8 datasets found
  1. NYC Yellow Taxi Trip Data

    • kaggle.com
    zip
    Updated Dec 9, 2021
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    Elemento (2021). NYC Yellow Taxi Trip Data [Dataset]. https://www.kaggle.com/datasets/elemento/nyc-yellow-taxi-trip-data
    Explore at:
    zip(1915626894 bytes)Available download formats
    Dataset updated
    Dec 9, 2021
    Authors
    Elemento
    License

    https://www.usa.gov/government-works/https://www.usa.gov/government-works/

    Area covered
    New York
    Description

    Context

    New York City (NYC) Taxi & Limousine Commission (TLC) keeps data from all its cabs, and it is freely available to download from its official website. You can access it here. Now, the TLC primarily keeps and manages data for 4 different types of vehicles: - Yellow Taxi: Yellow Medallion Taxicabs: These are the famous NYC yellow taxis that provide transportation exclusively through street hails. The number of taxicabs is limited by a finite number of medallions issued by the TLC. You access this mode of transportation by standing in the street and hailing an available taxi with your hand. The pickups are not pre-arranged. - Green Taxi: Street Hail Livery: The SHL program will allow livery vehicle owners to license and outfit their vehicles with green borough taxi branding, meters, credit card machines, and ultimately the right to accept street hails in addition to pre-arranged rides. - For-Hire Vehicles (FHVs): FHV transportation is accessed by a pre-arrangement with a dispatcher or limo company. These FHVs are not permitted to pick up passengers via street hails, as those rides are not considered pre-arranged.

    Complimentary Kernel

    • I have made a Kernel especially for this dataset, which uses Clustering, Regression, and Time-Series techniques for this dataset. You can check it out here.

    Important Points

    • In this dataset, we are considering only the Yellow Taxis Data, for the months of Jan 2015 & Jan-mar 2016.
    • If you go over to the website of NYC TLC, and download any of the CSV files, you will find a different format of these files. This is because, the TLC regularly adds more data, alongside updating the existing one.
    • One of the key changes that they have made to their data is that, instead of providing the pickup & dropoff coordinates, they have divided the NYC into regions and indexed those regions, and in the CSV files, they have provided these indices.
    • Due to this reason only, I have made this dataset using the previous version of the CSV files. This dataset allows me to practice my clustering knowledge alongside my time-series knowledge.
    • If you want to leave out the clustering part, then just go over to their website, and download the new CSV files.

    Attributes

    ...

    Field NameDescription
    VendorID A code indicating the TPEP provider that provided the record.
    1. Creative Mobile Technologies
    2. VeriFone Inc.
    tpep_pickup_datetimeThe date and time when the meter was engaged.
    tpep_dropoff_datetimeThe date and time when the meter was disengaged.
    Passenger_countThe number of passengers in the vehicle. This is a driver-entered value.
    Trip_distanceThe elapsed trip distance in miles reported by the taximeter.
    Pickup_longitudeLongitude where the meter was engaged.
    Pickup_latitudeLatitude where the meter was engaged.
    RateCodeIDThe 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
    Store_and_fwd_flagThis flag indicates whether the trip record was held in vehicle memory before sending to the vendor,
    aka “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
    Dropoff_longitudeLongitude where the meter was disengaged.
    Dropoff_ latitudeLatitude where the meter was disengaged.
    Payment_typeA 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
    Fare_amountThe time-and-distance fare calculated by the meter.
    ExtraMiscellaneous extras and surcharges. Currently, this only includes. the $0.50 and $1 rush hour and overnight charges.
    MTA_tax0.50 MTA tax that is automatically triggered based on the metered rate in use.
    Improvement_surcharge0.30 improvement surcharge assessed trips at the flag drop. the improvement surcharge began being levied in 2015.
  2. d

    TAXIS

    • datos.gob.es
    • valencia.aws-ec2-eu-central-1.opendatasoft.com
    • +1more
    Updated Feb 26, 2025
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    Ayuntamiento de Valencia (2025). TAXIS [Dataset]. https://datos.gob.es/ca/catalogo/l01462508-taxis
    Explore at:
    Dataset updated
    Feb 26, 2025
    Dataset authored and provided by
    Ayuntamiento de Valencia
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Ubicación de paradas de taxi

  3. o

    Parking spaces for taxis registered by Brussels Mobility (City of Brussels)

    • bruxellesdata.aws-ec2-eu-1.opendatasoft.com
    • opendata.bruxelles.be
    • +2more
    csv, excel, geojson +1
    Updated Nov 15, 2025
    + more versions
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    (2025). Parking spaces for taxis registered by Brussels Mobility (City of Brussels) [Dataset]. https://bruxellesdata.aws-ec2-eu-1.opendatasoft.com/explore/dataset/places-de-parking-taxis-recensees-par-bruxelles-mobilite-vbx/api/
    Explore at:
    geojson, csv, json, excelAvailable download formats
    Dataset updated
    Nov 15, 2025
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Brussels
    Description

    List of parking spaces for taxis registered by Brussels Mobility and located on the territory of the City of Brussels

    More info: https://www.brussels.be/taxi

  4. I

    New York City Hourly Traffic Estimates (2010-2013)

    • databank.illinois.edu
    • aws-databank-alb.library.illinois.edu
    Updated Feb 10, 2021
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    Brian Donovan; Alec Mori; Nimit Agrawal; Yalan Meng; Jong Lee; Daniel Work (2021). New York City Hourly Traffic Estimates (2010-2013) [Dataset]. http://doi.org/10.13012/B2IDB-4900670_V1
    Explore at:
    Dataset updated
    Feb 10, 2021
    Authors
    Brian Donovan; Alec Mori; Nimit Agrawal; Yalan Meng; Jong Lee; Daniel Work
    Area covered
    New York
    Dataset funded by
    U.S. National Science Foundation (NSF)
    Description

    This dataset contains hourly traffic estimates (speeds) for individual links of the New York City road network for the years 2010-2013, estimated from New York City Taxis.

  5. o

    Taxis collectifs "Collecto"

    • bruxellesdata.aws-ec2-eu-1.opendatasoft.com
    • opendata.brussels.be
    • +2more
    csv, excel, geojson +1
    Updated Sep 11, 2025
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    (2025). Taxis collectifs "Collecto" [Dataset]. https://bruxellesdata.aws-ec2-eu-1.opendatasoft.com/explore/dataset/arrets-collecto0/?flg=fr-fr
    Explore at:
    excel, csv, geojson, jsonAvailable download formats
    Dataset updated
    Sep 11, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Ce jeu de donnée géolocalise les arrêts Collecto sur le territoire de la Ville de Bruxelles. Collecto est un service de taxis collectifs disponible 7j/7 entre 23 heures et 6 heures du matin sur tout le territoire de la Région de Bruxelles-Capitale. Le service Collecto permet d’embarquer à un des 200 points d’embarquement situés à des arrêts de la STIB, et de débarquer à l’adresse de son choix, dans les limites de la Région bruxelloise. Ce jeu de donnée est mise à jour quelques fois par ans.

    Plus d'info: www.collecto.be

  6. b

    Collectieve taxis "Collecto"

    • opendata.brussel.be
    • opendata.bruxelles.be
    • +3more
    csv, excel, geojson +1
    Updated Sep 11, 2025
    + more versions
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    (2025). Collectieve taxis "Collecto" [Dataset]. https://opendata.brussel.be/explore/dataset/arrets-collecto0/?q=recordid%3A0d23b87fb74598867f1b63c4975834b203c184b2&flg=nl-nl
    Explore at:
    geojson, excel, json, csvAvailable download formats
    Dataset updated
    Sep 11, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Deze dataset bevat de geolokalisatie van de Collecto-haltes op het grondgebied van de Stad Brussel. Collecto is een collectieve taxidienst die zeven dagen op zeven beschikbaar is tussen 23 uur ‘s avonds en 6 uur ‘s morgens binnen het Brussels Hoofdstedelijk Gewest. De service maakt het mogelijk om op te stappen aan één van de 200 Collecto-haltes gelegen aan een MIVB-halte en om te worden afgezet aan een adres binnen het Brussels Hoofdstedelijk Gewest. De dataset wordt enkele malen per jaar bijgewerkt.

    Meer info: www.collecto.be

  7. n

    Namur - Parking - Emplacements (points)

    • opendata.namur.be
    • data.namur.be
    • +4more
    csv, excel, geojson +1
    Updated Nov 27, 2025
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    (2025). Namur - Parking - Emplacements (points) [Dataset]. https://opendata.namur.be/explore/dataset/namur-parking-emplacements/custom/
    Explore at:
    excel, geojson, csv, jsonAvailable download formats
    Dataset updated
    Nov 27, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Cartographie ponctuelle des emplacements de parking. Positionner au centre de chaque emprise.En attribut : la zone réglementée (rouge, verte, bleue, etc.), le type d'emplacement (Normal, privé, dépose minute, etc.), éventuellement les horaires d'utilisation et l'adresse la plus proche.Dépose minute : zone d’arrêt qui permet de déposer ou reprendre un étudiant, un travailleur, un navetteur,... L’arrêt y est autorisé uniquement pendant le temps nécessaire à l’embarquement ou au débarquement. Le stationnement y est interdit.Taxi : zone de stationnement réservée aux taxis.Car : zone de chargement, de déchargement et de stationnement réservée aux autocars.Bus scolaire : zone de chargement, de déchargement et de stationnement réservée pour les bus scolaires.Borne électrique : zone de stationnement équipée d’une borne de rechargement pour véhicule électrique, réservée à ce type de véhicules pendant leur chargement.Zones de livraisons : zone d’arrêt réservée pour les livraisons suivant l’horaire indiqué en début de zone (majoritairement de 7h30 à 11h30). L’arrêt y est autorisé uniquement pendant le temps nécessaire au chargement/déchargement. Zone cartographiée : zone d'agglomération du schéma de structure communale (voir jeu de donnée).

  8. o

    Parkeerplaatsen voor taxi’s geregistreerd door Brussel Mobiliteit (Stad...

    • bruxellesdata.opendatasoft.com
    • opendata.bruxelles.be
    • +3more
    csv, excel, geojson +1
    Updated Dec 2, 2025
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    (2025). Parkeerplaatsen voor taxi’s geregistreerd door Brussel Mobiliteit (Stad Brussel) [Dataset]. https://bruxellesdata.opendatasoft.com/explore/dataset/places-de-parking-taxis-recensees-par-bruxelles-mobilite-vbx/?flg=nl-nl
    Explore at:
    json, csv, geojson, excelAvailable download formats
    Dataset updated
    Dec 2, 2025
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Brussel, Brussel
    Description

    Lijst van parkeerplaatsen voor taxi’s geregistreerd door Brussel Mobiliteit en gelegen in de Stad Brussel

    Meer info: https://www.brussel.be/taxi

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Elemento (2021). NYC Yellow Taxi Trip Data [Dataset]. https://www.kaggle.com/datasets/elemento/nyc-yellow-taxi-trip-data
Organization logo

NYC Yellow Taxi Trip Data

Pratice your ML skills on this Time-Series Dataset!

Explore at:
zip(1915626894 bytes)Available download formats
Dataset updated
Dec 9, 2021
Authors
Elemento
License

https://www.usa.gov/government-works/https://www.usa.gov/government-works/

Area covered
New York
Description

Context

New York City (NYC) Taxi & Limousine Commission (TLC) keeps data from all its cabs, and it is freely available to download from its official website. You can access it here. Now, the TLC primarily keeps and manages data for 4 different types of vehicles: - Yellow Taxi: Yellow Medallion Taxicabs: These are the famous NYC yellow taxis that provide transportation exclusively through street hails. The number of taxicabs is limited by a finite number of medallions issued by the TLC. You access this mode of transportation by standing in the street and hailing an available taxi with your hand. The pickups are not pre-arranged. - Green Taxi: Street Hail Livery: The SHL program will allow livery vehicle owners to license and outfit their vehicles with green borough taxi branding, meters, credit card machines, and ultimately the right to accept street hails in addition to pre-arranged rides. - For-Hire Vehicles (FHVs): FHV transportation is accessed by a pre-arrangement with a dispatcher or limo company. These FHVs are not permitted to pick up passengers via street hails, as those rides are not considered pre-arranged.

Complimentary Kernel

  • I have made a Kernel especially for this dataset, which uses Clustering, Regression, and Time-Series techniques for this dataset. You can check it out here.

Important Points

  • In this dataset, we are considering only the Yellow Taxis Data, for the months of Jan 2015 & Jan-mar 2016.
  • If you go over to the website of NYC TLC, and download any of the CSV files, you will find a different format of these files. This is because, the TLC regularly adds more data, alongside updating the existing one.
  • One of the key changes that they have made to their data is that, instead of providing the pickup & dropoff coordinates, they have divided the NYC into regions and indexed those regions, and in the CSV files, they have provided these indices.
  • Due to this reason only, I have made this dataset using the previous version of the CSV files. This dataset allows me to practice my clustering knowledge alongside my time-series knowledge.
  • If you want to leave out the clustering part, then just go over to their website, and download the new CSV files.

Attributes

...

Field NameDescription
VendorID A code indicating the TPEP provider that provided the record.
  1. Creative Mobile Technologies
  2. VeriFone Inc.
tpep_pickup_datetimeThe date and time when the meter was engaged.
tpep_dropoff_datetimeThe date and time when the meter was disengaged.
Passenger_countThe number of passengers in the vehicle. This is a driver-entered value.
Trip_distanceThe elapsed trip distance in miles reported by the taximeter.
Pickup_longitudeLongitude where the meter was engaged.
Pickup_latitudeLatitude where the meter was engaged.
RateCodeIDThe 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
Store_and_fwd_flagThis flag indicates whether the trip record was held in vehicle memory before sending to the vendor,
aka “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
Dropoff_longitudeLongitude where the meter was disengaged.
Dropoff_ latitudeLatitude where the meter was disengaged.
Payment_typeA 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
Fare_amountThe time-and-distance fare calculated by the meter.
ExtraMiscellaneous extras and surcharges. Currently, this only includes. the $0.50 and $1 rush hour and overnight charges.
MTA_tax0.50 MTA tax that is automatically triggered based on the metered rate in use.
Improvement_surcharge0.30 improvement surcharge assessed trips at the flag drop. the improvement surcharge began being levied in 2015.
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