Data-Analytics Project for Beginners
This project involves analyzing data from the T20 World Cup 2022 to select the best 11-player team. The project combines web scraping, data cleaning, analysis, and visualization to provide comprehensive insights into player performance.
Web Scraping: Extracted cricket data from ESPN Cricinfo using Bright Data.
Data Cleaning and Transformation: Utilized Python and Pandas to clean and preprocess the data for analysis.
Data Analysis: Analyzed key player statistics such as batting averages and bowling performance to inform team selection.
Interactive Dashboard: Created a Power BI dashboard to visualize player performance metrics, enabling data-driven decision-making.
Python (Pandas): Data manipulation, cleaning, and transformation.
Power BI: Creating interactive visualizations and dashboards.
Web Scraping: Automated data extraction from websites.
data/: Contains raw and cleaned data files.
scripts/: Python scripts for web scraping and data processing.
dashboard/: Power BI dashboard file.
README.md: Project overview and usage instructions.
This project showcases the application of data analysis and visualization techniques to real-world sports data, providing actionable insights for team selection in T20 cricket.