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My Third Week: Starting Pandas (26 April-5 May 2025)
Overview Starting this week, I began learning Pandas and practiced data manipulation similar to what I do in Excel. I also learned how to visualize data using tools like Matplotlib and Seaborn. Daily Plan installing Pandas + Understanding DataFrame - Pandas 10-minute Complete Guide import CSVm View columns, Filter rows Extract specific team/Player data Calculate group averages(team scoring averages, etc) Practice: Calculating EPL Team Winning Percentage Visualization Taste: Getting Started with Matplotlib and Seaborn Mini Project: Create a Football Stats Report - Pandas + Matplotlib Reflection As I started learning Pandas, I was able to study the basics of building a sports analysis program in earnest. The deeper I delved into coding, the more I realized that programming requires creativity. It also made me question whether I could actually create a framework for a sports analysis program. Still, I want to see it through to the end.
Overview
Starting this week, I began learning Pandas and practiced data manipulation similar to what I do in Excel. I also learned how to visualize data using tools like Matplotlib and Seaborn.
Daily Plan
- installing Pandas + Understanding DataFrame - Pandas 10-minute Complete Guide
- import CSVm View columns, Filter rows
- Extract specific team/Player data
- Calculate group averages(team scoring averages, etc)
- Practice: Calculating EPL Team Winning Percentage
- Visualization Taste: Getting Started with Matplotlib and Seaborn
- Mini Project: Create a Football Stats Report - Pandas + Matplotlib
Reflection
As I started learning Pandas, I was able to study the basics of building a sports analysis program in earnest. The deeper I delved into coding, the more I realized that programming requires creativity. It also made me question whether I could actually create a framework for a sports analysis program. Still, I want to see it through to the end.
