Cox model for the risk of anxiety or depression by the different levels of tSCI compared with other health conditions and tSCI only.

Sociodemographic characteristics and comorbidities in the tSCI group and other health conditions group.

This dataset ends with 2023. Please see the Featured Content link below for the dataset that starts in 2024. Taxi trips from 2013 to 2023 reported to the City of Chicago in its role as a regulatory agency. To protect privacy but allow for aggregate analyses, the Taxi ID is consistent for any given taxi medallion number but does not show the number, Census Tracts are suppressed in some cases, and times are rounded to the nearest 15 minutes. Due to the data reporting process, not all trips are reported but the City believes that most are.

Context

Taxicabs in Chicago, Illinois, are operated by private companies and licensed by the city. There are about seven thousand licensed cabs operating within the city limits. Licenses are obtained through the purchase or lease of a taxi medallion which is then affixed to the top right hood of the car. Source: https://en.wikipedia.org/wiki/Taxicabs_of_the_United_States#Chicago

Content

This dataset includes taxi trips from 2013 to the present, reported to the City of Chicago in its role as a regulatory agency. To protect privacy but allow for aggregate analyses, the Taxi ID is consistent for any given taxi medallion number but does not show the number, Census Tracts are suppressed in some cases, and times are rounded to the nearest 15 minutes. Due to the data reporting process, not all trips are reported but the City believes that most are. See http://digital.cityofchicago.org/index.php/chicago-taxi-data-released for more information about this dataset and how it was created.

Fork this kernel to get started.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:chicago_taxi_trips

https://cloud.google.com/bigquery/public-data/chicago-taxi

Dataset Source: City of Chicago

This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source —https://data.cityofchicago.org — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by Ferdinand Stohr from Unplash.

Inspiration

What are the maximum, minimum and average fares for rides lasting 10 minutes or more? Which drop-off areas have the highest average tip? How does trip duration affect fare rates for trips lasting less than 90 minutes?

https://cloud.google.com/bigquery/images/chicago-taxi-fares-by-duration.png" alt=""> https://cloud.google.com/bigquery/images/chicago-taxi-fares-by-duration.png

LTW_Project_Analysis_Area_Di2

Don't forget to hit the Upvote

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.

Incidence rate for anxiety or depression between the tSCI group and other health conditions group.

TLC trip records contain a field corresponding to the location of the pickup or drop-off of the trip called a taxi zone. Taxi Zones are roughly based on NYC Department of City Planning’s Neighborhood Tabulation Areas (NTAs) and are meant to approximate neighborhoods, so you can see which neighborhood a passenger was picked up in, and which neighborhood they were dropped off in. TLC uses the taxi zone shapefile and trip records data to provide the public with data visualization tools to analyze our data. The TLC Factbook (https://nyc.gov/tlcdata), once a static report released by the agency every two years, is now a living, interactive, ever-expanding data dashboard updated with the latest data every month.

These records are generated from the trip record submissions made by yellow taxi Technology Service Providers (TSPs). Each row represents a single trip in a yellow taxi. The trip records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off taxi zone locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts.

NYC Taxi Trip Description Dataset

This dataset contains NYC taxi trip data from May 1-7, 2013, excluding trips to and from Staten Island. It includes 2,957 sequences with 362,374 events and 8 location types. The data can be downloaded from NYC Taxi Trips and is subject to the NYC Terms of Use. The detailed data preprocessing steps used to create this dataset can be found in the TPP-LLM paper and TPP-LLM-Embedding paper. If you find this dataset useful, we kindly invite you to cite… See the full description on the dataset page: https://huggingface.co/datasets/tppllm/nyc-taxi-description.

Taxi trips, starting January 2024, reported to the City of Chicago in its role as a regulatory agency. To protect privacy but allow for aggregate analyses, the Taxi ID is consistent for any given taxi medallion number but does not show the number, Census Tracts are suppressed in some cases, and times are rounded to the nearest 15 minutes. For earlier trips, see the link in the Featured Content section below. Due to the data reporting process, not all trips are reported but the City believes that most are.

These records are generated from the trip record submissions made by green taxi Technology Service Providers (TSPs). Each row represents a single trip in a green taxi. The trip records include fields capturing pick-up and drop-off dates/times, pick-up and drop-off taxi zone locations, trip distances, itemized fares, rate types, payment types, and driver-reported passenger counts.

This dataset contains mobility traces of taxi cabs in Rome, Italy. It contains GPS coordinates of approximately 320 taxis collected over 30 days.

; lorenzo.bracciale@uniroma2.it

2019

Global Robo-Taxi Market size valued at US$ 2.66 Billion in 2023, set to reach US$ 139.27 Billion by 2032 at a CAGR of about 55.27% from 2024 to 2032.

tomh/taxi dataset hosted on Hugging Face and contributed by the HF Datasets community

This is the image of data.

This dataset includes trip records from all trips completed in green taxis in NYC in 2015. 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. The data used in the attached datasets were collected and provided to the NYC Taxi and Limousine Commission (TLC) by technology providers authorized under the Livery Passenger Enhancement Program (LPEP). The trip data was not created by the TLC, and TLC makes no representations as to the accuracy of these data.

Stratified analysis of 14-day rehospitalization with new tSCI diagnosis for the patients with spine AIS 3 (N = 3521).

A. SUMMARY This dataset contains information on taxi trips including pickup location, destination, and fare. Additional fields have been integrated to the raw data through automated and manual procedures to facilitate easier data analysis. Those fields are indicated in the column metadata. B. HOW THE DATASET IS CREATED As required by the Transportation Code, all taxi companies permitted to operate in the City and County of San Francisco transmit digital records of their fleet’s activity to SFMTA in real time through the SFMTA Taxi Application Programming Interface (API). C. UPDATE PROCESS This dataset will be updated monthly with new taxi trip information. D. HOW TO USE THIS DATASET This dataset is useful for tracking average daily taxi trip counts and monitoring the impact of the Taxi Upfront Pricing Pilot program on driver income. E. RELATED DATASETS Taxi Medallion Holders