Urban Mobility Analytics

Citi Bike NYC — Usage Patterns & Operations

04

Citi Bike publishes one of the richest open mobility datasets in the world — every trip, every station, every second. This project joined the 2022 trip data with NOAA weather records to model what actually drives usage in a city as climatically variable as New York.

Top stations like Grove St PATH (~27K trips) anchor the network, and a clear positive correlation between temperature and daily rides confirmed the operational importance of seasonal staffing and redistribution planning. Commuter vs. leisure patterns were segmented by hour and user type for planning insights.

The final deliverable is an interactive Streamlit dashboard with Kepler.gl trip-flow maps — letting stakeholders explore station-to-station patterns, identify bottlenecks, and pressure-test redistribution scenarios directly.

Skills & Tools

Python (pandas, geopandas), Tableau, Streamlit, Kepler.gl, NOAA weather data integration

Analysis

Trip-flow geospatial analysis, weather correlation, station bottleneck detection, commuter vs. leisure segmentation, interactive dashboard delivery.

Key insights
  • Weather correlation analysis showed clear impact on daily trip volume — temperature threshold identified
  • High-traffic station bottlenecks mapped with Kepler.gl — redistribution recommendations delivered
  • Commuter vs. leisure usage patterns segmented by hour and user type — operational planning insights
PythonTableauStreamlitKepler.gl
A handful of stations carry the network: Grove St PATH alone anchors ~27K trips. Where these hubs cluster is where redistribution and staffing pay off most.
A handful of stations carry the network: Grove St PATH alone anchors ~27K trips. Where these hubs cluster is where redistribution and staffing pay off most.
Temperature explains a large share of daily volume — the curves track each other across 2022. Weather isn't context, it's a planning input for fleet and staffing.
Temperature explains a large share of daily volume — the curves track each other across 2022. Weather isn't context, it's a planning input for fleet and staffing.
Station-to-station flows on Kepler.gl expose the real commuter corridors into Manhattan — the directional patterns a totals chart hides, and the basis for redistribution scenarios.
Station-to-station flows on Kepler.gl expose the real commuter corridors into Manhattan — the directional patterns a totals chart hides, and the basis for redistribution scenarios.
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