NYC Taxi & Limousine Commission - green taxi trip records
The green taxi trip records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts.
Note
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This dataset is provided under the original terms that Microsoft received source data. The dataset may include data sourced from Microsoft.
Volume and retention
This dataset is stored in Parquet format. There are about 80M rows (2 GB) in total as of 2018.
This dataset contains historical records accumulated from 2009 to 2018. You can use parameter settings in our SDK to fetch data within a specific time range.
Storage location
This dataset is stored in the East US Azure region. Allocating compute resources in East US is recommended for affinity.
Additional information
NYC Taxi and Limousine Commission (TLC):
The data was collected and provided to the NYC Taxi and Limousine Commission (TLC) by technology providers authorized under the Taxicab & Livery Passenger Enhancement Programs (TPEP/LPEP). The trip data was not created by the TLC, and TLC makes no representations as to the accuracy of these data.
View the original dataset location and the original terms of use.
Columns
Name | Data type | Unique | Values (sample) | Description |
---|---|---|---|---|
doLocationId | string | 264 | 74 42 | DOLocationID TLC Taxi Zone in which the taximeter was disengaged. |
dropoffLatitude | double | 109,721 | 40.7743034362793 40.77431869506836 | Deprecated from 2016.07 onward |
dropoffLongitude | double | 75,502 | -73.95272827148438 -73.95274353027344 | Deprecated from 2016.07 onward |
extra | double | 202 | 0.5 1.0 | Miscellaneous extras and surcharges. Currently, this only includes the $0.50 and $1 rush hour and overnight charges. |
fareAmount | double | 10,367 | 6.0 5.5 | The time-and-distance fare calculated by the meter. |
improvementSurcharge | string | 92 | 0.3 0 | $0.30 improvement surcharge assessed on hailed trips at the flag drop. The improvement surcharge began being levied in 2015. |
lpepDropoffDatetime | timestamp | 58,100,713 | 2016-05-22 00:00:00 2016-05-09 00:00:00 | The date and time when the meter was disengaged. |
lpepPickupDatetime | timestamp | 58,157,349 | 2013-10-22 12:40:36 2014-08-09 15:54:25 | The date and time when the meter was engaged. |
mtaTax | double | 34 | 0.5 -0.5 | $0.50 MTA tax that is automatically triggered based on the metered rate in use. |
passengerCount | int | 10 | 1 2 | The number of passengers in the vehicle. This is a driver-entered value. |
paymentType | int | 5 | 2 1 | A numeric code signifying how the passenger paid for the trip. 1= Credit card 2= Cash 3= No charge 4= Dispute 5= Unknown 6= Voided trip |
pickupLatitude | double | 95,110 | 40.721351623535156 40.721336364746094 | Deprecated from 2016.07 onward |
pickupLongitude | double | 55,722 | -73.84429931640625 -73.84429168701172 | Deprecated from 2016.07 onward |
puLocationId | string | 264 | 74 41 | TLC Taxi Zone in which the taximeter was engaged. |
puMonth | int | 12 | 3 5 | |
puYear | int | 14 | 2015 2016 | |
rateCodeID | int | 7 | 1 5 | The final rate code in effect at the end of the trip. 1= Standard rate 2= JFK 3= Newark 4= Nassau or Westchester 5= Negotiated fare 6= Group ride |
storeAndFwdFlag | string | 2 | N Y | This flag indicates whether the trip record was held in vehicle memory before sending to the vendor, also known as “store and forward,” because the vehicle did not have a connection to the server. Y= store and forward trip N= not a store and forward trip |
tipAmount | double | 6,206 | 1.0 2.0 | Tip amount – This field is automatically populated for credit card tips. Cash tips are not included. |
tollsAmount | double | 2,150 | 5.54 5.76 | Total amount of all tolls paid in trip. |
totalAmount | double | 20,188 | 7.8 6.8 | The total amount charged to passengers. Does not include cash tips. |
tripDistance | double | 7,060 | 0.9 1.0 | The elapsed trip distance in miles reported by the taximeter. |
tripType | int | 3 | 1 2 | A code indicating whether the trip was a street-hail or a dispatch that is automatically assigned based on the metered rate in use but can be altered by the driver. 1= Street-hail 2= Dispatch |
vendorID | int | 2 | 2 1 | A code indicating the LPEP provider that provided the record. 1= Creative Mobile Technologies, LLC; 2= VeriFone Inc. |
Preview
vendorID | lpepPickupDatetime | lpepDropoffDatetime | passengerCount | tripDistance | puLocationId | doLocationId | rateCodeID | storeAndFwdFlag | paymentType | fareAmount | extra | mtaTax | improvementSurcharge | tipAmount | tollsAmount | totalAmount | tripType | puYear | puMonth |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2 | 6/24/2081 5:40:37 PM | 6/24/2081 6:42:47 PM | 1 | 16.95 | 93 | 117 | 1 | N | 1 | 52 | 1 | 0.5 | 0.3 | 0 | 2.16 | 55.96 | 1 | 2081 | 6 |
2 | 11/28/2030 12:19:29 AM | 11/28/2030 12:25:37 AM | 1 | 1.08 | 42 | 247 | 1 | N | 2 | 6.5 | 0 | 0.5 | 0.3 | 0 | 0 | 7.3 | 1 | 2030 | 11 |
2 | 11/28/2030 12:14:50 AM | 11/28/2030 12:14:54 AM | 1 | 0.03 | 42 | 42 | 5 | N | 2 | 5 | 0 | 0 | 0 | 0 | 0 | 5 | 2 | 2030 | 11 |
2 | 11/14/2020 11:38:07 AM | 11/14/2020 11:42:22 AM | 1 | 0.63 | 129 | 129 | 1 | N | 2 | 4.5 | 1 | 0.5 | 0.3 | 0 | 0 | 6.3 | 1 | 2020 | 11 |
2 | 11/14/2020 9:55:36 AM | 11/14/2020 10:04:54 AM | 1 | 3.8 | 82 | 138 | 1 | N | 2 | 12.5 | 1 | 0.5 | 0.3 | 0 | 0 | 14.3 | 1 | 2020 | 11 |
2 | 8/26/2019 4:18:37 PM | 8/26/2019 4:19:35 PM | 1 | 0 | 264 | 264 | 1 | N | 2 | 1 | 0 | 0.5 | 0.3 | 0 | 0 | 1.8 | 1 | 2019 | 8 |
2 | 7/1/2019 8:28:33 AM | 7/1/2019 8:32:33 AM | 1 | 0.71 | 7 | 7 | 1 | N | 1 | 5 | 0 | 0.5 | 0.3 | 1.74 | 0 | 7.54 | 1 | 2019 | 7 |
2 | 7/1/2019 12:04:53 AM | 7/1/2019 12:21:56 AM | 1 | 2.71 | 223 | 145 | 1 | N | 2 | 13 | 0.5 | 0.5 | 0.3 | 0 | 0 | 14.3 | 1 | 2019 | 7 |
2 | 7/1/2019 12:04:11 AM | 7/1/2019 12:21:15 AM | 1 | 3.14 | 166 | 142 | 1 | N | 2 | 14.5 | 0.5 | 0.5 | 0.3 | 0 | 0 | 18.55 | 1 | 2019 | 7 |
2 | 7/1/2019 12:03:37 AM | 7/1/2019 12:09:27 AM | 1 | 0.78 | 74 | 74 | 1 | N | 1 | 6 | 0.5 | 0.5 | 0.3 | 1.46 | 0 | 8.76 | 1 | 2019 | 7 |
Data access
Azure Notebooks
# This is a package in preview.
from azureml.opendatasets import NycTlcGreen
from datetime import datetime
from dateutil import parser
end_date = parser.parse('2018-06-06')
start_date = parser.parse('2018-05-01')
nyc_tlc = NycTlcGreen(start_date=start_date, end_date=end_date)
nyc_tlc_df = nyc_tlc.to_pandas_dataframe()
nyc_tlc_df.info()
Azure Databricks
# This is a package in preview.
# You need to pip install azureml-opendatasets in Databricks cluster. https://learn.microsoft.com/azure/data-explorer/connect-from-databricks#install-the-python-library-on-your-azure-databricks-cluster
from azureml.opendatasets import NycTlcGreen
from datetime import datetime
from dateutil import parser
end_date = parser.parse('2018-06-06')
start_date = parser.parse('2018-05-01')
nyc_tlc = NycTlcGreen(start_date=start_date, end_date=end_date)
nyc_tlc_df = nyc_tlc.to_spark_dataframe()
display(nyc_tlc_df.limit(5))
Azure Synapse
# This is a package in preview.
from azureml.opendatasets import NycTlcGreen
from datetime import datetime
from dateutil import parser
end_date = parser.parse('2018-06-06')
start_date = parser.parse('2018-05-01')
nyc_tlc = NycTlcGreen(start_date=start_date, end_date=end_date)
nyc_tlc_df = nyc_tlc.to_spark_dataframe()
# Display top 5 rows
display(nyc_tlc_df.limit(5))
# Display data statistic information
display(nyc_tlc_df, summary = True)
Next steps
View the rest of the datasets in the Open Datasets catalog.