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NFL offensive stats dataset

As explained in Learn AI-Assisted Python Programming, Second Edition

A book-specific dataset and CSV file containing National Football League offensive statistics from 2019 through 2022.

The NFL offensive stats dataset contains National Football League offensive information from 2019 through 2022. Its nfl_offensive_stats.csv file uses the standard comma-separated values format: a header identifies each column, commas separate cells, and each row occupies its own line. section 2.8.2

The dataset supports a practical data-processing workflow:

  • Preview the file through Kaggle, VS Code, or spreadsheet software such as Microsoft Excel. section 2.8.2
  • Use Python CSV tools to read the file and inspect fields such as player, team, position, and passing statistics. section 2.8.2

Ranking quarterbacks

A generated Python program reads nfl_offensive_stats.csv, identifies players whose position is QB, totals their passing yards, and prints the leaders. The displayed results begin with Patrick Mahomes, Tom Brady, Aaron Rodgers, Josh Allen, and Derek Carr; a follow-up change excludes Tom Brady from the output.

How Learn AI-Assisted Python Programming, Second Edition covers it

How deep it goes
Defines CSV structure and demonstrates filtering, aggregation, sorting, and conditional exclusion without requiring code comprehension.
Examples
Shows quarterback passing-yard totals, sorted rankings, and a revised ranking that excludes Tom Brady.
What it assumes
Assumes only interest in data processing and postpones code understanding until later instruction.
What you can do after
Apply it via Python to read a CSV, select quarterbacks, total passing yards, sort results, and alter output conditions.
How it connects
Connects CSV files with Python, data processing, and Copilot-generated code.
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Learn AI-Assisted Python Programming, Second Edition. The section links point to the parts of the book it draws on.