Davidson County election analysis

The following map and chart indicate that Kamala Harris was favored in Davidson county. The map shows that she was predictably more popular in urban areas closer to Nashville. The chart displays that the race was closer than the unanimous electoral votes casted for Donal Trump may suggest.

Code:

# Required packages

if (!require("tidyverse"))
  install.packages("tidyverse")
if (!require("mapview"))
  install.packages("mapview")
if (!require("sf"))
  install.packages("sf")
if (!require("leaflet"))
  install.packages("leaflet")
if (!require("leaflet.extras2"))
  install.packages("leaflet.extras2")
if (!require("plotly"))
  install.packages("plotly")

library(tidyverse)
library(mapview)
library(sf)
library(leaflet)
library(leafpop)
library(readxl)
library(plotly)

# Getting the election data

VoteData <- read.csv("https://github.com/drkblake/Data/raw/refs/heads/main/Davidson_Vote_Data.csv")

# Getting the map

download.file("https://github.com/drkblake/Data/raw/refs/heads/main/Davidson_Precincts.zip","DavidsonPrecinctMap.zip")

unzip("DavidsonPrecinctMap.zip")

MapInfo <- read_sf("Davidson_Precincts.shp")



# Enhancing the data

VoteData2 <- VoteData %>% 
  mutate(Total = Trump + Harris + Other,
         Pct_Trump = round((Trump / Total)*100,1),
         Pct_Harris = round((Harris / Total)*100,1),
         Pct_Other = round((Other / Total)*100,1),
         Margin_Trump = Trump - Harris,
         Margin_Harris = Harris - Trump,
         Winner = case_when(Trump > Harris ~ "Trump",
                            Harris > Trump ~ "Harris",
                            Other > (Trump + Harris) ~ "Other",
                            .default = "Tie"))

# Merging the data and the map

DataAndMap <- left_join(VoteData2,MapInfo)

# Converting the merged data and map into an sf object

DataAndMap <- st_as_sf(DataAndMap)

# Trump percentage map

mypalette = colorRampPalette(c('blue', 'red'))

PctTrumpMap <- mapview(
  DataAndMap,
  zcol = "Pct_Trump",
  col.regions = mypalette,
  map.types = ("OpenStreetMap"),
  layer.name = "Pct. Trump",
  popup = popupTable(
    DataAndMap,
    feature.id = FALSE,
    row.numbers = FALSE,
    zcol = c(
      "Precinct",
      "Trump",
      "Harris",
      "Other",
      "Total",
      "Pct_Trump",
      "Pct_Harris",
      "Pct_Other",
      "Margin_Trump",
      "Margin_Harris",
      "Winner"
    )
  )
)

PctTrumpMap

# Harris percentage map

mypalette = colorRampPalette(c('red', 'blue'))


PctHarrisMap <- mapview(
  DataAndMap,
  zcol = "Pct_Harris",
  col.regions = mypalette,
  map.types = ("OpenStreetMap"),
  layer.name = "Pct. Harris",
  popup = popupTable(
    DataAndMap,
    feature.id = FALSE,
    row.numbers = FALSE,
    zcol = c(
      "Precinct",
      "Trump",
      "Harris",
      "Other",
      "Total",
      "Pct_Trump",
      "Pct_Harris",
      "Pct_Other",
      "Margin_Trump",
      "Margin_Harris",
      "Winner"
    )
  )
)

PctHarrisMap

# Sort the data by the Total variable
# and make it stay sorted in the chart

ChartData <- DataAndMap %>% 
  arrange(Total) %>% 
  mutate(Precinct = factor(Precinct, levels = Precinct))

# Create and format the chart

Chart <- plot_ly(data = ChartData, orientation = 'h') %>% 
  add_trace(
    x = ~Trump, 
    y = ~Precinct, 
    name = 'Trump', 
    type = 'bar',
    marker = list(color = 'red') # We have made the red bars
  ) %>% 
  add_trace(
    x = ~Harris, 
    y = ~Precinct, 
    name = 'Harris', 
    type = 'bar',
    marker = list(color = 'darkblue') # We have added the blue bars
  ) %>% 
  add_trace(
    x = ~Other, 
    y = ~Precinct, 
    name = 'Other', 
    type = 'bar',
    marker = list(color = 'gray') #We have added the gray bars
  ) %>% 
  add_trace(
    x = ~Other,
    y = ~Precinct,
    type = 'bar',
    name = '',
    marker = list(color = 'rgba(0,0,0,0)'),
    text = ~Winner,
    textposition = 'outside',
    showlegend = FALSE # We have added the "winner" labels
  ) %>%
  layout(
    barmode = 'stack',
    xaxis = list(title = 'Number of Votes'),
    yaxis = list(title = 'Precinct',
                 tickfont = list(size = 10),
                 automargin = TRUE)) # We have made it a stacked bar chart

# Show the plot

Chart