About

This chart uses a vertical line chart to show the party advantage in the U.S. House of Representatives from 1976 to the present. The chart is inspired by a graphic from FiveThirtyEight and has been created by Aman Bhargava.

Thanks to him for sharing its work!

Libraries

First we start by loading the necessary libraries.

Note: Install urbnmapr with devtools::install_github("UrbanInstitute/urbnmapr") since it’s not on CRAN.

library(tidyverse)
library(tidytuesdayR)
library(scales)
library(urbnmapr)
library(patchwork)

Dataset

The main dataset is retrieved from the TidyTuesday GitHub repository.

path <- "https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2023/2023-11-07/house.csv"
data <- read.csv(path)

path <- "https://github.com/holtzy/R-graph-gallery/blob/master/DATA/democrats-and-republicans.csv?raw=true"
path <- "DATA/democrats-and-republicans.csv"
advantage_df <- read.csv(path)

path <- "https://github.com/holtzy/R-graph-gallery/blob/master/DATA/US-presidents.csv?raw=true"
path <- "DATA/US-presidents.csv"
presidents_df <- read.csv(path)

Creating the right chart

Use ggplot() to create the base plot
Add segments representing each president’s term, colored by party
Add text labels for each president’s name
Customize the theme to remove unnecessary elements
Set up the y-axis scale to align with the main chart
Use coord_flip() to make the chart vertical

right_chart <- ggplot() +
   geom_segment(
      data = presidents_df,
      aes(
         x = Start_Year,
         y = 330,
         xend = End_Year,
         yend = 330,
         colour = prez_party
      ),
      linewidth = 1.5,
      show.legend = FALSE
   ) +
   geom_text(
      data = presidents_df,
      aes(
         x = (Start_Year + End_Year) / 2 + 0.1,
         y = 400,
         label = president,
      ),
      color = "#7A7A7A",
      size = 3.8,
      hjust = 0, # Center the text horizontally
      vjust = 1, # Adjust vertical position of text,
      show.legend = FALSE
   ) +
   scale_y_continuous(
      limits = c(300, 1500),
      position = "left"
   ) +
   scale_color_manual(values = c("#64B6EC", "#FF8972")) +
   theme_void() +
   theme(plot.margin = margin(t = 0, r = 0, b = 0, l = 0, "points")) +
   coord_flip()

right_chart

Creating the left chart

Use ggplot to create the base plot with year on the y-axis and advantage on the x-axis
Add a line geom to show the trend over time
Add a horizontal line at y=0 to separate Democrat and Republican advantage
Add points to highlight non-zero advantage values
Customize the theme, colors, and labels to match the desired style
Set up the scales for x and y axes, including custom breaks and labels
Add title, subtitle, and caption to provide context for the chart

left_chart <- advantage_df %>%
   ggplot(aes(
      x = year,
      y = advantage,
      color = majority,
      fill = majority
   )) +
   geom_line(aes(group = 1), show.legend = FALSE) +
   geom_hline(yintercept = 0, aes(linewidth = 0.5, alpha = 0.8)) +
   geom_point(
      shape = 21,
      data = . %>% filter(advantage != 0),
      size = 2,
      stroke = 1,
      show.legend = FALSE
   ) +
   coord_flip() +
   theme_minimal() +
   theme(
      plot.margin = margin(15, 0, 15, 0),
      panel.grid.major.x = element_line(),
      panel.grid.minor.x = element_blank(),
      panel.grid.minor.y = element_blank(),
      panel.border = element_blank(),
      axis.title = element_text(
         colour = "#7A7A7A",
         size = 12,
         face = "bold",
      ),
      axis.ticks.x = element_blank(),
      axis.ticks.y.right = element_line(),
      axis.text = element_text(
         colour = "#7A7A7A",
         family = "DecimaMonoPro",
         size = 12,
         face = "bold"
      ),
      plot.title = element_text(
         size = 24,
         hjust = 0,
         lineheight = 1,
         face = "bold",
         margin = margin(b = 10)
      ),
      plot.subtitle = element_text(
         hjust = 0,
         lineheight = 1.1,
         size = 14,
         margin = margin(b = 20)
      ),
      plot.caption = element_text(
         hjust = 0,
         colour = "#7A7A7A",
         size = 11,
         margin = margin(t = 20)
      )
   ) +
   scale_color_manual(values = c("#FF330F", "#2FA3DC")) +
   scale_fill_manual(values = c("#FF8972", "#64B6EC")) +
   scale_y_continuous(
      breaks = c(-300, -200, -100, 0, 100, 200, 300),
      labels = function(x) {
         ifelse(x == -300, paste0(abs(x), " seats"), abs(x))
      },
      limits = c(-300, 300),
      position = "right"
   ) +
   scale_x_continuous(breaks = seq(1976, 2023, by = 4)) +
   labs(
      x = "",
      y = str_to_upper("  ◄ More Democrats | More Republicans ►"),
      title = str_wrap(
         "Party Advantage in the U.S. House of Representatives, 1976-Present",
         width = 50
      ),
      subtitle = str_wrap(
         "Recent trends in the U.S. House show a close margin between Democrats and Republicans, resulting in fewer dramatic swings in party dominance.",
         width = 75
      ),
      caption = "Source: MIT Election Data and Science Lab, tidytuesday project \nggplot re-creation of an original graphic by FiveThirtyEight\n\nGraphic: Aman Bhargava | Twitter: @thedivtagguy | 🔗 aman.bh"
   )

left_chart

Combine the charts with patchwork

Use the patchwork library to combine the two charts
Adjust the relative widths of the charts using plot_layout()

left_chart + right_chart + plot_layout(widths = c(8, 1))

Vertical linechart with ggplot2