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NBA Dataset Fork

✓ Published0🌍 Public
JJack Hanlon
Last edited Sep 12, 2024
Created on Sep 3, 2024

This example displays a single NBA player’s raw statistics as formatted JSON, using the v3 dataset from the 23/24 season. The `index.js` file imports the CSV data, coerces all numeric fields with unary plus operators, and renders the first record via `JSON.stringify` inside a template literal placed in a container’s `innerHTML`. The output shows the full base averages for that player, confirming the data structure without any charting or visualization libraries.

AI-generated description

The NBA Players 23/24 Season Statistics Dataset, loaded and parsed as CSV.

Shares the full base statistic averages for each player who suited up for a regular season game in the 23/24 season. No advanced statistics available.

Tasks for the dataset:

  1. Create a correlation matrix between all of the statistics tracked
  2. Find the best players in the league based on offensive stats
  3. Find the best players in the league based on defensive stats
  4. Find the relationship between minutes played and points per game and see who ranks above the rest
  5. See if there is a postive/upward trending relationship between ORB and FTA or DRB and AST as the two statistics should be heavily related with the way the game is played
MIT Licensed

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