Thematic Maps

Author

Josef Fruehwald

Published

March 23, 2023

Loading Packages

New for today

library(tmap)
library(gifski)

Old news

library(tidyverse)
library(units)
library(sf)
library(terra)
library(tigris)
library(mapview)

Downloading some data

lex_councils <- read_sf("https://services1.arcgis.com/Mg7DLdfYcSWIaDnu/arcgis/rest/services/Council_District/FeatureServer/0/query?outFields=*&where=1%3D1&f=geojson")
lex_bike <- read_sf("https://services1.arcgis.com/Mg7DLdfYcSWIaDnu/arcgis/rest/services/Bicycle_Network/FeatureServer/0/query?outFields=*&where=1%3D1&f=geojson")
ky <- counties(state = "KY", cb = T)
lex <- ky |> filter(NAME == "Fayette")

Map Plots

Default plotting

lex_councils |> 
  mutate(area = st_area(geometry))->
  lex_councils
plot(lex_councils)
Warning: plotting the first 10 out of 13 attributes; use max.plot = 13 to plot
all

mapview

mapview(lex_councils)

ggplot2

ggplot()+
  geom_sf(data = lex_councils)

tmap

Seems to have a number of defaults set to be more pleasant for maps.

tm_shape(lex_councils)+
  tm_fill()

tm_shape(lex_councils)+
  tm_borders()

tm_shape(lex_councils)+
  tm_fill()+
  tm_borders()

There are also some additional layers that are very map specific.

tm_shape(lex)+
  tm_fill()+
tm_shape(lex_bike)+
  tm_graticules()+
  tm_lines(col = "darkgreen")+
  tm_compass(type = "rose", 
             position = c(0.6, 0.7))+
  tm_scale_bar()
1
“graticule” is the longitude and latitude lines
2
There are a few different compass symbols that can be added
3
Scalebar

“mapping” data, in the plotting sense

tm_shape(lex)+
  tm_fill()+
tm_shape(lex_bike)+
  tm_lines(col = "Type_Facility")+
  tm_facets(by = c("Status"), free.coords = F)+
  tm_style("col_blind")+
  tm_scale_bar()

Animated Maps

tm_shape(lex) +
  tm_fill() +
tm_shape(lex_bike)+
  tm_lines()+
  tm_facets(along = "YearComplete", free.coords = F) ->
  bike_anim

This was not successful

tmap_animation(bike_anim, filename = "bike_anim.gif", delay = 25)

tmap_animation(bike_anim2, filename = "bike_anim2.gif", delay = 40)
Making it work 
lex_bike |> 
  replace_na(list(YearComplete = min(lex_bike$YearComplete, na.rm = T)))->
  lex_bike

min_year <- lex_bike |> filter(YearComplete >0) |> pull(YearComplete) |> min()
max_year <- lex_bike |> filter(YearComplete >0) |> pull(YearComplete) |> max()

tibble(
  anim_year = min_year:max_year
) |>
  left_join(
    lex_bike, 
    by = join_by( anim_year >= YearComplete)) |>
  st_sf() ->
  lex_bike_to_anim

tm_shape(lex)+
  tm_fill()+
tm_shape(lex_bike_to_anim)+
  tm_lines(col = "Type_Facility")+
  tm_facets(along = "anim_year", free.coords = F)+
  tm_layout(
    title = "Lexington Bike Network",
    frame = FALSE
  ) +
  tm_style("col_blind")->
  bike_anim2
1
I had to replace missing completion years with the earliest available completion year
2
Creating a data frame of all years between the first completion year and the last
3
This is the fun and tricky part
4
The result was technically not a spatial data frame.

Interactive Maps

lex_pop <- read_sf("https://services1.arcgis.com/Mg7DLdfYcSWIaDnu/arcgis/rest/services/Census2020_Precinct_P3_Race_18andOver/FeatureServer/0/query?outFields=*&where=1%3D1&f=geojson")
tmap_mode("view")
tm_shape(lex_pop)+
  tm_fill(col = "P0030001", alpha = 0.7, style = "cont")+
  tm_style("col_blind")

Works with Rasters too

download.file( 
  "https://ky.box.com/shared/static/urm3ecx8v0zi3ojxe6rpg8j586vs0qqa.zip", 
  destfile = "data/elev.zip" 
  ) 
unzip(zipfile = "data/elev.zip", exdir = "data")
pot_elev <- rast("data/N092E301_DEM_Phase2.tif")
tm_shape(pot_elev)+
  tm_raster(alpha = 0.6)
Warning: ignoring unrecognized unit: US survey foot
tmap_mode("plot")
tm_shape(pot_elev)+
  tm_raster(style = "equal")+
  tm_style("col_blind")
Warning: ignoring unrecognized unit: US survey foot