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NICAR Q&A with Nathaniel Lash


Nathaniel Lash

Nathaniel Lash is a data reporter for the Tampa Bay Times. He was part of a team of journalists who worked on "Failure Factories," a series that explored how five Pinellas County schools became some of the worst in Florida.

 

How would you describe your job?

I work at the Tampa Bay Times as a data reporter, where I develop and use technology to conceive of, report out and publish stories. Right now, I work mostly with members of the investigative team on their data-heavy projects, which involves acquiring, cleaning, connecting and analyzing data, as well as visualizing it for the web.

How did you get started in data journalism?

The summer before my sophomore year at the University of Illinois at Urbana-Champaign, I was lucky enough to attend an IRE Watchdog Workshop, which sparked an awareness of what kinds of records public agencies collect and maintain. It proved useful pretty quickly. That fall, news broke of "possible inaccuracies" in how the university’s law school reported student test scores, the benchmark of a law school’s quality (and rank). While the university’s investigation was ongoing, we requested the raw test scores for students admitted to the law school, and saw that the highly coveted median LSAT scores been inflated for years. Before we could publish — the day after we got the records — the university released findings that exactly matched ours. I’ve taken data journalism pretty seriously since then.

That got me working with data for a bit, but the only reason I was able to get into writing code and working with databases is thanks to Michael Corey and Augie Armendariz, who brought me under their wing at the Center for Investigative Reporting for a summer and taught me how code fits with investigative journalism.

What are your go-to tools and programs when working on a story that involves data?

For any story that involves data, the tool at the top of my list is experts. A lot of the time that means those who work either at the source of the data or as researchers. But another frequently untapped source is the people who deal with the real-world bits of that data all the time: reporters in your newsroom.

As far as technology is concerned, I do most of my data analysis in iPython notebooks, which makes working with the data analysis package pandas a breeze. It also makes on-the-fly visualization a lot simpler — one of my favorite libraries for that is Seaborn, which simplifies the process for a lot of standard statistical visualizations.

For projects like the Failure Factories series, we had to maintain and connect a lot of different datasets. For those kinds of tasks, I usually turn to something like Django, a Python web framework that makes managing, analyzing and publishing data much easier.

Still, as great as some of these tools are, nothing beats Excel when I need an answer from smaller datasets quickly.

"For any story that involves data, the tool at the top of my list is experts."

At what point in the reporting process for “Failure Factories” were you brought on to create the graphic?

Reporters Michael LaForgia, Cara Fitzpatrick and Lisa Gartner, and data specialist Connie Humburg had been requesting documents and records from the state’s department of education and the school district for eight months before I arrived at the Times as an intern in January. About a month after I started, I began switching between contributing analysis on the project and developing graphics until the stories started running in August.

Communication is key when working in a group, so how did you keep all the reporters working on various components of the story on the same page?

We work together! Cara and Lisa, education reporters who ordinarily worked on the other side of the newsroom, physically moved their desks over to the investigative team’s pods, and the data team — the group of data specialists, designers and developers to which I belong — works adjacent to that team. There was a constant back-and-forth between the other reporters and me, as well as the rest of the data team.

 

This interview has been edited for clarity. Interview by Maggie Angst.

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