https://github.com/rupeshkumar18123/dataset_analyzer
This app blends data visualization, conversational AI, and cloud hosting — ideal for analysts, students, and data-driven teams.
https://github.com/rupeshkumar18123/dataset_analyzer
azure-app-service langchain openai pandas plotly streamlit
Last synced: 3 months ago
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This app blends data visualization, conversational AI, and cloud hosting — ideal for analysts, students, and data-driven teams.
- Host: GitHub
- URL: https://github.com/rupeshkumar18123/dataset_analyzer
- Owner: rupeshkumar18123
- Created: 2025-07-10T14:29:54.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2025-07-10T15:15:28.000Z (12 months ago)
- Last Synced: 2025-07-10T21:20:29.006Z (12 months ago)
- Topics: azure-app-service, langchain, openai, pandas, plotly, streamlit
- Language: Python
- Homepage: https://dataset-analyzer-cqegewgnh5h2eqfc.centralindia-01.azurewebsites.net/
- Size: 9.77 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 📊 Dataset Analyzer
Dataset Analyzer is a powerful web-based tool that simplifies exploratory data analysis (EDA) for CSV and JSON datasets. Upload your data, visualize distributions, detect anomalies, and download summary reports — all in one intuitive dashboard.
---
## 🚀 Features
- ✅ Upload CSV or JSON datasets
- 📈 Interactive charts: histograms, scatter plots, box plots, correlation heatmaps
- 🔍 Automatic missing value detection & summary statistics
- ⚡ Fast in-browser analysis supported by Web Workers
- 📄 Exportable summary report (PDF format)
---
## 🧰 Tech Stack
- **Frontend**: React.js, Chart.js (or D3.js)
- **Backend**: Node.js, Express.js (optional API layer)
- **Data Processing**: Web Workers
- **Utilities**: Axios, FileSaver.js, react-dropzone
---
## 📦 Installation
### 1. Clone the repository
```bash
git clone https://github.com/rupeshkumar18123/Dataset_analyzer.git
cd Dataset_analyzer
````
### 2. Install dependencies
```bash
npm install
```
*(Or, if there is a `backend` folder:)*
```bash
cd backend
npm install
cd ../frontend
npm install
```
---
## ▶️ Running the App
Start the development server:
```bash
npm start
```
* If there’s a combined setup, the app should open automatically at `http://localhost:3000`.
* If separate: run both `npm start` in frontend and backend directories.
---
## ⚙️ Usage
1. Navigate to the web app.
2. Drag-and-drop or select your dataset.
3. Choose charts and analysis options.
4. View interactive visualizations.
5. Export summary PDF report via “Download Report” button.
---
## ⚠️ Requirements
* Node.js ≥ 12
* Modern browser (Chrome/Firefox/Edge/Safari)
---
## 📸 Screenshots
*(Insert screenshots of data upload, chart views, and export actions here.)*
---
## 💡 Future Enhancements
* 📑 Support for XLSX and SQL data
* 🗃️ Save/load analysis sessions
* 📊 Advanced EDA: clustering, PCA
* 🔧 Custom visualization palette & themes
---
## 🤝 Contributing
We welcome contributions!
1. Fork the repo
2. Create a branch: `feature/your-feature-name`
3. Commit your changes
4. Push to GitHub and open a PR
Please follow existing code style and write clear commit messages.
---
## 📄 License
This project is licensed under the MIT License.
---
## 🙋♂️ Author
Built with passion by [Rupesh Kumar](https://github.com/rupeshkumar18123).
Feel free to connect and share feedback!
```