Part of my 2025 resolution was to flex my quant research muscle - a natural progression from qual to mixed methods research, but also a sneaky way to keep my technical skills sharp. I swapped object-oriented programming, DBMS, and networking for data manipulation, visualization, and statistical analysis. Turns out years of computer science don't just disappear; they just find new ways to be useful.

As an international student with bills that definitely don't pay themselves, I had one burning question: Am I getting scammed on rent in Bridgeport, Chicago?

What better way to find out than going straight to the source - the Census Bureau API - and building some D3 visualizations to see where I actually stand.

Spoiler alert: At $800/month, I'm apparently living the dream. Illinois median rent sits at $1,238, and the national median is $1,226. My rent falls squarely in that beautiful $500-$999 category that represents a decent chunk of available units, but is way below what most people are paying.

The interactive map I built shows just how good this deal really is - especially when you see states like California and New York where that same $800 wouldn't even cover a closet.

Working with Census Bureau data through Observable and D3 felt like coming home, but with better graphics. Instead of building database schemas, I was cleaning datasets. Instead of optimizing algorithms, I was crafting visualizations that actually tell a story. The fundamentals were the same - problem-solving, logical thinking, working with APIs - but the output was so much more immediately meaningful.

There's something satisfying about answering a real-world question that affects your monthly budget with actual data rather than just hoping your landlord isn't taking advantage of your international student status.

Key Learning: Sometimes the best technical projects are the ones that solve your own problems. Also, I should probably stop complaining about my rent.

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Go to my Observable Public page HERE