The txhousing data is available when you install and load the ggplot2 package.

library(tidyverse)
txsamp <- txhousing %>% 
  filter(city %in% c("Houston", "Fort Worth", "San Antonio", "Dallas", "Austin"))

Austin is expensive

ggplot(data = txsamp, aes(x = sales, y = median)) +
   geom_point(aes(colour = city)) + 
   scale_colour_viridis_d("City\nCenter", option = params$viridis_palette)

Austin prices on the rise

ggplot(data = filter(txsamp, city == "Austin"), aes(x = sales, y = median)) +
   geom_point(aes(colour = year)) + 
   scale_colour_viridis_c("Austin by year", option = params$viridis_palette, direction = -1)

Fort Worth has more affordable housing

library(scales) # to make y-axis in non-scientific notation
ggplot(txsamp, aes(x = median, fill = city)) +
  geom_histogram(aes(weight = sales), position = "dodge", binwidth = 15000) +
  scale_fill_viridis_d(option = params$viridis_palette)+
  scale_y_continuous(labels = comma)

The current pace of sales is fast

“Months inventory”: amount of time it would take to sell all current listings at current pace of sales.

ggplot(data = txsamp, aes(x = year, y = inventory, colour = city)) +
  geom_point() + 
  geom_smooth(se = FALSE) +
  scale_colour_viridis_d("City\nCenter", option = params$viridis_palette)

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