California Housing Problem

Original Image

The image below was featured in BloomBerg. https://www.bloomberg.com/graphics/2019-california-housing-crisis/

Data Preparation

Below is the accompanying code to reproduce the chart above. The data is obtained from the source mentioned in the image.

library(ggplot2)
library(dplyr)
library(geofacet)
library(grid)

data <- read.csv(file = './data/us_housing_burdened.csv', stringsAsFactors = F) %>%
  janitor::clean_names() %>% 
  mutate_at(.vars = c("owner_burdened","renter_burdened","owner_per","renter_per"), .funs = function(x){gsub(",","",x)}) %>% 
  mutate_at(.vars = c("owner_burdened","renter_burdened","owner_per","renter_per"), .funs = as.numeric) %>% 
  mutate(cost_burdened = (owner_burdened+renter_burdened)/((owner_burdened/owner_per)+(renter_burdened/renter_per)), label = state) %>% 
  left_join(., us_state_grid2, by = c("state" = "name")) %>% 
  mutate(color_cat = cut(cost_burdened, breaks = c(0,25,30,35,40,Inf), labels = c("A","B","C","D","E")))
  

GGPLOT2

p <- ggplot(data = data) + 
  geom_rect(aes(fill = color_cat), 
            xmin = 0, xmax = 1, ymin = 0, ymax = 1, 
            alpha = 0.8) + 
  geom_text(aes(x = 0.5, y = 0.5,label = code)) +
  facet_geo(~state, grid = "us_state_grid2") + 
  scale_fill_manual(values = c("A" = "#fff117", "B" = "#ffc100","C" = "#ff5500","D" = "#ff000e","E" = "#000000"), 
                    labels = c("25","30","35","40","")) + 
  labs(title = "Cost Burdened",
       subtitle = "For both owners and renters, California has the highest share of households spending more than\n30% of their income on housing",
       x = NULL, y = NULL,
       caption = "Source: Harvard Joint Center for Housing Studies",
       fill = "Percentage of cost-burdened households") + 
  theme_classic() + 
  theme(panel.spacing = unit(0.05, "cm"),
        legend.position = "top",
        legend.direction = "horizontal",
        legend.title = element_text(size = 9),
        legend.key.width = unit(1, "cm"), 
        legend.key.height = unit(0.2, "cm"),
        legend.spacing.x  = unit(0,"cm"),
        axis.ticks = element_blank(),
        axis.text = element_blank(),
        axis.line = element_blank(),
        strip.background = element_blank(),
        strip.text = element_blank(),
        plot.caption = element_text(hjust = 0, size = 10),
        plot.title = element_text(size = 20),
        plot.subtitle = element_text(size = 12)) + 
  guides(fill = guide_legend(title.position = "top", 
                             title.hjust = 0.25,
                             label.position="bottom",
                             label.hjust = 1.25))
  # )) + 
  # annotate("text", x = 1, y = 5, label = "41.6%\nof California households\nare cost-burdened")
print(p)
grid.text(label = "46.1 %\nof California households\nare cost burdened",
          x = 0.16, y = 0.18)