Takeaways from the 2020 census for Maryland, in 5 charts

Country/area: United States

Organisation: Capital News Service – University of Maryland Philip Merrill College of Journalism

Organisation size: Small

Publication date: 07/10/2021

Credit: Aadit Tambe


Aadit Tambe is a second-year master’s student in data journalism and a fellow at the Howard Center for Investigative Journalism at the University of Maryland. He works at the intersection of data journalism and front-end design, and his goal is to write code and create graphics that explain the news. He has spent a semester working as a data and graphics reporter for Capital News Service, and has interned with the data and graphics team at NBC News.

Project description:

After the U.S. Census Bureau released the 2020 decennial counts, I produced a data-driven story after analyzing county-level data about the biggest takeaways for the state of Maryland, and created charts to explain the change in the state’s demographics.

Impact reached:

Census data showed that Maryland is a majority-minority state for the first time, as less than 50 percent of the state’s residents identified as white. The shift in demographics was largely because of the state’s younger population. The project used visualizations — which included interactive county-level maps — to explain the biggest takeaways from the census data.

Techniques/technologies used:

I used R for data analysis and created a notebook with all my findings — which was useful for fact-checking. The pie chart was created with D3.js and JavaScript. The interactive maps were developed using Leaflet, an open-source JavaScript library for developing mapping applications, along with JavaScript and jQuery. The bar charts were created with Adobe Illustrator and then exported as HTML using ai2html, so that the charts could be responsive.

What was the hardest part of this project?

The hardest part of the project was to analyze the data in a way that could be fact-checked and reproduced. I accomplished this by creating an R markdown notebook with the data and findings to back each takeaway. This also allowed me to view mock charts, before exporting the data and producing the finished charts.

What can others learn from this project?

Other journalists can learn that creating a reproducible data notebook can be a good practice when reporting data stories, instead of using Microsoft Excel or Google Sheets. This project used ai2html to create static yet responsive visualizations, which is a workflow other journalists can adopt instead of using images.

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