In this case study we will be looking at the housing collapse that occurred around 2005, and how it has effected Single Family permits. We will look at how this has effected the nation, and specifically Idaho.
US_data %>%
filter(year > 1989) %>%
group_by(state_abbr, year) %>%
ggplot(aes(x = year, y = value/10000, fill = year)) +
geom_col() +
facet_geo(~ state_abbr, scales = "free_y") +
scale_y_sqrt() +
theme_bw() +
theme(axis.text.x = element_text(angle = 90, hjust = 1),
axis.text.y = element_blank()) +
labs(x = "Year",
y = "Value Per 10,000",
title = "Housing Collapse of the Nation",
subtitle = "Single Family Permits: 1990 - 2010")
We can see from this graphic that Single Family permits went down drastically in every state after 2005.
idd %>%
filter(year > 2002 & year < 2009) %>%
ggplot() +
geom_sf(aes(fill = value)) +
facet_wrap(~ year) +
theme_bw() +
labs(title = "Housing Collapse: Idaho",
subtitle = "Single Family Permits: 2003 - 2008")
Well, there doesn’t seem to be a lot of building that goes on in the different counties of Idaho. We can see that the most activity is happening around Boise (Ada County) before 2005, and then starts to die down.
idd <- US_data %>%
filter(state_abbr == "ID")
Madison <- idd %>%
filter(name == "Madison")
Fremont <- idd %>%
filter(name == "Fremont")
Teton <- idd %>%
filter(name == "Teton")
Jefferson <- idd %>%
filter(name == "Jefferson")
Clark <- idd %>%
filter(name == "Clark")
Bonneville <- idd %>%
filter(name == "Bonneville")
idc <- rbind(Madison, Fremont, Teton, Jefferson, Clark, Bonneville)
idc %>%
filter(year > 2002 & year < 2009) %>%
ggplot() +
geom_sf(aes(fill = value)) +
facet_wrap(~ year) +
theme_bw() +
labs(title = "Housing Collapse: Idaho",
subtitle = "Single Family Permits: 2003 - 2008")
With this plot I was trying to see what was going on with the permits around my home county of Madison. It seems like there was not a lot of from 2003 - 2008. Bonneville county goes a little bit up, and then goes down.