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https://github.com/shubham200137/icc-women-s-t20-world-cup-data-analytics

Created a Power BI report to identify top 11 players for a T20 cricket team by scraping data from espncricinfo with Python, cleaning and transforming the data with pandas, and evaluating various player performance metrics.
https://github.com/shubham200137/icc-women-s-t20-world-cup-data-analytics

beautifulsoup4 data-analysis data-visualization numpy-python pandas-python powerbi web-scraping

Last synced: about 1 month ago
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Host: GitHub
URL: https://github.com/shubham200137/icc-women-s-t20-world-cup-data-analytics
Owner: Shubham200137
Created: 2023-03-08T09:28:50.000Z (almost 2 years ago)
Default Branch: main
Last Pushed: 2024-06-25T22:48:02.000Z (8 months ago)
Last Synced: 2024-11-10T21:14:11.780Z (3 months ago)
Topics: beautifulsoup4, data-analysis, data-visualization, numpy-python, pandas-python, powerbi, web-scraping
Language: Jupyter Notebook
Homepage:
Size: 1.01 MB
Stars: 0
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

README

## ICC Women's T20 World Cup - Cricket Analysis
## Overview

- Created a Power BI report to identify the top 11 players for a T20 cricket team.
- Scraped data from ESPNcricinfo using beautifulsoup4.
- Cleaned and transformed the data with Pandas.
- Evaluated various player performance metrics.
- Used the resulting Power BI dashboard to select players for various categories: openers, middle order/anchors, finishers, all-rounders, and specialist fast bowlers.
- The selected team from the Power BI dashboard has a 90% chance of winning the game.

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# Visuals

The visualizations created can be accessed through the following link:

[Visuals](https://docs.google.com/presentation/d/1SlifE_rLSzyA_UW2b-jpTkmrRzFlIkPr/edit?usp=sharing&ouid=101647169591373102805&rtpof=true&sd=true)