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Required Libraries

Prior to Running

  • Please ensure the following folders exist
    • raw_data
    • cleaned_data
    • final_data

Order of Execution

  • 01-get-data.py
  • 02-clean-game-logs.py
  • 03-get-advanced-box-scores.py
  • 04-calculate-advanced-box-scores.py
  • 05-extract-relevant-stats.py
  • 06-get-allstar-labels.py
  • 07-create-training-data.ipynb
  • 08-model-predict-ipynb

Note:
we recommend using the data provided in the repo and avoiding running steps 01 and 03 in their entirety as they involve calling an API and can take hours to run

Commands

  • Simply run each file without any command-line arguments (arguments are hard-coded)

Inputs

  • 01-get-data.py

    • None
  • 02-clean-game-logs.py

    • raw_data/game_logs.csv
  • 03-get-advanced-box-scores.py

    • cleaned_data/cleaned_game_logs.csv
  • 04-calculate-advanced-box-scores.py

    • raw_data/
      • pre_allstar_player_stats.csv
      • pre_allstar_team_stats.csv
      • raw_data/pre_allstar_player_stats.csv
      • advanced_team_box_scores.csv
    • cleaned_data/
      • cleaned_game_logs.csv.csv
  • 05-extract-relevant-stats.py

    • raw_data/
      • pre_allstar_player_stats.csv
      • advanced_player_box_scores.csv
      • advanced_player_stats.csv
    • cleaned_data/
      • cleaned_game_logs.csv
  • 06-get-allstar-labels.py

    • None
  • 07-create-training-data.ipynb

    • final_data/
      • allstars.csv
      • final_player_stats.csv
  • 08-model-predict-ipynb

    • final_data/
      • final_data.csv
      • 2023_season.csv

Files Produced

  • 01-get-data.py

    • raw_data/
      • pre_allstar_player_stats.csv
      • pre_allstar_team_stats.csv
      • game_logs.csv
  • 02-clean-game-logs.py

    • cleaned_data/cleaned_game_logs.csv
  • 03-get-advanced-box-scores.py

    • raw_data/
      • advanced_team_box_scores.csv
      • advanced_player_box_scores.csv
  • 04-calculate-advanced-box-scores.py

    • raw_data/advanced_player_stats
  • 05-extract-relevant-stats.py

    • final_data/final_player_stats.csv
  • 06-get-allstar-labels.py

    • final_data/allstars.csv
  • 07-create-training-data.ipynb

    • final_data/final_data.csv
  • 08-model-predict-ipynb

    • None

About

Data science project that scrapes and cleans NBA data, and analyzes it using machine learning algorithms to predict all-star selections

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