial 2.Some college 31-39 $60,000 - $79,999
## 426 3.laborer 2.Some college 31-39 $60,000 - $79,999
## 427 9.retired 2.Some college 60 and over $40,001 - $59,999
## 428 1.managerial 3.College graduate 30 and under $60,000 - $79,999
## 429 9.retired 4.Graduate degree 60 and over $40,001 - $59,999
## 430 7.stay at home mom 1.High School or less 31-39 $80,000 and over
## 431 4.office worker 2.Some college 30 and under $60,000 - $79,999
## 432 2.skilled trade 2.Some college 30 and under <NA>
## 433 3.laborer 1.High School or less 50-59 $40,000 or less
## 434 3.laborer 1.High School or less 30 and under $60,000 - $79,999
## 435 4.office worker 1.High School or less 40-49 $40,001 - $59,999
## 436 <NA> 1.High School or less 30 and under $40,000 or less
## 437 7.stay at home mom 2.Some college 50-59 $40,001 - $59,999
## 438 6.professional 1.High School or less 30 and under $80,000 and over
## 439 6.professional 4.Graduate degree 31-39 $80,000 and over
## 440 1.managerial 2.Some college 30 and under $60,000 - $79,999
## 441 6.professional 4.Graduate degree 30 and under $40,001 - $59,999
## 442 4.office worker 2.Some college 30 and under $40,000 or less
## 443 7.stay at home mom 2.Some college 60 and over $80,000 and over
## 444 6.professional 2.Some college 30 and under $40,001 - $59,999
## 445 6.professional 3.College graduate 40-49 $80,000 and over
## 446 6.professional 2.Some college 31-39 $80,000 and over
## 447 4.office worker 2.Some college 30 and under $40,001 - $59,999
## 448 2.skilled trade 1.High School or less 30 and under $60,000 - $79,999
## 449 4.office worker 2.Some college 50-59 $60,000 - $79,999
## 450 7.stay at home mom 2.Some college 60 and over $60,000 - $79,999
## 451 6.professional 3.College graduate 30 and under $80,000 and over
## 452 6.professional 4.Graduate degree 40-49 $80,000 and over
## 453 4.office worker 1.High School or less 31-39 $80,000 and over
## 454 6.professional 1.High School or less 30 and under $40,001 - $59,999
## 455 1.managerial 3.College graduate 30 and under $60,000 - $79,999
## 456 3.laborer 1.High School or less 31-39 $40,001 - $59,999
## 457 7.stay at home mom 1.High School or less 40-49 $40,001 - $59,999
## 458 <NA> 1.High School or less 50-59 $80,000 and over
## 459 6.professional 3.College graduate 31-39 $60,000 - $79,999
## 460 7.stay at home mom 1.High School or less 40-49 $80,000 and over
## 461 8.student 2.Some college 30 and under $80,000 and over
## 462 1.managerial 1.High School or less 40-49 <NA>
## 463 9.retired 1.High School or less 60 and over $60,000 - $79,999
## 464 7.stay at home mom 1.High School or less 60 and over $40,000 or less
## 465 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 466 6.professional 3.College graduate 30 and under $80,000 and over
## 467 3.laborer 1.High School or less 31-39 $80,000 and over
## 468 1.managerial 4.Graduate degree 40-49 $80,000 and over
## 469 8.student 2.Some college 30 and under $80,000 and over
## 470 <NA> 3.College graduate 31-39 $80,000 and over
## 471 <NA> 4.Graduate degree 50-59 $80,000 and over
## 472 6.professional 4.Graduate degree 60 and over $40,000 or less
## 473 8.student 1.High School or less 30 and under $80,000 and over
## 474 1.managerial 3.College graduate 31-39 $60,000 - $79,999
## 475 8.student 2.Some college 30 and under <NA>
## 476 6.professional 3.College graduate 30 and under $40,001 - $59,999
## 477 7.stay at home mom 2.Some college 60 and over $60,000 - $79,999
## 478 4.office worker 1.High School or less 31-39 $40,001 - $59,999
## 479 7.stay at home mom 3.College graduate 50-59 $60,000 - $79,999
## 480 8.student 2.Some college 30 and under $80,000 and over
## 481 9.retired 1.High School or less 60 and over <NA>
## 482 8.student 1.High School or less 30 and under <NA>
## 483 4.office worker 1.High School or less 40-49 $60,000 - $79,999
## 484 4.office worker 2.Some college 30 and under $40,001 - $59,999
## 485 <NA> 2.Some college 30 and under $40,001 - $59,999
## 486 <NA> 1.High School or less 50-59 $40,000 or less
## 487 6.professional 2.Some college 30 and under $60,000 - $79,999
## 488 4.office worker 2.Some college 31-39 $40,001 - $59,999
## 489 8.student 1.High School or less 30 and under $80,000 and over
## 490 1.managerial 4.Graduate degree 31-39 $80,000 and over
## 491 7.stay at home mom 3.College graduate 60 and over $60,000 - $79,999
## 492 9.retired 1.High School or less 60 and over $40,001 - $59,999
## 493 1.managerial 1.High School or less 31-39 $40,001 - $59,999
## 494 4.office worker 1.High School or less 50-59 $80,000 and over
## 495 6.professional 2.Some college 31-39 $80,000 and over
## 496 1.managerial 3.College graduate 31-39 $80,000 and over
## 497 9.retired 1.High School or less 60 and over <NA>
## 498 6.professional 4.Graduate degree 30 and under $60,000 - $79,999
## 499 1.managerial 3.College graduate 30 and under $80,000 and over
## 500 9.retired 3.College graduate 60 and over $80,000 and over
## 501 7.stay at home mom 3.College graduate 50-59 $80,000 and over
## 502 7.stay at home mom 1.High School or less 31-39 $40,001 - $59,999
## 503 7.stay at home mom 1.High School or less 60 and over $40,001 - $59,999
## 504 4.office worker 2.Some college 30 and under $40,000 or less
## 505 7.stay at home mom 2.Some college 40-49 <NA>
## 506 2.skilled trade 1.High School or less 50-59 $60,000 - $79,999
## 507 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 508 7.stay at home mom 1.High School or less 31-39 <NA>
## 509 3.laborer 2.Some college 30 and under $40,001 - $59,999
## 510 6.professional 4.Graduate degree 31-39 $80,000 and over
## 511 7.stay at home mom 2.Some college 30 and under $60,000 - $79,999
## 512 6.professional 4.Graduate degree 30 and under $80,000 and over
## 513 6.professional 2.Some college 50-59 $80,000 and over
## 514 1.managerial 4.Graduate degree 30 and under $60,000 - $79,999
## 515 4.office worker 1.High School or less 50-59 $40,001 - $59,999
## 516 1.managerial 2.Some college 40-49 $60,000 - $79,999
## 517 5.technical 2.Some college 31-39 $60,000 - $79,999
## 518 9.retired 1.High School or less 50-59 $40,000 or less
## 519 6.professional 4.Graduate degree 31-39 $80,000 and over
## 520 7.stay at home mom 3.College graduate 50-59 <NA>
## 521 7.stay at home mom 3.College graduate 30 and under $80,000 and over
## 522 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 523 1.managerial 2.Some college 31-39 <NA>
## 524 4.office worker 1.High School or less 40-49 $60,000 - $79,999
## 525 1.managerial 1.High School or less 31-39 $40,000 or less
## 526 4.office worker 3.College graduate 30 and under $40,001 - $59,999
## 527 4.office worker 1.High School or less 30 and under $60,000 - $79,999
## 528 1.managerial 2.Some college 40-49 <NA>
## 529 6.professional 3.College graduate 30 and under $40,001 - $59,999
## 530 <NA> 1.High School or less 50-59 $40,000 or less
## 531 6.professional 4.Graduate degree 31-39 $60,000 - $79,999
## 532 6.professional 4.Graduate degree 30 and under $40,001 - $59,999
## 533 4.office worker 1.High School or less <NA> <NA>
## 534 5.technical 2.Some college 30 and under $60,000 - $79,999
## 535 7.stay at home mom 2.Some college 30 and under $80,000 and over
## 536 <NA> 3.College graduate 30 and under $40,000 or less
## 537 8.student 2.Some college 30 and under $40,001 - $59,999
## 538 5.technical 2.Some college 30 and under $40,001 - $59,999
## 539 6.professional 3.College graduate 31-39 <NA>
## 540 4.office worker 1.High School or less 60 and over $60,000 - $79,999
## 541 5.technical 3.College graduate 30 and under $40,001 - $59,999
## 542 6.professional 2.Some college 31-39 $40,001 - $59,999
## 543 4.office worker 1.High School or less 30 and under $40,001 - $59,999
## 544 6.professional 3.College graduate 40-49 $80,000 and over
## 545 4.office worker 3.College graduate 31-39 $80,000 and over
## 546 7.stay at home mom 1.High School or less 31-39 $40,001 - $59,999
## 547 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 548 7.stay at home mom <NA> 40-49 $40,001 - $59,999
## 549 3.laborer 1.High School or less 50-59 $40,000 or less
## 550 4.office worker 1.High School or less 31-39 $40,001 - $59,999
## 551 8.student 1.High School or less 30 and under $80,000 and over
## 552 1.managerial 2.Some college 31-39 $60,000 - $79,999
## 553 6.professional 4.Graduate degree 60 and over <NA>
## 554 6.professional 1.High School or less 40-49 $80,000 and over
## 555 3.laborer 1.High School or less 50-59 $80,000 and over
## 556 6.professional 3.College graduate 40-49 $60,000 - $79,999
## 557 6.professional 2.Some college 50-59 $80,000 and over
## 558 7.stay at home mom 3.College graduate 30 and under $80,000 and over
## 559 7.stay at home mom 3.College graduate 40-49 $80,000 and over
## 560 8.student 3.College graduate 31-39 $80,000 and over
## 561 7.stay at home mom 1.High School or less 40-49 $40,001 - $59,999
## 562 5.technical 3.College graduate 30 and under $60,000 - $79,999
## 563 9.retired 1.High School or less 60 and over $40,000 or less
## 564 6.professional 4.Graduate degree 60 and over $40,000 or less
## 565 1.managerial 3.College graduate 50-59 $80,000 and over
## 566 2.skilled trade 2.Some college 40-49 $60,000 - $79,999
## 567 <NA> 2.Some college 30 and under $40,001 - $59,999
## 568 3.laborer 1.High School or less 30 and under $40,001 - $59,999
## 569 1.managerial 4.Graduate degree 30 and under $60,000 - $79,999
## 570 1.managerial 3.College graduate 60 and over $80,000 and over
## 571 6.professional 4.Graduate degree 30 and under $40,000 or less
## 572 7.stay at home mom 1.High School or less 30 and under $60,000 - $79,999
## 573 <NA> 2.Some college 40-49 $80,000 and over
## 574 6.professional 2.Some college 30 and under $40,001 - $59,999
## 575 7.stay at home mom 1.High School or less 50-59 $80,000 and over
## 576 1.managerial 2.Some college 40-49 $80,000 and over
## 577 8.student 1.High School or less 30 and under $40,000 or less
## 578 2.skilled trade 1.High School or less 40-49 $80,000 and over
## 579 1.managerial 2.Some college 31-39 $80,000 and over
## 580 4.office worker 3.College graduate 30 and under $60,000 - $79,999
## 581 8.student 3.College graduate 30 and under $40,001 - $59,999
## 582 2.skilled trade 1.High School or less <NA> <NA>
## 583 7.stay at home mom 1.High School or less 40-49 $80,000 and over
## 584 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 585 <NA> 2.Some college 31-39 $40,001 - $59,999
## 586 7.stay at home mom 2.Some college 50-59 $60,000 - $79,999
## 587 1.managerial 3.College graduate 30 and under $60,000 - $79,999
## 588 9.retired 4.Graduate degree 60 and over $80,000 and over
## 589 5.technical 2.Some college 30 and under $60,000 - $79,999
## 590 3.laborer <NA> 50-59 $60,000 - $79,999
## 591 2.skilled trade 1.High School or less <NA> <NA>
## 592 9.retired 3.College graduate 60 and over $40,001 - $59,999
## 593 7.stay at home mom 1.High School or less 50-59 $60,000 - $79,999
## 594 7.stay at home mom 3.College graduate 31-39 $80,000 and over
## 595 7.stay at home mom 1.High School or less 40-49 $60,000 - $79,999
## 596 6.professional 2.Some college 30 and under $40,001 - $59,999
## 597 7.stay at home mom 1.High School or less 30 and under $60,000 - $79,999
## 598 7.stay at home mom 3.College graduate 50-59 $80,000 and over
## 599 6.professional 2.Some college 31-39 <NA>
## 600 6.professional 2.Some college 30 and under $60,000 - $79,999
## 601 9.retired <NA> 60 and over $40,001 - $59,999
## 602 <NA> 2.Some college 30 and under $60,000 - $79,999
## 603 6.professional 3.College graduate 30 and under $40,001 - $59,999
## 604 8.student 2.Some college 30 and under $40,000 or less
## 605 4.office worker 3.College graduate 31-39 $60,000 - $79,999
## 606 6.professional 4.Graduate degree 31-39 $80,000 and over
## 607 7.stay at home mom 2.Some college 31-39 $60,000 - $79,999
## 608 6.professional 2.Some college 30 and under $80,000 and over
## 609 4.office worker 2.Some college 30 and under $60,000 - $79,999
## 610 7.stay at home mom 3.College graduate 30 and under $80,000 and over
## 611 7.stay at home mom 1.High School or less 31-39 $60,000 - $79,999
## 612 4.office worker 2.Some college 50-59 $80,000 and over
## 613 3.laborer 1.High School or less 50-59 $60,000 - $79,999
## 614 4.office worker 2.Some college 50-59 $40,001 - $59,999
## 615 6.professional 3.College graduate 50-59 $80,000 and over
## 616 4.office worker 2.Some college 50-59 $80,000 and over
## 617 7.stay at home mom 2.Some college 30 and under $60,000 - $79,999
## 618 6.professional 2.Some college 50-59 $60,000 - $79,999
## 619 7.stay at home mom 1.High School or less 30 and under $40,000 or less
## 620 7.stay at home mom 3.College graduate 40-49 $80,000 and over
## 621 7.stay at home mom 1.High School or less 30 and under $40,001 - $59,999
## 622 6.professional 4.Graduate degree 30 and under $60,000 - $79,999
## h_segments k_segments m_segments
## 1 1 2 1
## 2 1 2 1
## 3 1 1 1
## 4 1 2 1
## 5 1 2 2
## 6 2 1 1
## 7 2 1 1
## 8 2 1 1
## 9 1 2 1
## 10 1 2 1
## 11 1 2 2
## 12 2 1 1
## 13 1 2 2
## 14 2 2 1
## 15 1 2 2
## 16 1 2 2
## 17 1 2 1
## 18 2 2 1
## 19 2 2 1
## 20 2 1 1
## 21 1 2 2
## 22 2 1 3
## 23 2 1 1
## 24 1 2 1
## 25 1 2 2
## 26 1 2 2
## 27 2 1 3
## 28 1 2 2
## 29 2 1 3
## 30 1 2 2
## 31 1 2 1
## 32 1 2 2
## 33 1 1 1
## 34 1 2 1
## 35 2 1 1
## 36 1 2 1
## 37 1 2 1
## 38 1 2 2
## 39 2 1 3
## 40 1 1 3
## 41 1 2 3
## 42 2 2 1
## 43 2 1 1
## 44 2 2 3
## 45 2 1 1
## 46 1 1 3
## 47 2 1 3
## 48 2 1 3
## 49 1 2 1
## 50 1 2 1
## 51 1 2 2
## 52 2 1 1
## 53 1 2 2
## 54 2 1 3
## 55 1 2 2
## 56 1 1 1
## 57 1 2 1
## 58 1 2 2
## 59 1 2 1
## 60 1 2 2
## 61 1 2 2
## 62 2 1 1
## 63 2 1 3
## 64 1 2 2
## 65 1 2 1
## 66 1 2 1
## 67 2 1 3
## 68 2 1 3
## 69 1 1 3
## 70 3 3 3
## 71 1 2 1
## 72 3 3 3
## 73 1 2 1
## 74 2 1 3
## 75 1 2 1
## 76 2 1 3
## 77 2 1 1
## 78 3 3 3
## 79 2 1 1
## 80 1 2 1
## 81 2 1 1
## 82 1 2 1
## 83 2 1 1
## 84 1 2 2
## 85 1 2 1
## 86 1 2 1
## 87 2 2 1
## 88 2 1 1
## 89 2 2 1
## 90 1 1 1
## 91 1 2 1
## 92 2 1 3
## 93 2 1 1
## 94 2 1 3
## 95 1 2 2
## 96 1 2 1
## 97 2 1 3
## 98 1 2 1
## 99 1 2 2
## 100 1 1 1
## 101 1 1 1
## 102 2 1 1
## 103 1 2 1
## 104 2 1 1
## 105 1 2 2
## 106 1 2 2
## 107 1 2 2
## 108 1 2 1
## 109 3 3 3
## 110 2 1 1
## 111 3 3 3
## 112 2 1 1
## 113 2 2 1
## 114 1 1 3
## 115 1 2 1
## 116 1 2 1
## 117 2 1 1
## 118 1 2 2
## 119 1 2 1
## 120 1 2 2
## 121 1 2 1
## 122 2 2 1
## 123 1 2 1
## 124 1 2 1
## 125 2 2 1
## 126 1 2 1
## 127 3 3 3
## 128 1 2 1
## 129 2 1 3
## 130 2 1 1
## 131 2 1 1
## 132 3 3 3
## 133 1 2 1
## 134 2 1 1
## 135 1 2 2
## 136 2 1 1
## 137 1 2 2
## 138 2 2 1
## 139 1 2 2
## 140 1 2 1
## 141 2 1 1
## 142 2 2 1
## 143 1 1 1
## 144 2 1 3
## 145 2 1 3
## 146 1 2 1
## 147 2 2 3
## 148 1 2 1
## 149 2 1 1
## 150 1 2 1
## 151 2 1 1
## 152 3 3 3
## 153 1 2 1
## 154 2 1 1
## 155 2 1 1
## 156 2 2 1
## 157 1 2 2
## 158 2 1 3
## 159 1 2 2
## 160 2 1 3
## 161 1 1 1
## 162 1 2 1
## 163 2 1 1
## 164 1 2 1
## 165 1 2 1
## 166 1 2 1
## 167 3 3 3
## 168 1 2 1
## 169 2 1 1
## 170 2 1 1
## 171 3 3 3
## 172 2 1 1
## 173 1 2 1
## 174 2 1 3
## 175 1 2 2
## 176 2 1 1
## 177 1 2 2
## 178 1 2 3
## 179 1 2 1
## 180 2 1 1
## 181 1 2 2
## 182 1 2 2
## 183 2 1 3
## 184 2 1 3
## 185 2 1 3
## 186 1 1 1
## 187 1 2 2
## 188 1 2 2
## 189 1 2 1
## 190 1 2 2
## 191 2 1 1
## 192 2 1 1
## 193 2 2 1
## 194 1 2 1
## 195 2 1 1
## 196 2 1 1
## 197 2 1 3
## 198 2 1 1
## 199 1 2 2
## 200 1 2 2
## 201 1 2 2
## 202 1 2 2
## 203 2 1 1
## 204 1 2 1
## 205 1 2 2
## 206 2 1 1
## 207 2 1 3
## 208 1 1 1
## 209 1 2 1
## 210 1 2 1
## 211 1 2 1
## 212 2 1 1
## 213 1 1 1
## 214 2 2 1
## 215 2 1 1
## 216 2 1 1
## 217 1 2 2
## 218 2 1 3
## 219 1 2 1
## 220 2 2 3
## 221 1 2 2
## 222 1 2 1
## 223 1 2 2
## 224 1 1 1
## 225 1 2 1
## 226 1 2 1
## 227 1 2 2
## 228 2 1 1
## 229 1 2 2
## 230 1 2 1
## 231 1 2 2
## 232 1 2 2
## 233 1 2 3
## 234 1 2 2
## 235 2 1 1
## 236 1 1 1
## 237 2 1 3
## 238 3 3 3
## 239 2 1 1
## 240 2 2 3
## 241 1 2 3
## 242 2 1 3
## 243 2 1 3
## 244 3 3 3
## 245 1 2 1
## 246 3 3 3
## 247 1 2 1
## 248 1 2 1
## 249 1 2 1
## 250 2 1 1
## 251 1 2 2
## 252 2 1 1
## 253 1 2 2
## 254 1 2 1
## 255 2 1 1
## 256 2 1 1
## 257 1 2 1
## 258 2 1 1
## 259 2 1 1
## 260 1 2 1
## 261 1 2 1
## 262 1 2 2
## 263 2 1 3
## 264 1 1 1
## 265 1 2 1
## 266 1 1 1
## 267 1 2 2
## 268 2 1 3
## 269 2 1 1
## 270 1 2 2
## 271 1 2 2
## 272 2 1 1
## 273 2 1 1
## 274 1 1 3
## 275 1 2 2
## 276 1 2 1
## 277 1 2 1
## 278 1 2 1
## 279 1 2 2
## 280 1 2 1
## 281 1 2 2
## 282 1 2 3
## 283 1 2 1
## 284 1 1 1
## 285 3 3 3
## 286 1 2 1
## 287 2 1 3
## 288 2 1 1
## 289 2 1 1
## 290 2 2 1
## 291 2 1 3
## 292 1 2 1
## 293 2 2 1
## 294 2 1 1
## 295 1 2 2
## 296 1 2 2
## 297 2 2 1
## 298 1 2 2
## 299 1 2 1
## 300 1 2 1
## 301 1 2 2
## 302 1 2 1
## 303 1 2 1
## 304 1 2 1
## 305 1 2 2
## 306 2 2 1
## 307 2 1 1
## 308 1 2 2
## 309 1 2 1
## 310 2 1 3
## 311 2 1 3
## 312 2 1 3
## 313 1 2 2
## 314 2 1 3
## 315 1 2 1
## 316 2 1 3
## 317 2 1 3
## 318 2 1 1
## 319 2 1 1
## 320 2 1 3
## 321 1 2 2
## 322 1 2 2
## 323 1 2 1
## 324 1 2 2
## 325 1 2 2
## 326 1 2 2
## 327 1 2 1
## 328 2 1 1
## 329 1 2 1
## 330 1 2 1
## 331 2 1 3
## 332 1 2 1
## 333 1 1 1
## 334 2 1 3
## 335 1 2 1
## 336 1 1 1
## 337 2 1 1
## 338 2 1 1
## 339 1 2 1
## 340 3 3 3
## 341 1 2 1
## 342 1 2 1
## 343 2 1 1
## 344 3 3 3
## 345 1 2 2
## 346 1 2 2
## 347 1 2 1
## 348 2 1 1
## 349 1 1 1
## 350 1 1 1
## 351 1 2 1
## 352 2 2 1
## 353 1 2 2
## 354 1 2 2
## 355 1 2 1
## 356 3 3 3
## 357 1 2 1
## 358 3 3 3
## 359 1 2 2
## 360 3 3 3
## 361 1 2 1
## 362 1 2 3
## 363 2 1 1
## 364 1 2 1
## 365 1 2 1
## 366 1 2 2
## 367 1 1 1
## 368 1 2 1
## 369 1 2 3
## 370 2 1 1
## 371 2 1 1
## 372 2 1 1
## 373 2 1 3
## 374 2 1 1
## 375 2 1 3
## 376 2 1 1
## 377 2 1 1
## 378 1 2 1
## 379 2 1 1
## 380 2 1 1
## 381 2 1 3
## 382 1 2 1
## 383 1 2 2
## 384 2 1 1
## 385 1 1 3
## 386 2 1 3
## 387 1 2 3
## 388 2 1 3
## 389 2 1 3
## 390 1 2 3
## 391 3 1 3
## 392 2 1 3
## 393 1 2 3
## 394 2 1 3
## 395 2 2 1
## 396 1 2 1
## 397 1 2 2
## 398 1 2 2
## 399 2 1 3
## 400 1 1 1
## 401 1 2 1
## 402 2 1 3
## 403 1 2 1
## 404 3 3 3
## 405 1 2 1
## 406 3 3 3
## 407 3 3 3
## 408 3 3 3
## 409 1 1 3
## 410 2 1 3
## 411 2 1 3
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## 583 1 1 1
## 584 1 2 1
## 585 1 1 1
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## 588 1 2 1
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## 591 1 2 1
## 592 1 2 1
## 593 3 3 3
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## 595 1 2 3
## 596 1 1 3
## 597 1 2 2
## 598 1 2 1
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## 601 2 3 3
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## 612 1 2 2
## 613 1 2 2
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## 616 1 1 1
## 617 2 2 3
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## 619 2 1 1
## 620 1 2 2
## 621 2 2 1
## 622 2 1 1library(ggplot2)
tab = prop.table(table(data2$k_segments,data2[,18]),1)
tab2 = data.frame(round(tab,2))
library(RColorBrewer)
ggplot(data=tab2,aes(x=Var2,y=Var1,fill=Freq))+
geom_tile()+
geom_text(aes(label=Freq),size=3)+
xlab(label = '')+
ylab(label = '')+
scale_fill_gradientn(colors=brewer.pal(n=9,name = 'Greens'))
#use this to know cluster 1 situation. 12:21 is the variable has demographic
lapply(12:21,function(x) round(prop.table(table(data2$k_segments,data2[,x]),1),2)*100)## [[1]]
##
## 1.Less than $10 2.$10-$15 3.$15.01-$20 4.Over $20
## 1 35 26 16 23
## 2 30 25 20 25
## 3 26 13 21 39
##
## [[2]]
##
## 1.single 2.married 3.other
## 1 21 72 7
## 2 16 73 11
## 3 26 62 13
##
## [[3]]
##
## 1.male 2.female
## 1 46 54
## 2 31 69
## 3 52 48
##
## [[4]]
##
## 0 1 2 3 4 5 6 7
## 1 56 18 15 8 1 2 0 0
## 2 37 23 20 13 5 2 0 0
## 3 51 15 20 7 2 2 2 0
##
## [[5]]
##
## 1.rent 2.own
## 1 36 64
## 2 28 72
## 3 28 72
##
## [[6]]
##
## 1.house 2.apt 3.duplex
## 1 66 29 5
## 2 78 20 2
## 3 80 20 0
##
## [[7]]
##
## 1.managerial 2.skilled trade 3.laborer 4.office worker 5.technical
## 1 14 5 3 11 6
## 2 9 6 5 12 3
## 3 11 5 5 16 3
##
## 6.professional 7.stay at home mom 8.student 9.retired
## 1 23 23 12 4
## 2 16 33 8 8
## 3 29 21 5 5
##
## [[8]]
##
## 1.High School or less 2.Some college 3.College graduate 4.Graduate degree
## 1 28 32 27 13
## 2 47 26 19 8
## 3 35 25 28 12
##
## [[9]]
##
## 30 and under 31-39 40-49 50-59 60 and over
## 1 42 21 13 16 8
## 2 30 24 18 13 14
## 3 34 17 22 12 15
##
## [[10]]
##
## $40,000 or less $40,001 - $59,999 $60,000 - $79,999 $80,000 and over
## 1 10 25 31 34
## 2 8 24 34 34
## 3 14 16 38 32lapply(12:21,function(x) {
dat = round(prop.table(table(data2$k_segments,data2[,x]),1),2)*100
dat = data.frame(dat)
ggplot(data=dat,aes(x=Var2,y=Var1,fill=Freq))+
geom_tile()+
geom_text(aes(label=Freq),size=6)+
xlab(label = '')+
ylab(label = '')+
scale_fill_gradientn(colors=brewer.pal(n=9,name = 'Greens'))
})## [[1]]
##
## [[2]]
##
## [[3]]
##
## [[4]]
##
## [[5]]
##
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