Jared Whalen, Axios, will speak about batch-creating Datawrapper visualizations

We’re excited to announce that Jared Whalen will speak at our Unwrapped conference about how Batch chart creation with Datawrapper.

Jared is a data visual journalist, designer and web developer on the Axios Visuals team. He works with Datawrapper and its API regularly to make charts and maps and find ways to improve the graphic team’s workflow.

Time to ask him some questions:

Jared, what will you talk about at Unwrapped?

Axios publishes newsletters in multiple cities, and it is often the case that multiple locals will want a chart using the same dataset. Creating a chart manually for each local was unsustainable, especially as Axios expands into more cities. So I created a workflow using Bash and R that automates most of the work.

Using DatawRappr, an R wrapper for Datawrapper’s API, the script takes a base chart or map and iterates over a tidy dataset to create and publish a unique visual for each series. It also uses a templating pattern to update text fields like the title, description, and alt text. After creating the batch, a reference sheet with each chart’s embed code is uploaded to Google Drive for reporters to access.

How do you use Datawrapper at Axios?

The Axios Visuals team produces dozens of graphics a week using a variety of tools. We primarily use Datawrapper for those graphics that don’t require bespoke code, but are more advanced than what our in-house tool for reporters can handle. Over the years, we’ve come up with dozens of tips and tricks and code snippets to really expand upon the already vast array of options Datawrapper gives us.

2023 temperature anomalies by Erin Davis/Axios for the article How Colorado's summer weather looked in 3 maps

We automated everything about the Datawrapper map above in R. That includes downloading and processing raster data, converting it to a custom choropleth, trimming the choropleth to each state of interest, selecting the cities to show, and publishing the final maps. 

Here's a scatterplot we created with Datawrapper:

2023 ParkScores by Kavya Beheraj/Axios for the article The best U.S. cities for public parks

Parks confer a wealth of benefits on residents. Using data from the Trust for Public Land, these charts rank the country’s best cities for public parks and break down the metrics that make a great parks system. Using our batching process, we were able to create unique versions of this chart for each city in our local network, updating the title and highlighting data points as needed. 

What advice would you give to other Datawrapper users?

My advice is to be on the lookout for all of the ways the Datawrapper community is pushing the envelope of what is possible with the app. Datawrapper strikes an amazing balance between ease of use and the ability to get really creative. We frequently challenge ourselves to recreate bespoke graphics in Datawrapper just to see what is possible and often find that with some creative data layouts and CSS you can do a lot of amazing things.

We're looking forward to Jared's talk at Unwrapped! Learn more about him on his website. To sign up for Unwrapped and hear Jared and other great speakers, visit our conference website.