17 Less Basic Maps

The code in this chapter requires the following packages:

library(tidyverse)          # for syntactic manipulation of tables
library(rnaturalearth)      # world map data from Natural Earth
library(rnaturalearthdata)  # companion package of rnaturalearth

and the following table for storms in 1975:

storms75 <- filter(storms, year == 1975)

17.1 More mapping approaches

Another interesting map graphing approach is by using map-objects from the package "rnaturalearth".

We use the ne_countries() function—from "rnaturalearth"—to get world country polygons. In the following command, we specify a medium scale resolution, and a returned object of class "sf" (simple features).

# another world data frame
world_df <- ne_countries(scale = "medium", returnclass = "sf")
class(world_df)

## [1] "sf"         "data.frame"

Now we can pass world_df to ggplot(), and use geom_sf() which is the function that allows us to visualize simple features objects "sf".

# another world map (from "rnaturalearth")
ggplot(data = world_df) +
  geom_sf() + 
  theme_bw()

One advantage of using this other mapping approach is that we can zoom-in without having distorted polygons. To focus on a specific region, we set the x-axis and y-axis limits with the coord_sf() function. Again, for coding convenience, let’s create another "ggplot" object

# ggplot object to be used as a canvas
gg_world2 <- ggplot(data = world_df) +
  geom_sf() + 
  coord_sf(xlim = c(-150, 0), ylim = c(0, 90), expand = TRUE) +
  theme_bw()

gg_world2

Now let’s add the storms:

gg_world2 + 
  geom_path(data = storms75,
            aes(x = long, y = lat, color = name),
            lineend = "round", size = 2, alpha = 0.8)

17.1.1 Storms from 1975 to 1980

As a simple experiment, let’s graph storms between 1975 and 1980 (six years). First we create a dedicated data table storms_75_80 to select the rows we are interested in:

storms_75_80 <- filter(storms, year %in% 1975:1980)

And then we can use facet_wrap(~ year) to graph storms by year:

gg_world2 +
  geom_path(data = storms_75_80,
             aes(x = long, y = lat, group = name),
             lineend = "round") +
  xlim(c(-150, 0)) + 
  ylim(c(0, 90)) + 
  facet_wrap(~ year)