TalkWithData makes data analysis effortless. Simply upload a CSV file and receive smart, context-aware visualizations — complete with the Python code that generated them. No coding required. No setup hassles. Just insights, instantly.
From students to data professionals, many struggle to make sense of raw CSV files. Visualization often requires programming skills, which can become a barrier. Our mission: make data exploration as simple as uploading a file — with intelligent visual insights delivered by AI.
- Upload any CSV file and instantly receive:
- AI-generated charts: heatmaps, bar plots, scatter plots, and more.
- Concise summaries explaining each visualization.
- The full Python code behind each chart.
- Powered by Google Gemini AI to detect meaningful patterns and generate relevant visuals.
| Layer | Tools Used |
|---|---|
| Frontend | React.js, HTML/CSS |
| Backend | Flask (Python), CORS |
| Visualization | Matplotlib, Seaborn |
| AI Engine | Google Gemini |
- User uploads a
.csvfile through the React interface. - The frontend sends the file to the Flask backend.
- Flask + Gemini AI analyze the data and generate visualizations.
- Charts and code are returned as JSON, including base64 images.
- The frontend displays the visuals with interactive summaries and code blocks.
- Solved CORS issues for seamless frontend-backend communication.
- Handled inconsistent or messy CSV formats with robust parsing.
- Ensured AI-generated code was executable, secure, and relevant.
- Maintained responsive UI performance even for large datasets.
- Developed a no-code platform for AI-powered data insights.
- Created an end-to-end pipeline from upload to visualization in under a minute.
- Delivered a smooth, user-friendly UI that demystifies data analysis.
# Navigate to backend folder (if applicable)
python app.py# Navigate to frontend directory
npm install
npm startMake sure your Flask server is running at http://localhost:5000.
talkwithdata/
├── backend/
│ └── app.py
├── frontend/
│ ├── app.jsx
│ ├── index.js
│ └── ...
This project is open-source under the MIT License.