R for Business Analytics – Introduction to Geographical Maps


R is a powerful programming language that is widely used in business analytics, including the creation of geographical maps. In R, the most popular package for creating maps is ggplot2, which is built on the grammar of graphics and allows for the creation of highly customizable maps. Another package that is used often for making maps is leaflet.

To create a basic map using ggplot2, you would first need to install and load the package, and also the package maps or mapdata which contains the shapefiles that are used to create the maps.



Once the package is loaded, you can use the ggplot() function to create a base map, and then add layers to the map using the geom_map() function. For example, to create a map of the United States with each state colored according to its population, you would use the following code:

ggplot(data = map_data("state"), aes(x = long, y = lat, map_id = region)) +
geom_map(aes(fill = population), color = "white")


This will create a choropleth map with each state filled with a color according to the population data.

On the other hand, using leaflet package is also very simple and its syntax is straightforward. The package allows you to easily create interactive maps using a simple syntax. You can create a simple map by using the leaflet() function, and then add various layers such as markers, polygons, and pop-ups using other functions. For example, to create a map centered on New York City with a marker at Times Square, you would use the following code:

leaflet() %>% addTiles() %>%
setView(-73.9854, 40.7488, zoom = 12) %>%
addMarkers(lng = -73.9857, lat = 40.7577,
popup = "Times Square")


Both ggplot2 and leaflet are great packages for creating geographical maps in R. ggplot2 is more suited for static maps and is great for creating publications-ready maps, while leaflet is great for creating interactive maps and web mapping applications.

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R for Business Analytics – Introduction to Geographical Maps

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