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Installation
You can install the development version of Ukmaps such as Sun:
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)
What 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 cards use functions that collect the data set to keep the package size small.
Land 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 provincial 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$n), by = 1)) +
labs(title = "How many R's in each county name?") +
theme_minimal(base_size = 13)
How many R’s in each LAD name? Local Districts (LAD) (Local Government District (LGD) in Noord -Irland)
d <- lads() %>%
mutate(n = stringr::str_count(lad_name, "[rR]"))
ggplot(d) +
geom_sf(aes(fill = n, geometry = geometry), color = "white") +
scale_fill_gradient(low = "#165976", high = "#d04e66", name = "R's",
breaks = seq(0, max(d$n), by = 1)) +
labs(title = "How many R's in each LAD name?") +
theme_minimal(base_size = 13)
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