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| title: DataMind AI | |
| emoji: π§ | |
| colorFrom: blue | |
| colorTo: indigo | |
| sdk: docker | |
| pinned: false | |
| # π§ DataMind AI β Intelligent Data Analyst | |
| An AI-powered data analysis dashboard that automatically performs EDA, generates 20+ chart types, provides AI-driven insights, forecasting, and an interactive chat analyst. | |
| ## π Quick Start | |
| ### 1. Install Dependencies | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| ### 2. Set Your Groq API Key | |
| **Windows (PowerShell):** | |
| ```powershell | |
| $env:GROQ_API_KEY = "your_groq_api_key_here" | |
| ``` | |
| **Windows (CMD):** | |
| ```cmd | |
| set GROQ_API_KEY=your_groq_api_key_here | |
| ``` | |
| **Mac/Linux:** | |
| ```bash | |
| export GROQ_API_KEY="your_groq_api_key_here" | |
| ``` | |
| ### 3. Run the Application | |
| ```bash | |
| python app.py | |
| ``` | |
| ### 4. Open in Browser | |
| Navigate to: **http://localhost:5000** | |
| ## π Features | |
| - **CSV Upload** β Drag-and-drop any CSV file | |
| - **Simulated Datasets** β Pre-built Retail Sales and E-Commerce datasets | |
| - **Automated EDA** β Missing values, duplicates, outliers, correlations | |
| - **20+ Chart Types** β Line, bar, pie, heatmap, waterfall, radar, BCG, RFM, and more | |
| - **AI Chat Analyst** β Ask questions about your data in natural language | |
| - **Forecasting** β Time series forecasting with confidence intervals | |
| - **Key Insights** β AI-generated actionable business insights | |
| - **What-If Analysis** β Scenario simulation with adjustable parameters | |
| ## π οΈ Tech Stack | |
| - **Backend**: Python, Flask | |
| - **Frontend**: HTML, CSS, JavaScript (single-page app) | |
| - **AI**: Groq API (LLaMA 3.3 70B) | |
| - **Charts**: Matplotlib, Seaborn | |
| - **ML**: scikit-learn (KMeans), mlxtend (Apriori) | |
| - **Forecasting**: statsmodels (Exponential Smoothing) | |
| ## π Project Structure | |
| ``` | |
| βββ app.py # Flask backend | |
| βββ datasets.py # Simulated dataset generators | |
| βββ eda.py # EDA pipeline | |
| βββ charts.py # Chart orchestrator | |
| βββ charts_core.py # Core chart functions (12 types) | |
| βββ charts_advanced.py # Advanced chart functions (11 types) | |
| βββ ai_analyst.py # Groq API integration | |
| βββ templates/ | |
| β βββ index.html # Frontend SPA | |
| βββ requirements.txt # Dependencies | |
| βββ README.md # This file | |
| ``` | |