https://github.com/abhaysingh71/india-censes-data-analysis
This repo is a india censes data analysis in many domains
https://github.com/abhaysingh71/india-censes-data-analysis
data data-science data-visualization dataanalysis streamlit
Last synced: about 2 months ago
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This repo is a india censes data analysis in many domains
- Host: GitHub
- URL: https://github.com/abhaysingh71/india-censes-data-analysis
- Owner: AbhaySingh71
- Created: 2024-08-09T10:09:49.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-09-03T15:18:23.000Z (almost 2 years ago)
- Last Synced: 2025-07-15T20:56:53.777Z (12 months ago)
- Topics: data, data-science, data-visualization, dataanalysis, streamlit
- Language: Python
- Homepage: https://abhaysingh71-india-censes-data-analysis-app-q5mfiv.streamlit.app/
- Size: 52.7 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 📊 India Census Data Analysis App
Welcome to the India Census Data Analysis App! 🚀 This interactive app is designed to help users explore and visualize key insights from India's census data in an intuitive and user-friendly manner. Built with **Streamlit** and leveraging the powerful **Plotly** library for geo-mapping, this app provides a valuable tool for data enthusiasts, researchers, and especially UPSC aspirants.
## 🌟 Features
- **Interactive Data Visualization**: Easily explore and analyze data with interactive charts and graphs.
- **Geo-Mapping with Plotly**: Visualize key trends across India by mapping data using latitude and longitude.
- **Exploratory Data Analysis (EDA)**: Includes insights such as sex ratio, literacy rate, and more.
- **Data Cleaning**: Rigorous data preprocessing to ensure accurate and reliable insights (handling missing values, removing leading spaces, etc.).
- **Comprehensive Analysis**: Covers various aspects such as population, education, electricity access, religions, and sex ratio.
## 🔍 Exploratory Data Analysis (EDA)
To derive meaningful insights from the census data, the following EDA steps were performed:
- **Calculating Key Metrics**: Calculated sex ratio, literacy rate, and other important metrics.
- **Handling Missing Values**: Imputed missing values to maintain data consistency.
- **Data Cleaning**: Removed leading spaces and standardized formats to ensure data quality.
- **Visualizations**: Used Plotly for creating interactive plots to better understand geographic and demographic trends.
## 🚀 How to Run the App
To run this app locally, follow these steps:
1. **Clone the repository**:
```bash
git clone https://github.com/abhaysingh71/india-census-data-analysis.git
cd india-census-data-analysis
2. **Install the Required Packages:**
Ensure you have Python installed. Install the necessary packages using pip:
```bash
pip install -r requirements.txt
```
3. **Run the Streamlit App:**
```bash
streamlit run app.py
```
4. **Explore the Dashboard:**
Open the provided URL in your browser to explore the interactive dashboard and gain valuable insights into startup funding trends.
## 🌐 Deployed Version
The app is deployed on **Streamlit**! You can check out the live version and explore the analysis on your own: [Streamlit App](https://abhaysingh71-india-censes-data-analysis-app-q5mfiv.streamlit.app/).
## 📚 Resources
- **GitHub Repository**: Visit the [GitHub Repository]((https://github.com/AbhaySingh71/India-startup-analysis))for the complete codebase.
## 🤝 Contributing
We welcome contributions! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request.
## 🙏 Acknowledgments
A big thank you to the data science community for their support and resources. Special thanks to the providers of the dataset and all contributors who helped make this project a reality.
---
**Happy Learning! 😊**