├── CONTRIBUTING.md
├── LICENSE
├── README.md
├── data_notes.md
└── main.py


/CONTRIBUTING.md:
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1 | # Contribution Guidelines\nFeel free to open PRs!
2 | 


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/LICENSE:
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1 | MIT License
2 | 


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/README.md:
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 1 | # Election Data Visualization Project
 2 | # 🗳️ Election Data Visualization using Python
 3 | 
 4 | This project is a comprehensive exploratory data analysis (EDA) and visualization of Indian election data using Python. It extracts insights on voter demographics, turnout ratios, and category distributions across gender.
 5 | 
 6 | ## 📌 Overview
 7 | 
 8 | This project leverages real-world electoral data to:
 9 | - Analyze voter counts across Men, Women, and Third Gender categories
10 | - Compute turnout rates and identify participation trends
11 | - Visualize distributions and correlations using advanced plots
12 | 
13 | ---
14 | 
15 | ## 📂 Dataset
16 | 
17 | - Format: `election_data.csv`
18 | - Columns: `Category`, `Men`, `Women`, `Third Gender`, `Total`
19 | 
20 | ---
21 | 
22 | ## ⚙️ Tech Stack
23 | 
24 | - **Language**: Python 3.11+
25 | - **Libraries**:
26 |   - `pandas`
27 |   - `matplotlib`
28 |   - `seaborn`
29 |   - `numpy`
30 | 
31 | ---
32 | ## 📈 Features
33 | 
34 | - ✅ Clean and preprocess data (missing values, duplicates)
35 | - ✅ Gender-wise aggregation and visualizations
36 | - ✅ Turnout rate computation
37 | - ✅ Correlation heatmaps and outlier detection
38 | - ✅ Advanced plots:
39 |   - Bar charts
40 |   - Pie charts
41 |   - Box plots
42 |   - Violin plots
43 |   - Histograms
44 |   - Stacked bar charts
45 | 
46 | ---
47 | 
48 | 
49 | 
50 | 
51 | ### PR 1 Test: This is a dummy update for testing PRs.
52 | 


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/data_notes.md:
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1 | This file explains the dataset used in the project.
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/main.py:
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1 | # This is a test comment for PR 5
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