A spreadsheet of pickups tells you nothing. A good chart tells you when the city moves. Uber Data Visualization takes six months of New York City Uber pickup data, April through September 2014, and turns it into a story about how and when people actually get around.
The project builds 11 different graphs in R, each digging into a different slice of the data: the rhythm of rides across hours, days, and months, and the patterns that only show up once the raw CSVs become something you can see. The R script is written so each comment maps directly to the title of the chart it produces, keeping the code and the insights traceable side by side.
The point isn’t prediction, it’s communication. Data storytelling is a real part of machine learning, and this project is a study in making a messy dataset speak clearly through visuals alone.
Built with R.