🏏 IPL 2023 Auction Analysis

Welcome to the IPL 2023 Auction Analysis repository! This project explores the Indian Premier League (IPL) 2023 Auction dataset to uncover insights about player sales, pricing, and team acquisitions using Python and data visualization libraries.

📌 Project Overview

This analysis aims to:

• 📊 Perform Exploratory Data Analysis (EDA) on IPL auction data.
• 🏷️ Identify trends in player pricing, retention, and unsold players.
• 📈 Visualize insights using Matplotlib, Seaborn, and Squarify.

📂 Dataset

The dataset used in this project contains details about:

• Player names and roles
• Nationality
• Base price and final auction price
• Franchise allocation and player status (Sold/Unsold/Retained)

🛠️ Tech Stack

• Programming Language: Python 🐍
• Libraries Used:
  • pandas - for data manipulation
  • numpy - for numerical analysis
  • matplotlib & seaborn - for data visualization
  • squarify - for treemap visualizations

📜 Notebook Content

1. 📥 Loading the dataset
2. 🔍 Exploring the data (shape, columns, missing values)
3. 📊 Statistical insights (average prices, nationality distributions)
4. 🎨 Data visualization (histograms, bar charts, treemaps)

🚀 How to Run

1. Clone this repository:

   git clone https://github.com/yourusername/IPL2023_analysis.git

2. Install dependencies:

   pip install pandas numpy matplotlib seaborn squarify

3. Open and run the Jupyter Notebook:

   jupyter notebook IPL2023_analysis.ipynb

📸 Sample Visualizations

🤝 Contributing

Feel free to fork this repository and submit a pull request if you have additional insights or improvements!

📬 Contact

For any queries or collaboration opportunities, reach out via: 📧 Email: drbavaliya13@gmail.com

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