R Notebook
The term ‘Vintage’ refers to the month or quarter in which account was opened (loan was granted). In simple words, the vintage analysis measures the performance of a portfolio in different periods of time after the loan (or credit card) was granted.
In simple words, it is the risk of borrower not repaying loan, credit card or any other type of loan.
#load libraries
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(lubridate)##
## Attaching package: 'lubridate'## The following objects are masked from 'package:base':
##
## date, intersect, setdiff, unionlibrary(Rprofet)## Warning: package 'Rprofet' was built under R version 4.2.3library(dlookr)##
## Attaching package: 'dlookr'## The following object is masked from 'package:base':
##
## transformlibrary(flextable)#read the data
mydata = read.csv("E:/MScDataScience/predictive/projectgroup/April Vintage 2013.csv")
#checking the data
str(mydata)## 'data.frame': 92630 obs. of 24 variables:
## $ ID : int 24508841 24508841 24508841 24508841 24508841 24508841 24508841 24508841 24508841 24508841 ...
## $ OpenDate : chr "4/2/2013" "4/2/2013" "4/2/2013" "4/2/2013" ...
## $ DatePrevStmt : chr "NULL" "4/8/2013" "5/9/2013" "6/7/2013" ...
## $ StatementDt : chr "4/8/2013" "5/9/2013" "6/7/2013" "7/9/2013" ...
## $ MOB : int 0 1 2 3 4 5 6 7 8 9 ...
## $ ExtStatus : chr " " " " " " " " ...
## $ IntStatus : chr " " " " " " " " ...
## $ DaysDeliq : int 0 0 0 0 0 0 0 0 0 0 ...
## $ ActualMinPay : num 30 30 30 30 30 30 30 30 30 30 ...
## $ OverlimitAmount : num 0 0 0 0 0 0 0 0 0 0 ...
## $ DisplayMinPay : num 30 30 30 30 30 30 30 30 30 30 ...
## $ OpeningBalance : num 0 180 154 160 268 ...
## $ BillLateCharge : num 0 0 0 0 0 0 0 25 0 0 ...
## $ EndingBalance : num 180 154 160 268 246 ...
## $ CreditLimit : int 300 300 300 300 300 300 300 300 300 300 ...
## $ TotalNetPayments : num 0 30 30 30 30 30 30 30 30 30 ...
## $ TotalNetPurchaseAndCash: num 0 0 19.6 130 0 ...
## $ TotalFeesBilled : num 0 4.5 15.66 8.18 7.89 ...
## $ Concessions : num 0 0 0 0 0 0 0 0 0 0 ...
## $ QuarterlyCreditScore : int 0 536 536 536 536 515 515 515 515 509 ...
## $ Bscore : int 11 636 639 644 648 657 662 655 655 657 ...
## $ City : chr "NORTH LAS VEGAS " "NORTH LAS VEGAS " "NORTH LAS VEGAS " "NORTH LAS VEGAS " ...
## $ State : chr "NV" "NV" "NV" "NV" ...
## $ ZipCode : int 89031 89031 89031 89031 89031 89031 89031 89031 89031 89031 ...summary(mydata)## ID OpenDate DatePrevStmt StatementDt
## Min. :24508841 Length:92630 Length:92630 Length:92630
## 1st Qu.:24798025 Class :character Class :character Class :character
## Median :24817216 Mode :character Mode :character Mode :character
## Mean :24807089
## 3rd Qu.:24836995
## Max. :24856424
## MOB ExtStatus IntStatus DaysDeliq
## Min. : 0.000 Length:92630 Length:92630 Min. : 0.00
## 1st Qu.: 3.000 Class :character Class :character 1st Qu.: 0.00
## Median : 7.000 Mode :character Mode :character Median : 0.00
## Mean : 7.273 Mean : 25.54
## 3rd Qu.:12.000 3rd Qu.: 30.00
## Max. :17.000 Max. :390.00
## ActualMinPay OverlimitAmount DisplayMinPay OpeningBalance
## Min. : 0.0 Min. : 0.00 Min. :-401.01 Min. :-500.6
## 1st Qu.: 30.0 1st Qu.: 0.00 1st Qu.: 30.00 1st Qu.: 175.0
## Median : 30.0 Median : 0.00 Median : 33.71 Median : 304.6
## Mean : 63.2 Mean : 28.39 Mean : 84.99 Mean : 333.3
## 3rd Qu.: 60.0 3rd Qu.: 30.19 3rd Qu.: 90.00 3rd Qu.: 441.9
## Max. :1237.0 Max. :2199.63 Max. :2374.63 Max. :2499.6
## BillLateCharge EndingBalance CreditLimit TotalNetPayments
## Min. : 0.000 Min. :-500.6 Min. : 0.0 Min. :-817.77
## 1st Qu.: 0.000 1st Qu.: 203.1 1st Qu.:300.0 1st Qu.: 0.00
## Median : 0.000 Median : 310.6 Median :300.0 Median : 30.00
## Mean : 8.553 Mean : 351.4 Mean :428.7 Mean : 60.25
## 3rd Qu.:25.000 3rd Qu.: 455.9 3rd Qu.:700.0 3rd Qu.: 68.97
## Max. :35.000 Max. :2499.6 Max. :900.0 Max. :2770.07
## TotalNetPurchaseAndCash TotalFeesBilled Concessions
## Min. :-2007.74 Min. :-359.350 Min. :-607.8700
## 1st Qu.: 0.00 1st Qu.: 5.902 1st Qu.: 0.0000
## Median : 0.00 Median : 15.050 Median : 0.0000
## Mean : 59.46 Mean : 22.306 Mean : -0.7421
## 3rd Qu.: 63.88 3rd Qu.: 38.550 3rd Qu.: 0.0000
## Max. : 2488.63 Max. : 190.520 Max. : 414.3100
## QuarterlyCreditScore Bscore City State
## Min. : 0.0 Min. : 11.0 Length:92630 Length:92630
## 1st Qu.:513.0 1st Qu.:556.0 Class :character Class :character
## Median :576.0 Median :624.0 Mode :character Mode :character
## Mean :521.2 Mean :532.5
## 3rd Qu.:626.0 3rd Qu.:651.0
## Max. :798.0 Max. :717.0
## ZipCode
## Min. : 605
## 1st Qu.:29102
## Median :46224
## Mean :51290
## 3rd Qu.:77703
## Max. :99775#Changing data types of date variables (OpenDate, DatePrevStmt, StatementDt) to date data type
mydata$OpenDate = as.Date(mydata$OpenDate, format = "%m/%d/%Y")
mydata$DatePrevStmt = as.Date(mydata$DatePrevStmt, format = "%m/%d/%Y")
mydata$StatementDt = as.Date(mydata$StatementDt, format = "%m/%d/%Y")
summary(mydata)## ID OpenDate DatePrevStmt
## Min. :24508841 Min. :2013-04-01 Min. :2013-04-08
## 1st Qu.:24798025 1st Qu.:2013-04-07 1st Qu.:2013-07-09
## Median :24817216 Median :2013-04-11 Median :2013-10-20
## Mean :24807089 Mean :2013-04-11 Mean :2013-11-10
## 3rd Qu.:24836995 3rd Qu.:2013-04-17 3rd Qu.:2014-03-14
## Max. :24856424 Max. :2013-04-30 Max. :2014-09-28
## NA's :7060
## StatementDt MOB ExtStatus IntStatus
## Min. :2013-04-08 Min. : 0.000 Length:92630 Length:92630
## 1st Qu.:2013-07-12 1st Qu.: 3.000 Class :character Class :character
## Median :2013-11-08 Median : 7.000 Mode :character Mode :character
## Mean :2013-11-23 Mean : 7.273
## 3rd Qu.:2014-04-04 3rd Qu.:12.000
## Max. :2014-09-30 Max. :17.000
##
## DaysDeliq ActualMinPay OverlimitAmount DisplayMinPay
## Min. : 0.00 Min. : 0.0 Min. : 0.00 Min. :-401.01
## 1st Qu.: 0.00 1st Qu.: 30.0 1st Qu.: 0.00 1st Qu.: 30.00
## Median : 0.00 Median : 30.0 Median : 0.00 Median : 33.71
## Mean : 25.54 Mean : 63.2 Mean : 28.39 Mean : 84.99
## 3rd Qu.: 30.00 3rd Qu.: 60.0 3rd Qu.: 30.19 3rd Qu.: 90.00
## Max. :390.00 Max. :1237.0 Max. :2199.63 Max. :2374.63
##
## OpeningBalance BillLateCharge EndingBalance CreditLimit
## Min. :-500.6 Min. : 0.000 Min. :-500.6 Min. : 0.0
## 1st Qu.: 175.0 1st Qu.: 0.000 1st Qu.: 203.1 1st Qu.:300.0
## Median : 304.6 Median : 0.000 Median : 310.6 Median :300.0
## Mean : 333.3 Mean : 8.553 Mean : 351.4 Mean :428.7
## 3rd Qu.: 441.9 3rd Qu.:25.000 3rd Qu.: 455.9 3rd Qu.:700.0
## Max. :2499.6 Max. :35.000 Max. :2499.6 Max. :900.0
##
## TotalNetPayments TotalNetPurchaseAndCash TotalFeesBilled
## Min. :-817.77 Min. :-2007.74 Min. :-359.350
## 1st Qu.: 0.00 1st Qu.: 0.00 1st Qu.: 5.902
## Median : 30.00 Median : 0.00 Median : 15.050
## Mean : 60.25 Mean : 59.46 Mean : 22.306
## 3rd Qu.: 68.97 3rd Qu.: 63.88 3rd Qu.: 38.550
## Max. :2770.07 Max. : 2488.63 Max. : 190.520
##
## Concessions QuarterlyCreditScore Bscore City
## Min. :-607.8700 Min. : 0.0 Min. : 11.0 Length:92630
## 1st Qu.: 0.0000 1st Qu.:513.0 1st Qu.:556.0 Class :character
## Median : 0.0000 Median :576.0 Median :624.0 Mode :character
## Mean : -0.7421 Mean :521.2 Mean :532.5
## 3rd Qu.: 0.0000 3rd Qu.:626.0 3rd Qu.:651.0
## Max. : 414.3100 Max. :798.0 Max. :717.0
##
## State ZipCode
## Length:92630 Min. : 605
## Class :character 1st Qu.:29102
## Mode :character Median :46224
## Mean :51290
## 3rd Qu.:77703
## Max. :99775
## #Checking for blank records in date variables
sum(is.na(mydata$OpenDate))## [1] 0sum(is.na(mydata$StatementDt))## [1] 0sum(is.na(mydata$DatePrevStmt))## [1] 7060#Investigating the "blank" rows in DatePrevStmt variable
blankPrevStmt = mydata[which(is.na(mydata$DatePrevStmt)),]
data.frame(blankPrevStmt$DatePrevStmt, blankPrevStmt$OpenDate)uniqueData <- data.frame(mydata %>% group_by(ID) %>% filter(StatementDt == max(StatementDt)) %>% distinct(ID, .keep_all = TRUE))
length(uniqueData$ID)## [1] 7038str(uniqueData)## 'data.frame': 7038 obs. of 24 variables:
## $ ID : int 24508841 24510852 24515433 24520866 24521076 24521113 24521446 24525936 24527100 24530739 ...
## $ OpenDate : Date, format: "2013-04-02" "2013-04-01" ...
## $ DatePrevStmt : Date, format: "2014-08-08" "2014-08-08" ...
## $ StatementDt : Date, format: "2014-09-08" "2014-09-08" ...
## $ MOB : int 17 17 7 7 17 17 12 3 3 12 ...
## $ ExtStatus : chr " " " " "Z" "Z" ...
## $ IntStatus : chr " " "X" "X" "D" ...
## $ DaysDeliq : int 0 30 240 240 90 0 240 121 121 240 ...
## $ ActualMinPay : num 30 60 270 270 130 30 287 150 150 287 ...
## $ OverlimitAmount : num 0 49.1 128.1 0 217.3 ...
## $ DisplayMinPay : num 30 109 398 0 347 ...
## $ OpeningBalance : num 282 283 428 278 462 ...
## $ BillLateCharge : num 0 0 0 0 35 0 0 0 0 0 ...
## $ EndingBalance : num 267 349 428 0 517 ...
## $ CreditLimit : int 300 300 300 300 300 300 300 300 300 300 ...
## $ TotalNetPayments : num 30 -20 0 0 0 6.25 0 0 0 0 ...
## $ TotalNetPurchaseAndCash: num 0 0 0 0 0 ...
## $ TotalFeesBilled : num 14.6 45.9 0 0 55.1 ...
## $ Concessions : num 0 0 0 0 0 0 0 0 0 0 ...
## $ QuarterlyCreditScore : int 471 467 488 565 510 639 453 666 501 441 ...
## $ Bscore : int 655 578 245 260 271 638 264 234 234 263 ...
## $ City : chr "LOS ANGELES " "PHILADELPHIA " "WINDERMERE " "WORCESTER " ...
## $ State : chr "CA" "PA" "FL" "MA" ...
## $ ZipCode : int 90062 19124 34786 1605 40031 22407 27863 7050 43607 33012 ...#checking to confirm that there are no duplicate IDs
sum(duplicated(uniqueData$ID))## [1] 0#Calculating lifetime purchases and lifetime payments
LifetimePurchasesTotal = aggregate(TotalNetPurchaseAndCash ~ ID, mydata, sum)
LifetimePurchasesMin = aggregate(TotalNetPurchaseAndCash ~ ID, mydata, min)
LifetimePurchasesMin = LifetimePurchasesMin[,-1]
LifetimePurchasesMax = aggregate(TotalNetPurchaseAndCash ~ ID, mydata, max)
LifetimePurchasesMax =LifetimePurchasesMax[,-1]
LifetimePurchasesMean = aggregate(TotalNetPurchaseAndCash ~ ID, mydata, mean)
LifetimePurchasesMean = LifetimePurchasesMean[,-1]
LifetimePaymentsTotal = aggregate(TotalNetPayments ~ ID, mydata, sum)
LifetimePaymentsTotal = LifetimePaymentsTotal[,-1]
LifetimePaymentsMin = aggregate(TotalNetPayments ~ ID, mydata, min)
LifetimePaymentsMin = LifetimePaymentsMin[,-1]
LifetimePaymentsMax = aggregate(TotalNetPayments ~ ID, mydata, max)
LifetimePaymentsMax = LifetimePaymentsMax[,-1]
LifetimePaymentsMean = aggregate(TotalNetPayments ~ ID, mydata, mean)
LifetimePaymentsMean =LifetimePaymentsMean[,-1]
LifetimeActivity = data.frame(LifetimePurchasesTotal, LifetimePurchasesMin, LifetimePurchasesMax, LifetimePurchasesMean, LifetimePaymentsTotal, LifetimePaymentsMin, LifetimePaymentsMax, LifetimePaymentsMean)
LifetimeActivity$PossibleGainLoss = LifetimeActivity$LifetimePurchasesMean - LifetimeActivity$LifetimePaymentsMean
str(uniqueData)## 'data.frame': 7038 obs. of 24 variables:
## $ ID : int 24508841 24510852 24515433 24520866 24521076 24521113 24521446 24525936 24527100 24530739 ...
## $ OpenDate : Date, format: "2013-04-02" "2013-04-01" ...
## $ DatePrevStmt : Date, format: "2014-08-08" "2014-08-08" ...
## $ StatementDt : Date, format: "2014-09-08" "2014-09-08" ...
## $ MOB : int 17 17 7 7 17 17 12 3 3 12 ...
## $ ExtStatus : chr " " " " "Z" "Z" ...
## $ IntStatus : chr " " "X" "X" "D" ...
## $ DaysDeliq : int 0 30 240 240 90 0 240 121 121 240 ...
## $ ActualMinPay : num 30 60 270 270 130 30 287 150 150 287 ...
## $ OverlimitAmount : num 0 49.1 128.1 0 217.3 ...
## $ DisplayMinPay : num 30 109 398 0 347 ...
## $ OpeningBalance : num 282 283 428 278 462 ...
## $ BillLateCharge : num 0 0 0 0 35 0 0 0 0 0 ...
## $ EndingBalance : num 267 349 428 0 517 ...
## $ CreditLimit : int 300 300 300 300 300 300 300 300 300 300 ...
## $ TotalNetPayments : num 30 -20 0 0 0 6.25 0 0 0 0 ...
## $ TotalNetPurchaseAndCash: num 0 0 0 0 0 ...
## $ TotalFeesBilled : num 14.6 45.9 0 0 55.1 ...
## $ Concessions : num 0 0 0 0 0 0 0 0 0 0 ...
## $ QuarterlyCreditScore : int 471 467 488 565 510 639 453 666 501 441 ...
## $ Bscore : int 655 578 245 260 271 638 264 234 234 263 ...
## $ City : chr "LOS ANGELES " "PHILADELPHIA " "WINDERMERE " "WORCESTER " ...
## $ State : chr "CA" "PA" "FL" "MA" ...
## $ ZipCode : int 90062 19124 34786 1605 40031 22407 27863 7050 43607 33012 ...str(LifetimeActivity)## 'data.frame': 7038 obs. of 10 variables:
## $ ID : int 24508841 24510852 24515433 24520866 24521076 24521113 24521446 24525936 24527100 24530739 ...
## $ TotalNetPurchaseAndCash: num 368.3 924.8 230.9 101 84.3 ...
## $ LifetimePurchasesMin : num 0 0 0 0 0 0 0 0 0 0 ...
## $ LifetimePurchasesMax : num 130 199 186 101 60 ...
## $ LifetimePurchasesMean : num 20.46 51.38 28.86 11.22 4.68 ...
## $ LifetimePaymentsTotal : num 561 1225 250 0 512 ...
## $ LifetimePaymentsMin : num 0 -20 0 0 0 0 0 0 0 0 ...
## $ LifetimePaymentsMax : num 77 200 250 0 100 ...
## $ LifetimePaymentsMean : num 31.2 68.1 31.2 0 28.4 ...
## $ PossibleGainLoss : num -10.71 -16.68 -2.39 11.22 -23.76 ...#Combining newdata and lifetime activity data
newData = data.frame(cbind(uniqueData, LifetimeActivity[-1]))
str(newData)## 'data.frame': 7038 obs. of 33 variables:
## $ ID : int 24508841 24510852 24515433 24520866 24521076 24521113 24521446 24525936 24527100 24530739 ...
## $ OpenDate : Date, format: "2013-04-02" "2013-04-01" ...
## $ DatePrevStmt : Date, format: "2014-08-08" "2014-08-08" ...
## $ StatementDt : Date, format: "2014-09-08" "2014-09-08" ...
## $ MOB : int 17 17 7 7 17 17 12 3 3 12 ...
## $ ExtStatus : chr " " " " "Z" "Z" ...
## $ IntStatus : chr " " "X" "X" "D" ...
## $ DaysDeliq : int 0 30 240 240 90 0 240 121 121 240 ...
## $ ActualMinPay : num 30 60 270 270 130 30 287 150 150 287 ...
## $ OverlimitAmount : num 0 49.1 128.1 0 217.3 ...
## $ DisplayMinPay : num 30 109 398 0 347 ...
## $ OpeningBalance : num 282 283 428 278 462 ...
## $ BillLateCharge : num 0 0 0 0 35 0 0 0 0 0 ...
## $ EndingBalance : num 267 349 428 0 517 ...
## $ CreditLimit : int 300 300 300 300 300 300 300 300 300 300 ...
## $ TotalNetPayments : num 30 -20 0 0 0 6.25 0 0 0 0 ...
## $ TotalNetPurchaseAndCash : num 0 0 0 0 0 ...
## $ TotalFeesBilled : num 14.6 45.9 0 0 55.1 ...
## $ Concessions : num 0 0 0 0 0 0 0 0 0 0 ...
## $ QuarterlyCreditScore : int 471 467 488 565 510 639 453 666 501 441 ...
## $ Bscore : int 655 578 245 260 271 638 264 234 234 263 ...
## $ City : chr "LOS ANGELES " "PHILADELPHIA " "WINDERMERE " "WORCESTER " ...
## $ State : chr "CA" "PA" "FL" "MA" ...
## $ ZipCode : int 90062 19124 34786 1605 40031 22407 27863 7050 43607 33012 ...
## $ TotalNetPurchaseAndCash.1: num 368.3 924.8 230.9 101 84.3 ...
## $ LifetimePurchasesMin : num 0 0 0 0 0 0 0 0 0 0 ...
## $ LifetimePurchasesMax : num 130 199 186 101 60 ...
## $ LifetimePurchasesMean : num 20.46 51.38 28.86 11.22 4.68 ...
## $ LifetimePaymentsTotal : num 561 1225 250 0 512 ...
## $ LifetimePaymentsMin : num 0 -20 0 0 0 0 0 0 0 0 ...
## $ LifetimePaymentsMax : num 77 200 250 0 100 ...
## $ LifetimePaymentsMean : num 31.2 68.1 31.2 0 28.4 ...
## $ PossibleGainLoss : num -10.71 -16.68 -2.39 11.22 -23.76 ...#Filter the data where MOB > 3
newData = uniqueData[which(uniqueData$MOB > 3),]
nrow(newData)## [1] 6038#Obtaining summary statistics of the data
summary(newData)## ID OpenDate DatePrevStmt
## Min. :24508841 Min. :2013-04-01 Min. :2013-05-09
## 1st Qu.:24796902 1st Qu.:2013-04-07 1st Qu.:2014-03-31
## Median :24816652 Median :2013-04-12 Median :2014-08-08
## Mean :24806362 Mean :2013-04-12 Mean :2014-05-15
## 3rd Qu.:24836453 3rd Qu.:2013-04-17 3rd Qu.:2014-08-15
## Max. :24856424 Max. :2013-04-30 Max. :2014-09-28
## NA's :1
## StatementDt MOB ExtStatus IntStatus
## Min. :2013-08-06 Min. : 4.00 Length:6038 Length:6038
## 1st Qu.:2014-04-30 1st Qu.:12.00 Class :character Class :character
## Median :2014-09-08 Median :17.00 Mode :character Mode :character
## Mean :2014-06-11 Mean :13.69
## 3rd Qu.:2014-09-15 3rd Qu.:17.00
## Max. :2014-09-30 Max. :17.00
##
## DaysDeliq ActualMinPay OverlimitAmount DisplayMinPay
## Min. : 0.00 Min. : 0.0 Min. : 0.00 Min. : 0.00
## 1st Qu.: 0.00 1st Qu.: 30.0 1st Qu.: 0.00 1st Qu.: 25.00
## Median : 30.00 Median : 60.0 Median : 0.00 Median : 42.12
## Mean : 90.61 Mean : 147.4 Mean : 62.11 Mean : 170.91
## 3rd Qu.:151.00 3rd Qu.: 236.0 3rd Qu.: 124.90 3rd Qu.: 341.01
## Max. :390.00 Max. :1237.0 Max. :1100.77 Max. :1681.36
##
## OpeningBalance BillLateCharge EndingBalance CreditLimit
## Min. :-326.9 Min. : 0.000 Min. :-224.06 Min. : 0.0
## 1st Qu.: 287.1 1st Qu.: 0.000 1st Qu.: 28.68 1st Qu.:300.0
## Median : 429.3 Median : 0.000 Median : 345.25 Median :300.0
## Mean : 443.7 Mean : 4.083 Mean : 352.48 Mean :423.3
## 3rd Qu.: 564.4 3rd Qu.: 0.000 3rd Qu.: 505.83 3rd Qu.:700.0
## Max. :1681.4 Max. :35.000 Max. :1681.36 Max. :900.0
##
## TotalNetPayments TotalNetPurchaseAndCash TotalFeesBilled Concessions
## Min. :-455.87 Min. :-256.7500 Min. :-294.14 Min. :-607.870
## 1st Qu.: 0.00 1st Qu.: 0.0000 1st Qu.: 0.00 1st Qu.: 0.000
## Median : 0.00 Median : 0.0000 Median : 6.25 Median : 0.000
## Mean : 47.02 Mean : 23.4614 Mean : 14.50 Mean : -2.283
## 3rd Qu.: 50.00 3rd Qu.: 0.9725 3rd Qu.: 22.97 3rd Qu.: 0.000
## Max. :1450.00 Max. :1675.5700 Max. : 129.28 Max. : 326.900
##
## QuarterlyCreditScore Bscore City State
## Min. : 0.0 Min. : 13.0 Length:6038 Length:6038
## 1st Qu.:479.0 1st Qu.:246.0 Class :character Class :character
## Median :538.0 Median :596.0 Mode :character Mode :character
## Mean :490.5 Mean :465.8
## 3rd Qu.:612.0 3rd Qu.:653.0
## Max. :797.0 Max. :711.0
##
## ZipCode
## Min. : 612
## 1st Qu.:29073
## Median :46138
## Mean :51106
## 3rd Qu.:77520
## Max. :99775
## #Obtaining summary table of variables of character data type
table(newData$ExtStatus)##
## C E F I U Z
## 2923 372 14 185 30 1 2513table(newData$IntStatus)##
## D N O X
## 2295 179 33 417 3114table(newData$City)##
## ABBEVILLE ABERDEEN
## 1 3
## ABILENE ABSECON
## 1 2
## ACTON ACUSHNET
## 1 1
## ACWORTH ADDISON
## 1 1
## AGOURA HILLS AIKEN
## 1 1
## AKRON ALABASTER
## 12 1
## ALACHUA ALAMEDA
## 2 2
## ALAMO ALBANY
## 2 6
## ALBEMARLE ALBERTVILLE
## 3 2
## ALBRIGHTSVILLE ALBUQUERQUE
## 1 13
## ALDEN ALEXANDER
## 1 1
## ALEXANDRIA ALGONAC
## 8 1
## ALISO VIEJO ALLEGAN
## 3 2
## ALLEN PARK ALLENTON
## 1 1
## ALLENTOWN ALLIANCE
## 6 1
## ALLISON PARK ALPHARETTA
## 1 2
## ALTAMONTE SPRINGS ALTMAR
## 1 1
## ALTOONA AMADO
## 3 1
## AMARILLO AMERY
## 2 1
## AMES AMESBURY
## 1 1
## AMITY AMORY
## 1 1
## ANAHEIM ANAHUAC
## 8 1
## ANCHORAGE ANDERSON
## 4 6
## ANDOVER ANETH
## 1 1
## ANGOLA ANKENY
## 2 1
## ANNA ANNAPOLIS
## 1 1
## ANNISTON ANOKA
## 1 1
## ANSLEY ANSONIA
## 1 1
## ANTELOPE ANTHONY
## 2 1
## ANTIOCH APACHE JUNCTION
## 5 2
## APEX APO
## 1 3
## APOLLO BEACH APOPKA
## 1 2
## ARCADIA ARDEN
## 1 2
## ARDMORE ARECIBO
## 1 1
## ARGYLE ARITON
## 1 1
## ARLINGTON ARNAUDVILLE
## 15 1
## ARNOLD ARVADA
## 2 6
## ASBURY PARK ASH
## 2 1
## ASHEBORO ASHEVILLE
## 1 1
## ASHLAND ASHLAND CITY
## 1 1
## ASHTABULA ASHVILLE
## 1 1
## ASTON ASTORIA
## 1 2
## ATCHISON ATHENS
## 1 5
## ATLANTA ATLANTIC BEACH
## 30 1
## ATLANTIC CITY ATMORE
## 1 2
## ATOKA ATTALLA
## 1 1
## ATTICA ATTLEBORO
## 1 2
## ATWATER AUBREY
## 1 1
## AUBURN AUBURN HILLS
## 3 1
## AUBURNDALE AUGUSTA
## 1 10
## AULT AURORA
## 1 10
## AUSTELL AUSTIN
## 2 18
## AVENAL AVOCA
## 1 1
## AVON AVON PARK
## 3 1
## AVONDALE AYDEN
## 6 2
## AYNOR AZUSA
## 1 1
## BABYLON BACLIFF
## 1 2
## BAKER BAKERSFIELD
## 1 13
## BALA CYNWYD BALDWIN
## 1 1
## BALL GROUND BALLSTON SPA
## 1 1
## BALTIMORE BARBERTON
## 20 1
## BARNEGAT BARNWELL
## 3 2
## BARRACKVILLE BARRANQUITAS
## 1 1
## BARSTOW BARTLETT
## 2 1
## BATESVILLE BATH
## 1 1
## BATON ROUGE BATTLE CREEK
## 11 2
## BATTLEBORO BAUXITE
## 1 1
## BAY SAINT LOUIS BAYAMON
## 1 1
## BAYONNE BAYSIDE
## 3 1
## BAYTOWN BEACHWOOD
## 5 1
## BEAR BEASLEY
## 2 1
## BEASON BEATRICE
## 1 1
## BEAUFORT BEAUMONT
## 1 4
## BEAVERTON BECKLEY
## 1 1
## BEDFORD BEECH ISLAND
## 3 1
## BEEVILLE BELEN
## 1 1
## BELFAST BELLEVILLE
## 1 5
## BELLEVUE BELLFLOWER
## 4 4
## BELLINGHAM BELLMORE
## 1 1
## BELLWOOD BELTSVILLE
## 2 2
## BELVIDERE BEMIDJI
## 1 1
## BEND BENSALEM
## 2 1
## BENSENVILLE BENSON
## 3 1
## BENTLEYVILLE BENTON HARBOR
## 1 1
## BENTONVILLE BERLIN
## 1 1
## BERWICK BERWYN
## 2 3
## BESSEMER BETHANY
## 1 2
## BETHESDA BETHLEHEM
## 1 1
## BETHPAGE BEVERLY HILLS
## 1 1
## BIG SPRING BIG SUR
## 3 1
## BILLERICA BILLINGS
## 1 3
## BILOXI BIRCH RUN
## 2 1
## BIRMINGHAM BIXBY
## 20 2
## BLACK MOUNTAIN BLACK RIVER FALLS
## 1 1
## BLACKFOOT BLACKLICK
## 3 3
## BLACKSBURG BLACKWOOD
## 1 1
## BLAKESLEE BLANCHESTER
## 1 1
## BLEVINS BLOOMFIELD
## 1 3
## BLOOMINGDALE BLOOMINGTON
## 2 3
## BLOOMVILLE BLOUNTVILLE
## 1 1
## BLUE ISLAND BLUE RIDGE
## 1 1
## BLUE SPRINGS BLUEFIELD
## 1 3
## BLUFFTON BLYTHEVILLE
## 1 2
## BOCA RATON BOERNE
## 8 2
## BOGART BOGOTA
## 1 1
## BOILING SPRINGS BOISE
## 1 4
## BOLINGBROOK BOLTON
## 4 1
## BONAIRE BONANZA
## 3 1
## BONDURANT BONNER SPRINGS
## 1 1
## BOONE BOONTON
## 1 1
## BOSSIER CITY BOSTON
## 3 9
## BOSWELL BOTHELL
## 1 1
## BOULDER BOULDER CREEK
## 1 1
## BOUNTIFUL BOWIE
## 1 2
## BOWLING GREEN BOYNTON BEACH
## 7 4
## BRADDOCK BRADENTON
## 1 5
## BRADFORD BRANDON
## 2 2
## BRANFORD BRANSON
## 2 1
## BRAWLEY BRAXTON
## 2 1
## BRAZIL BREA
## 1 1
## BREAUX BRIDGE BREMERTON
## 1 1
## BRENTWOOD BREWER
## 2 1
## BREWSTER BREWTON
## 2 1
## BRIDGEPORT BRIDGETON
## 10 3
## BRIDGEWATER BRIGHTON
## 2 4
## BRISTOL BRISTOLVILLE
## 3 1
## BROCKTON BROKEN ARROW
## 2 2
## BRONX BROOK PARK
## 28 1
## BROOKFIELD BROOKLYN
## 1 32
## BROOKPORT BROOMFIELD
## 1 2
## BROUSSARD BROWNS MILLS
## 1 2
## BROWNS SUMMIT BROWNSBURG
## 1 2
## BROWNSVILLE BROWNWOOD
## 4 1
## BRUNSWICK BRYAN
## 1 3
## BRYANT BUCHANAN
## 1 1
## BUCKEYE BUCKHANNON
## 2 1
## BUCYRUS BUENA PARK
## 1 3
## BUENA VISTA BUFFALO
## 1 5
## BUFORD BURBANK
## 1 2
## BURGETTSTOWN BURLESON
## 1 4
## BURLEY BURLINGAME
## 1 1
## BURLINGTON BURNSVILLE
## 3 3
## BURTONSVILLE BUSHKILL
## 1 2
## BUTLER BUTTE
## 1 2
## BYFIELD BYHALIA
## 1 1
## BYNUM BYRAM
## 1 2
## CABOT CAGUAS
## 1 2
## CALDWELL CALIFORNIA
## 1 1
## CALIFORNIA CITY CALIMESA
## 1 1
## CALL CALLAHAN
## 1 1
## CALUMET CITY CAMANCHE
## 3 1
## CAMBRIDGE CAMBY
## 1 1
## CAMDEN CAMERON
## 3 1
## CAMP HILL CAMPBELL HALL
## 1 1
## CAMPBELLSBURG CANAL WINCHESTER
## 1 2
## CANEYVILLE CANON CITY
## 2 1
## CANTERBURY CANTON
## 1 14
## CANTONMENT CANYON COUNTRY
## 1 5
## CANYON LAKE CAPE CORAL
## 1 7
## CAPE MAY CAPITOL HEIGHTS
## 1 3
## CARIBOU CARLIN
## 1 1
## CARLISLE CARLSBAD
## 1 4
## CARMEL CAROLINA
## 1 3
## CARPINTERIA CARRBORO
## 1 1
## CARRIZO SPRINGS CARROLLTON
## 1 6
## CARSON CARTERET
## 1 1
## CARTERSVILLE CARTHAGE
## 1 4
## CARY CARYVILLE
## 4 1
## CASA GRANDE CASPER
## 5 1
## CASSVILLE CASTLE HAYNE
## 1 1
## CATAWBA CATHEDRAL CITY
## 1 2
## CAVE JUNCTION CEDAR CREEK
## 1 1
## CEDAR GLEN CEDAR HILL
## 1 1
## CEDAR PARK CEDAR RAPIDS
## 2 4
## CENTERVILLE CENTRAL ISLIP
## 1 1
## CENTRAL POINT CENTRALIA
## 1 2
## CENTURY CERES
## 1 2
## CHAMBERSBURG CHAMPAIGN
## 1 1
## CHANDLER CHAPARRAL
## 5 1
## CHAPMAN CHARLES CITY
## 1 1
## CHARLESTON CHARLESTOWN
## 8 2
## CHARLOTTE CHASKA
## 28 1
## CHATSWORTH CHATTANOOGA
## 1 3
## CHELSEA CHENEY
## 2 1
## CHERRY HILL CHESAPEAKE
## 3 5
## CHESHIRE CHESTER
## 2 2
## CHESTERFIELD CHICAGO
## 1 66
## CHICAGO HEIGHTS CHICAGO RIDGE
## 5 1
## CHICO CHICOPEE
## 1 4
## CHRISTIANSBURG CHUGIAK
## 1 1
## CHULA VISTA CHURCH HILL
## 5 2
## CICERO CINCINNATI
## 3 23
## CITRUS HEIGHTS CLANTON
## 3 1
## CLARENCE CENTER CLARENDON HILLS
## 1 1
## CLARINDA CLARK
## 1 2
## CLARKSBURG CLARKSTON
## 2 1
## CLARKSVILLE CLAYTON
## 4 5
## CLE ELUM CLEAR SPRING
## 1 1
## CLEARWATER CLEARWATER BEACH
## 1 1
## CLEMENTON CLEMENTS
## 2 1
## CLERMONT CLEVELAND
## 1 29
## CLEVER CLEVES
## 1 1
## CLIFTON CLIFTON FORGE
## 4 1
## CLINTON CLINTON TOWNSHIP
## 10 3
## CLIO CLOVIS
## 1 1
## CLYDE CLYMER
## 1 1
## CLYO COACHELLA
## 1 1
## COAL TOWNSHIP COARSEGOLD
## 1 1
## COATESVILLE COATS
## 4 1
## COCOA COLCHESTER
## 1 1
## COLDWATER COLFAX
## 1 1
## COLLEGE STATION COLLINSVILLE
## 1 2
## COLORADO SPRINGS COLUMBIA
## 9 16
## COLUMBIANA COLUMBUS
## 1 45
## COMMERCE COMMERCE CITY
## 1 1
## COMPTON COMSTOCK PARK
## 4 2
## CONCORD CONLEY
## 4 2
## CONOVER CONROE
## 1 3
## CONWAY CONYERS
## 3 3
## COOKEVILLE COOPERSBURG
## 1 1
## COOS BAY COPPELL
## 1 1
## COPPERAS COVE CORALVILLE
## 2 1
## CORAOPOLIS CORBIN
## 1 1
## CORDOVA CORINTH
## 4 2
## CORNELIA CORNELIUS
## 1 1
## CORONA CORONA DEL MAR
## 6 1
## CORPUS CHRISTI CORSICANA
## 4 2
## CORTEZ CORTLAND
## 1 2
## COS COB COSTA MESA
## 1 1
## COTTONDALE COTTONTOWN
## 2 1
## COUNCIL BLUFFS COUNTRY CLUB HILLS
## 2 1
## COURTLAND COVELO
## 1 1
## COVINA COVINGTON
## 1 8
## CRAIGSVILLE CRANDALL
## 1 1
## CRANSTON CRAWFORDVILLE
## 3 2
## CREAM RIDGE CRESSON
## 1 1
## CRESTON CRISFIELD
## 1 1
## CROFTON CROMWELL
## 1 1
## CROSS PLAINS CROSSVILLE
## 2 1
## CROWLEY CROWN POINT
## 3 1
## CRYSTAL CRYSTAL LAKE
## 1 2
## CRYSTAL SPRINGS CULLMAN
## 2 3
## CULPEPER CUMBERLAND
## 1 1
## CUMMING CURRIE
## 1 1
## CURTICE CUYAHOGA FALLS
## 1 2
## CYNTHIANA CYPRESS
## 1 3
## D HANIS DACULA
## 1 3
## DALHART DALLAS
## 1 25
## DALTON DALY CITY
## 1 1
## DANA DANA POINT
## 1 2
## DANBURY DANSVILLE
## 1 1
## DANVILLE DAPHNE
## 5 2
## DARLINGTON DAVENPORT
## 2 2
## DAVIS DAWSON
## 1 1
## DAWSONVILLE DAYTON
## 2 4
## DAYTONA BEACH DE KALB
## 2 2
## DE SOTO DEARBORN
## 1 4
## DEARBORN HEIGHTS DEBARY
## 1 1
## DECATUR DEDHAM
## 11 1
## DEER TRAIL DEERFIELD BEACH
## 1 1
## DEKALB DELAND
## 1 1
## DELAWARE DELMAR
## 2 2
## DELRAY BEACH DELTONA
## 3 2
## DEMOTTE DENHAM SPRINGS
## 1 3
## DENISON DENTON
## 2 3
## DENVER DEPEW
## 22 2
## DERBY DERRY
## 1 1
## DERWOOD DES MOINES
## 1 7
## DES PLAINES DESERT HOT SPRINGS
## 1 3
## DESOTO DESTIN
## 3 1
## DETROIT DEXTER
## 27 1
## DIAMOND BAR DILLON
## 1 1
## DILLWYN DISCOVERY BAY
## 1 2
## DISTRICT HEIGHTS DITTMER
## 3 1
## DIXON DOBSON
## 3 1
## DOCENA DODSON
## 1 1
## DOLTON DONALDSONVILLE
## 3 1
## DORADO DOS PALOS
## 1 1
## DOTHAN DOUGLAS
## 2 1
## DOUGLASS DOUGLASVILLE
## 1 3
## DOVER DOWAGIAC
## 6 1
## DOWELLTOWN DOWNERS GROVE
## 1 3
## DOWNEY DOYLESTOWN
## 1 3
## DRACUT DRAPER
## 1 1
## DREXEL HILL DRIPPING SPRINGS
## 1 1
## DRY RIDGE DU BOIS
## 1 1
## DUARTE DUBLIN
## 1 5
## DULUTH DUMFRIES
## 4 1
## DUMONT DUNCANNON
## 1 1
## DUNCANSVILLE DUNDEE
## 1 1
## DUNN DUNNELLON
## 1 1
## DURANGO DURHAM
## 1 6
## DUSON DYERSBURG
## 1 1
## EAGLE NEST EAGLE POINT
## 1 2
## EAGLE RIVER EAGLE ROCK
## 1 1
## EASLEY EAST BRADY
## 1 1
## EAST BRUNSWICK EAST DUBLIN
## 1 1
## EAST EARL EAST HAMPTON
## 1 1
## EAST HANOVER EAST HARTFORD
## 1 2
## EAST LANSING EAST ORANGE
## 1 4
## EAST PETERSBURG EAST PITTSBURGH
## 1 1
## EAST PRAIRIE EAST PROVIDENCE
## 1 2
## EAST SPENCER EAST STROUDSBURG
## 1 4
## EAST TEMPLETON EAST WAREHAM
## 1 1
## EAST WEYMOUTH EASTLAKE
## 1 2
## EASTMAN EASTON
## 2 3
## EASTPOINTE EATON RAPIDS
## 2 1
## ECORSE EDEN
## 1 1
## EDEN PRAIRIE EDGARD
## 1 1
## EDGEMONT EDGEWATER
## 1 1
## EDGEWOOD EDINBURG
## 2 1
## EDISON EDMOND
## 2 2
## EDWARD EDWARDS
## 1 1
## EFFORT EIGHT MILE
## 1 1
## EL CAJON EL CAMPO
## 2 1
## EL CENTRO EL DORADO
## 2 1
## EL MONTE EL PASO
## 2 15
## EL SEGUNDO EL SOBRANTE
## 1 1
## ELDRED ELGIN
## 1 5
## ELIZABETH ELIZABETH CITY
## 3 1
## ELIZABETHTON ELIZABETHTOWN
## 1 1
## ELK GROVE ELK GROVE VILLAGE
## 4 2
## ELK POINT ELKRIDGE
## 1 2
## ELKTON ELLABELL
## 4 1
## ELLAVILLE ELLENTON
## 1 1
## ELLENWOOD ELLINGTON
## 4 1
## ELLOREE ELMER
## 1 1
## ELMHURST ELMONT
## 1 1
## ELSIE ELWOOD
## 1 1
## ELYRIA EMMAUS
## 5 1
## EMMITSBURG EMPIRE
## 1 1
## ENCINO ENGLEWOOD
## 1 7
## ENGLISHTOWN ENTERPRISE
## 1 1
## EPHRATA EPPING
## 1 1
## EPPS ERIE
## 1 3
## ERWIN ESCONDIDO
## 1 2
## ESSEX ESSEX JUNCTION
## 1 2
## ESTERO ESTILL
## 1 1
## EUCLID EUGENE
## 5 2
## EULESS EUREKA
## 2 1
## EUREKA SPRINGS EUSTIS
## 1 2
## EVANS EVANSVILLE
## 2 3
## EVERETT EWA BEACH
## 5 2
## FAIRBANKS FAIRBORN
## 1 1
## FAIRBURN FAIRFAX
## 2 2
## FAIRFIELD FAIRLESS HILLS
## 11 1
## FAIRMONT FAIRVIEW
## 1 2
## FAIRVIEW HEIGHTS FALKVILLE
## 1 1
## FALL RIVER FALLBROOK
## 2 1
## FALLING WATERS FALLS CHURCH
## 1 2
## FALLS CITY FALMOUTH
## 2 1
## FAR ROCKAWAY FARGO
## 2 1
## FARIBAULT FARMERSVILLE
## 5 1
## FARMINGDALE FARMINGTON
## 1 5
## FARMINGVILLE FARRELL
## 1 1
## FAYETTE FAYETTEVILLE
## 2 10
## FEASTERVILLE TREVOSE FEDERAL WAY
## 1 5
## FELTON FENTON
## 1 4
## FERNDALE FERNLEY
## 1 2
## FINDLAY FINKSBURG
## 2 1
## FINLEY FINLEYVILLE
## 1 1
## FITZGERALD FITZWILLIAM
## 1 1
## FLAGSTAFF FLAT ROCK
## 1 1
## FLATGAP FLINT
## 1 3
## FLORALA FLORENCE
## 1 2
## FLORISSANT FLOWER MOUND
## 7 3
## FLOWERY BRANCH FLUSHING
## 2 3
## FOND DU LAC FONTANA
## 1 5
## FORD FOREST CITY
## 1 1
## FOREST HILLS FORKLAND
## 1 1
## FORT APACHE FORT ATKINSON
## 1 1
## FORT BRAGG FORT CAMPBELL
## 1 2
## FORT COLLINS FORT DEFIANCE
## 5 1
## FORT LAUDERDALE FORT LEE
## 19 1
## FORT LUPTON FORT MEADE
## 1 2
## FORT MILL FORT MYERS
## 1 7
## FORT PIERCE FORT PLAIN
## 2 1
## FORT RILEY FORT SMITH
## 1 2
## FORT WALTON BEACH FORT WASHINGTON
## 1 2
## FORT WAYNE FORT WORTH
## 5 29
## FOSTERS FOSTORIA
## 1 1
## FOUNTAIN FOUNTAIN HILLS
## 1 1
## FOUNTAIN RUN FOWLER
## 1 1
## FRAMINGHAM FRANKFORT
## 2 1
## FRANKLIN FRANKLINTON
## 3 1
## FRANKSVILLE FRAZEE
## 1 1
## FRAZIER PARK FREDERICK
## 1 2
## FREDERICKSBURG FREDERICKTOWN
## 3 1
## FREDERIKSTED FREEHOLD
## 1 1
## FREEPORT FREMONT
## 4 5
## FRESNO FRIENDSVILLE
## 18 1
## FRIENDSWOOD FRISCO
## 1 1
## FRONT ROYAL FROST
## 3 1
## FROSTBURG FRUITLAND PARK
## 1 1
## FT MITCHELL FULLERTON
## 1 1
## GADSDEN GAFFNEY
## 1 1
## GAINESVILLE GALAX
## 7 1
## GALENA GALION
## 1 1
## GALLATIN GALLIANO
## 3 1
## GALVESTON GANSEVOORT
## 1 1
## GARDEN CITY GARDEN GROVE
## 1 3
## GARDNERVILLE GARFIELD
## 1 3
## GARLAND GARNER
## 11 1
## GARRETTSVILLE GARRISON
## 1 1
## GARY GASTON
## 1 1
## GASTONIA GEISMAR
## 4 2
## GENEVA GEORGETOWN
## 2 3
## GERMANTOWN GIBBON
## 5 1
## GIBBSTOWN GIBSON CITY
## 1 1
## GIG HARBOR GILBERT
## 1 3
## GILCHRIST GILLETTE
## 1 1
## GILMANTON GILROY
## 1 2
## GIRARD GLADEWATER
## 2 3
## GLEN ALLEN GLEN BURNIE
## 1 4
## GLENDALE GLENDIVE
## 5 1
## GLENN DALE GLENPOOL
## 1 1
## GLENWOOD GLOUCESTER
## 3 1
## GLOUCESTER CITY GLOVERSVILLE
## 1 1
## GOLD BAR GOLDSBORO
## 1 3
## GOLETA GOODVIEW
## 2 2
## GOOSE CREEK GORDON
## 2 2
## GORHAM GOSHEN
## 1 2
## GRAFTON GRAHAM
## 1 3
## GRAND BLANC GRAND ISLAND
## 1 4
## GRAND JUNCTION GRAND PRAIRIE
## 2 5
## GRAND RAPIDS GRANDVIEW
## 7 1
## GRANITE CITY GRANTS PASS
## 1 2
## GRAVOIS MILLS GRAY
## 1 1
## GRAYSON GREELEY
## 1 1
## GREEN BAY GREEN COVE SPRINGS
## 1 2
## GREEN RIVER GREEN VALLEY
## 1 1
## GREENACRES GREENBELT
## 1 1
## GREENCASTLE GREENE
## 2 1
## GREENEVILLE GREENFIELD
## 1 2
## GREENSBORO GREENSBURG
## 9 2
## GREENTOWN GREENVILLE
## 1 12
## GREENWICH GREENWOOD
## 1 4
## GREER GRETNA
## 2 1
## GRIFFIN GRIFFITHSVILLE
## 1 1
## GRIMES GROTON
## 1 1
## GROVE CITY GROVEPORT
## 1 1
## GROVETOWN GULF BREEZE
## 4 1
## GUNTOWN GURNEE
## 1 1
## GUTHRIE GUY
## 1 1
## GWYNN OAK HACKETTSTOWN
## 5 1
## HADLEY HAGERSTOWN
## 1 3
## HAINES CITY HALEDON
## 1 3
## HALIFAX HALLANDALE
## 1 2
## HALSTAD HAMBURG
## 1 1
## HAMDEN HAMILTON
## 2 2
## HAMMOND HAMMONTON
## 4 1
## HAMPSTEAD HAMPTON
## 1 9
## HANA HANAHAN
## 1 1
## HANFORD HANSCOM AFB
## 2 2
## HAPPY VALLEY HARKER HEIGHTS
## 1 1
## HARPERS FERRY HARRINGTON
## 1 1
## HARRISBURG HARRISON
## 4 2
## HARTFORD HARTINGTON
## 3 1
## HARTSELLE HARVARD
## 1 1
## HARVEY HARWICH PORT
## 7 1
## HASLET HASTINGS
## 1 3
## HATBORO HAUGHTON
## 1 1
## HAUPPAUGE HAVANA
## 2 1
## HAVERHILL HAVERTOWN
## 1 1
## HAWTHORNE HAYDEN
## 5 1
## HAYNEVILLE HAYTI
## 1 1
## HAYWARD HAZARD
## 2 1
## HAZEL CREST HAZELWOOD
## 2 1
## HAZLETON HEALDSBURG
## 4 1
## HEATH HEBER CITY
## 1 1
## HEBRON HELENA
## 2 1
## HEMET HENDERSON
## 3 16
## HENDERSONVILLE HENRYETTA
## 1 1
## HEPHZIBAH HEREFORD
## 1 1
## HERKIMER HERMITAGE
## 1 2
## HERNDON HERRIN
## 1 2
## HESPERIA HIALEAH
## 4 14
## HICKORY HIGH POINT
## 2 1
## HIGHLAND HIGHLAND PARK
## 4 3
## HIGHLANDS HIGHTSTOWN
## 1 3
## HIGHWOOD HILLIARD
## 1 2
## HILLSBORO HILLSBOROUGH
## 2 1
## HILLVIEW HILO
## 1 1
## HILTON HILTON HEAD ISLAND
## 1 1
## HINTON HIRAM
## 1 3
## HIXSON HOBBS
## 1 2
## HOBE SOUND HOBOKEN
## 1 1
## HOCKLEY HODGENVILLE
## 2 1
## HOGANSVILLE HOLIDAY
## 1 1
## HOLLISTER HOLLY
## 1 1
## HOLLY POND HOLLY SPRINGS
## 1 1
## HOLLYWOOD HOLSTEIN
## 12 1
## HOLTS SUMMIT HOLTVILLE
## 1 1
## HOLYOKE HOME
## 1 1
## HOMER HOMERVILLE
## 1 1
## HOMESTEAD HOMETOWN
## 6 1
## HOMEWOOD HONESDALE
## 2 1
## HONOLULU HOOPA
## 3 1
## HOPE HOPE MILLS
## 1 1
## HOPEDALE HOPEWELL
## 1 3
## HOPEWELL JUNCTION HOPKINS
## 1 1
## HOPKINSVILLE HOQUIAM
## 1 2
## HORN LAKE HORSHAM
## 2 2
## HOT SPRINGS NATIONAL PARK HOUGHTON
## 5 1
## HOUMA HOUSE SPRINGS
## 2 3
## HOUSTON HOWARD BEACH
## 81 1
## HOWELL HUDSON
## 1 4
## HULL HUMBLE
## 1 6
## HUNTINGTON HUNTINGTON BEACH
## 3 2
## HUNTINGTON PARK HUNTINGTOWN
## 1 1
## HUNTSVILLE HURRICANE
## 8 1
## HURST HUTTO
## 1 2
## HYATTSVILLE HYDE PARK
## 6 1
## IMPERIAL IMPERIAL BEACH
## 4 2
## INDEPENDENCE INDIAN TRAIL
## 2 1
## INDIAN WELLS INDIANA
## 1 1
## INDIANAPOLIS INDIANOLA
## 34 1
## INDIO INGLESIDE
## 1 1
## INGLEWOOD INMAN
## 8 1
## IOWA CITY IPSWICH
## 1 1
## IRMO IRVINE
## 1 6
## IRVING IRVINGTON
## 4 2
## IRWIN ISANTI
## 1 1
## ISLIP TERRACE ITASCA
## 1 2
## JACKSON JACKSONVILLE
## 18 20
## JAMAICA JAMAICA PLAIN
## 3 1
## JAMESTOWN JASPER
## 2 5
## JEFFERSON JEFFERSON CITY
## 4 3
## JENKS JEROME
## 1 1
## JERSEY CITY JESSUP
## 9 1
## JESUP JEWELL RIDGE
## 1 1
## JOHNSONVILLE JOHNSTON
## 1 5
## JOHNSTOWN JOLIET
## 5 4
## JONESBORO JONESVILLE
## 4 1
## JOPLIN JOSEPH
## 3 1
## JUANA DIAZ JUNCTION CITY
## 1 3
## JUPITER JUSTICE
## 2 1
## KAHUKU KAHULUI
## 1 1
## KALAMAZOO KAMPSVILLE
## 4 1
## KANNAPOLIS KANSAS CITY
## 1 18
## KAPOLEI KATHRYN
## 3 1
## KATY KAUFMAN
## 6 1
## KAYENTA KAYSVILLE
## 2 2
## KEANSBURG KEARNEY
## 1 1
## KEENE KEITHVILLE
## 1 1
## KELLER KELSO
## 2 1
## KEMAH KENBRIDGE
## 1 1
## KENDALL PARK KENDALLVILLE
## 1 2
## KENEDY KENLY
## 1 1
## KENNEBUNK KENNER
## 1 4
## KENNESAW KENNETT
## 2 1
## KENNEWICK KENT
## 1 3
## KENTON KENWOOD
## 1 1
## KEOKUK KERRVILLE
## 1 2
## KESWICK KETCHUM
## 1 1
## KEVIL KEW GARDENS
## 1 1
## KEWANNA KILLEEN
## 1 5
## KING KING AND QUEEN COURT HOUSE
## 1 1
## KING CITY KING SALMON
## 1 1
## KINGMAN KINGS MOUNTAIN
## 1 1
## KINGSHILL KINGSLAND
## 1 2
## KINGSTON KINSTON
## 1 3
## KIRKWOOD KISSIMMEE
## 1 7
## KITTITAS KLAMATH FALLS
## 1 1
## KNOXVILLE KRUM
## 3 1
## LA GRANGE LA LUZ
## 2 1
## LA MARQUE LA MESA
## 1 1
## LA MIRADA LA PLATA
## 1 1
## LA PORTE LA PUENTE
## 1 5
## LA VERGNE LA VERNIA
## 4 1
## LACEY LADY LAKE
## 1 1
## LADYS ISLAND LAFAYETTE
## 1 10
## LAGRANGE LAGUNA BEACH
## 2 1
## LAKE ALFRED LAKE ARIEL
## 1 1
## LAKE CHARLES LAKE CITY
## 3 2
## LAKE ELSINORE LAKE FOREST
## 4 1
## LAKE ISABELLA LAKE LUZERNE
## 1 1
## LAKE OSWEGO LAKE PLACID
## 1 1
## LAKE SAINT LOUIS LAKE STATION
## 1 1
## LAKE VILLAGE LAKE WORTH
## 1 4
## LAKELAND LAKESIDE
## 9 2
## LAKESIDE MARBLEHEAD LAKEVILLE
## 1 1
## LAKEWOOD LANCASTER
## 5 10
## LAND O LAKES LANDING
## 1 1
## LANHAM LANSDOWNE
## 2 2
## LANSING LAREDO
## 5 7
## LARGO LARKSPUR
## 3 1
## LAS CRUCES LAS PIEDRAS
## 3 1
## LAS VEGAS LATHAM
## 52 1
## LAUDERDALE LAUGHLIN
## 1 1
## LAUREL LAUREL SPRINGS
## 5 1
## LAVEEN LAVON
## 2 1
## LAWNDALE LAWRENCE
## 1 6
## LAWRENCE TOWNSHIP LAWRENCEBURG
## 3 2
## LAWRENCEVILLE LAWTEY
## 5 1
## LAWTON LAYTON
## 2 1
## LE MARS LEAGUE CITY
## 1 1
## LEBANON LECOMPTE
## 6 2
## LEEDS LEES SUMMIT
## 1 3
## LEESBURG LEHI
## 4 1
## LEHIGHTON LEMONT
## 1 1
## LEMOORE LENEXA
## 3 2
## LENORE LEOMINSTER
## 1 1
## LEVITTOWN LEWISTON
## 2 1
## LEWISTOWN LEWISVILLE
## 1 1
## LEXINGTON LIBERTY
## 8 2
## LILBURN LIMA
## 1 1
## LINCOLN LINCOLN PARK
## 8 2
## LINCOLN UNIVERSITY LINCOLNTON
## 1 2
## LINDEN LINDENHURST
## 1 1
## LINDSAY LINDSBORG
## 1 1
## LINTHICUM HEIGHTS LISLE
## 1 1
## LITCHFIELD LITCHFIELD PARK
## 1 1
## LITHIA SPRINGS LITHONIA
## 1 7
## LITTLE ELM LITTLE FERRY
## 2 1
## LITTLE ROCK LITTLETON
## 9 6
## LIVE OAK LIVONIA
## 2 2
## LOCK HAVEN LOCKPORT
## 1 1
## LOCUST GROVE LODI
## 2 3
## LOGAN LOGANVILLE
## 2 1
## LOMA LINDA LOMBARD
## 1 1
## LOMPOC LONDONDERRY
## 1 1
## LONE PINE LONG BEACH
## 1 15
## LONG VALLEY LONGVIEW
## 1 2
## LONGWOOD LORAIN
## 2 1
## LORANGER LOS ALAMITOS
## 1 1
## LOS ANGELES LOS FRESNOS
## 42 2
## LOS GATOS LOS LUNAS
## 2 1
## LOS MOLINOS LOS OSOS
## 1 1
## LOST NATION LOUISBURG
## 1 1
## LOUISVILLE LOVES PARK
## 16 1
## LOWELL LOWELLVILLE
## 3 1
## LUBBOCK LUCAMA
## 5 1
## LULING LUMBER BRIDGE
## 1 1
## LUMBER CITY LUMBERTON
## 1 2
## LUTCHER LUTHERVILLE TIMONIUM
## 1 1
## LUTZ LYDIA
## 4 1
## LYNCHBURG LYNDEN
## 4 1
## LYNDHURST LYNN
## 1 6
## LYNNWOOD LYNWOOD
## 2 2
## MABANK MACCLESFIELD
## 1 1
## MACHESNEY PARK MACON
## 1 3
## MADERA MADISON
## 1 11
## MADISON HEIGHTS MADISONVILLE
## 4 2
## MAGNA MAGNOLIA
## 1 2
## MALTA MALVERN
## 1 2
## MAMARONECK MANASSAS
## 1 3
## MANCHESTER MANCHESTER TOWNSHIP
## 7 1
## MANDEVILLE MANHATTAN
## 2 3
## MANHATTAN BEACH MANISTEE
## 1 1
## MANKATO MANNING
## 2 1
## MANSFIELD MANTECA
## 4 4
## MANTENO MAPLE HEIGHTS
## 1 4
## MAPLESVILLE MARANA
## 1 1
## MARCUS HOOK MARENGO
## 2 2
## MARICOPA MARIETTA
## 1 9
## MARINA MARINGOUIN
## 1 1
## MARION MARKHAM
## 6 3
## MARKSVILLE MARLBOROUGH
## 1 2
## MARLINTON MARLTON
## 1 2
## MARMORA MARRERO
## 1 1
## MARSHALL MARSHALLTOWN
## 3 1
## MARTINSBURG MARTINSVILLE
## 1 1
## MARYSVILLE MASCOUTAH
## 1 1
## MASON MASON CITY
## 2 1
## MASONTOWN MASSILLON
## 1 1
## MASTIC MATAWAN
## 1 1
## MATTAPAN MATTOON
## 2 2
## MAUMEE MAYAGUEZ
## 1 1
## MAYBEE MAYO
## 1 1
## MAYS LANDING MAYSVILLE
## 2 1
## MC ALPIN MC CORDSVILLE
## 2 1
## MC DONALD MC HENRY
## 1 1
## MCALESTER MCALLEN
## 1 4
## MCDONOUGH MCKEESPORT
## 2 1
## MCKENNA MCKINNEY
## 1 1
## MCMINNVILLE MCPHERSON
## 1 1
## MEAD MEADOWVIEW
## 2 1
## MEADVILLE MEBANE
## 1 3
## MECHANICSVILLE MEDFORD
## 1 1
## MEDINA MELBOURNE
## 1 3
## MELROSE PARK MEMPHIS
## 2 17
## MENDENHALL MENDON
## 2 1
## MENIFEE MENTMORE
## 1 1
## MENTONE MERCED
## 2 3
## MERIDEN MERIDIAN
## 1 3
## MERRILLVILLE MERRIMACK
## 4 1
## MERRITT ISLAND MESA
## 1 12
## MESQUITE METAIRIE
## 7 1
## MEXICO MIAMI
## 1 60
## MIAMI BEACH MIAMISBURG
## 3 1
## MIDDLE ISLAND MIDDLE RIVER
## 1 1
## MIDDLEBORO MIDDLETOWN
## 2 4
## MIDKIFF MIDLAND
## 1 3
## MILFORD MILILANI
## 5 2
## MILLEDGEVILLE MILLEN
## 2 1
## MILLERTON MILLINGTON
## 1 1
## MILLS MILLSBORO
## 1 1
## MILLVILLE MILPITAS
## 1 2
## MILWAUKEE MINDEN
## 1 1
## MINGO JUNCTION MINNEAPOLIS
## 1 15
## MINOT MIRA LOMA
## 3 3
## MISHAWAKA MISSION
## 1 3
## MISSION VIEJO MISSOURI CITY
## 2 3
## MITCHELL MITCHELLVILLE
## 1 1
## MOAB MOBERLY
## 1 1
## MOBILE MOCKSVILLE
## 9 1
## MODESTO MOKANE
## 8 1
## MOLINE MONAHANS
## 1 1
## MONCKS CORNER MONROE
## 1 5
## MONROE CITY MONTAGUE
## 1 2
## MONTEBELLO MONTEREY
## 1 1
## MONTEREY PARK MONTEVALLO
## 1 2
## MONTGOMERY MONTICELLO
## 10 2
## MONTROSE MONUMENT
## 3 1
## MOORESBURG MOORESVILLE
## 1 1
## MORA MOREHEAD CITY
## 1 1
## MORENO VALLEY MORGANTON
## 13 2
## MORRIS MORRISVILLE
## 3 2
## MORROW MORTON
## 1 2
## MOSCOW MOSES LAKE
## 2 1
## MOSS POINT MOULTRIE
## 1 1
## MOUND MOUNDS
## 1 1
## MOUNT AIRY MOUNT BETHEL
## 1 1
## MOUNT HOLLY MOUNT JULIET
## 1 3
## MOUNT KISCO MOUNT LAUREL
## 1 1
## MOUNT MORRIS MOUNT OLIVE
## 1 1
## MOUNT PLEASANT MOUNT PROSPECT
## 1 1
## MOUNT RAINIER MOUNT STERLING
## 1 1
## MOUNT VERNON MOUNTAIN TOP
## 3 3
## MOUNTAINBURG MUIR
## 1 1
## MULDOON MUNCIE
## 1 2
## MUNSTER MURFREESBORO
## 1 1
## MURPHYSBORO MURRIETA
## 1 2
## MUSCLE SHOALS MUSKEGON
## 1 1
## MYRTLE BEACH NACOGDOCHES
## 1 1
## NAMPA NANJEMOY
## 2 1
## NAPA NAPERVILLE
## 2 2
## NAPLES NAPPANEE
## 4 1
## NASHUA NASHVILLE
## 3 13
## NATCHEZ NATIONAL CITY
## 2 3
## NAVARRE NEOSHO
## 1 1
## NEVADA NEW ALBANY
## 1 1
## NEW BALTIMORE NEW BEDFORD
## 1 2
## NEW BERN NEW BRAUNFELS
## 3 2
## NEW BRITAIN NEW BRUNSWICK
## 1 1
## NEW BUFFALO NEW CARLISLE
## 1 2
## NEW CASTLE NEW CITY
## 2 1
## NEW CONCORD NEW EGYPT
## 1 1
## NEW GLOUCESTER NEW HAVEN
## 1 4
## NEW LEXINGTON NEW ORLEANS
## 2 13
## NEW PORT RICHEY NEW RICHMOND
## 2 1
## NEW TOWN NEW VIENNA
## 1 1
## NEW WINDSOR NEW YORK
## 2 24
## NEWARK NEWAYGO
## 17 1
## NEWBERG NEWBURG
## 3 2
## NEWBURGH NEWFANE
## 3 1
## NEWINGTON NEWNAN
## 2 5
## NEWPORT NEWPORT BEACH
## 3 2
## NEWPORT NEWS NEWTON
## 6 2
## NIAGARA FALLS NICHOLASVILLE
## 2 1
## NICHOLS NILES
## 1 1
## NITRO NIXA
## 1 1
## NOBLESVILLE NOCONA
## 2 1
## NORCO NORCROSS
## 1 6
## NORFOLK NORMAL
## 8 1
## NORMAN NORTH APOLLO
## 2 1
## NORTH ATTLEBORO NORTH AUGUSTA
## 1 1
## NORTH AURORA NORTH BEND
## 1 1
## NORTH CHARLESTON NORTH CHICAGO
## 2 1
## NORTH CHILI NORTH FERRISBURGH
## 1 1
## NORTH FORT MYERS NORTH HAVEN
## 1 1
## NORTH HIGHLANDS NORTH HOLLYWOOD
## 1 6
## NORTH LAS VEGAS NORTH LIBERTY
## 5 1
## NORTH LITTLE ROCK NORTH PORT
## 1 1
## NORTH PORT CARRIER ANNEX NORTH PROVIDENCE
## 2 1
## NORTH RICHLAND HILLS NORTH RIDGEVILLE
## 1 1
## NORTH TAZEWELL NORTH VERNON
## 1 1
## NORTH WEBSTER NORTH WILKESBORO
## 1 1
## NORTHAMPTON NORTHFIELD
## 1 1
## NORTHWOOD NORWALK
## 1 9
## NORWAY NORWICH
## 1 1
## NORWOOD NOVATO
## 2 2
## NOVI NUTLEY
## 2 1
## O FALLON OAK FOREST
## 7 1
## OAK HILL OAK ISLAND
## 1 1
## OAK LAWN OAK PARK
## 1 1
## OAK RIDGE OAKLAND
## 1 6
## OAKLEY OAKRIDGE
## 3 1
## OCALA OCEAN CITY
## 7 1
## OCEAN ISLE BEACH OCEANSIDE
## 1 2
## ODESSA ODIN
## 5 1
## OGDEN OJAI
## 4 1
## OKEECHOBEE OKLAHOMA CITY
## 1 14
## OLATHE OLD BRIDGE
## 2 1
## OLD ORCHARD BEACH OLDSMAR
## 1 1
## OLIVE BRANCH OLIVEHURST
## 1 1
## OLIVIA OLNEY
## 1 2
## OLYMPIA OLYMPIA FIELDS
## 1 1
## OLYPHANT OMAHA
## 2 14
## OMEGA ONANCOCK
## 1 1
## ONTARIO OOLTEWAH
## 5 1
## OPA LOCKA OPELOUSAS
## 10 1
## OPP ORANGE
## 1 3
## ORANGE PARK ORANGEBURG
## 4 2
## OREGON ORFORD
## 2 1
## ORLANDO ORMOND BEACH
## 33 3
## OROVILLE OSCEOLA MILLS
## 3 1
## OSWEGO OTTAWA
## 1 1
## OTTERBEIN OTTUMWA
## 1 1
## OTWAY OVERLAND PARK
## 1 3
## OVERTON OVIEDO
## 1 1
## OWENSBORO OWINGS
## 1 1
## OWINGS MILLS OWOSSO
## 3 1
## OXFORD OXNARD
## 4 7
## OXON HILL OYSTER BAY
## 1 1
## OZARK OZONE PARK
## 1 1
## PACIFIC CITY PACIFICA
## 1 1
## PACOIMA PAHRUMP
## 1 1
## PAIA PAINTSVILLE
## 1 1
## PALA PALATINE
## 1 1
## PALATKA PALESTINE
## 1 2
## PALM BAY PALM BEACH GARDENS
## 7 2
## PALM DESERT PALM HARBOR
## 2 1
## PALM SPRINGS PALMDALE
## 3 9
## PALMETTO PALMYRA
## 1 3
## PALO ALTO PANAMA CITY
## 2 2
## PARAMOUNT PARIS
## 2 2
## PARK CITY PARK FOREST
## 1 3
## PARK RIDGE PARKER
## 1 2
## PARKSLEY PARKVILLE
## 1 2
## PASADENA PASCAGOULA
## 6 1
## PASCO PASS CHRISTIAN
## 1 1
## PATERSON PAULDING
## 3 1
## PAX PAYNESVILLE
## 1 2
## PEABODY PEACHTREE CITY
## 1 3
## PEARCY PEARL
## 1 2
## PEARL CITY PEARLAND
## 1 1
## PEASE PEEKSKILL
## 1 1
## PELAHATCHIE PELHAM
## 1 2
## PELLA PEMBERTON
## 1 1
## PENDLETON PENNSAUKEN
## 1 2
## PENNSBORO PENNSVILLE
## 1 1
## PENSACOLA PEORIA
## 5 6
## PERRIS PERRYSBURG
## 3 1
## PERTH AMBOY PETALUMA
## 1 2
## PETOSKEY PEYTON
## 1 1
## PFAFFTOWN PFLUGERVILLE
## 1 3
## PHELPS PHENIX CITY
## 1 1
## PHILADELPHIA PHILLIPSBURG
## 54 1
## PHOENIX PHOENIXVILLE
## 21 1
## PICAYUNE PICKENS
## 1 1
## PICKERINGTON PIEDMONT
## 2 1
## PIKEVILLE PIMA
## 1 1
## PINCKNEY PINE BLUFF
## 2 3
## PINE GROVE PINE RIVER
## 1 1
## PINEHURST PINELLAS PARK
## 1 3
## PINEVILLE PINNACLE
## 2 2
## PINOLE PIQUA
## 2 1
## PISGAH FOREST PISMO BEACH
## 1 1
## PITTS PITTSBURG
## 1 2
## PITTSBURGH PITTSFIELD
## 14 4
## PITTSVIEW PLACERVILLE
## 1 1
## PLAINFIELD PLAINSBORO
## 6 1
## PLAINVILLE PLANO
## 3 4
## PLANT CITY PLAZA
## 3 1
## PLYMOUTH POLAND
## 2 1
## POLK CITY POLKTON
## 1 1
## POLSON POMEROY
## 1 1
## POMFRET CENTER POMONA
## 1 4
## POMPANO BEACH PONCA CITY
## 9 2
## PONCE PONTIAC
## 2 3
## POOLER POPLAR
## 1 1
## POPLAR BLUFF PORT ANGELES
## 2 2
## PORT ARTHUR PORT CHARLOTTE
## 1 3
## PORT CLINTON PORT HURON
## 1 3
## PORT JEFFERSON STATION PORT ORCHARD
## 1 1
## PORT SAINT LUCIE PORT TOWNSEND
## 4 1
## PORTAGE PORTAGEVILLE
## 2 1
## PORTER PORTLAND
## 1 17
## PORTSMOUTH POST FALLS
## 2 1
## POTEAU POTTERVILLE
## 2 1
## POTTSTOWN POULSBO
## 1 1
## POUND POWDER SPRINGS
## 1 2
## PRAGUE PRAIRIE DU ROCHER
## 1 1
## PRAIRIEVILLE PRATTVILLE
## 1 3
## PRENTISS PRESCOTT
## 1 1
## PRESCOTT VALLEY PRESTON
## 3 2
## PRINCE FREDERICK PRINCETON
## 1 5
## PROCTORVILLE PROSPECT HEIGHTS
## 1 1
## PROSSER PROVIDENCE
## 1 4
## PRYOR PUEBLO
## 1 3
## PULASKI PUTNAM
## 2 1
## PUYALLUP QUEBECK
## 2 1
## QUEEN CREEK QUINCY
## 4 5
## QUINTON RACINE
## 1 1
## RAEFORD RAHWAY
## 2 3
## RALEIGH RAMSEUR
## 13 1
## RANCHO CUCAMONGA RANCHO MIRAGE
## 3 1
## RANCHO SANTA MARGARITA RANDALLSTOWN
## 2 1
## RANDOLPH RANSON
## 3 1
## RANTOUL RAPID CITY
## 1 2
## RAVENNA RAYVILLE
## 3 1
## READING REALITOS
## 1 1
## RED LEVEL RED OAK
## 1 2
## RED SPRINGS REDDICK
## 1 1
## REDDING REDFIELD
## 5 1
## REDFORD REDLANDS
## 2 2
## REDMOND REEDSPORT
## 1 1
## REESE REISTERSTOWN
## 1 2
## RENFREW RENO
## 1 4
## RENTON RESEDA
## 2 3
## REX REYNOLDSBURG
## 2 1
## RIALTO RICEBORO
## 5 1
## RICHLAND RICHMOND
## 2 15
## RICHMOND HILL RICHTON PARK
## 1 2
## RIDGE SPRING RIDGEFIELD
## 1 1
## RIDGEFIELD PARK RIDGELAND
## 1 1
## RIDGEWAY RIENZI
## 1 1
## RIGBY RINGGOLD
## 1 1
## RIO FRIO RIO GRANDE CITY
## 1 1
## RIO RANCHO RIO VISTA
## 1 1
## RIPLEY RISON
## 1 1
## RITZVILLE RIVERDALE
## 1 5
## RIVERSIDE RIVERTON
## 15 2
## RIVERVIEW RIVES
## 1 1
## ROANOKE ROANOKE RAPIDS
## 7 2
## ROARING SPRING ROBINS
## 1 1
## ROBSTOWN ROCHELLE
## 3 2
## ROCHESTER ROCK CREEK
## 7 1
## ROCK FALLS ROCK HILL
## 1 2
## ROCK SPRINGS ROCKFORD
## 1 7
## ROCKLEDGE ROCKLIN
## 3 2
## ROCKPORT ROCKVALE
## 1 1
## ROCKVILLE ROCKVILLE CENTRE
## 2 1
## ROCKWELL ROCKWOOD
## 1 1
## ROCKY HILL ROCKY MOUNT
## 1 2
## ROGERS ROHNERT PARK
## 1 1
## ROLLA ROME
## 1 3
## ROMEOVILLE ROMULUS
## 3 5
## ROOTSTOWN ROPER
## 1 1
## ROSAMOND ROSEBURG
## 1 1
## ROSEDALE ROSEMEAD
## 1 1
## ROSENBERG ROSEVILLE
## 1 8
## ROSWELL ROUND LAKE
## 1 4
## ROUND ROCK ROWLAND HEIGHTS
## 1 1
## ROWLETT ROYAL OAK
## 2 1
## ROYERSFORD ROYSE CITY
## 1 2
## RUMFORD RURAL HALL
## 1 1
## RUSKIN RUSSELLVILLE
## 2 1
## RUSTON RUTLEDGE
## 1 1
## RYAN SABINA
## 1 1
## SACHSE SACRAMENTO
## 3 24
## SADDLE BROOK SAGINAW
## 1 1
## SAGUACHE SAINT AUGUSTINE
## 1 3
## SAINT CHARLES SAINT CLOUD
## 3 3
## SAINT GEORGE SAINT JAMES
## 2 2
## SAINT JOE SAINT JOHNSVILLE
## 1 1
## SAINT LOUIS SAINT PAUL
## 20 14
## SAINT PETERS SAINT PETERSBURG
## 3 7
## SALADO SALEM
## 1 14
## SALINAS SALISBURY
## 3 5
## SALT LAKE CITY SALTSBURG
## 5 1
## SAN ANTONIO SAN BERNARDINO
## 45 6
## SAN CLEMENTE SAN DIEGO
## 3 22
## SAN FRANCISCO SAN JOSE
## 15 20
## SAN JUAN SAN LEANDRO
## 4 2
## SAN LUIS OBISPO SAN MARCOS
## 2 5
## SAN PEDRO SAN RAMON
## 2 1
## SAN YSIDRO SAND SPRINGS
## 2 1
## SANDSTON SANDUSKY
## 2 4
## SANDY SANDY RIDGE
## 1 1
## SANFORD SANGER
## 6 3
## SANTA ANA SANTA BARBARA
## 2 1
## SANTA CLARA SANTA CLARITA
## 1 1
## SANTA MARIA SANTA ROSA
## 1 5
## SANTA ROSA BEACH SANTEE
## 1 1
## SARASOTA SARATOGA
## 6 1
## SATELLITE BEACH SAUGERTIES
## 1 1
## SAUGUS SAVANNAH
## 1 4
## SCHAUMBURG SCHENECTADY
## 2 1
## SCHERTZ SCIO
## 1 1
## SCOTT SCOTTSDALE
## 1 4
## SCRANTON SEABROOK
## 3 2
## SEADRIFT SEAFORD
## 1 1
## SEASIDE SEATTLE
## 1 11
## SEFFNER SEGUIN
## 1 1
## SELBYVILLE SELMA
## 1 2
## SEMINOLE SENATOBIA
## 1 1
## SEQUIM SEVERN
## 2 3
## SEVERNA PARK SEVIERVILLE
## 1 2
## SEWICKLEY SHAMOKIN
## 1 1
## SHANNON SHARON HILL
## 1 1
## SHAW A F B SHAWNEE
## 1 3
## SHELBY SHELTON
## 1 1
## SHERIDAN SHERMAN
## 1 1
## SHERWOOD SHILOH
## 1 1
## SHINGLE SPRINGS SHINNSTON
## 2 1
## SHIPROCK SHIPSHEWANA
## 1 1
## SHIRLEY SHREVEPORT
## 2 5
## SHREWSBURY SICKLERVILLE
## 1 1
## SIDNEY SIERRA VISTA
## 1 1
## SILVER SPRING SILVER SPRINGS
## 4 1
## SILVERTHORNE SILVIS
## 2 1
## SIMI VALLEY SIMPSONVILLE
## 2 2
## SIOUX FALLS SITKA
## 1 1
## SKOKIE SLIDELL
## 1 2
## SLOCOMB SMITHFIELD
## 1 3
## SMITHTON SMITHVILLE
## 1 2
## SMYRNA SNELLVILLE
## 4 5
## SNOHOMISH SNOQUALMIE
## 1 1
## SNOW CAMP SNYDER
## 1 2
## SODDY DAISY SOMERS
## 1 1
## SOMERVILLE SOPERTON
## 5 1
## SOPHIA SORRENTO
## 1 1
## SOUDERTON SOUTH BAY
## 1 1
## SOUTH BEND SOUTH BERWICK
## 3 1
## SOUTH CHATHAM SOUTH DENNIS
## 1 1
## SOUTH EL MONTE SOUTH GATE
## 1 2
## SOUTH GRAFTON SOUTH HILL
## 1 1
## SOUTH HOLLAND SOUTH HOUSTON
## 1 1
## SOUTH LAKE TAHOE SOUTH LYON
## 1 1
## SOUTH MILWAUKEE SOUTH OZONE PARK
## 1 2
## SOUTH SAINT PAUL SOUTH WINDSOR
## 1 4
## SOUTHAVEN SOUTHFIELD
## 4 2
## SOUTHMAYD SOUTHWICK
## 1 1
## SPANAWAY SPANISH FORT
## 3 1
## SPARROWS POINT SPARTA
## 1 2
## SPENCER SPENCERVILLE
## 1 1
## SPINDALE SPLENDORA
## 1 1
## SPOKANE SPRING
## 6 9
## SPRING GROVE SPRING HILL
## 1 4
## SPRING HOPE SPRING VALLEY
## 1 2
## SPRINGBORO SPRINGDALE
## 1 2
## SPRINGFIELD SPRINGFIELD GARDENS
## 11 1
## SPRINGTOWN STAFFORD
## 1 3
## STAMFORD STANARDSVILLE
## 5 1
## STANLEY STANTON
## 1 1
## STARR STATE COLLEGE
## 1 1
## STATEN ISLAND STATESVILLE
## 5 2
## STERLING STEUBENVILLE
## 4 1
## STEVENS POINT STILLWATER
## 1 1
## STIRLING STOCKBRIDGE
## 1 3
## STOCKTON STONE MOUNTAIN
## 11 6
## STRATFORD STREETSBORO
## 2 1
## STRONGSVILLE STUART
## 1 1
## SUFFOLK SUGAR LAND
## 2 2
## SUISUN CITY SUITLAND
## 1 6
## SULLIGENT SULPHUR
## 1 1
## SUMMERVILLE SUMNER
## 4 1
## SUMTER SUN CITY
## 2 2
## SUNLAND PARK SUNNYVALE
## 1 2
## SURPRISE SUTHERLIN
## 3 1
## SUWANEE SWAMPSCOTT
## 2 1
## SWANSEA SWARTHMORE
## 1 1
## SWEDESBORO SWEET WATER
## 1 1
## SWEETWATER SYLACAUGA
## 1 2
## SYLMAR SYLVANIA
## 1 1
## SYRACUSE TABOR CITY
## 4 1
## TACOMA TAHOKA
## 3 1
## TAKOMA PARK TALBOTT
## 1 1
## TALLAHASSEE TALLULAH
## 4 2
## TAMPA TANEYTOWN
## 13 1
## TARBORO TARRYTOWN
## 1 1
## TAUNTON TAYLOR
## 1 6
## TAYLORVILLE TEANECK
## 1 1
## TECUMSEH TELFORD
## 1 1
## TELLICO PLAINS TEMECULA
## 1 2
## TEMPE TEMPLE
## 1 4
## TEMPLE HILLS TERRE HAUTE
## 1 3
## TERREBONNE TEXARKANA
## 1 1
## TEXAS CITY THAYER
## 4 1
## THE COLONY THE PLAINS
## 2 1
## THEODORE THIBODAUX
## 1 1
## THOMASTON THOMASVILLE
## 1 1
## THOUSAND OAKS THREE RIVERS
## 1 1
## TICKFAW TIFFIN
## 1 1
## TIFTON TIMPSON
## 2 1
## TISHOMINGO TITUSVILLE
## 1 2
## TIVERTON TOA ALTA
## 1 1
## TOANO TOBYHANNA
## 1 1
## TOLEDO TOLLESON
## 6 1
## TOMBALL TOMS RIVER
## 1 1
## TONAWANDA TONOPAH
## 1 1
## TOOELE TOPEKA
## 2 2
## TORRINGTON TOWAOC
## 1 1
## TOWN CREEK TRACY
## 1 3
## TRANSFER TRANSYLVANIA
## 1 1
## TRAPPER CREEK TRAVELERS REST
## 1 1
## TRAVIS AFB TRENTON
## 1 8
## TRIANGLE TRIMBLE
## 1 1
## TRION TROY
## 1 3
## TUALATIN TUCKER
## 1 1
## TUCKERTON TUCSON
## 1 16
## TULARE TULSA
## 2 8
## TUNKHANNOCK TUPELO
## 1 1
## TURLOCK TURNERS FALLS
## 2 1
## TUSCALOOSA TUSTIN
## 2 2
## TWINSBURG TYLER
## 1 1
## TYNER UMATILLA
## 1 1
## UNCASVILLE UNION
## 1 2
## UNION CITY UNIONDALE
## 6 1
## UNIONTOWN UNIVERSAL CITY
## 1 1
## UNIVERSITY PLACE UPLAND
## 1 3
## UPPER DARBY UPPER MARLBORO
## 4 5
## UPPER SANDUSKY UTICA
## 1 2
## UVALDE VACAVILLE
## 1 4
## VALDOSTA VALENCIA
## 3 1
## VALLEJO VALLEY CITY
## 3 1
## VALPARAISO VALRICO
## 1 5
## VAN NUYS VANCLEAVE
## 7 1
## VANCOUVER VANDALIA
## 10 1
## VARNELL VEGA BAJA
## 1 2
## VENICE VERADALE
## 3 1
## VERNON HILLS VERNON ROCKVILLE
## 1 1
## VERO BEACH VERSAILLES
## 4 2
## VICTORIA VICTORVILLE
## 2 3
## VIDALIA VIDOR
## 2 1
## VIENNA VILLA PARK
## 3 1
## VILLA RICA VILLE PLATTE
## 4 1
## VINCENTOWN VINE GROVE
## 1 1
## VINELAND VINTON
## 5 1
## VIRGINIA BEACH VISALIA
## 13 4
## VISTA VOORHEES
## 5 1
## WACO WADENA
## 5 1
## WAIANAE WAIPAHU
## 2 1
## WAKE FOREST WAKEFIELD
## 1 1
## WALDORF WALKER
## 4 1
## WALL WALLA WALLA
## 1 1
## WALLINGTON WALNUT
## 1 1
## WALTERBORO WALTON
## 1 1
## WAPPINGERS FALLS WARMINSTER
## 2 1
## WARREN WARRENTON
## 9 2
## WARSAW WARTRACE
## 1 1
## WARWICK WASHINGTON
## 1 21
## WASHINGTON COURT HOUSE WATER VALLEY
## 1 1
## WATERBORO WATERBURY
## 1 4
## WATERFLOW WATERFORD
## 1 4
## WATERLOO WATERTOWN
## 1 5
## WATERVILLE WATSONVILLE
## 2 3
## WAUKAU WAUKEGAN
## 1 3
## WAVELAND WAVERLY HALL
## 1 1
## WAXAHACHIE WAXHAW
## 1 1
## WAYCROSS WAYLAND
## 1 1
## WAYNE WAYNESBORO
## 1 2
## WAYNESVILLE WAYZATA
## 1 1
## WEAVERVILLE WEBB CITY
## 2 1
## WEBSTER CITY WEIRTON
## 1 1
## WELDON WELLFLEET
## 1 1
## WENATCHEE WENTZVILLE
## 1 2
## WESLACO WESLEY CHAPEL
## 1 1
## WESSON WEST BABYLON
## 1 1
## WEST BRANCH WEST CHESTER
## 1 1
## WEST COVINA WEST GROVE
## 4 1
## WEST HATFIELD WEST HELENA
## 1 1
## WEST HEMPSTEAD WEST HOLLYWOOD
## 1 3
## WEST JORDAN WEST LAFAYETTE
## 1 1
## WEST LIBERTY WEST MEMPHIS
## 1 1
## WEST MILFORD WEST NEW YORK
## 1 1
## WEST PALM BEACH WEST PLAINS
## 14 1
## WEST POINT WEST SACRAMENTO
## 2 1
## WEST TISBURY WEST WARWICK
## 1 2
## WESTBURY WESTCHESTER
## 1 1
## WESTERLY WESTERVILLE
## 1 2
## WESTLAKE VILLAGE WESTLAND
## 1 2
## WESTMINSTER WESTMORELAND
## 3 1
## WESTVILLE WETUMKA
## 1 1
## WHEATFIELD WHEATON
## 1 2
## WHEELING WHITAKERS
## 2 1
## WHITE LAKE WHITE OAK
## 1 1
## WHITEFIELD WHITEHALL
## 1 1
## WHITESVILLE WHITT
## 1 1
## WHITTIER WHITWELL
## 3 1
## WICHITA WIGGINS
## 7 1
## WILBRAHAM WILDWOOD
## 1 2
## WILKES BARRE WILLARD
## 4 1
## WILLCOX WILLIAMSBURG
## 1 1
## WILLIAMSTOWN WILLIMANTIC
## 3 1
## WILLISTON WILMER
## 1 1
## WILMINGTON WILMOT
## 7 1
## WILSON WINCHENDON
## 1 1
## WINCHESTER WINDER
## 1 2
## WINDERMERE WINDSOR
## 1 3
## WINDSOR MILL WINFIELD
## 3 1
## WINNETKA WINONA
## 2 1
## WINSLOW WINSTON SALEM
## 2 7
## WINTER GARDEN WINTER HAVEN
## 2 1
## WINTER PARK WINTER SPRINGS
## 2 1
## WINTERS WINTERVILLE
## 1 1
## WIXOM WOBURN
## 1 2
## WOODBRIDGE WOODHAVEN
## 2 1
## WOODLAND HILLS WOODLAWN
## 1 1
## WOODRIDGE WOODSTOCK
## 1 2
## WOODWARD WOONSOCKET
## 1 1
## WORCESTER WORTH
## 4 1
## WYANDOTTE WYCKOFF
## 1 1
## WYOMING YADKINVILLE
## 3 1
## YAKIMA YAUCO
## 5 1
## YAZOO CITY YELM
## 1 1
## YONKERS YORBA LINDA
## 6 1
## YORK YORKTOWN
## 2 1
## YORKTOWN HEIGHTS YORKVILLE
## 1 1
## YOUNGSTOWN YOUNGTOWN
## 4 1
## YOUNGWOOD YPSILANTI
## 1 2
## YUBA CITY YUCCA VALLEY
## 3 2
## YUKON YUMA
## 1 3
## ZACHARY ZANESVILLE
## 1 2
## ZEBULON ZELLWOOD
## 1 1
## ZEPHYRHILLS ZION
## 2 2table(newData$State)##
## AE AK AL AR AZ CA CO CT DC DE FL GA HI IA ID IL IN KS KY LA
## 3 10 127 58 117 726 99 77 14 25 489 280 19 48 18 268 116 45 65 110
## MA MD ME MI MN MO MS MT NC ND NE NH NJ NM NV NY OH OK OR PA
## 123 158 19 197 70 120 76 10 215 12 41 23 176 35 78 218 261 56 60 231
## PR RI SC SD TN TX UT VA VI VT WA WI WV WY
## 22 26 73 9 126 555 30 131 2 4 108 13 39 7table(as.character(newData$ZipCode))##
## 10009 10019 10025 10026 10027 10029 10030 10031 10032 10033 10034 10035 10039
## 1 1 1 1 2 2 2 2 3 1 2 2 2
## 10040 10128 1013 1020 10305 10306 10312 1040 10451 10452 10453 10454 10455
## 1 1 2 2 1 2 2 1 1 1 2 2 1
## 10456 10457 10459 10460 10461 10466 10467 10469 10473 10475 10509 10512 10543
## 3 3 2 3 1 1 3 1 3 1 1 1 1
## 10549 10550 10552 10566 10591 10598 1060 1062 10701 10702 10703 10704 10705
## 1 1 1 1 1 1 1 1 2 1 1 1 1
## 1077 1088 10916 10924 1095 10956 10962 11003 1104 1109 11103 11106 1119
## 1 1 1 1 1 1 1 1 3 2 1 1 1
## 11203 11207 11208 11209 11210 11211 11212 11213 11215 11220 11221 11223 11225
## 3 1 2 1 3 2 4 1 1 1 3 1 1
## 11226 11229 11233 11235 11236 11239 11249 11354 11355 11361 11368 11373 11375
## 1 2 1 1 1 1 1 1 1 1 1 1 1
## 11413 11414 11415 11416 11418 11420 11421 11422 11434 11435 11510 11552 11553
## 1 1 1 1 1 2 1 1 2 1 1 1 1
## 11570 11590 11691 11702 11704 11710 11714 11717 11722 11735 11738 11743 11752
## 1 1 2 1 1 1 1 2 1 1 1 1 1
## 11757 11771 11776 11780 11783 11788 11950 11953 11967 1201 12020 12054 12078
## 1 1 1 2 1 2 1 1 1 3 1 1 1
## 12110 12202 12306 12477 12533 12534 12538 12546 12550 12553 12590 1267 12701
## 1 1 1 1 1 1 1 1 2 2 2 1 1
## 12831 12846 13045 13114 13135 13204 13206 13212 13302 13339 13350 13440 13452
## 1 1 1 1 1 1 1 1 1 1 1 2 1
## 13502 13603 1376 13795 14004 14006 14032 14043 14108 14150 14215 14225 14226
## 1 1 1 1 1 1 1 2 1 1 2 1 1
## 14301 14304 1438 14437 14468 14513 14514 14522 1453 14532 14605 14619 14620
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 14621 14622 14701 1475 15021 15091 1510 15101 15104 15108 15112 15126 15132
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 15143 1516 15204 15206 15209 15212 15213 15217 15218 15219 15221 15229 15235
## 1 1 1 1 1 3 2 1 1 1 1 1 1
## 15301 15311 15314 15332 1545 1560 15601 1562 15642 15673 15681 15697 15701
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 15725 15728 15747 15801 15902 15904 15905 16002 16028 1605 16053 1609 1610
## 1 1 1 1 1 1 1 1 1 1 1 1 2
## 16121 16130 16154 16335 16417 16502 16506 16509 16602 16635 16666 16673 16731
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 16803 1701 17011 17015 17020 17032 17046 17078 17104 17110 17111 17202 1731
## 1 2 1 1 1 1 1 1 1 2 1 1 2
## 17362 17403 17408 1747 17512 17519 1752 17520 17522 1756 17603 17745 17866
## 1 1 1 1 1 1 2 1 1 1 3 1 1
## 17872 17921 17963 1801 18017 18036 18040 18042 18049 18052 18056 18102 18103
## 1 1 1 2 1 1 2 1 1 1 1 4 2
## 18201 18202 1821 18210 18235 1826 18301 1832 18324 18330 18337 18343 1841
## 2 2 1 1 1 1 4 1 2 1 1 1 2
## 1843 18431 18436 18447 18466 18504 18505 18508 1851 1852 18603 18610 18612
## 2 1 1 2 1 1 1 1 1 2 1 1 2
## 18644 18657 18701 18702 18704 18706 18707 1880 18801 18901 18964 18969 18974
## 1 1 1 2 1 1 3 1 1 3 1 1 1
## 19003 19004 19013 19014 1902 19020 19026 19030 19040 19044 1905 19050 19053
## 1 1 1 1 4 1 1 1 1 2 2 2 1
## 19055 19056 1906 19061 19067 1907 19079 19081 19082 19083 19104 19111 19115
## 1 1 1 2 1 1 1 1 4 1 1 1 1
## 19120 19121 19124 19129 1913 19131 19132 19133 19134 19135 19136 19139 19141
## 3 2 4 1 1 3 1 2 4 1 2 2 5
## 19142 19143 19144 19145 19146 19147 19148 19149 19150 19151 19154 1922 19320
## 2 2 1 2 1 3 4 1 1 2 1 1 4
## 19352 19380 19390 19405 19460 19464 19468 1960 19601 19701 19702 19711 19720
## 1 1 1 1 1 1 1 1 1 2 2 2 2
## 19802 19805 19809 19901 19904 19940 19955 19956 19962 19966 19975 19977 20001
## 1 2 1 2 4 1 1 1 1 1 1 1 2
## 20002 20003 20005 20009 20010 20011 20017 20019 20109 20110 20115 20164 20165
## 1 1 1 2 1 2 1 3 1 2 1 2 1
## 20170 20175 20198 2026 2045 20601 20602 20603 20619 2062 20624 20639 20646
## 1 1 1 1 1 1 2 1 1 2 1 1 1
## 20662 20664 20678 20705 20706 20707 20708 20712 20720 20724 20731 20735 20736
## 1 2 1 2 2 1 1 1 1 1 1 3 1
## 20743 20744 20745 20746 20747 20748 20769 20770 20772 20781 20782 20785 20794
## 2 2 1 6 3 1 1 1 5 4 1 1 1
## 20817 20832 20850 20855 20866 20871 20874 20875 20876 20901 20903 20906 20912
## 1 1 2 1 1 1 1 1 1 1 1 2 1
## 21001 21012 21040 21044 21048 21060 21061 21074 21075 21090 21093 21114 21117
## 3 1 2 4 1 2 2 1 2 1 1 1 3
## 21133 21136 21144 21146 21157 2119 21201 21205 21206 21207 21209 2121 21211
## 1 2 3 1 1 2 2 2 2 5 2 1 1
## 21213 21215 21216 21217 21218 21219 21220 21221 21229 21230 21234 21244 2125
## 1 1 2 3 1 1 1 1 1 2 2 3 3
## 2126 2128 2129 2130 21401 2143 2145 2149 2150 21502 21532 21613 21625
## 2 3 1 1 1 1 2 1 1 1 1 1 1
## 21655 2169 21702 21722 21727 21740 21771 21787 21801 21804 21817 21830 2189
## 1 1 2 1 1 3 1 1 2 1 1 1 1
## 21921 22025 22031 22033 22041 22042 22172 22182 22191 22201 22206 22304 22310
## 3 1 1 1 1 1 1 1 1 1 2 1 1
## 22312 22314 22401 22407 22554 22630 22645 22701 22827 22851 22947 22973 22980
## 1 1 1 1 1 3 1 1 1 1 1 1 1
## 2301 2302 23030 23059 23061 23085 23111 23141 23150 23168 2322 23220 23222
## 1 1 1 1 1 1 1 1 2 1 1 1 1
## 23223 23224 23234 23235 2324 23294 23320 23322 23417 23421 23430 23434 23435
## 1 1 1 1 2 1 1 2 1 1 2 1 1
## 23451 23453 23454 23455 23456 2346 23462 2347 23502 23503 23509 23511 23513
## 1 2 5 1 1 2 3 1 1 3 1 1 1
## 23518 2360 23601 23606 23607 23608 23666 23669 2368 23692 23701 23703 23832
## 1 2 2 2 1 1 2 1 2 1 1 1 1
## 23837 23860 23936 23944 23970 24016 24017 24018 24019 24060 24066 24073 24095
## 1 3 1 1 1 1 1 1 1 1 1 1 2
## 24112 24179 24263 24279 24301 24333 24361 24422 24426 24437 24502 24541 24605
## 1 1 1 1 1 1 1 1 2 1 2 1 2
## 24622 24630 24701 2472 24740 24954 25143 25174 25260 25271 25286 25306 25314
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 2538 25387 25403 2541 25419 25425 25438 25521 25526 25601 25676 25703 25705
## 1 2 1 1 1 1 1 1 1 1 1 1 1
## 2575 25802 25904 25921 26003 26062 26105 26201 26205 2631 26354 26415 26426
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 26431 2646 26542 26554 26559 26570 2659 2660 2667 26833 27017 27021 27023
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 27025 27028 2703 27040 27043 27045 27046 27055 27101 27103 27104 27107 2720
## 1 1 2 1 2 1 1 1 4 1 1 1 2
## 27203 27214 27217 27239 27253 27265 27288 27292 27302 27316 27332 27349 2738
## 1 1 1 1 1 1 1 3 3 1 2 1 1
## 2740 27401 27404 27406 27407 27409 27416 2743 2745 27502 27510 27511 27513
## 1 2 1 1 2 1 1 1 1 1 1 1 2
## 27521 27525 27529 27530 27534 27537 27540 27542 27549 27560 27576 27577 27587
## 1 1 1 1 2 1 1 1 1 1 1 1 1
## 27589 27597 2760 27601 27604 27608 27609 27610 27612 27614 27615 27616 2762
## 2 1 1 1 2 1 1 3 1 1 2 1 1
## 2770 27703 27704 27705 27707 2777 2780 27801 27809 27821 27834 27851 27852
## 1 2 1 1 2 1 1 2 1 1 2 1 1
## 27858 27863 27870 27882 27886 27890 27891 27895 27909 27919 27925 27970 27980
## 1 1 2 1 1 1 1 1 1 1 1 1 1
## 28001 28002 28025 28031 28039 28043 28053 28054 28079 2808 28081 28086 28115
## 1 2 2 1 1 1 1 3 1 2 1 1 1
## 28120 28134 28135 28138 28144 28152 28160 28173 28203 28205 28208 28210 28211
## 1 1 1 1 2 1 1 1 1 1 3 2 1
## 28212 28213 28215 28216 28217 28226 28227 28262 28269 2827 28273 28304 28306
## 2 2 2 2 1 2 3 1 3 1 1 1 1
## 28307 28311 28314 28326 28334 28348 28357 28376 28377 2840 28403 28405 28412
## 1 2 1 1 1 1 1 2 1 2 1 1 1
## 28420 28429 28435 28463 28465 28469 28501 28504 28513 28540 28546 28557 28560
## 1 1 1 1 1 1 2 1 2 1 1 1 2
## 28562 28590 28602 28609 28613 28625 28644 28655 28659 28704 28711 28714 28716
## 1 1 2 1 1 2 1 2 1 2 1 1 1
## 28734 28752 28753 28768 2878 28787 28806 2889 2891 2893 2895 2903 2904
## 2 1 1 1 1 2 1 1 1 2 1 1 1
## 29047 29053 29063 29073 2908 29080 2909 2910 29102 2911 29115 29129 2914
## 1 1 1 2 1 2 1 1 1 1 1 1 2
## 29152 29153 2916 2919 2920 29212 29223 29229 29316 29341 29349 29403 29405
## 1 2 1 4 2 1 2 2 1 1 1 1 1
## 29406 29410 29412 29420 29445 29461 29477 29483 29485 29488 29511 29526 29532
## 1 1 1 1 2 1 1 2 2 1 1 1 2
## 29555 29560 29571 29577 29581 29607 29609 29615 29617 29625 29641 29650 29670
## 1 1 1 1 1 1 1 2 1 1 1 2 1
## 29681 29684 29690 29707 29730 29732 29801 29812 29841 29842 29902 29907 29910
## 2 1 1 1 1 1 1 2 1 1 1 1 1
## 29918 29926 29940 30009 30012 30013 30014 30016 30017 30019 30021 30024 30030
## 1 1 1 2 1 1 1 3 1 3 1 2 2
## 30032 30033 30034 30035 30038 30039 30041 30043 30044 30045 30047 30052 30058
## 1 1 2 2 4 3 1 1 2 2 1 1 3
## 30060 30061 30062 30064 30067 30071 30078 30080 30082 30084 30087 30088 30092
## 3 1 1 2 1 1 2 1 1 1 1 5 1
## 30093 30094 30096 30097 30101 30106 30107 30114 30115 30121 30122 30123 30127
## 4 1 3 1 1 1 1 1 1 1 1 1 2
## 30134 30135 30141 30144 30152 30165 30168 30172 30179 30180 30188 30213 30214
## 2 1 3 1 1 1 1 1 1 4 1 2 1
## 30224 30228 30230 30233 30236 30240 30241 30248 30252 30260 30263 30265 30269
## 1 5 1 1 1 1 1 2 2 1 2 3 3
## 30273 30274 30281 30286 30288 30291 30294 30296 30308 30310 30311 30313 30314
## 2 3 3 1 2 1 4 2 1 2 1 1 1
## 30315 30316 30318 30324 30331 30337 30342 30344 30345 30349 30350 30354 3038
## 4 1 1 1 5 1 2 2 1 1 1 2 1
## 30411 3042 30434 30442 30457 30467 30474 30501 30513 30519 30525 30528 30529
## 1 1 1 1 1 1 2 2 1 1 1 1 1
## 3053 30531 30534 3054 30542 30549 3060 30607 30622 3064 30642 30650 30680
## 1 1 2 1 2 2 2 1 1 1 1 1 2
## 30721 30736 30752 30753 30756 3076 3079 30809 30813 30815 30817 30830 30905
## 1 1 1 1 1 1 1 2 4 1 2 1 2
## 30906 30909 30917 31005 31021 31023 31027 31031 31032 3104 31061 31072 3109
## 3 2 1 3 2 2 1 1 1 1 2 1 1
## 31092 31107 31146 31204 31206 31217 31303 31308 31322 31323 31405 31408 31412
## 1 1 1 1 1 1 1 1 1 1 2 1 1
## 31501 31525 31542 31546 31548 31549 31566 31602 31605 31634 31701 31704 31705
## 1 1 1 1 2 1 1 1 2 1 1 1 1
## 31707 31750 31768 31775 31792 31794 31806 31826 31831 31903 31907 31909 32008
## 1 1 1 1 1 2 1 1 1 2 3 1 1
## 32011 32043 32055 32058 32060 32062 32065 32066 32073 32080 32084 32086 32114
## 1 2 1 1 1 2 2 1 2 1 1 1 1
## 32117 32141 32145 32159 32174 32176 32177 32206 32208 32209 32210 32218 32219
## 1 1 1 1 2 1 1 1 1 2 2 1 1
## 3222 32220 32221 32224 32226 32233 32244 32257 32301 32303 32304 32309 32327
## 1 3 1 1 1 1 3 1 1 1 1 1 2
## 32333 32351 3237 32401 32404 32431 32439 32459 32501 32503 32507 32514 32526
## 1 1 1 1 1 1 2 1 1 1 1 1 1
## 32533 32535 32541 32547 32563 32601 32607 32608 3261 32615 32617 3263 32686
## 1 1 1 1 1 1 2 1 1 2 1 1 1
## 32703 32708 32713 32714 32720 32725 32726 32732 32738 32752 32765 32771 32773
## 2 1 1 1 1 1 2 1 1 1 1 2 2
## 32779 32780 32784 32789 32792 32798 32808 32809 32810 32811 32818 32821 32822
## 1 2 1 1 1 1 4 1 2 3 2 1 3
## 32824 32825 32826 32828 32835 32837 32839 32904 32905 32907 32908 32909 32922
## 4 3 1 2 3 1 3 2 2 2 1 2 1
## 32935 32937 32952 32955 32956 32962 32966 32967 33009 33010 33012 33013 33014
## 1 1 1 2 1 1 1 2 2 2 4 1 1
## 33015 33016 33018 33020 33023 33024 33025 33027 33028 33029 33030 33031 33032
## 3 2 1 1 2 4 2 1 1 1 1 1 1
## 33033 33054 33055 33056 33060 33065 33068 33069 33071 33073 33076 33092 33125
## 2 5 4 1 1 2 1 2 1 1 1 1 1
## 33126 33130 33131 33133 33134 33135 33138 33140 33141 33142 33144 33145 33147
## 3 2 2 3 2 1 2 1 1 1 1 3 1
## 33154 33155 33157 33161 33165 33168 33169 33170 33172 33173 33175 33176 33177
## 1 1 1 3 3 2 2 1 1 3 3 1 1
## 33179 33181 33182 33183 33184 33185 33186 33189 33265 33269 33308 33311 33312
## 1 2 1 2 2 1 2 3 1 1 2 3 2
## 33313 33314 33322 33324 33331 33351 33401 33403 33404 33407 33409 33411 33413
## 5 1 1 3 1 1 2 1 1 1 2 3 1
## 33414 33415 33417 33418 33431 33433 33435 33436 33437 33442 33444 33445 33455
## 1 1 1 2 1 2 1 1 1 1 2 1 1
## 33458 33460 33462 33463 33467 33472 33477 33487 33493 33498 33510 33511 33540
## 1 1 1 1 1 1 1 1 1 4 1 1 1
## 33542 33543 33558 33559 33563 33565 33566 33570 33572 33576 33578 33584 33594
## 1 1 3 1 1 1 1 2 1 1 1 1 4
## 33596 33606 33607 33610 33611 33614 33616 33619 33624 33625 33626 33647 33682
## 1 1 1 1 1 1 1 2 1 1 1 1 1
## 33701 33704 33705 33712 33714 33764 33767 33770 33771 33776 33781 33782 33801
## 1 1 1 3 1 1 1 1 2 1 2 1 3
## 33802 33805 33809 33810 33815 33823 33825 33834 33837 33838 33841 33844 33850
## 1 1 2 1 1 1 1 1 1 1 2 1 1
## 33852 33868 33882 33901 33903 33904 33905 33909 33912 33913 33914 33916 33928
## 1 1 1 2 1 1 1 1 1 1 1 2 1
## 33952 33954 33990 33991 34104 34113 34114 34116 34205 34208 34210 34221 34222
## 2 1 1 3 1 1 1 1 2 1 1 1 1
## 34234 34235 34238 34239 34242 34281 34285 34287 34288 34291 34292 34432 34465
## 2 1 1 1 1 1 1 1 1 1 1 1 1
## 3447 34470 34474 34475 34482 34488 34607 34608 34609 34610 34639 34655 34667
## 1 1 3 1 2 1 1 1 1 1 1 2 1
## 34677 34685 34691 34711 34731 34741 34743 34744 34746 34748 34749 34769 34772
## 1 1 1 1 1 2 3 1 1 1 1 1 1
## 34785 34786 34787 34945 34952 34972 34982 34983 34986 34997 35007 35020 35046
## 1 1 2 1 2 1 1 1 1 1 1 1 1
## 35049 35051 35055 35057 35060 35064 35083 35094 35115 35116 35117 35124 35150
## 1 1 1 2 1 2 1 1 2 1 1 1 2
## 35202 35205 35206 35207 35208 35211 35212 35214 35215 35217 35218 35228 35234
## 1 1 1 1 1 3 1 2 2 2 1 1 1
## 35235 35242 35404 35405 35453 35463 35501 35503 35555 35570 35586 35594 35601
## 1 1 1 1 1 1 1 1 2 1 1 1 1
## 3561 35611 35622 35640 35648 35661 35670 35672 3570 35758 35802 35810 35811
## 1 2 1 1 1 1 1 1 1 3 1 4 2
## 35903 35950 35954 3598 36015 3603 36040 36066 36067 36079 36108 36110 36111
## 1 1 1 1 1 1 1 1 2 1 1 1 3
## 36116 36117 36203 36206 36253 36301 36303 36310 36311 36330 36360 36375 36426
## 2 2 2 1 1 1 1 1 1 1 1 1 1
## 36442 36467 36474 36502 36526 36527 36582 36587 36606 36608 36609 36613 36617
## 1 1 1 2 2 1 1 1 1 1 2 1 2
## 36618 36688 36695 36740 36750 36756 36782 36862 36870 36871 37013 37015 37030
## 1 1 1 1 1 1 1 1 1 1 2 1 1
## 37033 37040 37042 37043 37048 37049 37059 37066 37075 37076 37086 37087 37115
## 1 2 1 1 1 2 1 2 1 2 4 2 2
## 37122 37129 37153 37167 37183 37184 37186 37191 37204 37207 37208 37209 37211
## 3 1 1 1 1 1 1 1 1 1 1 1 4
## 37214 37218 37221 37311 37312 37323 37341 37343 37355 37363 37379 37385 37397
## 2 1 2 2 1 2 1 1 2 1 1 1 1
## 37405 37415 37421 37617 37620 37642 37643 37650 37714 37716 37737 37745 3777
## 1 1 1 1 1 2 1 1 1 2 1 1 1
## 37777 37811 37831 37861 37864 37874 37876 37877 37917 37930 37931 38002 38016
## 1 1 1 1 1 1 1 1 1 1 1 1 2
## 38018 38024 38053 38057 38069 38108 38109 38111 38112 38115 38118 38120 38125
## 1 1 1 1 1 1 3 1 1 2 1 1 1
## 38127 38128 38135 38139 38183 38253 38305 38340 3842 38478 3849 38506 38571
## 1 2 3 1 1 1 4 2 1 1 1 1 1
## 38579 38583 38611 38637 38654 38655 38668 38671 38672 38701 38801 38821 38834
## 1 1 1 2 1 1 1 2 2 1 1 1 2
## 38849 38865 38870 38930 38965 3901 39041 39044 39045 39046 39051 39056 39059
## 1 1 1 2 1 1 1 1 1 2 1 2 2
## 3908 39110 39114 39120 39145 39146 39157 39191 39194 39202 39206 39208 39209
## 1 1 2 2 1 1 1 1 1 1 2 2 1
## 39212 39213 39272 39301 39305 39328 39335 39348 39350 39443 39455 39466 39474
## 3 1 2 1 1 1 1 1 1 1 1 1 1
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## 43103 43110 43123 43125 43147 43160 43201 43203 43204 43206 43207 43211 43219
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## 43223 43224 43228 43229 43231 43232 43235 43240 43302 43334 43351 43357 43402
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## 43412 43440 43452 4346 43537 43551 43605 43606 43614 43616 43701 43758 43762
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## 48439 48442 48458 48506 48507 48601 48661 48757 48813 48818 48823 48827 48831
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## 48854 48858 48860 48867 48876 48906 48911 48917 49007 49009 4901 49010 49014
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## 49015 49019 49022 49024 49036 49047 49064 49082 49093 49117 4915 49201 49252
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## 50701 51031 51442 51501 51534 51632 52144 52240 52241 52254 52317 52328 52402
## 1 1 1 2 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 2 1 1 1
## 55123 55124 55125 55301 55303 55304 55306 55318 55337 55343 55346 55364 55374
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## 55391 55404 55405 55407 55411 55419 55421 55423 55432 55433 55435 55438 55446
## 1 2 1 1 1 1 2 1 1 2 1 1 1
## 55901 55912 55987 56001 56003 56069 56114 56277 56303 56308 56362 56363 56474
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## 59105 59255 59330 59457 59601 59701 59860 60002 60007 60013 60014 60016 6002
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## 60031 60033 60040 60056 60061 60064 60068 60070 60073 60074 60077 60085 60087
## 1 1 1 1 1 1 1 1 4 1 1 1 2
## 60098 60099 6010 60103 60104 60106 60108 60115 60120 60121 60123 60134 60143
## 1 2 1 1 2 3 2 1 1 1 3 1 2
## 60148 60152 60154 60160 60164 60173 60174 60175 60181 60187 60189 60193 6040
## 1 1 1 1 1 1 1 1 1 1 1 1 3
## 60402 60406 60409 60411 60415 60419 60425 60426 60428 60429 60430 60432 60435
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## 60439 60440 60441 60442 60446 60450 60452 60453 60456 60458 60461 60466 60471
## 1 4 1 1 3 2 1 1 1 1 1 3 2
## 60473 60478 60482 60514 60515 60516 60517 60525 6053 60532 60542 60543 60544
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## 60545 60560 60564 60565 60586 60606 60608 60609 60611 60612 60613 60614 60615
## 1 1 1 1 2 1 1 1 1 2 1 1 2
## 60616 60617 60618 60619 6062 60620 60621 60623 60624 60625 60628 60629 60630
## 1 3 2 5 2 2 2 3 3 2 4 2 3
## 60631 60633 60636 60637 60638 60639 60643 60644 60647 60649 60652 60653 60656
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## 60657 60659 6066 6071 6074 60804 60936 6095 60950 61021 61032 6105 6106
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## 1 1 1 1 2 2 1 2 1 1 1 1 1
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## 1 2 1 1 1 1 1 4 1 1 1 1 1
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## 1 1 1 2 2 1 1 1 1 1 3 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1 2
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## 1 1 1 1 1 1 1 1 3 2 1 1 1
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## 2 1 1 2 1 1 1 4 2 3 3 3 1
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## 2 3 1 1 3 3 1 1 1 1 2 1 2
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## 1 3 3 1 1 2 1 2 1 1 1 1 1
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## 1 1 3 1 1 1 1 1 1 1 1 1 3
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## 1 1 1 1 2 1 2 4 1 1 1 2 2
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## 2 2 2 1 3 3 1 1 1 4 1 1 2
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## 1 2 1 3 2 1 1 1 2 1 2 1 1
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## 1 2 2 2 1 1 1 1 2 1 1 1 1
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## 1 1 1 1 3 1 3 1 1 1 1 2 1
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## 1 1 4 2 1 1 2 2 2 1 2 1 1
## 91730 91732 91733 91744 91746 91748 91752 91755 91761 91762 91764 91765 91766
## 1 2 1 1 4 1 3 1 3 1 1 1 2
## 91767 91768 91770 91784 91786 91788 91790 91791 91792 91910 91911 91915 91932
## 1 1 1 1 2 1 1 2 1 2 2 1 2
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## 1 3 1 1 1 1 1 1 1 1 1 1 2
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## 1 3 1 1 1 2 2 1 2 3 1 2 4
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## 1 1 1 1 1 1 2 2 1 1 1 1 2
## 92234 92235 92236 92240 92243 92250 92251 92260 92263 92264 92270 92284 92311
## 1 1 1 3 2 1 1 2 1 2 1 2 1
## 92312 92320 92321 92334 92335 92336 92337 92344 92345 92346 92354 92359 92374
## 1 1 1 1 1 1 2 2 1 1 1 2 2
## 92376 92377 92392 92394 92395 92404 92405 92406 92407 92411 92501 92503 92504
## 2 3 1 1 1 2 1 1 1 1 1 3 4
## 92505 92506 92507 92508 92509 92530 92532 92543 92544 92545 92551 92553 92557
## 1 1 2 1 2 3 1 1 1 1 3 8 2
## 92562 92563 92570 92584 92585 92587 92591 92592 92596 926 92612 92614 92615
## 1 1 3 1 1 1 1 1 1 2 1 2 1
## 92620 92625 92627 92629 92630 92647 92651 92656 92658 92662 92672 92673 92683
## 3 1 1 2 1 1 1 3 1 1 2 1 1
## 92688 92691 92692 927 92703 92780 92801 92802 92804 92807 92821 92833 92843
## 2 1 1 1 2 2 3 2 2 1 1 1 2
## 92845 92860 92880 92882 92886 93013 93023 93030 93033 93036 93065 93103 93117
## 1 1 3 2 1 1 1 3 3 1 2 1 2
## 93204 93223 93225 93230 93240 93245 93247 93274 93277 93291 93292 93301 93304
## 1 1 1 2 1 3 1 2 1 1 2 1 1
## 93306 93307 93308 93311 93312 93313 93314 93401 93402 93436 93449 93458 93505
## 3 1 2 1 2 1 1 2 1 1 1 1 1
## 93534 93535 93536 93545 93550 93551 93552 93560 93614 93620 93625 93637 9366
## 1 1 4 1 2 6 1 1 1 1 1 1 1
## 93702 93703 93705 93706 93711 93720 93722 93726 93727 93728 93747 93906 93907
## 1 2 2 2 2 3 2 1 1 1 1 1 1
## 93912 93920 93927 93930 93933 93940 93955 94015 94044 94085 94087 94103 94109
## 1 1 1 1 1 1 1 1 1 1 1 2 1
## 94110 94112 94114 94122 94129 94131 94134 94188 94303 94501 94505 94518 94520
## 2 1 1 1 1 1 4 1 2 2 2 1 1
## 94531 94533 94534 94535 94536 94538 94544 94545 94558 94559 94560 94561 94564
## 1 5 1 1 2 1 1 1 1 1 1 3 2
## 94565 94568 94571 94578 94582 94585 94587 94590 94591 94601 94602 94603 94604
## 2 1 1 2 1 1 2 2 1 1 1 2 1
## 94610 94803 94805 94928 94945 94954 95006 95018 95020 95023 95030 95032 95035
## 1 1 1 1 2 2 1 1 2 1 1 1 2
## 95050 95070 95076 95112 95116 95118 95121 95122 95123 95125 95126 95127 95128
## 1 1 3 3 1 1 1 2 2 2 1 3 2
## 95148 95201 95204 95205 95206 95207 95209 95210 95242 953 95301 95307 95319
## 2 1 2 1 3 1 1 2 2 1 1 2 1
## 95336 95337 95340 95341 95350 95354 95355 95357 95358 95376 95380 95382 95401
## 2 2 2 1 1 1 3 1 2 3 1 1 2
## 95403 95404 95406 95428 95448 95452 95546 95605 95610 95620 95621 95624 95648
## 1 1 1 1 1 1 1 1 1 2 2 2 2
## 95660 95661 95667 95677 95678 95682 95687 95688 95694 95713 95757 95758 95765
## 1 1 1 1 2 2 3 1 1 1 1 1 1
## 95815 95816 95820 95821 95822 95823 95827 95828 95829 95831 95833 95834 95842
## 1 1 4 1 1 3 1 3 2 1 2 1 3
## 95843 95926 95953 95961 95966 95971 95991 96001 96003 96007 96055 96064 961
## 2 1 1 1 3 1 3 2 3 3 1 1 1
## 96158 96706 96707 96713 96720 96731 96733 96779 96782 96789 96792 96797 96817
## 1 2 3 1 1 1 1 1 1 2 2 1 1
## 96819 96826 97008 97035 97062 97086 97124 97128 97132 97135 97203 97206 97209
## 1 1 1 1 1 1 1 1 3 1 1 1 1
## 97211 97213 97216 97222 97223 97229 97233 97239 97266 97292 97301 97304 97305
## 1 1 1 1 1 1 1 1 2 1 5 1 2
## 97317 97322 97338 97374 97378 97401 97404 97420 97448 97449 97459 97463 97467
## 1 1 1 1 1 1 1 1 1 1 1 1 1
## 97470 97479 97501 97502 97523 97524 97526 97528 97601 97623 97701 97702 97760
## 1 1 1 1 1 2 1 1 1 1 1 1 1
## 97846 979 98003 98006 98012 98023 98032 98036 98042 98052 98058 98059 98065
## 1 1 3 1 1 2 1 2 1 1 1 1 1
## 98092 98109 98118 98133 98148 98155 98168 98178 98188 98198 98201 98203 98208
## 2 1 1 1 1 1 1 3 1 1 1 1 2
## 98223 98228 98251 98264 98270 98272 98290 983 98332 98337 98338 98362 98363
## 1 1 1 1 1 1 1 1 1 1 2 1 1
## 98366 98368 98370 98375 98382 98387 98390 984 98404 98422 98445 98467 98499
## 1 1 1 2 2 3 1 1 1 1 1 1 1
## 98503 98512 98531 9855 98550 98558 98597 98626 98632 98660 98661 98662 98665
## 1 1 2 1 2 1 1 1 1 1 1 1 1
## 98682 98683 98684 98686 98801 98837 98901 98902 98908 98922 98934 99004 99013
## 2 2 1 1 1 1 1 2 2 1 1 1 1
## 99016 99021 99037 99134 99169 99201 99203 99206 99211 99212 99301 99337 99350
## 1 1 1 1 1 1 1 2 1 1 1 1 1
## 99354 99362 99501 99508 99518 99567 99577 99603 99613 99683 99775
## 1 1 1 2 1 1 1 1 1 1 1#Creating a variable called Bad
newData$Bad = ifelse((newData$DaysDeliq >= 60 | (newData$ExtStatus != "C" & newData$ExtStatus != " ")),1,0)
data.frame(newData$Bad, newData$ExtStatus, newData$DaysDeliq)sum(newData$Bad)## [1] 2938# Calculating Badrate
BadRate = sum(newData$Bad)/nrow(newData)
paste("The bad rate is : ", round(BadRate*100,2) ,"Percent")## [1] "The bad rate is : 48.66 Percent"newData$ChargeOffDollars = ifelse((newData$Bad ==1&newData$EndingBalance>0), newData$EndingBalance, 0)
summary(newData$ChargeOffDollars)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 0.0 0.0 0.0 188.9 428.3 1681.4sum(newData$ChargeOffDollars)## [1] 1140717diagnose(newData)convert variables
newData$City <- as.factor(newData$City)
newData$State <- as.factor(newData$State)
newData$ZipCode <- as.factor(newData$ZipCode)
newData$Bad <- as.factor(newData$Bad)
newData$ExtStatus <- as.factor(newData$ExtStatus)
newData$IntStatus <- as.factor(newData$IntStatus)library(sjPlot)
view_df(newData, show.frq = T, show.prc = T, show.na = T, CSS = list(css.table = "border: 2px solid;",
css.tdata = "border: 1px solid;",
css.arc = "color:blue;"))| ID | Name | Label | missings | Values | Value Labels | Freq. | % |
|---|---|---|---|---|---|---|---|
| 1 | ID | 0 (0.00%) | range: 24508841-24856424 | ||||
| 2 | OpenDate | 0 (0.00%) | |||||
| 3 | DatePrevStmt | 1 (0.02%) | |||||
| 4 | StatementDt | 0 (0.00%) | |||||
| 5 | MOB | 0 (0.00%) | range: 4-17 | ||||
| 6 | ExtStatus | 0 (0.00%) |
C E F I U Z |
2923 372 14 185 30 1 2513 |
48.41 6.16 0.23 3.06 0.50 0.02 41.62 |
||
| 7 | IntStatus | 0 (0.00%) |
D N O X |
2295 179 33 417 3114 |
38.01 2.96 0.55 6.91 51.57 |
||
| 8 | DaysDeliq | 0 (0.00%) | range: 0-390 | ||||
| 9 | ActualMinPay | 0 (0.00%) | range: 0.0-1237.0 | ||||
| 10 | OverlimitAmount | 0 (0.00%) | range: 0.0-1100.8 | ||||
| 11 | DisplayMinPay | 0 (0.00%) | range: 0.0-1681.4 | ||||
| 12 | OpeningBalance | 0 (0.00%) | range: -326.9-1681.4 | ||||
| 13 | BillLateCharge | 0 (0.00%) | range: 0.0-35.0 | ||||
| 14 | EndingBalance | 0 (0.00%) | range: -224.1-1681.4 | ||||
| 15 | CreditLimit | 0 (0.00%) | range: 0-900 | ||||
| 16 | TotalNetPayments | 0 (0.00%) | range: -455.9-1450.0 | ||||
| 17 | TotalNetPurchaseAndCash | 0 (0.00%) | range: -256.8-1675.6 | ||||
| 18 | TotalFeesBilled | 0 (0.00%) | range: -294.1-129.3 | ||||
| 19 | Concessions | 0 (0.00%) | range: -607.9-326.9 | ||||
| 20 | QuarterlyCreditScore | 0 (0.00%) | range: 0-797 | ||||
| 21 | Bscore | 0 (0.00%) | range: 13-711 | ||||
| 22 | City | 0 (0.00%) |
ABBEVILLE ABERDEEN ABILENE ABSECON ACTON ACUSHNET ACWORTH ADDISON AGOURA HILLS AIKEN AKRON ALABASTER ALACHUA ALAMEDA ALAMO <… truncated> |
1 3 1 2 1 1 1 1 1 1 12 1 2 2 2 |
0.02 0.05 0.02 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.20 0.02 0.03 0.03 0.03 |
||
| 23 | State | 0 (0.00%) |
AE AK AL AR AZ CA CO CT DC DE FL GA HI IA ID <… truncated> |
3 10 127 58 117 726 99 77 14 25 489 280 19 48 18 |
0.05 0.17 2.10 0.96 1.94 12.02 1.64 1.28 0.23 0.41 8.10 4.64 0.31 0.79 0.30 |
||
| 24 | ZipCode | 0 (0.00%) |
612 646 680 693 698 716 725 731 771 794 795 841 851 917 926 <… truncated> |
1 1 1 2 1 1 2 1 1 1 1 1 1 1 2 |
0.02 0.02 0.02 0.03 0.02 0.02 0.03 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.03 |
||
| 25 | Bad | 0 (0.00%) |
0 1 |
3100 2938 |
51.34 48.66 |
||
| 26 | ChargeOffDollars | 0 (0.00%) | range: 0.0-1681.4 | ||||
library(flextable)
library(dlookr)
describe(newData) %>% flextable()described_variables | n | na | mean | sd | se_mean | IQR | skewness | kurtosis | p00 | p01 | p05 | p10 | p20 | p25 | p30 | p40 | p50 | p60 | p70 | p75 | p80 | p90 | p95 | p99 | p100 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ID | 6,038 | 0 | 24,806,362.115270 | 48,912.642255 | 629.46932286 | 39,551.0000 | -2.6421410 | 9.14345788 | 24,508,841.00 | 24,588,185.2400 | 24,712,968.250 | 24,758,614.800 | 24,786,900.80 | 24,796,902.2500 | 24,801,113.700 | 24,809,948.400 | 24,816,651.500 | 24,825,283.200 | 24,832,351.800 | 24,836,453.2500 | 24,840,288.600 | 24,848,183.200 | 24,852,184.6000 | 24,855,854.4100 | 24,856,424.00 |
MOB | 6,038 | 0 | 13.689798 | 4.467392 | 0.05749202 | 5.0000 | -1.0082790 | -0.50172513 | 4.00 | 4.0000 | 5.000 | 6.000 | 9.00 | 12.0000 | 12.000 | 14.000 | 17.000 | 17.000 | 17.000 | 17.0000 | 17.000 | 17.000 | 17.0000 | 17.0000 | 17.00 |
DaysDeliq | 6,038 | 0 | 90.606989 | 105.740128 | 1.36079680 | 151.0000 | 0.8411509 | -0.44360552 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.00 | 0.0000 | 0.000 | 0.000 | 30.000 | 121.000 | 151.000 | 151.0000 | 180.000 | 240.000 | 300.0000 | 360.0000 | 390.00 |
ActualMinPay | 6,038 | 0 | 147.379631 | 154.414317 | 1.98719741 | 206.0000 | 1.4972256 | 2.79865091 | 0.00 | 0.0000 | 0.000 | 17.697 | 30.00 | 30.0000 | 30.000 | 46.000 | 60.000 | 162.000 | 191.000 | 236.0000 | 275.000 | 353.000 | 428.1500 | 659.0000 | 1,237.00 |
OverlimitAmount | 6,038 | 0 | 62.113968 | 102.458327 | 1.31856246 | 124.9025 | 2.6423942 | 12.31236208 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.000 | 14.216 | 85.593 | 124.9025 | 142.126 | 197.706 | 247.0705 | 381.6619 | 1,100.77 |
DisplayMinPay | 6,038 | 0 | 170.907965 | 229.748715 | 2.95669507 | 316.0150 | 1.5611097 | 2.20087386 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.00 | 25.0000 | 30.000 | 30.000 | 42.115 | 63.990 | 237.941 | 341.0150 | 397.200 | 466.286 | 665.4750 | 903.3405 | 1,681.36 |
OpeningBalance | 6,038 | 0 | 443.697342 | 253.098381 | 3.25718790 | 277.2625 | 0.4282230 | 0.06033486 | -326.90 | -10.4815 | 12.127 | 114.001 | 261.95 | 287.1225 | 312.728 | 384.998 | 429.285 | 447.720 | 504.518 | 564.3850 | 666.846 | 855.029 | 922.2325 | 1,028.3335 | 1,681.36 |
BillLateCharge | 6,038 | 0 | 4.083157 | 10.662983 | 0.13722466 | 0.0000 | 2.2815712 | 3.32816100 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.0000 | 0.000 | 30.000 | 35.0000 | 35.0000 | 35.00 |
EndingBalance | 6,038 | 0 | 352.476830 | 284.714018 | 3.66405763 | 477.1525 | 0.4909044 | -0.31777913 | -224.06 | 0.0000 | 0.000 | 0.000 | 0.00 | 28.6800 | 179.959 | 284.570 | 345.245 | 421.462 | 460.195 | 505.8325 | 577.904 | 745.900 | 900.8665 | 1,032.4289 | 1,681.36 |
CreditLimit | 6,038 | 0 | 423.277575 | 183.482606 | 2.36128466 | 400.0000 | 0.7299535 | -0.88462483 | 0.00 | 0.0000 | 300.000 | 300.000 | 300.00 | 300.0000 | 300.000 | 300.000 | 300.000 | 400.000 | 400.000 | 700.0000 | 700.000 | 700.000 | 700.0000 | 700.0000 | 900.00 |
TotalNetPayments | 6,038 | 0 | 47.021184 | 101.637676 | 1.30800129 | 50.0000 | 4.2511735 | 27.33948553 | -455.87 | 0.0000 | 0.000 | 0.000 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.000 | 30.000 | 43.171 | 50.0000 | 60.000 | 121.814 | 250.0000 | 484.3350 | 1,450.00 |
TotalNetPurchaseAndCash | 6,038 | 0 | 23.461436 | 71.884742 | 0.92510315 | 0.9725 | 6.2266627 | 73.24711935 | -256.75 | 0.0000 | 0.000 | 0.000 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.9725 | 19.598 | 70.034 | 149.9830 | 347.9058 | 1,675.57 |
TotalFeesBilled | 6,038 | 0 | 14.499485 | 22.469281 | 0.28916293 | 22.9675 | -1.1687811 | 20.98297047 | -294.14 | -6.2500 | 0.000 | 0.000 | 0.00 | 0.0000 | 0.000 | 0.000 | 6.250 | 14.500 | 18.660 | 22.9675 | 33.744 | 45.446 | 54.5350 | 74.5867 | 129.28 |
Concessions | 6,038 | 0 | -2.282700 | 26.630932 | 0.34272028 | 0.0000 | -10.3808680 | 182.85909231 | -607.87 | -99.8150 | 0.000 | 0.000 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | 0.0000 | 0.000 | 0.000 | 0.0000 | 3.8741 | 326.90 |
QuarterlyCreditScore | 6,038 | 0 | 490.519709 | 198.206713 | 2.55077296 | 133.0000 | -1.7341415 | 1.86605487 | 0.00 | 0.0000 | 0.000 | 0.000 | 462.00 | 479.0000 | 490.000 | 515.000 | 538.000 | 568.000 | 598.000 | 612.0000 | 626.000 | 655.000 | 675.0000 | 709.0000 | 797.00 |
Bscore | 6,038 | 0 | 465.820139 | 200.130367 | 2.57552896 | 407.0000 | -0.1857054 | -1.88569251 | 13.00 | 217.0000 | 231.000 | 234.000 | 244.00 | 246.0000 | 252.000 | 264.000 | 596.000 | 627.000 | 647.000 | 653.0000 | 659.000 | 674.000 | 685.0000 | 699.0000 | 711.00 |
ChargeOffDollars | 6,038 | 0 | 188.922965 | 298.128637 | 3.83669380 | 428.3175 | 1.4018452 | 0.97936185 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.00 | 0.0000 | 0.000 | 0.000 | 0.000 | 0.000 | 380.643 | 428.3175 | 449.368 | 564.073 | 900.0765 | 1,032.4289 | 1,681.36 |
select important variables
df2 <- newData %>% dplyr::select(c(5:26)) # select all variables with the exception of the dates# select minimal variables for plotting
df3 <- df2 %>% dplyr::select(c(1:4), 21)
df4 <- df2 %>% dplyr::select(c(5:8), 21)
df5 <- df2 %>% dplyr::select(c(9:12), 21)
df6 <- df2 %>% dplyr::select(c(13:17), 22, 21)library(GGally)## Loading required package: ggplot2## Registered S3 method overwritten by 'GGally':
## method from
## +.gg ggplot2df3 %>%
ggpairs(aes(col = Bad, fill = Bad, alpha = 0.6),
upper = list(combo = 'box'),
diag = list(discrete = wrap('barDiag', position = 'fill')),
lower = "blank") +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
df4 %>%
ggpairs(aes(col = Bad, fill = Bad, alpha = 0.6),
upper = list(combo = 'box'),
diag = list(discrete = wrap('barDiag', position = 'fill')),
lower = "blank") +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
df5 %>%
ggpairs(aes(col = Bad, fill = Bad, alpha = 0.6),
upper = list(combo = 'box'),
diag = list(discrete = wrap('barDiag', position = 'fill')),
lower = "blank") +
theme(axis.text.x = element_text(angle = 90, hjust = 1))
df6 %>%
ggpairs(aes(col = Bad, fill = Bad, alpha = 0.6),
upper = list(combo = 'box'),
diag = list(discrete = wrap('barDiag', position = 'fill')),
lower = "blank") +
theme(axis.text.x = element_text(angle = 90, hjust = 1))## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
## Warning in cor(x, y): the standard deviation is zero
diagnose_outlier(newData)plot_outlier(newData)
