Power Bi Project | IPL Data Anaysis | Data Cleaning
🧹 Power BI IPL Data Analysis – Part 3 | Data Cleaning using Python 🏏
Welcome to Part 3 of the IPL Data Analysis Project using Power BI.
In this video, we focus on one of the most important steps in any data project — Data Cleaning.
I’ve taken 3 raw IPL CSV files and cleaned them using Python, making the data analysis-ready for upcoming Power BI dashboards.
🔍 What’s covered in this video:
• Understanding raw IPL datasets
• Cleaning 3 CSV files using Python
• Handling missing values
• Fixing data inconsistencies
• Renaming columns & standardizing formats
• Exporting cleaned CSV files
• Preparing data for Power BI
📁 GitHub Repository (Python Notebooks + Cleaned CSV Files):
👉 https://github.com/dipakwaghmode007/IPL_Da...
💡 Why data cleaning matters?
Clean data leads to:
✔️ Accurate insights
✔️ Better Power BI visuals
✔️ Correct DAX calculations
✔️ Professional dashboards
📌 Previous Videos in this Playlist:
• Part 1 – IPL Data Analysis Project Introduction
• Part 2 – Data Scraping using Python
🚀 Upcoming Videos:
• Data Modeling in Power BI
• DAX Measures & KPIs
• Interactive IPL Dashboards
🔔 If you want to master Power BI with real-world projects, don’t forget to Like, Share & Subscribe to the channel.
📩 For queries, feedback, or collaboration:
[email protected]
Optional Short Version (for Pinned Comment)
📌 Resources used in this video:
✔️ Python data cleaning notebooks
✔️ 3 cleaned IPL CSV files
👉 GitHub: https://github.com/dipakwaghmode007/IPL_Da...