How to Remove State Abbreviations from a Choroplethr Map

Today I will demonstrate how to remove state abbreviations from a choroplethr map. I will also demonstrate how to combine multiple maps into a single image. This is what the final image looks like:

In this case the abbreviations obscure information for the northeast part of the country, so it’s useful to remove them.

Step 1: Create a Map With Abbreviations

The map with abbreviations is fairly straightforward to create. In fact, it is very similar to the map created in the first lesson of my course Learn to Map Census Data in R. Let’s create the map, render it, and then save it as a variable:

library(choroplethr)
library(choroplethrMaps)

data(df_pop_state)
with_abbr = state_choropleth(df_pop_state,
                title = "2012 State Population Estimates",
                legend = "Population")

with_abbr

w-abbr

Step 2: Learn About Object-Oriented Choropleths

To make the map without abbreviations we need to use the object oriented features of choroplethr. This is much easier than it sounds; in fact, all that the function state_choropleth does is create a StateChoropleth object:

> state_choropleth
function (df, title = "", legend = "", num_colors = 7, zoom = NULL) 
{
    c = StateChoropleth$new(df)
    c$title = title
    c$legend = legend
    c$set_num_colors(num_colors)
    c$set_zoom(zoom)
    c$render()
}

If this type of code is new to you, then I recommend taking a few minutes to run it yourself from an R command line.

Step 3: Create a Map Without Abbreviations

The StateChoropleth object has a member variable called show_labels, which defaults to TRUE. You can see it in the source code here. If we set it to FALSE before calling render() then the map will render without labels.

c = StateChoropleth$new(df_pop_state)
c$title = "2012 State Population Estimates"
c$legend = "Population"
c$set_num_colors(7)
c$set_zoom(NULL)
c$show_labels = FALSE
without_abbr = c$render()

without_abbr

Step 4: Merge the Maps

A common task when doing data analysis is to compare two maps side by side. We can accomplish this with the grid.arrange function in the gridExtra package:

library(gridExtra)
grid.arrange(with_abb, without_abb)

In Other News

Vivek Patial was kind enough to mention choroplethr in his recent talk Display of Geographic Data in R.
I have been mentioning for a while that I want to create an online course. As a concrete step in that direction I created my first YouTube video: How to Make a State Choropleth Map in R. Feedback is welcome!
KDnuggets, one of the top data mining blogs, was kind enough to cover my free course “Learn to Map Census Data in R”.

5 comments

Lung-Chang Chien says August 20, 2015

Hi Ari,

Those maps look weird. How to show the U.S map proportionally?

Ari Lamstein says August 20, 2015

You’re right – they look wierd because there’s no way to apply projections to maps with insets in ggplot2 2. I could have just used the continental US for my example, but it would have made the code slightly more complicated. In this case I chose simplicity of code over quality of the map, because I wanted the methodology to be as easy to follow as possible. See this post for a full treatment of the topic of projections in choroplethr: https://arilamstein.com/blog/2015/07/23/administrative-level-1-maps-and-projections/

Lung-Chang Chien says August 20, 2015

I see. Thank you!

Ari Lamstein says August 20, 2015

My pleasure. I’m hoping to implement a workaround for the projections-with-insets issue in the next version of choroplethr.

Ram says November 2, 2015

Hi Ari,

Good to know that we can remove the state abbreviations from the map. It is helpful. Thank you.

Question: Is there a way to print the state abbreviations using a smaller font size?

Thanks
Ram