An ode to Statistics Scotland

library(tidyverse)
library(ggrepel)

housing = read_csv("https://statistics.gov.scot/slice/observations.csv?&dataset=http%3A%2F%2Fstatistics.gov.scot%2Fdata%2Flocal-authority-housing-stock-by-type&http%3A%2F%2Fpurl.org%2Flinked-data%2Fcube%23measureType=http%3A%2F%2Fstatistics.gov.scot%2Fdef%2Fmeasure-properties%2Fcount&http%3A%2F%2Fstatistics.gov.scot%2Fdef%2Fdimension%2FtypeOfDwelling=http%3A%2F%2Fstatistics.gov.scot%2Fdef%2Fconcept%2Ftype-of-dwelling%2Fall", skip = 7) %>% 
  rename(id = `http://purl.org/linked-data/sdmx/2009/dimension#refArea`) %>% 
  pivot_longer(!c(`Reference Area`, id), names_to = "year", values_to = "homes")

population = read_csv("https://statistics.gov.scot/slice/observations.csv?&dataset=http%3A%2F%2Fstatistics.gov.scot%2Fdata%2Fpopulation-estimates-2011-datazone-linked-dataset&http%3A%2F%2Fpurl.org%2Flinked-data%2Fcube%23measureType=http%3A%2F%2Fstatistics.gov.scot%2Fdef%2Fmeasure-properties%2Fcount&http%3A%2F%2Fstatistics.gov.scot%2Fdef%2Fdimension%2Fage=http%3A%2F%2Fstatistics.gov.scot%2Fdef%2Fconcept%2Fage%2Fall&http%3A%2F%2Fstatistics.gov.scot%2Fdef%2Fdimension%2Fsex=http%3A%2F%2Fstatistics.gov.scot%2Fdef%2Fconcept%2Fsex%2Fall", skip = 8) %>% 
  rename(id = `http://purl.org/linked-data/sdmx/2009/dimension#refArea`) %>% 
  pivot_longer(!c(`Reference Area`, id), names_to = "year", values_to = "population")

df = housing %>% 
  left_join(population) %>% 
  select(-id, area = `Reference Area`) %>% 
  drop_na() %>% 
  mutate(year = as.numeric(year),
         homes_per_100cap = 100 * homes / population)

# split by regions
df_reg = tibble(area = c("Aberdeen City", "Aberdeenshire", "Angus", "Argyll and Bute", "City of Edinburgh", "Clackmannanshire", "Dumfries and Galloway", "Dundee City", "East Ayrshire", "East Dunbartonshire", "East Lothian", "East Renfrewshire", "Falkirk", "Fife", "Glasgow City", "Highland", "Inverclyde", "Midlothian", "Moray", "Na h-Eileanan Siar", "North Ayrshire", "North Lanarkshire", "Orkney Islands", "Perth and Kinross", "Renfrewshire", "Scottish Borders", "Shetland Islands", "South Ayrshire", "South Lanarkshire", "Stirling", "West Dunbartonshire", "West Lothian"),
       region = c("North East", "North East", "North East", "Highlands and Islands","Lothians", "Strathclyde", "Southern", "North East", "Southern", "Strathclyde", "Lothians", "Strathclyde", "Lothians", "North East", "Strathclyde", "Highlands and Islands", "Strathclyde", "Lothians", "North East", "Highlands and Islands", "Highlands and Islands", "Strathclyde", "Highlands and Islands", "North East", "Strathclyde", "Southern", "Highlands and Islands", "Southern", "Southern", "Highlands and Islands", "Strathclyde", "Lothians")) %>% 
  mutate(region = factor(region, levels = c("Highlands and Islands", "North East", "Strathclyde", "Lothians", "Southern")))

df %>% 
  inner_join(df_reg) %>% 
  group_by(area) %>% 
  mutate(label = if_else(year == max(year), as.character(area), NA_character_)) %>%
  ungroup() %>% 
  ggplot(aes(year, homes_per_100cap,
             group = area, colour = area)) +
  geom_line(linetype = 2) +
  geom_label_repel(aes(label = label),
                   nudge_x = 2,
                   na.rm = TRUE) +
  facet_wrap(~region, ncol = 2) +
  labs(title = "How many council homes do local authorities in Scotland provide?",
       subtitle = "Created by @MikeRSpencer with data from statistics.gov.scot",
       x = "Year",
       y = "Homes per 100 people") +
  theme_bw() +
  theme(legend.position = "none",
        text = element_text(size = 15),
        plot.subtitle=element_text(size=10),
        panel.grid.minor = element_blank())