Original link: http://tecdat.cn/?p=7553

data

Reddit user imjasonh fhoffa parsed and raw data, as shown in the following modes:

Each have very specific ride on / off position and start / end time details. An example is shown below:

We left 158,320,608 taxi trip data set is divided into 32,654 different start / finish.

Since 1987, in the East 79th Street and York Avenue taxi stand has been brought to the residents of the eastern Wall Street.

I found 252,210 trips along this route in the data. Taxi takes an average of 20.35 minutes to travel at a speed of 22.11 mph. Of course, you will go faster at 4:00, but most people until 6:00 or 7:00 began commuting:

In a year, the most exclusive of the taxi route with 234 times (only seven taxi traveling the route 100 times):

Although the top ten most common taxi driver's average speed more predictable, but their forward speed is not faster than most people (perhaps because they often drive at the same time every day).

SELECT
  pickup_street1, pickup_street2, dropoff_street1, dropoff_street2,
  trips_medallion, trips_pickup_datetime, trips_dropoff_datetime,
  ROUND(trips_avg_mph,4) AS avg_mpg,
  ROUND(trips_trip_duration_hours,4) AS num_hours
FROM
  [taxi_strava.joined_geohash_geonames]
WHERE
  trips_geohashed_dropoff = 'dr5ru2'
  AND trips_geohashed_pickup = 'dr5rvj'

If you have any questions, please leave a comment below.

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