world_cities.R

library(tidyverse)
library(animation)
library(readxl)
library(extrafont)

# Download file from: https://esa.un.org/unpd/wup/cd-rom/WUP2014_XLS_CD_FILES/WUP2014-F11a-30_Largest_Cities.xls

df <- read_excel('WUP2014-F11a-30_Largest_Cities.xls', skip = 17, 
                 col_names = c("index", "year", "order", "ccode", 
                               "country", "city", "name", "note", "lat", 
                               "lon", "pop")) %>%
  mutate(name = str_replace(name, " \\(.*|,.*", "")) %>%
  mutate(name = str_trim(name))


na <- c("New York-Newark", "Chicago", "Los Angeles-Long Beach-Santa Ana", 
        "Philadelphia", "Detroit", "Boston", "San Francisco-Oakland")

latam <- c("Buenos Aires", "Ciudad de México", "Rio de Janeiro", 
           "São Paulo", "Lima")

europe <- c("London", "Paris", "Moskva", "Berlin", "Sankt Peterburg",
            "Birmingham", "Roma", "Milano", "Barcelona", 
            "Istanbul", "Manchester", "Madrid")

sasia <- c("Kolkata", "Mumbai", "Delhi", "Tehran", "Karachi", 
           "Dhaka", "Chennai", "Bangalore", "Lahore", 
           "Hyderabad")

easia <- c("Tokyo", "Kinki M.M.A.", "Shanghai", "Tianjin", "Chukyo M.M.A.", 
           "Shenyang", "Beijing", "Hong Kong", "Kitakyushu-Fukuoka M.M.A.", 
           "Jakarta", "Seoul", "Manila", "Krung Thep", "Chongqing", 
           "Guangzhou", "Shenzhen")

africa <- c("Al-Qahirah", "Lagos", "Kinshasa")

dfb <- df %>%
  mutate(region = case_when(
    name %in% na ~ "United States",
    name %in% latam ~ "Latin America",
    name %in% europe ~ "Europe",
    name %in% sasia ~ "South Asia",
    name %in% easia ~ "East Asia",
    name %in% africa ~ "Africa"
  ),
  poplabel = paste0(round(pop, 1), "m")
  )

saveGIF({
  
  for (i in seq(1950, 2030, 5)) {
    
    yearly <- filter(dfb, year == i)
    
    g <- ggplot() + 
      geom_bar(data = yearly, aes(y = pop, x = reorder(name, pop), 
                                 fill = region), stat = "identity") + 
      geom_text(data = yearly, aes(y = pop + 1.5, x = reorder(name, pop), 
                                  label = poplabel), fontface = "bold") + 
      coord_flip() +
      scale_y_continuous(limits = c(0, 42), expand = c(0, 0)) + 
      scale_fill_brewer(palette = "Set1") + 
      theme_minimal(base_size = 16, base_family = "Tahoma") + 
      theme(panel.grid.major.x = element_blank(), 
            panel.grid.minor.x = element_blank(), 
            panel.grid.major.y = element_blank(), 
            panel.grid.minor.y = element_blank(), 
            plot.title = element_text(face = "bold"), 
            axis.text.x = element_blank(), 
            legend.position = "bottom") + 
      labs(y = "", 
           x = "", 
           fill = "", 
           caption = "Data source: United Nations World Urbanization Prospects | Chart by @kyle_e_walker", 
           title = paste0("30 largest metropolitan areas, ", as.character(round(i, 0)))) 
    
    print(g)
    
  }
  
  
}, movie.name = "pop.gif", interval = 1.5, ani.width = 700, ani.height = 600)