A collection of pieces by both current and former Lede students.
Are you a potential applicant wondering what data analysis and visualization can bring to your skillset? Let’s take a look.
Are you a potential employer looking for data-driven applicants? Get in touch at firstname.lastname@example.org.
A front-page Bloomberg investigative report about “how an obscure legal document turned New York’s court system into a debt-collection machine that’s chewing up small businesses across America.” Data analysis featuring Demetrios Pogkas (Lede 2017).
Read more at at Bloomberg.
An investigation into how German firms hide political contributions, by Gianna Gruen (Lede 2016) .
Read more at at Deutche Welle.
Barnaby Skinner (Lede 2016) and his team scraped and analyzed 30,000 verdicts on asylum seekers appealing their deportation, illustrating the political bias of various Swiss judges.
Coursework, Homework, and Projects
Data Studio is a Lede 12 summer course that focuses on reproducing a newsroom – projects are quick, rough around the edges, and subject to continual critique. Students are constantly confronted with new and untested data sets, and learn sometimes failure is a viable option. Most projects are completed in about a week.
We spend much of the course exporting graphics from Python, then cleaning them up in Adobe Illustrator. You can see a handful of projects below, or check out all of 2017’s projects or the GitHub repository for 2016 – both feature finished visuals along with code!
Storytelling with Data
The samples below are student homework, and are often midway points in learning new concepts – as a result they are not tailored for publication. Please excuse missing axes, clashing colors, or any other missteps!
Data & Databases + Algorithms
Data & Databases and Algorithms are Lede 12 summer courses that center on processing large datasets with the Python programming language. While not nearly as aesthetically pleasing as visualization projects, analysis is the foundation of deeper understanding, providing valuable insights and leads from otherwise disorganized data.
If you’d like to know more, don’t hesitate to reach out to us at email@example.com
Ready to apply?
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Looking to find talented applicants to fill roles in data analysis and visualization? Let us know.