This project was developed as part of my Data Analyst Internship at Infotact Solutions, alongside two other team members. The aim of this project is to extract valuable insights from IPL match data using data analytics techniques.
The IPL Data Analysis project aims to extract valuable insights from IPL match data using data analytics techniques. By analyzing historical match outcomes, player performances, team comparisons, and venue statistics, the project visualizes trends and patterns through interactive graphs like bar charts, line graphs, and scatter plots.
With Python’s powerful libraries like Pandas, Matplotlib, and Seaborn, and Tableau for advanced dashboards, this project provides a comprehensive overview of IPL data for in-depth analysis and decision-making.
graph TD
A["Raw IPL Data"] -->|Data Cleaning| B["Cleaned Data (CSV)"]
B -->|Data Analysis| C{"Python Libraries"}
C --> D["Pandas & NumPy for Data Processing"]
C --> E["Matplotlib for Data Visualization"]
D -->|Processed Data| F["Graphs & Trends Analysis"]
E -->|Plots & Charts| F
F -->|For Better Visualization| G["Tableau Dashboard"]
G -->|Final Insights| H["Decision Making & Reporting"]
✅ Visualize match outcomes (Win/Loss) across different years.
✅ Analyze team performance based on historical data and seasonal trends.
✅ Track individual player statistics like runs, wickets, and strike rates.
✅ Use bar graphs and scatter plots to visualize player contributions.
✅ Compare team performance using line and pie charts for win percentage.
✅ Analyze the impact of team changes, including player transfers or injuries.
✅ Evaluate match outcomes across different IPL venues.
✅ Present venue-based performance using heatmaps or bar charts.
✅ Visualize average run rates for different teams and players.
✅ Use line graphs to track scoring trends over the years.
✅ Identify and visualize top batting pairs using histograms.
✅ Analyze successful partnerships based on runs scored and boundary rates.
🔹 Overall Team Analysis Dashboard
🔹 Batting Statistics Dashboard
🔹 Bowling Statistics Dashboard
📌 Check out the interactive Tableau dashboards here:
👉 View Dashboards
Player Stats Analysis Dashboard
- Programming Language: Python 🐍
- Libraries: Pandas, NumPy, Matplotlib, Seaborn, Plotly
- Data Visualization: Tableau, Bar Charts, Line Graphs, Scatter Plots, Heatmaps, Pie Charts
- Clone the repository
git clone https://github.com/your-username/ipl-data-analysis.git cd ipl-data-analysis