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CO.Rmd
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CO.Rmd
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---
title: "Colorado Early Voting Statistics"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
library(knitr)
library(kableExtra)
library(scales)
state_stats <- read_csv("D:/DropBox/Dropbox/Mail_Ballots_2020/markdown/2020G_Early_Vote.csv")
CO_stats <- read_csv("D:/DropBox/Dropbox/Mail_Ballots_2020/markdown/2020G_Early_Vote_CO.csv")
# Setup
party_shell <- data.frame(Party=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
party_shell[1,1] <- "Democrats"
party_shell[2,1] <- "Republicans"
party_shell[3,1] <- "Minor"
party_shell[4,1] <- "No Party Affiliation"
party_shell[5,1] <- "TOTAL"
race_shell <- data.frame(Race=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
race_shell[1,1] <- "Non-Hispanic White"
race_shell[2,1] <- "Non-Hispanic Black"
race_shell[3,1] <- "Hispanic"
race_shell[4,1] <- "Non-Hispanic Asian American"
race_shell[5,1] <- "Non-Hispanic Native American"
race_shell[6,1] <- "Other/Multiple/Unknown"
race_shell[7,1] <- "TOTAL"
gender_shell <- data.frame(Gender=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
gender_shell[1,1] <- "Female"
gender_shell[2,1] <- "Male"
gender_shell[3,1] <- "Unknown"
gender_shell[4,1] <- "TOTAL"
age_shell <- data.frame(Age=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
age_shell[1,1] <- "18 to 24"
age_shell[2,1] <- "25 to 34"
age_shell[3,1] <- "35 to 44"
age_shell[4,1] <- "45 to 54"
age_shell[5,1] <- "55 to 64"
age_shell[6,1] <- "65 and up"
age_shell[7,1] <- "TOTAL"
party_shell_returned <- data.frame(Party=character(),
Count=integer(),
Frequency=double(),
Count2=integer(),
Rate=integer(),
stringsAsFactors=FALSE)
party_shell_returned[1,1] <- "Democrats"
party_shell_returned[2,1] <- "Republicans"
party_shell_returned[3,1] <- "Minor"
party_shell_returned[4,1] <- "No Party Affiliation"
party_shell_returned[5,1] <- "TOTAL"
# Colorado
CO_voted_party <- party_shell_returned
CO_voted_party[1,2] <- state_stats[6,29] + state_stats[6,77]
CO_voted_party[2,2] <- state_stats[6,30] + state_stats[6,78]
CO_voted_party[3,2] <- state_stats[6,31] + state_stats[6,79]
CO_voted_party[4,2] <- state_stats[6,32] + state_stats[6,80]
CO_voted_party[5,2] <- state_stats[6,6] + state_stats[6,7]
CO_voted_party[1,4] <- state_stats[6,10]
CO_voted_party[2,4] <- state_stats[6,11]
CO_voted_party[3,4] <- state_stats[6,12]
CO_voted_party[4,4] <- state_stats[6,13]
CO_voted_party[5,4] <- state_stats[6,5]
CO_voted_party$Frequency <- 100*CO_voted_party$Count/CO_voted_party[5,2]
CO_voted_party$Rate <- 100*CO_voted_party$Count/CO_voted_party$Count2
colnames(CO_voted_party) <- c("Party", "Total Voted", "Freq. Distribution", "Voter Registration", "Voted Rate")
CO_req_send_party <- party_shell
CO_req_send_party[1,2] <- state_stats[6,10]
CO_req_send_party[2,2] <- state_stats[6,11]
CO_req_send_party[3,2] <- state_stats[6,12]
CO_req_send_party[4,2] <- state_stats[6,13]
CO_req_send_party[5,2] <- state_stats[6,5]
CO_req_send_party$Percent <- 100*CO_req_send_party$Count/CO_req_send_party[5,2]
CO_req_send_party <- party_shell
CO_req_send_party[1,2] <- state_stats[6,10]
CO_req_send_party[2,2] <- state_stats[6,11]
CO_req_send_party[3,2] <- state_stats[6,12]
CO_req_send_party[4,2] <- state_stats[6,13]
CO_req_send_party[5,2] <- state_stats[6,5]
CO_req_send_party$Percent <- 100*CO_req_send_party$Count/CO_req_send_party[5,2]
CO_returned_party <- party_shell
CO_returned_party[1,2] <- state_stats[6,29]
CO_returned_party[2,2] <- state_stats[6,30]
CO_returned_party[3,2] <- state_stats[6,31]
CO_returned_party[4,2] <- state_stats[6,32]
CO_returned_party[5,2] <- state_stats[6,6]
CO_returned_party$Percent <- 100*CO_returned_party$Count/CO_returned_party[5,2]
CO_inperson_party <- party_shell
CO_inperson_party[1,2] <- state_stats[6,77]
CO_inperson_party[2,2] <- state_stats[6,78]
CO_inperson_party[3,2] <- state_stats[6,79]
CO_inperson_party[4,2] <- state_stats[6,80]
CO_inperson_party[5,2] <- state_stats[6,7]
CO_inperson_party$Percent <- 100*CO_inperson_party$Count/CO_inperson_party[5,2]
CO_req_send_gender <- gender_shell
CO_req_send_gender[1,2] <- sum(state_stats[6,21])
CO_req_send_gender[2,2] <- sum(state_stats[6,20])
CO_req_send_gender[3,2] <- sum(state_stats[6,22])
CO_req_send_gender[4,2] <- sum(state_stats[6,5])
CO_req_send_gender$Percent <- 100 * CO_req_send_gender$Count/CO_req_send_gender[4,2]
CO_req_send_age <- age_shell
CO_req_send_age[1,2] <- state_stats[6,23]
CO_req_send_age[2,2] <- state_stats[6,24]
CO_req_send_age[3,2] <- state_stats[6,25]
CO_req_send_age[4,2] <- state_stats[6,26]
CO_req_send_age[5,2] <- state_stats[6,27]
CO_req_send_age[6,2] <- state_stats[6,28]
CO_req_send_age[7,2] <- state_stats[6,5]
CO_req_send_age$Percent <- 100*CO_req_send_age$Count/CO_req_send_age[7,2]
CO_stats <- mutate(CO_stats, Pct.Voted = Voted.Tot/Reg.Voters)
CO_stats_voted <- CO_stats %>%
select(COUNTY, Reg.Voters, Voted.Tot, Pct.Voted)
```
## {.tabset}
Last Report: `r state_stats[6,9]`
Source: `r state_stats[6,2]`
Total Vote: **`r format(as.numeric(state_stats[6,8]), big.mark =",")`**
Total Vote as Percentage of 2016 Total Turnout: **`r paste(round(100*as.integer(state_stats[6,8])/as.integer(state_stats[6,3]), digits = 1),"%", sep = "")`**
Colorado is an all-mail state, with an in-person voting option. To measure participation, I combine voters who have cast mail ballots and in-person votes into a single "Total Voted" category.
### Total Voted
Total Voted: **`r format(as.numeric(state_stats[6,8]), big.mark =",")`**
#### Total Voted by Party Registation
``` {r echo = FALSE}
kable(CO_voted_party, format.args = list(big.mark = ",",
scientific = FALSE), digits = 1) %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "left")
```
``` {r echo = FALSE}
CO_2020g_map_data <- CO_stats
CO_2020g_map_data$fips <- paste("0",as.character(CO_2020g_map_data$fips), sep="")
CO_2020g_map_data <- mutate(CO_2020g_map_data, percent = round(100*Pct.Voted, digits = 1))
mapfile <- download_map_data("countries/us/us-co-all.js")
mapdata <- get_data_from_map(mapfile)
mapdata$row <- as.integer(rownames(mapdata))
CO_2020g_map_data <- left_join(CO_2020g_map_data, mapdata, by = "fips")
CO_2020g_map_data <- arrange(CO_2020g_map_data, row)
hcmap(map = "countries/us/us-co-all", data = CO_2020g_map_data,
value = "percent", name = "Percent Voted", joinBy = "fips") %>%
hc_title(text ="Turnout Rates") %>%
hc_subtitle(text = "County plots may not be shaded using the same scale")
```
``` {r echo = FALSE}
datatable(CO_stats_voted, colnames = c("County", "Voter Registration", "Total Voted", "Percent Voted"), rownames = F) %>%
formatPercentage('Pct.Voted', 1) %>%
formatRound(c('Voted.Tot', 'Reg.Voters'), 0, mark = ",")
```
### In-Person Early Vote
Ballots Returned: **`r format(as.numeric(state_stats[6,7]), big.mark =",")`**
#### In-Person Vote by Party Registration
``` {r echo = FALSE}
kable(CO_inperson_party, format.args = list(big.mark = ",",
scientific = FALSE), digits = 1) %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "left")
```
### Mail Ballots Returned and Accepted
Ballots Returned and Accepted: **`r format(as.numeric(state_stats[6,6]), big.mark =",")`**
#### Mail Ballots Returned and Accepted by Party Registration
``` {r echo = FALSE}
kable(CO_returned_party, format.args = list(big.mark = ",",
scientific = FALSE), digits = 1) %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "left")
```
### Requested Mail Ballots
Ballots Requested: **`r format(as.numeric(state_stats[6,5]), big.mark =",")`**
Colorado is an all-mail ballot state. Ballot requests reported here are counts of the state's registered voters.
#### Mail Ballot Requests by Party Registration
``` {r echo = FALSE}
kable(CO_req_send_party,format.args = list(big.mark = ",",
scientific = FALSE), digits = 1) %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "left")
```
Colorado registered Democrats have a **`r format(as.numeric(CO_req_send_party[1,2]-CO_req_send_party[2,2]), big.mark =",")`** ballot request lead over registered Republicans.
#### Mail Ballot Requests by Age
``` {r echo = FALSE}
kable(CO_req_send_age, format.args = list(big.mark = ",",
scientific = FALSE), digits = 1) %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "left")
```