R code to render cartogram bug example

### We need the following packages for this example.
packages <- c("tidyverse", "lubridate", "ggplot2", "maps", "sf",
              "ggthemes", "tsibble", "dplyr", "broom", "ggfortify",
              "usmap", "forecast", "gridExtra", "cartogram", "RColorBrewer")

### Install packages if needed, then load them quietly
new_packages <- packages[!(packages %in% installed.packages()[, "Package"])]
if (length(new_packages)) install.packages(new_packages, quiet = TRUE)
invisible(lapply(packages, "library", quietly = TRUE,
                 character.only = TRUE, warn.conflicts = FALSE))

# Load data for the graphs from a spreadsheet file.
# The Pastebin URL for this data file is:
# https://pastebin.com/a5N4JAwL
state_data <- read_csv("cartogram-bug-data.csv",
                       col_names = TRUE,
                       col_types = "ccnnni")

### Load a map of states in the USA.   The maps have a list of lowercase
### state names, which will use to match against "pres" down below
us_map <- maps::map("state", plot = FALSE, fill = TRUE)

### Change the latitude/longitude data to a simple feature object
us_map <- sf::st_as_sf(us_map)

### Change the name of the "ID" column to "state_name"
names(us_map) <- c("geometry", "state_name")

### Remove the District of Colombia from our map
us_map <- us_map %>% filter(state_name != "district of columbia")

### Join the state data to the map
us_map <- us_map %>% left_join(state_data, by = "state_name")

### Population-weighted cartogram using 6 iterations...
us_map_cartogram_6 <- us_map %>%
                      st_transform(crs = 2163) %>%
                      cartogram_cont("pop2020", itermax = 6) #%>%

### Population-weighted cartogram using 7 iterations...
us_map_cartogram_7 <- us_map %>%
                      st_transform(crs = 2163) %>%
                      cartogram_cont("pop2020", itermax = 7) #%>%

p_unemployment <- ggplot(us_map, aes(fill = unemployment), col = "black") +
     theme_void() +
     labs(title = "Unemployment rate by state (SA)") +
     geom_sf() +
     coord_sf(crs = "+proj=aea +lat_1=25 +lat_2=50 +lon_0=-100", ndiscr = 0) +
     scale_fill_gradientn(name = "Unemployment (%)",
                           colours = rev(brewer.pal(9, "Blues")),
                           trans = "log10")

p_unemployment_cartogram_6 <- ggplot(us_map_cartogram_6, aes(fill = unemployment), col = "black") +
     theme_void() +
     labs(title = "Cartogram with 6 iterations") +
     geom_sf() +
     coord_sf(crs = "+proj=aea +lat_1=25 +lat_2=50 +lon_0=-100", ndiscr = 0) +
     scale_fill_gradientn(name = "Unemployment (%)",
                          colours = rev(brewer.pal(9, "Blues")),
                          trans = "log10")

p_unemployment_cartogram_7 <- ggplot(us_map_cartogram_7, aes(fill = unemployment), col = "black") +
     theme_void() +
     labs(title = "Cartogram with 7 iterations") +
     geom_sf() +
     coord_sf(crs = "+proj=aea +lat_1=25 +lat_2=50 +lon_0=-100", ndiscr = 0) +
     scale_fill_gradientn(name = "Unemployment (%)",
                          colours = rev(brewer.pal(9, "Blues")),
                          trans = "log10")

grid.arrange(p_unemployment,
             p_unemployment_cartogram_6,
             p_unemployment_cartogram_7,
             nrow = 3)