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This tutorial goes over how to work with nflfastR data in Python and concludes four parts:
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Part 1 - Importing Packages and Scraping the Data
- Overview of the core python data science packages
- How to scrape nflfastR data
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Part 2 - Getting to Know the Data
- Basic pandas methods
- Data cleaning
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Part 3 - Basic Data Manipulation
- Subsetting/querying overview
- Using the data to compute important fantasy metrics
- Air yards data
- Redzone targets
- Carries inside the 5
- Calculating fantasy points for every play along with player totals
- One-Hot Encoding
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Part 4 - Data Viz! ๐
- Basic viz with fantasy relevant data
- Advanced viz using a function to show air yards distributions for any player