Making Dot and Bubble Maps with ggplot

This lesson is called Making Dot and Bubble Maps with ggplot, part of the Mapping with R course. This lesson is called Making Dot and Bubble Maps with ggplot, part of the Mapping with R course.

Transcript

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View code shown in video

library(tidyverse)
library(tidycensus)
library(tigris)
library(janitor)
library(sf)
library(scales)

oregon <-
  states() |>
  clean_names() |>
  filter(name == "Oregon")

oregon_places <-
  read_sf("https://raw.githubusercontent.com/rfortherestofus/mapping-with-r-v2/refs/heads/main/data/oregon_places.geojson")

oregon_places

options(scipen = 999)

ggplot() +
  geom_sf(data = oregon, fill = "transparent") +
  geom_sf(data = oregon_places) +
  theme_void()

ggplot() +
  geom_sf(data = oregon, fill = "transparent") +
  geom_sf(
    data = oregon_places,
    aes(size = population),
    alpha = 0.5
  ) +
  scale_size_continuous(range = c(1, 15), label = comma_format()) +
  theme_void()

languages_spoken <-
  get_acs(
    geography = "county",
    state = "OR",
    variable = c(
      spanish = "S1601_C01_004",
      other_indo_european = "S1601_C01_008",
      asian_pacific_islander = "S1601_C01_012",
      other = "S1601_C01_016"
    ),
    geometry = TRUE
  ) |>
  clean_names() |>
  select(variable, name, estimate)

languages_spoken

ggplot() +
  geom_sf(data = languages_spoken, aes(fill = estimate)) +
  scale_fill_viridis_c() +
  facet_wrap(vars(variable)) +
  theme_void()

languages_spoken_dots <-
  languages_spoken |>
  filter(name == "Washington County, Oregon") |>
  as_dot_density(
    value = "estimate",
    values_per_dot = 100,
    group = "variable"
  )

languages_spoken_dots

ggplot() +
  geom_sf(data = languages_spoken_dots, aes(color = variable)) +
  geom_sf(
    data = languages_spoken |>
      filter(name == "Washington County, Oregon"),
    fill = "transparent"
  ) +
  theme_void()

ggplot() +
  geom_sf(data = languages_spoken_dots, aes(color = variable)) +
  geom_sf(
    data = languages_spoken |>
      filter(name == "Washington County, Oregon"),
    fill = "transparent"
  ) +
  theme_void() +
  facet_wrap(vars(variable))

Your Turn

Turn your refguees choropleth map from before into a bubble map

Import data on refugees by country with the following code:

refugees_by_country <-
  read_sf(
    "https://raw.githubusercontent.com/rfortherestofus/mapping-with-r-v2/refs/heads/main/data/refugees.geojson"
  )

Use this code to import centroids (i.e. one point in the center of each country)

refugees_country_centroids <-
  read_sf(
    "https://raw.githubusercontent.com/rfortherestofus/mapping-with-r-v2/refs/heads/main/data/refugees_country_centroids.geojson"
  )

Learn More

The example maps I showed in this lesson are below:

A related type of map is a spike map, which uses height to show some outcome. Here is an example from Der Spiegel showing election outcomes in Germany.