Plotting UK Maps with ggplot2 v0.0.4

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Installation

You can install the development version of ukmaps like so:

remotes::install_github("pachadotdev/ukmaps")

Examples

Yes/No map of London administrative areas:

library(ukmaps)
library(dplyr)
library(ggplot2)

d <- boundaries %>%
  mutate(
    region_name = if_else(is.na(region_name), "Notr Available", region_name),
    is_london = if_else(region_name == "London", "Yes", "No")
  )

pal <- c("#165976", "#d04e66")

ggplot(d) + 
  geom_sf(aes(fill = is_london, geometry = geometry), color = "white", linewidth = 0) +
  scale_fill_manual(values = pal, name = "Is this London?") +
  labs(title = "Map of England with Administrative Boundaries") +
  theme_minimal(base_size = 13)

Which part of London is Barnet?

d <- boundaries %>%
  filter(region_name == "London") %>%
  mutate(is_barnet = if_else(lad_name == "Barnet", "Yes", "No"))

pal <- c("#165976", "#d04e66")

ggplot(d) + 
  geom_sf(aes(fill = is_barnet, geometry = geometry), color = "white") +
  scale_fill_manual(values = pal, name = "Is this Barnet?") +
  labs(title = "Which part of London is Barnet?") +
  theme_minimal(base_size = 13)

Which part of London is Golders Green?

d <- boundaries %>%
  filter(region_name == "London") %>%
  mutate(
    is_golders_green = if_else(ward_name == "Golders Green", "Yes", "No")
  )

pal <- c("#165976", "#d04e66")

ggplot(d) + 
  geom_sf(aes(fill = is_golders_green, geometry = geometry), color = "white") +
  scale_fill_manual(values = pal, name = "Is this Golders Green?") +
  labs(title = "Which part of London is Golders Green?") +
  theme_minimal(base_size = 13)

The following maps use functions that aggregate the dataset to keep the package size small.

Country level map of the UK:

pal <- c("#165976", "#365158", "#d04e66", "#ffd613")

# country() aggregates the map to country level
ggplot(country()) + 
  geom_sf(aes(fill = country_name, geometry = geometry), color = "white") +
  scale_fill_manual(values = pal, name = "Country") +
  labs(title = "Map of England with Country Boundaries") +
  theme_minimal(base_size = 13)

How many R’s in each county name?

# number of R's in county names
d <- counties() %>%
  mutate(n = stringr::str_count(county_name, "[rR]"))

# region() aggregates the map to country level
ggplot(d) + 
  geom_sf(aes(fill = n, geometry = geometry), color = "white") +
  scale_fill_gradient(low = "#165976", high = "#d04e66", name = "R's",
                      breaks = seq(0, max(d$n), by = 1)) +
  labs(title = "How many R's in each county name?") +
  theme_minimal(base_size = 13)

How many R’s in each LAD name? Local Authority Districts (LAD) (Local Government District (LGD) in Northern Ireland)

d <- lads() %>%
  mutate(n = stringr::str_count(lad_name, "[rR]"))

ggplot(d) + 
  geom_sf(aes(fill = n, geometry = geometry), color = "white") +
  scale_fill_gradient(low = "#165976", high = "#d04e66", name = "R's",
                      breaks = seq(0, max(d$n), by = 1)) +
  labs(title = "How many R's in each LAD name?") +
  theme_minimal(base_size = 13)

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