Bike Sharing Demand in Washington D.C. for 2011-2012

Two years of historical bike rental data from the Capital Bikeshare system in Washington D.C., aggregated hourly and daily. The dataset includes environmental and seasonal information such as weather, holiday, and time-of-day variables. It was created by Hadi Fanaee-T and Joao Gama for research on event labeling and mobility sensing.

Use Cases

• Predicting bike rental demand based on weather conditions and time of day.
• Analyzing the impact of holidays and weekends on urban transportation patterns.
• Sensing city-wide mobility events by treating the bike-sharing network as a sensor network.
• Benchmarking regression algorithms on mixed categorical and numerical features.

Strengths

• Includes two full years of data (2011 and 2012), providing seasonal coverage.
• Enriched with external data sources for weather, holidays, and seasonal information.
• Explicitly records travel duration and positions, which is noted as a distinctive feature for research.

Limitations

• Row count and file size are unknown, making suitability assessment difficult.
• Column-level documentation beyond the listed attributes is absent; field semantics for unlisted columns must be inferred.
• Last update date is unknown; freshness unverified.

Provenance

Source

Capital Bikeshare system, Washington D.C., USA.

Collection Method

Historical logs aggregated on two-hourly and daily basis, with weather and seasonal information added from external sources.

Time Range

2011 to 2012

Geography

Washington D.C., USA