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FL.Rmd
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---
title: "Florida 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")
FL_stats <- read_csv("D:/DropBox/Dropbox/Mail_Ballots_2020/markdown/2020G_Early_Vote_FL.csv")
FL_FIPS <- read_csv("D:/DropBox/Dropbox/Mail_Ballots_2020/markdown/FL_FIPS.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"
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"
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"
# Florida
FL_req_send_party <- party_shell
FL_req_send_party[1,2] <- state_stats[10,10]
FL_req_send_party[2,2] <- state_stats[10,11]
FL_req_send_party[3,2] <- state_stats[10,12]
FL_req_send_party[4,2] <- state_stats[10,13]
FL_req_send_party[5,2] <- state_stats[10,5]
FL_req_send_party$Percent <- 100*FL_req_send_party$Count/FL_req_send_party[5,2]
colnames(FL_req_send_party) <- c("Party", "Requested Ballots", "Freq. Distribution")
FL_return_party <- party_shell
FL_return_party[1,2] <- state_stats[10,29]
FL_return_party[2,2] <- state_stats[10,30]
FL_return_party[3,2] <- state_stats[10,31]
FL_return_party[4,2] <- state_stats[10,32]
FL_return_party[5,2] <- state_stats[10,6]
FL_return_party$Percent <- 100*FL_return_party$Count/FL_return_party[5,2]
FL_return_party <- party_shell_returned
FL_return_party[1,2] <- state_stats[10,29]
FL_return_party[2,2] <- state_stats[10,30]
FL_return_party[3,2] <- state_stats[10,31]
FL_return_party[4,2] <- state_stats[10,32]
FL_return_party[5,2] <- state_stats[10,6]
FL_return_party[1,4] <- state_stats[10,10]
FL_return_party[2,4] <- state_stats[10,11]
FL_return_party[3,4] <- state_stats[10,12]
FL_return_party[4,4] <- state_stats[10,13]
FL_return_party[5,4] <- state_stats[10,5]
FL_return_party$Frequency <- 100*FL_return_party$Count/FL_return_party[5,2]
FL_return_party$Rate <- 100*FL_return_party$Count/FL_return_party$Count2
colnames(FL_return_party) <- c("Party", "Returned Ballots", "Freq. Distribution", "Requested Ballots", "Return Rate")
FL_stats_requests <- select(FL_stats, County, Reg.Voters, Mail.Req.Tot, Pct.Request)
FL_stats_returns <- select(FL_stats, County, Mail.Req.Tot, Mail.Return.Tot, Pct.Return)
```
Last Report: `r state_stats[10,9]`
Source: `r state_stats[10,2]`
## {.tabset}
### Mail Returned
#### Mail Ballots Returned by Party Registration
``` {r echo = FALSE}
kable(FL_return_party, format.args = list(big.mark = ",",
scientific = FALSE), digits = 1) %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "left")
```
``` {r echo = FALSE}
FL_2020g_map_data <- left_join(FL_stats, FL_FIPS, by = "County")
FL_2020g_map_data$fips <- as.character(FL_2020g_map_data$FIPS_NUM)
FL_2020g_map_data <- mutate(FL_2020g_map_data, percent_returned = round(100*Pct.Return, digits = 1))
mapfile <- download_map_data("countries/us/us-fl-all.js")
mapdata <- get_data_from_map(mapfile)
mapdata$row <- as.integer(rownames(mapdata))
FL_2020g_map_data <- left_join(FL_2020g_map_data, mapdata, by = "fips")
FL_2020g_map_data <- arrange(FL_2020g_map_data, row)
hcmap(map = "countries/us/us-fl-all", data = FL_2020g_map_data,
value = "percent_returned", name = "Percent Returned", joinby = "fips") %>%
hc_title(text ="Mail Ballot Return Rates") %>%
hc_subtitle(text = "County plots may not be shaded using the same scale")
```
``` {r echo = FALSE}
datatable(FL_stats_returns, colnames = c("County", "Mail Ballots Requested", "Mail Ballots Returned", "Percent Returned"), rownames = F) %>%
formatPercentage('Pct.Return', 1) %>%
formatRound(c('Mail.Req.Tot','Mail.Return.Tot'), 0, mark = ",")
```
### Mail Requested
To calculate the number of requested ballots from the Florida Division of Elections website, add the rows *Vote-by-Mail Provided (Not Yet Returned)* and *Voted Vote-by-Mail*.
#### Mail Ballots Requested by Party Registration
``` {r echo = FALSE}
kable(FL_req_send_party,format.args = list(big.mark = ",",
scientific = FALSE), digits = 1) %>%
kable_styling(bootstrap_options = "striped", full_width = F, position = "left")
```
Florida registered Democrats have a **`r format(as.numeric(FL_req_send_party[1,2]-FL_req_send_party[2,2]), big.mark =",")`** ballot request lead over registered Republicans.
Voter Registration Statistics are as of July 31, 2020.
``` {r echo = FALSE}
FL_2020g_map_data <- left_join(FL_stats, FL_FIPS, by = "County")
FL_2020g_map_data$fips <- as.character(FL_2020g_map_data$FIPS_NUM)
FL_2020g_map_data <- mutate(FL_2020g_map_data, percent_requested = round(100*Pct.Request, digits = 1))
mapfile <- download_map_data("countries/us/us-fl-all.js")
mapdata <- get_data_from_map(mapfile)
mapdata$row <- as.integer(rownames(mapdata))
FL_2020g_map_data <- left_join(FL_2020g_map_data, mapdata, by = "fips")
FL_2020g_map_data <- arrange(FL_2020g_map_data, row)
hcmap(map = "countries/us/us-fl-all", data = FL_2020g_map_data,
value = "percent_requested", 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(FL_stats_requests, colnames = c("County", "Registered Voters", "Mail Ballot Requests", "Percent Requested"), rownames = F) %>%
formatPercentage('Pct.Request', 1) %>%
formatRound(c('Reg.Voters','Mail.Req.Tot'), 0, mark = ",")
```