Symbol Point Map with Datawrapper

We first introduced you to the free and easy-to-learn Datawrapper tool in Chapter 7: Chart Your Data. It’s also offers powerful features to create different types of maps, with professional-looking design elements. With Datawrapper you can start to work right away in your browser, with no account required unless you wish to save and share your work online.

In this section, you’ll learn how to create a symbol point map, which displays specific locations using variable-sized shapes or colors to represent their data values. Our sample symbol map displays about 300 major US cities as point locations with two variables: the 2019 estimated population (using circle size) and the percent change in population since 2010 (using circle color), as shown in Figure 8.25. Remember that we use point data to create symbol maps, but polygon data to create choropleth maps, and you’ll learn how to design those with Datawrapper in the subsequent section. Later in the book, we’ll explain how to embed your interactive Datawrapper maps on the web in Chapter 10.

Figure 8.25: Symbol point map of US city population growth with Datawrapper. Explore the interactive version.

Datawrapper splits the process of creating a map into four steps: select map, add data, visualize, then publish and embed. To create your own symbol point map, follow this tutorial.

  1. Open the US Cities Population Change 2010-2019 data in Google Sheets. Read the notes to understand its origin and some data issues. We downloaded city population data for 2010-2019 from the US Census. But during this time period, some cities were newly incorporated or merged with outlying areas, which skews their population data over time. Also, we collected data for 5 major cities in Puerto Rico, a US territory, but they do not appear in the Datawrapper map for reasons explained in step 4.

Good maps often require cleaning up messy data as described in Chapter 5. In our spreadsheet we narrowed the original list down to about 300 cities with more than 100,000 residents in either 2010 or 2019. Also, since we’re relying on Datawrapper to correctly identify place names, we combined city and state into one column to improve geocoding accuracy. Learn more about place name geocoding at the Datawrapper Academy. Also, we created a new column named Percent Change, which we calculated this way: (2019 - 2010) / 2010 * 100.

  1. Go to File > Download in CSV format to save the data to your local computer.

  2. Open Datawrapper, click the New Map button, and select Symbol map as shown in Figure 8.26.

Start to create a symbol map in Datawrapper.

Figure 8.26: Start to create a symbol map in Datawrapper.

  1. In the Select your map screen, enter USA and search for options. Note that we selected USA > States* as our best current option, because USA > States and Territories does not yet correctly display geocoded locations for Puerto Rico, a US territory. Proceed to the next screen.

  2. In the Add your data screen, click the Import your dataset button. In the next window, click the Addresses and Place Names button because our data is organized this way. In the Import window, click to Upload a CSV file, and select the file you downloaded above.

  3. In the Match your columns screen, select the City-State column to be Matched as Address, then scroll down to click the Next button, as shown in Figure 8.27. In the next screen click Go, then see your geocoded data displayed on a map in the following screen.

Select the City-State column to be matched as the Address.

Figure 8.27: Select the City-State column to be matched as the Address.

  1. Click the Visualize button to Refine your map. Our goal is to display two variables: 2019 population as the circle size, and percent change as the circle color. Under Symbol shape and size, select the circle symbol, to be sized by Pop Estimate 2019, with a maximum symbol size of 25 pixels. Under Symbol colors, select the Percent Change 2010-2019 column, as shown in Figure 8.28.
Refine your map by selecting data to display symbol shapes, sizes, and colors.

Figure 8.28: Refine your map by selecting data to display symbol shapes, sizes, and colors.

  1. If you wish to customize the color palette and intervals to match our example, click the wrench symbol next to the palette. Click the Import colors button and paste in five hexadecimal codes from ColorBrewer, as described in the Choropleth Design section. The first code is dark pink, followed by a 4-class sequential green: #d01c8b,#bae4b3,#74c476,#31a354,#006d2c. See Figure 8.29.
Create a new color palette by importing five hexadecimal color codes from ColorBrewer.

Figure 8.29: Create a new color palette by importing five hexadecimal color codes from ColorBrewer.

  1. To continue customizing intervals to match our example, set the steps to 5 and Custom. Manually type in custom intervals for below 0% (bright pink), 0 to 5% (light green), and so forth up the scale. Click the More options button, and under Legend, change Labels to custom, and click each label to edit the text that appears on the map menu, as shown in Figure 8.30. Learn more about these options in the Datawrapper Academy post on customizing your symbol map.
Customize the interval ranges and edit the legend.

Figure 8.30: Customize the interval ranges and edit the legend.

  1. Click the Annotate tab to insert a title, source notes, credits, and customize the tooltips as described by Datawrapper Academy. Proceed to the Publish & Embed screen to share your map online.

For assistance and additional options, see the Datawrapper Academy support pages on symbol maps.

Now that you’ve created a symbol point map with Datawrapper, in the next section we’ll build our skills with this tool to create a choropleth map.