How to create a choropleth map

This tutorial walks you through the steps to prepare and import data for a  choropleth map in Datawrapper. We have a separate, equally short tutorial on how to create a symbol map

A choropleth map is a map in which areas (like states or countries) are filled with colors according to your data. Let's assume you want to map unemployment rates in the US. A choropleth map is perfect for that: Each county will be filled with a color:


Choosing a map

To create a map, go to and select Choropleth map.

The first question that Datawrapper will ask you after you've decided on a choropleth map, is: "What type of map do you want to create?" Even if you know that you want a US map, you can still decide between different levels, e.g. states, counties, district courts or congressional districts and sometimes even different years. We know that we want to make a US county map, so we'll search for "USA", click on "USA » counties (2018)" and then click "Proceed":


Preparing the data

Before we can visualize the unemployment rates, we need to bring it in the right format. Datawrapper will need a table with at least two columns: 

  1. The geocode of each region you want to fill with a color. Most often, that's the name, like county names. But for some regions, we have specific IDs, e.g. the FIPS-Code for counties in the US (which we'll use). Each map will have specific geocodes, and it's best to check which ones are accepted at the beginning of your data preparation process. You'll find the accepted geocodes above the table in step 2:

  2. The value for each region. The values can be percentages (43.4%), full numbers (38430), or categories (yes/no/maybe). Our table will have the column "Unemployment Rate" with numerical values.

Here is our table (data is from the  US Bureau of Labour Statistics, August 2017). As you can see, we have a third column, "County Name". In fact, we can have as many columns as we like, as long as one of them has a geocode and one of them has numeric values. Extra information like the name of the county can be useful for tooltips, so we want to keep them in our table:

FIPS Code County Name Unemployment Rate
01001 Autaga County 4.0
01003 Baldwin County 3.8
01005 Barbour County 
etc. etc.  etc.

Tip: You can speed up the process to import your data by firstly going into Datawrapper, look for the map you want to use and then copy the names (e.g. for countries, provinces, regions) which are used by Datawrapper into your own data table. This will make the import process later much faster. We are usually using English names for all regions at this time. Plus, we use a specific form of writing. 

We are aware that in some regions the same place might be written in different ways (e.g. "Saint James" or "St. James" or "St James). Datawrapper, at this stage of development, will only understand one specific way of writing. So, by copying the names from Datawrapper the process will be faster.


Importing the data

There are three ways to import your table with names/ID and values: 

  1. Write your values directly into the Datawrapper table. This takes a long time, so we don't recommend it for maps with lots of areas (like our US county map). 
  2. Click on "Import Data", then copy & paste your data into the table that appears. That is the most convenient option and you'll probably use it most often. 
  3. Click on "Import Data", then "Click here to upload a CSV file" and upload a CSV. If you're a fan of CSVs (e.g. because you export them out of R or Python), this will be your preferred option.

If something's wrong with your data, our map feature will tell you immediately and will let you correct it on the spot. 



If you successfully imported the data, you will see the following dialogue: 

Click "GO!", check the data in the table again and then click "Proceed" to get to the next screen, where you can customize your map. We will cover this part in the next tutorial: Customizing your choropleth map.