DATA SUBMISSION 3

library(tidycensus)
library(tidyverse)

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## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.3     ✔ tibble    3.3.1
## ✔ lubridate 1.9.5     ✔ tidyr     1.3.2
## ✔ purrr     1.2.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(readxl)

district_data <- read_excel("district.xls")

names(district_data)

##   [1] "DISTNAME"      "DISTRICT"      "DZCNTYNM"      "REGION"       
##   [5] "DZRATING"      "DZCAMPUS"      "DPETALLC"      "DPETBLAP"     
##   [9] "DPETHISP"      "DPETWHIP"      "DPETINDP"      "DPETASIP"     
##  [13] "DPETPCIP"      "DPETTWOP"      "DPETECOP"      "DPETLEPP"     
##  [17] "DPETSPEP"      "DPETBILP"      "DPETVOCP"      "DPETGIFP"     
##  [21] "DA0AT21R"      "DA0912DR21R"   "DAGC4X21R"     "DAGC5X20R"    
##  [25] "DAGC6X19R"     "DA0GR21N"      "DA0GS21N"      "DDA00A001S22R"
##  [29] "DDA00A001222R" "DDA00A001322R" "DDA00AR01S22R" "DDA00AR01222R"
##  [33] "DDA00AR01322R" "DDA00AM01S22R" "DDA00AM01222R" "DDA00AM01322R"
##  [37] "DDA00AC01S22R" "DDA00AC01222R" "DDA00AC01322R" "DDA00AS01S22R"
##  [41] "DDA00AS01222R" "DDA00AS01322R" "DDB00A001S22R" "DDB00A001222R"
##  [45] "DDB00A001322R" "DDH00A001S22R" "DDH00A001222R" "DDH00A001322R"
##  [49] "DDW00A001S22R" "DDW00A001222R" "DDW00A001322R" "DDI00A001S22R"
##  [53] "DDI00A001222R" "DDI00A001322R" "DD300A001S22R" "DD300A001222R"
##  [57] "DD300A001322R" "DD400A001S22R" "DD400A001222R" "DD400A001322R"
##  [61] "DD200A001S22R" "DD200A001222R" "DD200A001322R" "DDE00A001S22R"
##  [65] "DDE00A001222R" "DDE00A001322R" "DA0CT21R"      "DA0CC21R"     
##  [69] "DA0CSA21R"     "DA0CAA21R"     "DPSATOFC"      "DPSTTOFC"     
##  [73] "DPSCTOFP"      "DPSSTOFP"      "DPSUTOFP"      "DPSTTOFP"     
##  [77] "DPSETOFP"      "DPSXTOFP"      "DPSCTOSA"      "DPSSTOSA"     
##  [81] "DPSUTOSA"      "DPSTTOSA"      "DPSAMIFP"      "DPSAKIDR"     
##  [85] "DPSTKIDR"      "DPST05FP"      "DPSTEXPA"      "DPSTADFP"     
##  [89] "DPSTURNR"      "DPSTBLFP"      "DPSTHIFP"      "DPSTWHFP"     
##  [93] "DPSTINFP"      "DPSTASFP"      "DPSTPIFP"      "DPSTTWFP"     
##  [97] "DPSTREFP"      "DPSTSPFP"      "DPSTCOFP"      "DPSTBIFP"     
## [101] "DPSTVOFP"      "DPSTGOFP"      "DPFVTOTK"      "DPFTADPR"     
## [105] "DPFRAALLT"     "DPFRAALLK"     "DPFRAOPRT"     "DPFRASTAP"    
## [109] "DZRVLOCP"      "DPFRAFEDP"     "DPFRAORVT"     "DPFUNAB1T"    
## [113] "DPFUNA4T"      "DPFEAALLT"     "DPFEAOPFT"     "DPFEAOPFK"    
## [117] "DPFEAINSP"     "DZEXADMP"      "DZEXADSP"      "DZEXPLAP"     
## [121] "DZEXOTHP"      "DPFEAINST"     "DPFEAINSK"     "DPFPAREGP"    
## [125] "DPFPASPEP"     "DPFPACOMP"     "DPFPABILP"     "DPFPAVOCP"    
## [129] "DPFPAGIFP"     "DPFPAATHP"     "DPFPAHSAP"     "DPFPREKP"     
## [133] "DPFPAOTHP"     "DISTSIZE"      "COMMTYPE"      "PROPWLTH"     
## [137] "TAXRATE"

summary(district_data$DPETALLC)

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
##      4.0    337.5    884.0   4476.3   2746.0 193727.0

hist(district_data$DPETALLC)

plot(district_data$DPETALLC, district_data$DPETASIP)

cor(district_data$DPETALLC, district_data$DPETASIP)

## [1] 0.2377282