Student Work
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 jrncomputation@columbia.edu.
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.
What does the ratio of single men to single women look at in various area of China?
Read more at The Shanghai Observer (mobile recommended)
Interactive map by Shuyao Xiao, Lede 2016
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.
Read the published piece as a PDF, and see more of Barnaby’s work at barnabyskinner.com and the Tages-Anzeiger Datablog.
A look at the geography of heroin treatment with Suboxone.
Read more at The Huffington Post
Map-based piece by Nicky Forster, Lede 2014
A D3-based, in-progress final project for Lede 24’s Storytelling with Data, by Mercy Benzaquen, Lede 2016
A quick look at the shift in American last names due to the growth of Hispanic and Asian Americans.
Graphic and analysis by Spe Chen, Lede 2015
Watch the fall of rock and the rise of hip hop in this set of visuals by Rebecca Schuetz, Lede 2016.
One of the weekly projects for Data Studio. The Python code used for accessing, combining, and visualizing the four data sets is available, too.
A look at how NBA teams perform when they lose a superstar.
Piece by Spe Chen, see more at the Palm Beach Post
A longform piece of data journalism, featuring analysis and visualization of 10,000 Craigslist Missed Connections posts.
Read more at iliablinderman.com
Personal Project by Lede 2014 graduate Ilia Blinderman
An in-depth, interactive look at Melville’s classic.
By Andrew Kahn, 2014 Lede graduate and Assistant Interactives Editor at Slate. And if reading just isn’t enough, you can also hear him discuss the piece on the Slate Culture Gabfest.
How the Supreme Court and bitter partisanship over Obamacare are letting Red America slip further behind while Blue America moves forward.
Read more at The Huffington Post.
An interactive data piece from Nicky Forster, a Lede 2014 graduate and HuffPo Data Journalist Fellow.
An animated interactive of the history of the Atlantic Slave Trade.
An animated data piece from Andrew Kahn, a Lede 2014 graduate and Assistant Interactives Editor at Slate.
Coursework, Homework, and Projects
Data Studio
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!
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Analyzing dialogue from "Friends" -
The evolution of women in marathons -
The German car industry vs. the government -
The world's most sampled drum loop -
Analysis of German polling numbers -
Liver transplant wait times -
The drawings that defeat Google -
Brazil's Recession -
He Who Must Not Be Named -
Women in War -
GDP vs Coups -
Koch University -
Number of Incarcerated People -
Marathoner Evolution -
How accessible is your subway? -
Inflation in Venezuela -
Stop-and-Frisk Racial Bias -
Short-Term Lodging Alert -
A Better NBA Contract -
Rise and Fall of Genres
Storytelling with Data
Storytelling with Data is a Lede 24 fall course focused on learning D3, a JavaScript data visualization library. Students spend the first half of the course learning the ropes of data visualization, and the second half critiquing projects and building on their abilities.
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!
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India measures -
National Park Visitors -
Life expectancy -
American UFOs -
FINAL PROJECT: Immigration is Human -
This Century in Natural Disasters -
FINAL PROJECT: Love Actually -
Political Endorsements -
Walmart confusion matrix -
The Cost of Clothing -
NYC Felony Report -
Tiny Dots -
FINAL PROJECT: AirBNB -
Personal Workout History -
FINAL PROJECT: Marvel vs. DC -
Eating Europe -
Animal Cafes in Seoul -
The Price of Weed -
Crime in Context -
Offers -
Housing Listings in Prospect Park -
Late Night Bike Ride -
Inequality and New York's Subway -
Climate Change -
Top 100 Sci-Fi Books -
FINAL PROJECT: Love Actually -
Global Poverty Index -
Sci-Fi Books -
Happy Countries -
NBA Teams -
NYC Subway Mapping -
Life in Cities -
China GDP by Industry
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.
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Apartment Hunting in Reverse -
NYC Taxi Complaint Data -
Weibo Text Mining
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Is there a housing bubble in Switzerland? -
Teacher Diversity
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Predicting disease spread based on climate change -
Civic Engagement Measures -
Political Donors in Norway
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Airbnb Data -
Scrapers Used on Github -
Exploring Global Terrorism -
Mapping home-delivery postal service in Switzerland
Questions?
If you’d like to know more, don’t hesitate to reach out to us at jrncomputation@columbia.edu
Ready to apply?
Let’s get the ball rolling – applications open soon.
Potential Employers
Looking to find talented applicants to fill roles in data analysis and visualization? Let us know.