https://github.com/akashparley/ipl-data-analysis
The IPL Data Analysis project focuses on extracting valuable insights from IPL match data using various data analytics techniques. By analyzing historical match outcomes, player performances, team comparisons, and venue statistics, the project visualizes trends and patterns through graphs like bar charts, line graphs, and scatter plots.
https://github.com/akashparley/ipl-data-analysis
analytics data-visualization excel metplotlib numpy pandas python seaborn tableau-dashboards
Last synced: 3 months ago
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The IPL Data Analysis project focuses on extracting valuable insights from IPL match data using various data analytics techniques. By analyzing historical match outcomes, player performances, team comparisons, and venue statistics, the project visualizes trends and patterns through graphs like bar charts, line graphs, and scatter plots.
- Host: GitHub
- URL: https://github.com/akashparley/ipl-data-analysis
- Owner: AkashParley
- Created: 2025-02-13T20:08:20.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2025-02-14T16:34:26.000Z (10 months ago)
- Last Synced: 2025-02-24T06:18:46.301Z (10 months ago)
- Topics: analytics, data-visualization, excel, metplotlib, numpy, pandas, python, seaborn, tableau-dashboards
- Language: Jupyter Notebook
- Homepage: https://public.tableau.com/views/Book1_17287292047080/Netflix?:language=en-US&publish=yes&:sid=&:redirect=auth&:display_count=n&:origin=viz_share_link
- Size: 23.8 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# 🏏 IPL Data Analysis
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.
## 📌 Overview
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**.
---
## 📊 IPL Data Analysis Workflow
```mermaid
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"]
```
## 🚀 Features
### 🔹 1. Match Outcome Analysis
✅ Visualize match outcomes (Win/Loss) across different years.
✅ Analyze team performance based on historical data and seasonal trends.
### 🔹 2. Player Performance
✅ Track individual player statistics like runs, wickets, and strike rates.
✅ Use bar graphs and scatter plots to visualize player contributions.
### 🔹 3. Team Comparison
✅ Compare team performance using **line and pie charts** for win percentage.
✅ Analyze the impact of team changes, including **player transfers or injuries**.
### 🔹 4. Venue Performance
✅ Evaluate match outcomes across different **IPL venues**.
✅ Present venue-based performance using **heatmaps or bar charts**.
### 🔹 5. Run Rate & Scoring Analysis
✅ Visualize **average run rates** for different teams and players.
✅ Use **line graphs** to track scoring trends over the years.
### 🔹 6. Best Batting Partnerships
✅ Identify and visualize **top batting pairs** using **histograms**.
✅ Analyze successful partnerships based on **runs scored and boundary rates**.
---
## 📊 Tableau Dashboards
🔹 **Overall Team Analysis Dashboard**
🔹 **Batting Statistics Dashboard**
🔹 **Bowling Statistics Dashboard**
📌 Check out the interactive Tableau dashboards here:
**👉 View Dashboards**
[Team Analysis Dashboard](https://public.tableau.com/views/IPLDataAnalysis_17393967228710/Dashboard1?:language=en-US&publish=yes&:sid=&:redirect=auth&:display_count=n&:origin=viz_share_link)
---
**[Player Stats Analysis Dashboard](https://public.tableau.com/views/Playerperformancedashboard_17393957507580/Dashboard2?:language=en-US&publish=yes&:sid=&:redirect=auth&:display_count=n&:origin=viz_share_link)**
**Batting Stats Dashboard**
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**Bowling Stats Dashboard**
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---
## 🛠️ Tech Stack
- **Programming Language:** Python 🐍
- **Libraries:** Pandas, NumPy, Matplotlib, Seaborn, Plotly
- **Data Visualization:** Tableau, Bar Charts, Line Graphs, Scatter Plots, Heatmaps, Pie Charts
---
## 🚀 Installation & Usage
1. **Clone the repository**
```sh
git clone https://github.com/your-username/ipl-data-analysis.git
cd ipl-data-analysis