89 datasets found
  1. h

    538-NBA-Historical-Raptor

    • huggingface.co
    Updated Aug 8, 2023
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    Andrew Kroening (2023). 538-NBA-Historical-Raptor [Dataset]. https://huggingface.co/datasets/andrewkroening/538-NBA-Historical-Raptor
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Aug 8, 2023
    Authors
    Andrew Kroening
    License

    https://choosealicense.com/licenses/cc/https://choosealicense.com/licenses/cc/

    Description

    Dataset Overview

      Intro
    

    This dataset was downloaded from the good folks at fivethirtyeight. You can find the original (or in the future, updated) versions of this and several similar datasets at this GitHub link.

      Data layout
    

    Here are the columns in this dataset, which contains data on every NBA player, broken out by season, since the 1976 NBA-ABA merger:

    Column Description

    player_name Player name

    player_id Basketball-Reference.com player ID

    season… See the full description on the dataset page: https://huggingface.co/datasets/andrewkroening/538-NBA-Historical-Raptor.

  2. R

    Custom Segmentation 538 Dataset

    • universe.roboflow.com
    zip
    Updated Mar 28, 2025
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    ACD2 (2025). Custom Segmentation 538 Dataset [Dataset]. https://universe.roboflow.com/acd2/custom-segmentation-538
    Explore at:
    zipAvailable download formats
    Dataset updated
    Mar 28, 2025
    Dataset authored and provided by
    ACD2
    License

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

    Variables measured
    Cracks Polygons
    Description

    Custom Segmentation 538

    ## Overview
    
    Custom Segmentation 538 is a dataset for instance segmentation tasks - it contains Cracks annotations for 538 images.
    
    ## Getting Started
    
    You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
    
      ## License
    
      This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
    
  3. A

    ‘Biden Approval Polling’ analyzed by Analyst-2

    • analyst-2.ai
    Updated Jan 10, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Biden Approval Polling’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/kaggle-biden-approval-polling-9acc/cdf74032/?iid=004-975&v=presentation
    Explore at:
    Dataset updated
    Jan 10, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

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

    Description

    Analysis of ‘Biden Approval Polling’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/kaggleqrdl/biden-approval-polling on 28 January 2022.

    --- Dataset description provided by original source is as follows ---

    Context

    There is a contract on Predictit.org tracking Biden's approval rating that I've followed out of fun (no profit). I often used this data to help predict where it will go next. For example, Rasmussen is a very fresh pollster (daily), while the others are somewhat lagging. You can even subscribe to Rasmussen's service and get updates before most people, though this particular exploit is well known.

    Content

    The data is fairly straightforward and I include a brief description of each of the columns.

    Something to be aware: a few pollsters, such as Ipsos, will report wildly different results within days because they are sometimes polling for specific organizations, such as the Economist and sometimes just for themselves. In these different surveys, there are different questions used, and thus different 'house effects' (ie: political bias). For example, some surveys start with the question "Do you approve of the direction of the country?", while others will start with "Do you approve of Joe Biden?"

    Acknowledgements

    I would like to acknowledge Nate Silver and the whole 538 crew for aggregating this data. Very interesting and informative - https://projects.fivethirtyeight.com/biden-approval-rating/

    Please note I have removed all 538 model specific information such as weights, grades, etc.

    Inspiration

    I think it'd be very cool to see how far ahead we could predict changes in Biden's approval ratings, possibly using other sources such as twitter and news organizations, plus maybe other datasets on Kaggle itself.

    --- Original source retains full ownership of the source dataset ---

  4. d

    Advance Weekly Initial and Continued Claims (ETA-538)

    • catalog.data.gov
    • s.cnmilf.com
    Updated Apr 18, 2024
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    Employment and Training Administration (2024). Advance Weekly Initial and Continued Claims (ETA-538) [Dataset]. https://catalog.data.gov/dataset/advance-weekly-initial-and-continued-claims-eta-538
    Explore at:
    Dataset updated
    Apr 18, 2024
    Dataset provided by
    Employment and Training Administration
    Description

    Historical series of Advance Weekly Initial and Continued Claims reports (ETA 538). This information is provided by states on a weekly basis and includes the advance weekly claims data as reported by states in the ETA 538 report. These data are not revised after the initial submission and subsequent publication in the UI weekly claims news release.

  5. FiveThirtyEight Daily Show Guests Dataset

    • kaggle.com
    zip
    Updated Jan 13, 2019
    + more versions
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    FiveThirtyEight (2019). FiveThirtyEight Daily Show Guests Dataset [Dataset]. https://www.kaggle.com/fivethirtyeight/fivethirtyeight-daily-show-guests-dataset
    Explore at:
    zip(37571 bytes)Available download formats
    Dataset updated
    Jan 13, 2019
    Dataset authored and provided by
    FiveThirtyEighthttps://abcnews.go.com/538
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    Daily Show Guests

    This folder contains data behind the story Every Guest Jon Stewart Ever Had On ‘The Daily Show’.

    HeaderDefinition
    YEARThe year the episode aired
    GoogleKnowlege_OccupationTheir occupation or office, according to Google's Knowledge Graph or, if they're not in there, how Stewart introduced them on the program.
    ShowAir date of episode. Not unique, as some shows had more than one guest
    GroupA larger group designation for the occupation. For instance, us senators, us presidents, and former presidents are all under "politicians"
    Raw_Guest_ListThe person or list of people who appeared on the show, according to Wikipedia. The GoogleKnowlege_Occupation only refers to one of them in a given row.

    Source: Google Knowlege Graph, The Daily Show clip library, Wikipedia.

    Context

    This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

    • Update Frequency: This dataset is updated daily.

    Acknowledgements

    This dataset is maintained using GitHub's API and Kaggle's API.

    This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

    Cover photo by Oscar Nord on Unsplash
    Unsplash Images are distributed under a unique Unsplash License.

  6. C

    Sheet 538 of the Digital Elevation Model with 25 meter mesh pitch (Spain)

    • processor1.francecentral.cloudapp.azure.com
    ecma, zip
    Updated Apr 14, 2023
    + more versions
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    IGN ES (2023). Sheet 538 of the Digital Elevation Model with 25 meter mesh pitch (Spain) [Dataset]. http://processor1.francecentral.cloudapp.azure.com/dataset/sheet-538-of-the-digital-model-of-elevations-with-mesh-step-25-meters-spain
    Explore at:
    zip, ecmaAvailable download formats
    Dataset updated
    Apr 14, 2023
    Dataset provided by
    IGN ES
    Area covered
    Spain
    Description

    Digital terrain model with a 25 m mesh pitch, with the same leaf distribution as the MTN50. ASCII ESRI Matrix (asc) file format. Geodetic reference system ETRS89 (in the Canary Islands REGCAN95, compatible with ETRS89) and UTM projection in the zone corresponding to each leaf and also in the extended zone 30 (for leaves located in zones 29 and 31). In the Canary Islands, the UTM zone is 28. The MDT25 has been obtained by interpolation of digital terrain models with a 5 m mesh pitch from the National Plan for Aerial Orthophotography (PNOA).

  7. 3 Million Russian Troll Tweets (538)

    • kaggle.com
    zip
    Updated Aug 1, 2018
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    iXiOiXi (2018). 3 Million Russian Troll Tweets (538) [Dataset]. https://www.kaggle.com/datasets/ixioixi/3-million-russian-troll-tweets-538
    Explore at:
    zip(183448163 bytes)Available download formats
    Dataset updated
    Aug 1, 2018
    Authors
    iXiOiXi
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Dataset

    This dataset was created by iXiOiXi

    Released under CC0: Public Domain

    Contents

  8. FiveThirtyEight Mad Men Dataset

    • kaggle.com
    zip
    Updated Dec 13, 2018
    + more versions
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    FiveThirtyEight (2018). FiveThirtyEight Mad Men Dataset [Dataset]. https://www.kaggle.com/fivethirtyeight/fivethirtyeight-mad-men-dataset
    Explore at:
    zip(16691 bytes)Available download formats
    Dataset updated
    Dec 13, 2018
    Dataset authored and provided by
    FiveThirtyEighthttps://abcnews.go.com/538
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    Mad Men

    This directory contains the data behind the story ‘Mad Men’ Is Ending. What’s Next For The Cast?

    The primary file show-data.csv contains data of actors who appeared on at least half the episodes of television shows that were nominated for an Emmy for Outstanding Drama since the year 2000. It contains the following variables:

    HeaderDefinition
    PerformerThe name of the actor, according to IMDb. This is not a unique identifier - two performers appeared in more than one program
    ShowThe television show where this actor appeared in more than half the episodes
    Show StartThe year the television show began
    Show EndThe year the television show ended, "PRESENT" if the show remains on the air as of May 10.
    Status?Why the actor is no longer on the program: "END" if the show has concluded, "LEFT" if the show remains on the air.
    CharEndThe year the character left the show. Equal to "Show End" if the performer stayed on until the final season.
    Years Since2015 minus CharEnd
    #LEADThe number of leading roles in films the performer has appeared in since and including "CharEnd", according to OpusData
    #SUPPORTThe number of leading roles in films the performer has appeared in since and including "CharEnd", according to OpusData
    #ShowsThe number of seasons of television of which the performer appeared in at least half the episodes since and including "CharEnd", according to OpusData
    Score#LEAD + #Shows + 0.25*(#SUPPORT)
    Score/Y"Score" divided by "Years Since"
    lead_notesThe list of films counted in #LEAD
    support_notesThe list of films counted in #SUPPORT
    show_notesThe seasons of shows counted in #Shows

    The supplemental file performer-scores.csv is the consolidated data from show-data.csv made into a pivot table.

    Context

    This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

    • Update Frequency: This dataset is updated daily.

    Acknowledgements

    This dataset is maintained using GitHub's API and Kaggle's API.

    This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

  9. g

    gi 538-20240612T1005

    • gimi9.com
    • data.ioos.us
    • +2more
    Updated Jun 12, 2024
    + more versions
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    (2024). gi 538-20240612T1005 [Dataset]. https://gimi9.com/dataset/data-gov_gi_538-20240612t1005/
    Explore at:
    Dataset updated
    Jun 12, 2024
    License

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

    Description

    The Global component of the OOI includes arrays at critical, yet under-sampled, high-latitude locations such as within the Irminger Sea in the North Atlantic. The Global Irminger Sea Array includes two types of gliders that provide simultaneous spatial and temporal sampling capabilities. Open-Ocean Gliders follow track lines around the triangular mooring array and are equipped with acoustic modems to relay data from the Flanking Moorings to shore via satellite telemetry. Profiling Gliders sample the upper water column near the Apex Profiler Mooring.

  10. NCAA Women 538 team ratings

    • kaggle.com
    Updated Mar 16, 2023
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    raddar (2023). NCAA Women 538 team ratings [Dataset]. https://www.kaggle.com/raddar/ncaa-women-538-team-ratings/tasks
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 16, 2023
    Dataset provided by
    Kaggle
    Authors
    raddar
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description
  11. o

    538 Road Cross Street Data in Tahlequah, OK

    • ownerly.com
    Updated Jan 16, 2022
    + more versions
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    Ownerly (2022). 538 Road Cross Street Data in Tahlequah, OK [Dataset]. https://www.ownerly.com/ok/tahlequah/538-rd-home-details
    Explore at:
    Dataset updated
    Jan 16, 2022
    Dataset authored and provided by
    Ownerly
    Area covered
    Tahlequah, Oklahoma, North 538 Road, North 538 Road
    Description

    This dataset provides information about the number of properties, residents, and average property values for 538 Road cross streets in Tahlequah, OK.

  12. FiveThirtyEight Obama Commutations Dataset

    • kaggle.com
    zip
    Updated Jan 4, 2019
    + more versions
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    FiveThirtyEight (2019). FiveThirtyEight Obama Commutations Dataset [Dataset]. https://www.kaggle.com/fivethirtyeight/fivethirtyeight-obama-commutations-dataset
    Explore at:
    zip(87648 bytes)Available download formats
    Dataset updated
    Jan 4, 2019
    Dataset authored and provided by
    FiveThirtyEight
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    Obama Commutation

    This folder contains data behind the story Obama Granted Clemency Unlike Any Other President In History.

    The data in obama_commutations.csv is copied from the Justice Department website. The python script parses it by looking at the first column to figure out what is contained in the second column.

    Source: Department of Justice

    Context

    This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

    • Update Frequency: This dataset is updated daily.

    Acknowledgements

    This dataset is maintained using GitHub's API and Kaggle's API.

    This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

  13. o

    Scr 538 Cross Street Data in Morton, MS

    • ownerly.com
    Updated Aug 15, 2022
    + more versions
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    Ownerly (2022). Scr 538 Cross Street Data in Morton, MS [Dataset]. https://www.ownerly.com/ms/morton/scr-538-home-details
    Explore at:
    Dataset updated
    Aug 15, 2022
    Dataset authored and provided by
    Ownerly
    Area covered
    Morton, Mississippi
    Description

    This dataset provides information about the number of properties, residents, and average property values for Scr 538 cross streets in Morton, MS.

  14. g

    ga 538-20151124T1730-delayed

    • gimi9.com
    • gliders.ioos.us
    • +1more
    Updated Nov 24, 2015
    + more versions
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    (2015). ga 538-20151124T1730-delayed [Dataset]. https://gimi9.com/dataset/data-gov_ga_538-20151124t1730-delayed1/
    Explore at:
    Dataset updated
    Nov 24, 2015
    License

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

    Description

    The Global component of the OOI includes arrays at critical, yet under-sampled, locations such as within the Argentine Basin in the South Atlantic Ocean. The Global Argentine Basin Array includes two types of gliders that provide simultaneous spatial and temporal sampling capabilities. Open-Ocean Gliders follow track lines around the triangular mooring array and are equipped with acoustic modems to relay data from the Flanking Moorings to shore via satellite telemetry. Profiling Gliders sample the upper water column near the Apex Profiler Mooring.

  15. FiveThirtyEight Antiquities Act Dataset

    • kaggle.com
    zip
    Updated Feb 1, 2019
    + more versions
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    FiveThirtyEight (2019). FiveThirtyEight Antiquities Act Dataset [Dataset]. https://www.kaggle.com/fivethirtyeight/fivethirtyeight-antiquities-act-dataset
    Explore at:
    zip(8324 bytes)Available download formats
    Dataset updated
    Feb 1, 2019
    Dataset authored and provided by
    FiveThirtyEighthttps://abcnews.go.com/538
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    Antiquities Act

    This folder contains the data behind the story Trump Might Be The First President To Scrap A National Monument.

    This data was compiled by the National Parks Conservation Association and includes national monuments that were created by presidents by under the Antiquities Act. It does not include national monuments created by Congress.

    HeaderDefinition
    current_nameCurrent name of piece of land designated under the Antiquities Act
    statesState(s) or territory where land is located
    original_nameIf included, original name of piece of land designated under the Antiquities Act
    current_agencyCurrent land management agency. NPS = National Parks Service, BLM = Bureau of Land Management, USFS = US Forest Service, FWS = US Fish and Wildlife Service, NOAA = National Oceanic and National Oceanic and Atmospheric Administration
    actionType of action taken on land
    dateDate of action
    yearYear of action
    pres_or_congressPresident or congress that issued action
    acres_affectedAcres affected by action. Note that total current acreage is not included. National monuments that cover ocean are listed in square miles.

    Sources: National Parks Conservation Association and National Parks Service Archeology Program

    Context

    This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

    • Update Frequency: This dataset is updated daily.

    Acknowledgements

    This dataset is maintained using GitHub's API and Kaggle's API.

    This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

    Cover photo by Nick Tiemeyer on Unsplash
    Unsplash Images are distributed under a unique Unsplash License.

  16. o

    County Road 538 Cross Street Data in Ripley, MS

    • ownerly.com
    Updated Dec 11, 2021
    + more versions
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    Ownerly (2021). County Road 538 Cross Street Data in Ripley, MS [Dataset]. https://www.ownerly.com/ms/ripley/county-road-538-home-details
    Explore at:
    Dataset updated
    Dec 11, 2021
    Dataset authored and provided by
    Ownerly
    Area covered
    Ripley, County Road 538, Mississippi
    Description

    This dataset provides information about the number of properties, residents, and average property values for County Road 538 cross streets in Ripley, MS.

  17. f

    S2 File -

    • plos.figshare.com
    odt
    Updated Nov 9, 2023
    + more versions
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    Michael Bonert; Alison Berzins; Housne Begum; Jens Schittenhelm; Jian-Qiang Lu; Rosalyn A. Juergens; Anand Swaminath; Jean-Claude Cutz; Asghar H. Naqvi (2023). S2 File - [Dataset]. http://doi.org/10.1371/journal.pone.0294154.s002
    Explore at:
    odtAvailable download formats
    Dataset updated
    Nov 9, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Michael Bonert; Alison Berzins; Housne Begum; Jens Schittenhelm; Jian-Qiang Lu; Rosalyn A. Juergens; Anand Swaminath; Jean-Claude Cutz; Asghar H. Naqvi
    License

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

    Description

    Brain metastases are a frequent occurrence in neuropathology practices. The literature on their neuroanatomical location is frequently derived from radiological analyses. This work examines brain metastases through the lens of pathology specimens. All brain surgical pathology reports for cases accessioned 2011–2020 were retrieved from a laboratory. Specimens were classified by neuroanatomical location, diagnosis and diagnostic category with a hierarchical free text string-matching algorithm (HFTSMA) and also subsequently audited. All reports classified as probable metastasis were reviewed by a pathologist. The provided history was compared to the final categorization by a pathologist. The cohort had 4,625 cases. The HFTSMA identified 854 cases (including metastases from a definite primary, metastases from primary not known and improperly classified cases). 514/854 cases had one definite primary site per algorithm and on report review 538/854 cases were confirmed as such. The 538 cases originated from 511 patients. Primaries from breast, gynecologic tract, and gastrointestinal tract not otherwise specified were most frequently found in the cerebellum. Kidney metastases were most frequently found in the occipital lobe. Lung, metastatic melanoma and colorectal primaries were most commonly found in the frontal lobe. The provided clinical history predicted the primary in 206 cases (40.3%), was discordant in 17 cases (3.3%) and non-contributory in 280 cases (54.8%). The observed distribution of the metastatic tumours in the brain is dependent on the primary site. In the majority (54.8%) of cases, the provided clinical history was non-contributory; this suggests surgeon-pathologist communication may have the potential for optimization.

  18. FiveThirtyEight Police Locals Dataset

    • kaggle.com
    Updated Mar 26, 2019
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    FiveThirtyEight (2019). FiveThirtyEight Police Locals Dataset [Dataset]. https://www.kaggle.com/fivethirtyeight/fivethirtyeight-police-locals-dataset/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 26, 2019
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    FiveThirtyEight
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Content

    Police Residence

    This folder contains data behind the story Most Police Don’t Live In The Cities They Serve.

    Includes the cities with the 75 largest police forces, with the exception of Honolulu for which data is not available. All calculations are based on data from the U.S. Census.

    The Census Bureau numbers are potentially going to differ from other counts for three reasons:

    1. The census category for police officers also includes sheriffs, transit police and others who might not be under the same jurisdiction as a city’s police department proper. The census category won’t include private security officers.
    2. The census data is estimated from 2006 to 2010; police forces may have changed in size since then.
    3. There is always a margin of error in census numbers; they are estimates, not complete counts.

    How to read police-locals.csv

    HeaderDefinition
    cityU.S. city
    police_force_sizeNumber of police officers serving that city
    allPercentage of the total police force that lives in the city
    whitePercentage of white (non-Hispanic) police officers who live in the city
    non-whitePercentage of non-white police officers who live in the city
    blackPercentage of black police officers who live in the city
    hispanicPercentage of Hispanic police officers who live in the city
    asianPercentage of Asian police officers who live in the city

    Note: When a cell contains ** it means that there are fewer than 100 police officers of that race serving that city.

    Context

    This is a dataset from FiveThirtyEight hosted on their GitHub. Explore FiveThirtyEight data using Kaggle and all of the data sources available through the FiveThirtyEight organization page!

    • Update Frequency: This dataset is updated daily.

    Acknowledgements

    This dataset is maintained using GitHub's API and Kaggle's API.

    This dataset is distributed under the Attribution 4.0 International (CC BY 4.0) license.

  19. p

    News Services in Spain - 538 Available (Free Sample)

    • poidata.io
    csv
    Updated May 13, 2025
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    Poidata.io (2025). News Services in Spain - 538 Available (Free Sample) [Dataset]. https://www.poidata.io/report/news-service/spain
    Explore at:
    csvAvailable download formats
    Dataset updated
    May 13, 2025
    Dataset provided by
    Poidata.io
    Area covered
    Spain
    Description

    This dataset provides information on 538 in Spain as of May, 2025. It includes details such as email addresses (where publicly available), phone numbers (where publicly available), and geocoded addresses. Explore market trends, identify potential business partners, and gain valuable insights into the industry. Download a complimentary sample of 10 records to see what's included.

  20. O

    Data from: 538

    • data.qld.gov.au
    Updated May 9, 2023
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    Geological Survey of Queensland (2023). 538 [Dataset]. https://www.data.qld.gov.au/dataset/bh035569
    Explore at:
    Dataset updated
    May 9, 2023
    Dataset authored and provided by
    Geological Survey of Queensland
    License

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

    Description
Share
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Andrew Kroening (2023). 538-NBA-Historical-Raptor [Dataset]. https://huggingface.co/datasets/andrewkroening/538-NBA-Historical-Raptor

538-NBA-Historical-Raptor

andrewkroening/538-NBA-Historical-Raptor

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CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Aug 8, 2023
Authors
Andrew Kroening
License

https://choosealicense.com/licenses/cc/https://choosealicense.com/licenses/cc/

Description

Dataset Overview

  Intro

This dataset was downloaded from the good folks at fivethirtyeight. You can find the original (or in the future, updated) versions of this and several similar datasets at this GitHub link.

  Data layout

Here are the columns in this dataset, which contains data on every NBA player, broken out by season, since the 1976 NBA-ABA merger:

Column Description

player_name Player name

player_id Basketball-Reference.com player ID

season… See the full description on the dataset page: https://huggingface.co/datasets/andrewkroening/538-NBA-Historical-Raptor.

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