Taxi Trip Data Through Payment

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This dataset represents a detailed compilation of trips made using yellow taxis in New York City. The data encapsulates a wide range of information, from pickup and drop_off times to fare amounts and payment types, offering a comprehensive view into urban mobility and the economics of taxi rides within the city. This dataset is invaluable for anyone interested in urban transportation trends, fare analysis, geographic movement patterns within New York City, and the study of temporal variations in taxi usage.

Column Description:

VendorID: A code indicating the provider associated with the trip record.

tpep_pickup_datetime: The date and time when the meter was engaged.

tpep_dropoff_datetime: The date and time when the meter was disengaged.

passenger_count: The number of passengers in the vehicle. This is a driver-entered value.

trip_distance: The distance of the trip measured in miles.

RatecodeID: The final rate code in effect at the end of the trip.

store_and_fwd_flag: Indicates whether the trip record was held in vehicle memory before sending to the vendor, Y=store and forward, N=not a store and forward trip.

PULocationID: The Taxi and Limousine Commission (TLC) Taxi Zone ID for the pickup location.

DOLocationID: The Taxi and Limousine Commission (TLC) Taxi Zone ID for the dropoff location.

payment_type: A numeric code signifying how the passenger paid for the trip.

fare_amount: The time-and-distance fare calculated by the meter.

extra: Miscellaneous extras and surcharges.

mta_tax: $0.50 MTA tax that is automatically triggered based on the metered rate in use.

tip_amount: Tip amount – This field is automatically populated for credit card tips. Cash tips are not included.

tolls_amount: Total amount of all tolls paid in trip.

improvement_surcharge: $0.30 improvement surcharge assessed trips at the flag drop. The surcharge began in 2015.

total_amount: The total amount charged to passengers. Does not include cash tips.

congestion_surcharge: A surcharge applied on trips that start, end, or pass through certain areas at specific times.

Usage Ideas

*Suggest several research questions or project ideas that could be explored using the dataset. For example: *

-Analyzing the impact of weather conditions on taxi usage.

-Exploring the correlation between trip distances and fares to identify pricing patterns.

-Investigating the effect of different times of day or days of the week on taxi demand.