Most migrants cross at the Texas border. Here’s how the flow of people intersects with Trump’s policies.

Category: Best visualization (small and large newsrooms)

Country/area: United States

Organisation: Texas Tribune

Organisation size: Small

Publication date: 9 Oct 2019

Credit: Mandi Cai and Connie Hanzhang Jin

Project description:

Since President Donald Trump took office in 2017, his administration has tried to curb migration at the southern border. Most migrants cross into Texas — here’s how the flow of people intersects with Trump’s ever-shifting policies. The Tribune continues to update the tracker monthly with the latest available data.

Impact reached:

This project was designed during the summer of 2019, when a huge surge in migration sent federal officials scrambling to change U.S. policies and stem the flow. We set out to use data to measure the impact of those policies, with a focus on Texas, where the majority of people cross the border. We also wanted to improve our workflow for publishing a regular graphic breaking down migration levels in stories, such as this one. Reader reaction to the project was positive; many appreciated how the data visualizations gave them extra context in understanding a complex and fast-moving issue.

Techniques/technologies used:

This project is powered by a Python scraper that fetches new data from U.S. Customs and Border Protection each month. The Texas border map was created with ai2html, and the data changes to reflect monthly border crossing totals for each sector. The two charts were made with d3.js, which makes regular updates easy. The entire project is built on the Texas Tribune’s open source development environment, which is based in node.

What was the hardest part of this project?

Collaboration with researchers who study this data and reporters and editors to understand how to best contextualize the flow of migrants was essential. The data also contained critical flaws: Specifically, the Border Patrol reports numbers of “inadmissibles,” people presenting themselves at ports of entry, in some parts of the data but not in others. In order to present the most complete picture of migration, including a breakdown of children arriving alone and families arriving together, we had to use data with and without inadmissibles and describe each chart correctly.  

What can others learn from this project?

Building and regularly updating a tracker graphic is not easy, but it’s worthwhile for topics that newsrooms cover frequently. We implemented a scraper and built this graphic with regular updates in mind, which means spending more development time with tools like d3.js. It’s also easy for anyone on the Tribune’s data visuals team to run an update. This graphic includes an embeddable version, which saves us time making the same migration chart each month when our border reporter writes about the latest numbers.

Mandi Cai tells stories with code and graphics as part of the data visuals team. Previously, she created dashboards for scientists at BioBright, a Boston-based biotechnology company, and visualized defense data for Defense Footprint, a project contextualizing the United States’ international military presence. She graduated from Brown University in 2017 with a concentration in neuroscience, focusing on the intersection of cognitive science and design.


Connie Hanzhang Jin, a recent graduate of the University of North Carolina, was the Tribune’s data visuals fellow in 2019. At the Tribune, they covered migration and water policy. Connie now works at NPR. Previously, they worked as a design assistant at Carolina Union Communications and Creative Services and was an intern for Clarkston Consulting and Chapel Hill/Durham Magazine. In 2018, Connie traveled to Puerto Rico to work as the web developer for the multimedia documentary storytelling project “Aftermath: Puerto Rico Rebuilds After Maria,” which won a student award from the Online News Association.

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