Data
Frank ramirez
2026-09-23
options(scipen = 999)
#Oh my good god it worked. I tried several iterations of this and it just was not working oh hell yes.
library(readr)
# This line creates the object that R is complaining is missing:
X2020Election <- read_csv("2020Election.csv")## Rows: 52 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (6): State, Source, Official/Unofficial, VEP Turnout Rate, % Non-citizen...
## num (9): Total Ballots Counted (Estimate), Vote for Highest Office (Presiden...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.2.1 ✔ purrr 1.2.2
## ✔ forcats 1.0.1 ✔ stringr 1.6.0
## ✔ ggplot2 4.0.3 ✔ tibble 3.3.1
## ✔ lubridate 1.9.5 ✔ tidyr 1.3.2
## ── 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 errorsread_csv("2020Election.csv")## Rows: 52 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (6): State, Source, Official/Unofficial, VEP Turnout Rate, % Non-citizen...
## num (9): Total Ballots Counted (Estimate), Vote for Highest Office (Presiden...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.## # A tibble: 52 × 15
## State Source `Official/Unofficial` Total Ballots Counte…¹
## <chr> <chr> <chr> <dbl>
## 1 United States <NA> <NA> 158835004
## 2 Alabama https://ww… Unofficial 2306587
## 3 Alaska https://ww… <NA> 367000
## 4 Arizona https://re… <NA> 3400000
## 5 Arkansas https://re… Unofficial 1212030
## 6 California https://el… Unofficial 16800000
## 7 Colorado https://re… <NA> 3295000
## 8 Connecticut <NA> <NA> 1850000
## 9 Delaware https://el… Unofficial 507805
## 10 District of Columbia https://el… <NA> 350000
## # ℹ 42 more rows
## # ℹ abbreviated name: ¹​`Total Ballots Counted (Estimate)`
## # ℹ 11 more variables: `Vote for Highest Office (President)` <dbl>,
## # `VEP Turnout Rate` <chr>, `Voting-Eligible Population (VEP)` <dbl>,
## # `Voting-Age Population (VAP)` <dbl>, `% Non-citizen` <chr>, Prison <dbl>,
## # Probation <dbl>, Parole <dbl>, `Total Ineligible Felon` <dbl>,
## # `Overseas Eligible` <dbl>, `State Abv` <chr>summary(data$x)
hist(data$x) - for continuous variables
plot(data\(x,data\)y) - to compare variables
(ggplot is fine if you are comfortable with it)
- cor(data\(x,data\)y) - to see a correlation between two variables
data1<-(X2020Election[-1,])
summary(data1)## State Source Official/Unofficial
## Length :51 Length :51 Length :51
## N.unique :51 N.unique :40 N.unique : 2
## N.blank : 0 N.blank : 0 N.blank : 0
## Min.nchar: 4 Min.nchar:23 Min.nchar: 8
## Max.nchar:20 Max.nchar:99 Max.nchar:10
## NAs :11 NAs :26
##
## Total Ballots Counted (Estimate) Vote for Highest Office (President)
## Min. : 278503 Min. : 276765
## 1st Qu.: 867500 1st Qu.: 753784
## Median : 2155000 Median : 1447106
## Mean : 3114412 Mean : 2178698
## 3rd Qu.: 3912500 3rd Qu.: 2638094
## Max. :16800000 Max. :11231799
## NAs :27
## VEP Turnout Rate Voting-Eligible Population (VEP) Voting-Age Population (VAP)
## Length :51 Min. : 431364 Min. : 447915
## N.unique :47 1st Qu.: 1338126 1st Qu.: 1403390
## N.blank : 0 Median : 3312250 Median : 3479257
## Min.nchar: 5 Mean : 4600645 Mean : 5051080
## Max.nchar: 5 3rd Qu.: 5313422 3rd Qu.: 5934260
## Max. :25962648 Max. :30783255
##
## % Non-citizen Prison Probation Parole
## Length :51 Min. : 0 Min. : 0 Min. : 0
## N.unique :37 1st Qu.: 6080 1st Qu.: 0 1st Qu.: 0
## N.blank : 0 Median : 18099 Median : 5989 Median : 1860
## Min.nchar: 4 Mean : 23719 Mean : 38167 Mean : 9972
## Max.nchar: 5 3rd Qu.: 31208 3rd Qu.: 42236 3rd Qu.: 10066
## Max. :154913 Max. :416771 Max. :109213
##
## Total Ineligible Felon Overseas Eligible State Abv
## Min. : 0 Min. : NA Length :51
## 1st Qu.: 11590 1st Qu.: NA N.unique :51
## Median : 33933 Median : NA N.blank : 0
## Mean : 57354 Mean :NaN Min.nchar: 2
## 3rd Qu.: 73060 3rd Qu.: NA Max.nchar: 2
## Max. :492390 Max. : NA
## NAs :51- hist(data$x) - for continuous variables
hist(data1$`Voting-Eligible Population (VEP)`)
- plot(data\(x,data\)y) - to compare variables
plot(data1$`Voting-Eligible Population (VEP)`,data1$`Total Ballots Counted (Estimate)`) 
4) cor(data\(x,data\)y) - to see a
correlation between two variables
cor(data1$`Voting-Eligible Population (VEP)`,data1$`Total Ballots Counted (Estimate)`)## [1] 0.9955596