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WI.Rmd
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WI.Rmd
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---
title: "Wisconsin Early Voting Statistics"
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library(tidyverse)
library(knitr)
library(kableExtra)
library(scales)
library(DT)
library(highcharter)
state_stats <- read_csv("D:/DropBox/Dropbox/Mail_Ballots_2020/markdown/2020G_Early_Vote.csv")
WI_stats <- read_csv("D:/DropBox/Dropbox/Mail_Ballots_2020/markdown/2020G_Early_Vote_WI.csv")
# Setup
party_shell <- data.frame(Party=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
party_shell[1,1] <- "Democrats"
party_shell[2,1] <- "Republicans"
party_shell[3,1] <- "Minor"
party_shell[4,1] <- "No Party Affiliation"
party_shell[5,1] <- "TOTAL"
race_shell <- data.frame(Race=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
race_shell[1,1] <- "Non-Hispanic White"
race_shell[2,1] <- "Non-Hispanic Black"
race_shell[3,1] <- "Hispanic"
race_shell[4,1] <- "Non-Hispanic Asian American"
race_shell[5,1] <- "Non-Hispanic Native American"
race_shell[6,1] <- "Other/Multiple/Unknown"
race_shell[7,1] <- "TOTAL"
gender_shell <- data.frame(Gender=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
gender_shell[1,1] <- "Female"
gender_shell[2,1] <- "Male"
gender_shell[3,1] <- "Unknown"
gender_shell[4,1] <- "TOTAL"
age_shell <- data.frame(Age=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
age_shell[1,1] <- "18 to 24"
age_shell[2,1] <- "25 to 34"
age_shell[3,1] <- "35 to 44"
age_shell[4,1] <- "45 to 54"
age_shell[5,1] <- "55 to 64"
age_shell[6,1] <- "65 and up"
age_shell[7,1] <- "TOTAL"
# Wisconsin
WI_req_send_tot <- data.frame(Total=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
WI_req_send_tot[1,1] <- "TOTAL"
WI_req_send_tot[1,2] <- sum(state_stats[50,5])
WI_req_send_tot$Percent <- 100.0
WI_return_tot <- data.frame(Total=character(),
Count=integer(),
Percent=double(),
stringsAsFactors=FALSE)
WI_return_tot[1,1] <- "TOTAL"
WI_return_tot[1,2] <- sum(state_stats[50,6])
WI_req_send_tot$Percent <- 100.0
WI_stats_requests <- select(WI_stats, County, Reg.Voters, Mail.Req.Tot)
WI_stats_requests <- mutate(WI_stats_requests, Pct.Request = Mail.Req.Tot/Reg.Voters)
WI_stats_returns <- select(WI_stats, County, Mail.Req.Tot, Mail.Rtn.Tot)
WI_stats_returns <- mutate(WI_stats_returns, Pct.Return = Mail.Rtn.Tot/Mail.Req.Tot)
```
## {.tabset}
Last Report: `r state_stats[50,9]`
Source: `r state_stats[50,2]`
### Total Voted
In-Person Votes: **`r format(as.numeric(state_stats[50,8]), big.mark =",")`**
### In-Person Votes
In-Person Votes: **`r format(as.numeric(sum(WI_stats$Inperson.Tot)), big.mark =",")`**
### Mail Ballots Returned
Ballots Returned: **`r format(as.numeric(sum(WI_stats$Mail.Rtn.Tot)), big.mark =",")`**
Return Rate: **`r paste(round(100*sum(WI_stats$Mail.Rtn.Tot)/sum(WI_stats$Mail.Req.Tot), digits = 1),"%", sep = "")`**
``` {r echo = FALSE}
WI_map_data <- WI_stats
WI_map_data <- mutate(WI_map_data, percent = round(100*(Mail.Rtn.Tot/Mail.Req.Tot), digits = 1))
WI_map_data <- mutate(WI_map_data, fips = as.character(fips))
mapfile <- download_map_data("countries/us/us-wi-all.js")
mapdata <- get_data_from_map(mapfile)
mapdata$row <- as.integer(rownames(mapdata))
WI_map_data <- left_join(WI_map_data, mapdata, by = "fips")
WI_map_data <- arrange(WI_map_data, row)
hcmap(map = "countries/us/us-wi-all", data = WI_map_data,
value = "percent", name = "Percent Returned", joinBy = "fips") %>%
hc_title(text ="Mail Ballot Return Rates") %>%
hc_subtitle(text = "County plots may not be shaded using the same scale")
```
``` {r echo = FALSE}
datatable(WI_stats_returns, colnames = c("County", "Mail Ballots Requested", "Mail Ballots Returned", "Percent Returned"), rownames = F) %>%
formatPercentage('Pct.Return', 1) %>%
formatRound(c('Mail.Req.Tot','Mail.Rtn.Tot'), 0, mark = ",")
```
### Mail Ballots Requested
Ballots Requested: **`r format(as.numeric(sum(WI_stats$Mail.Req.Tot)), big.mark =",")`**
Request Rate: **`r paste(round(100*sum(WI_stats$Mail.Req.Tot)/sum(WI_stats$Reg.Voters), digits = 1),"%", sep = "")`**
``` {r echo = FALSE}
WI_map_data <- WI_stats
WI_map_data <- mutate(WI_map_data, percent = round(100*(Mail.Req.Tot/Reg.Voters), digits = 1))
WI_map_data <- mutate(WI_map_data, fips = as.character(fips))
mapfile <- download_map_data("countries/us/us-wi-all.js")
mapdata <- get_data_from_map(mapfile)
mapdata$row <- as.integer(rownames(mapdata))
WI_map_data <- left_join(WI_map_data, mapdata, by = "fips")
WI_map_data <- arrange(WI_map_data, row)
hcmap(map = "countries/us/us-wi-all", data = WI_map_data,
value = "percent", name = "Percent Requested", joinBy = "fips") %>%
hc_title(text ="Mail Ballot Request Rates") %>%
hc_subtitle(text = "County plots may not be shaded using the same scale")
```
``` {r echo = FALSE}
datatable(WI_stats_requests, colnames = c("County", "Registered Voters", "Mail Ballots Requested", "Percent Requested"), rownames = F) %>%
formatPercentage('Pct.Request', 1) %>%
formatRound(c('Reg.Voters','Mail.Req.Tot'), 0, mark = ",")
```