Docked Bikeshare Ridership by System and Hour from 2019 to 2023

5 years of docked bikeshare trip data from January 2019 through 2023, aggregated by system, month, and hour. The U.S. Bureau of Transportation Statistics compiled this data to specifically analyze the impacts of COVID-19 on urban mobility patterns. Trips shorter than 1 minute or longer than 2 hours are excluded from the totals.

Use Cases

• Model hourly ridership (hour, num_trip) by system (sysname) and trip type (trip_type) to forecast station demand.
• Analyze the impact of COVID-19 on monthly ridership trends (assigned_month, year, num_trip) across different cities (sysname).
• Compare average trip duration (sum_min) and trip counts (num_trip) between systems allowing dockless parking (trip_type) and traditional docked systems.
• Identify seasonal ridership patterns by correlating assigned_month with num_trip for each system identifier (sysid).

Strengths

• Data spans a 5-year period from 2019 to 2023, capturing pre-pandemic, pandemic, and recovery phases.
• Includes 10 distinct data columns for granular analysis by time, system, and trip characteristics.
• Methodology explicitly details trip inclusion/exclusion rules, such as filtering trips under 1 minute or over 2 hours.

Limitations

• Ridership data is not available for all docked bikeshare systems in the U.S., limiting geographic coverage.
• The dataset excludes trips that began on December 31, 2019 and ended on January 1, 2020, creating a small data gap.
• Months are rearranged to align days of the week across years, which deviates from standard calendar months.

Provenance

Source

U.S. Bureau of Transportation Statistics (data.bts.gov).

Collection Method

Aggregated from trip records submitted by docked bikeshare systems, with defined cleaning rules.

Time Range

January 2019 through December 2023.

Freshness

Historic data through 2023 was last updated in June 2024.

Geography

Multiple U.S. cities with docked bikeshare systems that report data.