Merging the Legend from ggpattern and ggplot2

When working with maps, it’s not uncommon to encounter regions that require special treatment, such as countries with unique characteristics like stripes. In this case, we’ll explore how to merge the legend of ggplot2 and ggpattern packages.

Introduction to ggpattern and ggplot2

The ggpattern package provides an easy-to-use interface for creating patterns on maps using ggplot2. On the other hand, ggplot2 is a powerful data visualization library that offers a wide range of mapping tools. By combining these two libraries, we can create visually appealing maps with custom patterns.

Creating a Map with Custom Patterns

Let’s start by importing the required libraries and creating a sample map:

library(tidyverse)
library(ggplot2)
library(ggpattern)

world_map <- map_data(map = "world")

data <- data.frame(country_map = unique(world_map$region))
data$mean <- -1
data$mean[data$country_map == "Russia"] <- 1

# Create a pattern based on the mean value
data$group <- cut(data$mean, breaks = c(-Inf, 0, Inf), labels = c("negative", "positive"))
data$pattern <- ifelse(data$mean < 0, "stripe", NA)

In this example, we create a sample map of the world and assign a random value to each region. We then use the cut() function to categorize these values into three groups: negative, positive, or undefined (NA). Based on these categories, we create a pattern using the ggpattern package.

Adding Patterns to the Map

To add patterns to our map, we’ll use the geom_map_pattern() function from ggplot2. This function allows us to specify a pattern for each region based on the group column in our data frame:

# Add patterns to the map
ggplot(data) + 
  geom_map(aes(map_id = country_map, fill = fct_rev(group)), map = world_map) + 
  geom_polygon(data = world_map, aes(x = long, y = lat, group = group), colour = 'grey', size = 0, fill = NA) + 
  expand_limits(x = world_map$long, y = world_map$lat) + 
  theme_void() +
  geom_map_pattern(
    data = data,
    map = world_map,
    aes(map_id = country_map, pattern = pattern),
    pattern_fill = "black",
    fill = NA,
    pattern_density = 0.1,
    pattern_angle = 30,
    pattern_spacing = 0.02
  )

In this example, we add a layer to our map using geom_map_pattern(), which creates a pattern for each region based on the pattern column in our data frame.

Merging the Legend

Now that we have patterns added to our map, let’s explore how to merge the legend from ggplot2 and ggpattern. One approach is to restrict plot limits using the coord_sf() function. This allows us to adjust the size of our map and control the extent of the legend.

Restricting Plot Limits

To create a larger map, we can use the st_bbox() function from the sf package to determine the bounding box of our map. We then set this bounding box as the plot limits using the xlim() and ylim() functions:

# Create a larger map
world_sf <- ne_countries(returnclass = "sf")

library(sf)
world_sf |> 
  mutate(is_russia = name_en == 'Russia') |> 
  ggplot() +    
  geom_sf_pattern(
    aes(fill = is_russia, pattern = is_russia), 
  ) +
  coord_sf(
    crs = '+proj=robin',
    xlim = c(-16810131 / 180 * 135, 16810131 / 180 * 178.5),
    ylim = c(-8625155 / 90 * 56, 8343004 / 90 * 84)
  )

In this example, we create a larger map by adjusting the plot limits to include more of the world.

Conclusion

By combining ggplot2 and ggpattern, we can create visually appealing maps with custom patterns. To merge the legend from these two libraries, we can restrict plot limits using the coord_sf() function. This allows us to control the extent of the legend and ensure that it appears correctly on our map.

References

Data Science Blog (2023)
rnaturalearth (2023)

Additional Resources

For more information on ggpattern and its capabilities, please refer to the official documentation: https://ggplotology.github.io/ggpattern/reference/geom_map_pattern.html

Similarly, for more details on using sf with ggplot2, please visit: Stack Overflow

Last modified on 2024-11-03