NYC Taxis: A Day in the Life

This visualization displays the data for one random NYC yellow taxi on a single day in 2013. See where it operated, how much money it made, and how busy it was over 24 hours.


Begin


A Special Thanks goes out to Mapbox and Heroku for assistance with covering the surge of activity when this project was first released in 2014.

Here's Technical Blog Post #1 and #2 about how this visualization was built.

About

NYC Taxis: A Day in the Life - A Data Visualization by Chris Whong

This civic technology project visualizes taxi trip data from 2013, showing the activities of a single taxi on a single day. The original data include ~170 Million trips. Of these, 30 cab/days were queried at random for inclusion in this project. The data were provided by the Taxi and Limousine Commission via a FOIL request.

The intent is to analyze running counts of fares, taxes, etc, over the course of a day, and to see how/when taxis move around New York.

The raw data include only start and end locations for each trip. These points were run through Google's Directions API to create the routes shown in this visualization. Of course, these are Google's best choice, not necessarily the one the taxi took.

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Code on Github



Asterisks

Here are some gotchas:

  • Trip Routes are a result of passing the start and end locations to the Google Directions API. They are a possible route that the taxi took, but should not be assumed to be accurate.
  • Empty Taxis also follow the "best route" between a dropoff and the next pickup. Just as with the trips, this is just an effective way to move the marker around, but doesn't reflect the reality of where the taxi traveled.
  • Tips are only reported in the data for credit card transactions. Cash tips are not included.

Attribution

  • Mike Bostock's D3 + Leaflet - The foundation for throwing geoJSON onto Leaflet with external tiles.
  • KoGor's Marker Animation Along SVG Path - This technique made the animated cab marker work!
  • Mapbox for super-simple subdued basemap tiles, and for releasing a totally sweet node package for converting Google Encoded Polylines into raw Coordinates.
  • Thanks to u/fhoffa on Reddit for importing the data into BigQuery helping me with the custom query I needed to pull full days of data for random taxis.
Time Factor: minutes per second
Legend

Full Taxi

Empty Taxi*

Trip Start Point

Trip End Point

Trip Route*

Running Totals

Fares:

Surcharge:

MTA Tax:

Tips*:

Tolls:

Total:

Passengers: