Datawrapper is an easy to use, statistics oriented, graphing program that will allow you to create charts, maps, and graphs. For my application in a digital history project, all three of those tools will come in handy. Signing up was easy, you just put in the standard email and password and boom, you’re in.

The tutorial I followed from my Digital History class syllabus had me begin by creating a bar graph. The tutorial was very simple to follow and provided me with a basic understanding of how Datawrapper worked for charting data. In the ‘visualize’ section of Datawrapper there are many ways that you can choose to display your data. I played around for a bit in this section just to see what each of the selections looked like and how it effected the interpretation of the chart. Once everything is in place and you have chosen your color scheme and layout you can publish and embed your chart.

At this point I thought that the tutorial had diverged from Datawrapper. The page that was displayed to me after proceeding to ‘Publish’ said that my graph would be emailed to me while the tutorial had the ability to embed the chart. This confused me because after checking my email I confirmed that I did not have the chart I had just created. All that was emailed to me was a request to confirm my email. Once I had done that, I refreshed the page on Datawrapper and was relieved to see that my page now matched the tutorial. To avoid that minor headache in the future I made the note to myself, once you sign up, confirm your account before you proceed with anything else.

From there it was smooth sailing to embed the chart into this post. Check it out below!

After the bar chart, the tutorial moved on to a line graph. While the basic instructions remained the same as before, the method of data entry changed. For the bar chart I copied and pasted the data into Datawrapper, this time the tutorial explained how to link the data from a spreadsheet. Each section of the tutorial adds something new for the user while also allowing for repetition of certain actions to build connections for the user with the program. The hardest part of the line graph for me was figuring out the range highlights and annotations. Once that process clicked in my head it made everything easier.

The final section of the tutorial covered map making. Because my digital history project will most likely deal with territory loss through colonization, mapping will play a key role. The mapping section of the Datawrapper tutorial was by far the hardest to complete. I don’t know if the issues I was having were due to not being able to download the data as a .csv file or if Datawrapper has undergone updates since the tutorial was first posted. The instructions were out of order for how the mapping is done now and I had to skip around to find the sections that were relevant to what the tutorial wanted me to work on. In the end though, I was able to get the heat map to work.

Datawrapper is incredible free software that will be useful not just in this digital history class but also throughout graduate school. The ability to take quantifiable data and display it quickly and professionally through maps, charts, and graphs is an incredible tool in a digital historian’s bag. The tutorial by Lena Groeger, while clearly written, could possibly use an update to keep up with Datawrapper updates to their U.I. Overall, I was very impressed by how intuitive creating data visualizations was.