special topics

map data

plotting boundaries

There is a simple way to plot maps with ggplot. The map data comes with ggplot2! Let’s have a look. See below some of the data sets included. Options included with ggplot are: world, world2, usa, state (US), county (US), nz, italy, and france. geom_polygon() is useful for plotting these, at (at least to me) seems more intuitive than geom_map().

head(map_data("world"))
##        long      lat group order region subregion
## 1 -69.89912 12.45200     1     1  Aruba      <NA>
## 2 -69.89571 12.42300     1     2  Aruba      <NA>
## 3 -69.94219 12.43853     1     3  Aruba      <NA>
## 4 -70.00415 12.50049     1     4  Aruba      <NA>
## 5 -70.06612 12.54697     1     5  Aruba      <NA>
## 6 -70.05088 12.59707     1     6  Aruba      <NA>

head(map_data("state"))
##        long      lat group order  region subregion
## 1 -87.46201 30.38968     1     1 alabama      <NA>
## 2 -87.48493 30.37249     1     2 alabama      <NA>
## 3 -87.52503 30.37249     1     3 alabama      <NA>
## 4 -87.53076 30.33239     1     4 alabama      <NA>
## 5 -87.57087 30.32665     1     5 alabama      <NA>
## 6 -87.58806 30.32665     1     6 alabama      <NA>

head(map_data("county"))
##        long      lat group order  region subregion
## 1 -86.50517 32.34920     1     1 alabama   autauga
## 2 -86.53382 32.35493     1     2 alabama   autauga
## 3 -86.54527 32.36639     1     3 alabama   autauga
## 4 -86.55673 32.37785     1     4 alabama   autauga
## 5 -86.57966 32.38357     1     5 alabama   autauga
## 6 -86.59111 32.37785     1     6 alabama   autauga

head(map_data("france"))
##       long      lat group order region subregion
## 1 2.557093 51.09752     1     1   Nord      <NA>
## 2 2.579995 51.00298     1     2   Nord      <NA>
## 3 2.609101 50.98545     1     3   Nord      <NA>
## 4 2.630782 50.95073     1     4   Nord      <NA>
## 5 2.625894 50.94116     1     5   Nord      <NA>
## 6 2.597699 50.91967     1     6   Nord      <NA>

Cool! We can see that lat, lon, group, order, region, and subregion are included. That makes plotting easy. Note that coord_map() can help preserve aspect ratios:

ggplot(map_data("world")) +
  geom_point(aes(x = long, y = lat, color = group), size = 0.5) +
  theme_void() +
  coord_map()

Note that we can use coord_map() to do some pretty cool things!

ggplot(map_data("world")) +
  geom_point(aes(x = long, y = lat, color = group), size = 0.5) +
  theme_void() +
  coord_map(projection = "albers", lat0 = 39, lat1 = 45)

We can use filtering to produce maps of specific regions.

ggplot() +
  geom_polygon(
    data = filter(map_data("county"), region == "minnesota"),
    aes(x = long, y = lat, group = subregion, fill = subregion),
    color = "black"
  ) +
  theme_void() +
  coord_map()

further reading

For more on plotting maps in R: datavizplyr

For more advanced map plotting: R Spatial

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