dfw_places.R

library(tidycensus)
library(tidyverse)
library(extrafont)
library(plotly)

place00 <- get_decennial(geography = "place", state = "TX", 
                         variables = "P001001", year = 2000) %>%
  mutate(NAME = str_replace(NAME, " city.*", "")) %>%
  select(NAME, pop00 = value)

place16 <- get_acs(geography = "place", state = "TX", 
                   variables = "B01003_001", survey = "acs1") %>%
  mutate(NAME = str_replace(NAME, " city.*", "")) %>%
  select(NAME, pop16 = estimate) %>%
  inner_join(place00, by = "NAME")

dfwp <- c("Allen", "Arlington", "Carrollton", "Dallas", "Denton", 
         "Fort Worth", "Frisco", "Garland", "Grand Prairie", 
         "Irving", "Lewisville", "McKinney", "Mansfield", 
         "Mesquite", "Plano", "Richardson")

dfw <- filter(place16, NAME %in% dfwp)

p <- ggplot(dfw) + 
  geom_segment(aes(x = pop00, xend = pop16, 
                   y = reorder(NAME, pop16), 
                   yend = reorder(NAME, pop16))) + 
  geom_point(aes(x = pop16, y = reorder(NAME, pop16), text = paste0("2016: ", pop16)), 
             color = "navy", size = 3) + 
  geom_point(aes(x = pop00, y = reorder(NAME, pop16), text = paste0("2000: ", pop00)), 
             color = "#90b4d2", size = 3) + 
  geom_text(data = data.frame(), aes(x = 1188580, y = "Dallas", label = "2000"), 
            color = "#90b4d2", hjust = 1, size = 3, fontface = "bold", 
            nudge_x = -80000) + 
  geom_text(data = data.frame(), aes(x = 1317942, y = "Dallas", label = "2016"), 
            color = "navy", hjust = 0, size = 3, fontface = "bold", 
            nudge_x = 80000) + 
  scale_x_continuous(labels = scales::comma, expand = c(0.1, 0.1)) + 
  theme_minimal(base_family = "Verdana", base_size = 12) + 
  labs(x = "Population size", 
       y = "", 
       title = "Population change in Dallas-Fort Worth") + 
  theme(panel.grid.major.y=element_blank())

ggplotly(p, tooltip = "text")