This repository contains various files that I generated as part of my quest to animate the daily and/or weekly lifecycle of New York City's CitiBike system. All of the scoping, done in Python using Jupyter notebooks, is here, as are various toy datasets generated along the way, and—critically—the scripts which generate the visualization's backend. The only thing not in this repository is the final visualization itself, which is optimized for and hosted at my personal website, and can be found there.

If you are interested in following along, read this technical blog post first. Then, if you're still interested, start reading the materials in the notebooks folder.

Note that station depots and New Jersey locations (on which no data is yet available, annoyingly) have been removed from this dataset during processing.

• station id — The unique identifier for this station.
• latitude
• longitude
• station name — The station name.
  • Usually the name of an intersection (ex. W 52 St & 11 Ave) or landmark (ex. Yankee Ferry Terminal).
  • Penn Station Valet is a special exception.
  • Storage depots (removed from this dataset) have DEPOT in their name.
• incoming trips — Number of trips whose endpoint is this station.
• outgoing trips — Number of trips whose starting point is this station.
• all trips — Number of trips that end or being here (incoming trips + outgoing trips)
• kind — Active if the station is in use, Inactive if it is down/out for maintenance, Depot if it is a storage depot.
• bikes outbound — Number of bikes which start their day here and get ridden out.
• outbound trips — Number of trips taken by bikes which start their day here.
• bikes inbound — Number of bikes which end their day here.
• inbound trips — Number of trips taken by bikes which end their day here.
• delta bikes — Difference in number of bikes between start and end of the day (bikes inbound - bikes outbound).
• delta trips — Difference in number of trips taken by bikes which start their day here (incoming trips + outgoing trips).