data-raw/cities.R

In alarm-redist/ggredist: Scales, Geometries, and Extensions of 'ggplot2' for Election Mapping

library(dplyr)
library(sf)
library(tigris)
library(stringr)
library(rmapshaper)

x <- purrr::map_dfr(c(state.abb, 'DC'),
                    function(st) {
                      tidycensus::get_decennial('place', 'P2_001N', year = 2020, state = st, geometry = TRUE) %>%
                        dplyr::mutate(geometry = st_centroid(geometry)) %>%
                        dplyr::arrange(desc(value)) %>%
                        dplyr::slice(1:40) %>%
                        dplyr::mutate(state = st) %>%
                        dplyr::select(-variable) %>%
                        dplyr::rename(pop_2020 = value)
                    })
y <- x %>%
  filter(NAME %in% c('Frankfort city, Kentucky', 'Augusta city, Maine', 'Helena city, Montana', 'Pierre city, South Dakota', 'Montpelier city, Vermont'))

x <- x %>%
  dplyr::arrange(desc(pop_2020)) %>%
  dplyr::slice(1:1000)

x <- bind_rows(x, y)

x <- x %>%
  dplyr::select(
    name = NAME, state, GEOID, pop_2020, geometry
  )

cities <- x %>%
  dplyr::mutate(name = sapply(strsplit(x$name, ','), `[`, 1))

# c('(Honolulu County)', '(Baltimore County)', '(balance)', 'city and borough', 'city', 'borough', 'town', 'township', 'CDP', 'county', 'village',  'municipality')
cities <- cities %>%
  mutate(
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('(Honolulu County)')), str_sub(name, 1, -18), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('(Baltimore County)')), str_sub(name, 1, -19), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('(balance)')), str_sub(name, 1, -10), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('city and borough')), str_sub(name, 1, -17), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('city')), str_sub(name, 1, -5), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('borough')), str_sub(name, 1, -8), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('town')), str_sub(name, 1, -5), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('township')), str_sub(name, 1, -9), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('CDP')), str_sub(name, 1, -4), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('county')), str_sub(name, 1, -7), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('village')), str_sub(name, 1, -8), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('municipality')), str_sub(name, 1, -13), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('government ')), str_sub(name, 1, -12), name),
    name = ifelse(endsWith(str_to_lower(name), str_to_lower('city')), str_sub(name, 1, -6), name),
    name = str_squish(name))

cities <- cities %>%
  mutate(
    name = case_when(
      name == 'Urban Honolulu' & state == 'HI' ~ 'Honolulu',
      name == 'Boise City' & state == 'ID' ~ 'Boise',
      name == 'Indianapolis city' & state == 'IN'  ~  'Indianapolis',
      name == 'St. Paul' & state == 'MN'  ~  'Saint Paul',
      name == 'Carson' & state == 'NV'  ~  'Carson City',
      name == 'Nashville-Davidson metropolitan' & state == 'TN'  ~  'Nashville',
      TRUE ~ name
    )
  )

capitals <- structure(
  list(
    state_name = c("Alabama", "Alaska", "Arizona",
                   "Arkansas", "California", "Colorado", "Connecticut", "Delaware",
                   "Florida", "Georgia", "Hawaii", "Idaho", "Illinois", "Indiana",
                   "Iowa", "Kansas", "Kentucky", "Louisiana", "Maine", "Maryland",
                   "Massachusetts", "Michigan", "Minnesota", "Mississippi", "Missouri",
                   "Montana", "Nebraska", "Nevada", "New Hampshire", "New Jersey",
                   "New Mexico", "New York", "North Carolina", "North Dakota", "Ohio",
                   "Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", "South Carolina",
                   "South Dakota", "Tennessee", "Texas", "Utah", "Vermont", "Virginia",
                   "Washington", "West Virginia", "Wisconsin", "Wyoming", 'District of Columbia'),
    state = c("AL",
              "AK", "AZ", "AR", "CA", "CO", "CT", "DE", "FL", "GA", "HI", "ID",
              "IL", "IN", "IA", "KS", "KY", "LA", "ME", "MD", "MA", "MI", "MN",
              "MS", "MO", "MT", "NE", "NV", "NH", "NJ", "NM", "NY", "NC", "ND",
              "OH", "OK", "OR", "PA", "RI", "SC", "SD", "TN", "TX", "UT", "VT",
              "VA", "WA", "WV", "WI", "WY", 'DC'),
    capital = c("Montgomery", "Juneau",
                "Phoenix", "Little Rock", "Sacramento", "Denver", "Hartford",
                "Dover", "Tallahassee", "Atlanta", "Honolulu", "Boise", "Springfield",
                "Indianapolis", "Des Moines", "Topeka", "Frankfort", "Baton Rouge",
                "Augusta", "Annapolis", "Boston", "Lansing", "Saint Paul", "Jackson",
                "Jefferson City", "Helena", "Lincoln", "Carson City", "Concord",
                "Trenton", "Santa Fe", "Albany", "Raleigh", "Bismarck", "Columbus",
                "Oklahoma City", "Salem", "Harrisburg", "Providence", "Columbia",
                "Pierre", "Nashville", "Austin", "Salt Lake City", "Montpelier",
                "Richmond", "Olympia", "Charleston", "Madison", "Cheyenne", 'Washington')
  ),
  class = "data.frame",
  row.names = c(NA, -51L)
)

cities <- cities %>%
  left_join(capitals) %>%
  mutate(capital = capital == name) %>%
  relocate(geometry, .after = everything())

usethis::use_data(cities, overwrite=TRUE, compress="xz")