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Creating a bivariate choropleth color scheme

I recently created an infographic on the cost of child care in the U.S. for my graphic design in cartography class this semester. One of the assignment requirements was to include a bivariate map in the visual story.

A bivariate map is one that shows two different pieces of data on one map. You can also have multivariate maps, showing more than two variables (my personal fave is pop vs. soda). Bivariate choropleth maps shade different units (in my case, states - but could be counties or countries) different colors based on these variables.

Bivariate choropleth maps are difficult to understand, and thus difficult to make. Truth is, I don’t even think this map should be a bivariate map. You could probably better tell this story by simply mapping what percentage of people’s income goes towards child care.

But, alas, that is beside the point because I am here today to tell you how I created my bivariate choropleth color scheme. If you don’t know much about bivariate choropleth maps or want to make one yourself, I highly recommend Josh Stevens’ tutorial. It’s what I used to help me through the process, and it worked like a charm.

Creating a bivariate choropleth color scheme

First, you could start by looking at other people’s schemes. Josh’s tutorial has a bunch of great starter schemes at the bottom of the post. As far as I know, no one has intellectual property of choropleth color schemes, and maybe someone else spent a lot of time thinking about a great scheme - you can benefit from their hard work.

Here’s the one that I ended up with:

Here are some rules for a good bivariate color scheme:

1. Don’t use more than 9 classes. Your legend should look like a 3x3 grid. More colors make it harder to distinguish between classes. The main idea here is for the map reader to think something like “oh it’s high in this variable but low in the other one” or “it’s high in both” but not necessarily for them to pull specific statistics out of your map. If you want them to look at specific statistics, give them a table.

2. Each row and column should stand as its own choropleth color scheme. If you look at each row and column of the above color scheme (even the diagonal one!), they could each stand as their own univariate color scheme. For example:

Would totally work on a univariate map. From left to right, the color is changing in value (aka how dark it is). Since darker typically = more, this means we can discern that as we go from pink to light purple to dark purple, there is more of that variable present. When I was playing around with the colors, I would cover up two of the rows and just look at one to see if it made sense (lighter to darker colors meaning increase in that variable). Same with the columns.

3. Make sure the colors are distinguishable. Don’t have two colors so close together that you won’t be able to tell which one is which on the map. Try testing out your scheme on the map and identifying which state has which color. I found it helpful to make the darkest color darker than I thought it needed to be.

4. Don’t reinvent the wheel. No need to create something from scratch. I tweaked one from Aileen Buckley’s 2013 NACIS presentation (slide 20 has a bunch of ArcMap schemes). Josh’s tutorial has a bunch of starter schemes at the bottom. If you find colors in an image you like on the internet, you can always take a screenshot or save the image, then use the eyedropper tool in Illustrator to pull out the colors you want.

5. Use gradients to find the middle colors. I found it wasn’t too hard to pick corner colors, but I needed a way to find the middle colors to make sure they were visually in the middle. So I used the gradient tool in Illustrator to create a rectangle with a gradient using the two corner colors. Then you go to Object > Expand and you can basically turn this rectangle into a bunch of tiny rectangles. You can then use the eyedropper tool to grab the color in the middle of the gradient and that’s your middle color of your scheme. MAGIC.