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---
title: EDAONSTERIOD
emoji: π
colorFrom: green
colorTo: indigo
sdk: gradio
sdk_version: 5.34.1
app_file: app.py
pinned: false
short_description: Analytic
---
# π₯ Odyssey: The AI Data Science Workspace
π CognitiveEDA: The Adaptive Intelligence Engine



CognitiveEDA is not just another EDA tool; it's a world-class data discovery platform that intelligently adapts to your data.
This enterprise-grade application goes beyond static profiling by automatically detecting the nature of your dataset (e.g., time-series, text-heavy) and unlocking specialized analysis modules on the fly. Powered by Google's Gemini LLM, it delivers a rich, context-aware, and deeply insightful user experience that transforms raw data into a clear narrative with actionable recommendations.
(A GIF showcasing the adaptive UI revealing specialized tabs after data upload)
β¨ Key Features: The "Wow" Factor
CognitiveEDA is designed to impress data professionals by providing intelligent, context-aware analysis that feels magical.
π§ Adaptive Analysis Modules: The UI isn't static. It intelligently detects your data's characteristics and dynamically reveals specialized tabs:
β Time-Series Analysis: Automatically appears if date/time columns are found. Perform decomposition, check for stationarity (ADF Test), and visualize trends.
π Text Analysis: Unlocks if long-form text columns are present. Instantly generate word clouds to visualize high-frequency terms.
π§© Clustering (K-Means): Becomes available for datasets with strong numeric features, allowing you to discover latent groups and customer segments.
π€ Hyper-Contextual AI Narrative: The integrated Gemini AI doesn't give a generic report. It receives context about the type of data it's analyzing, leading to far more specific and valuable insights (e.g., suggesting ARIMA for time-series or sentiment analysis for text).
** Universal Data Ingestion:** Don't be limited to CSV. CognitiveEDA handles CSV and Excel files seamlessly.
β‘ Performance-Aware: For massive datasets, the tool automatically samples the data for UI interactions to ensure a fast, responsive experience, while still using the full dataset for backend calculations where feasible.
π Comprehensive Core EDA: All the essentials, done better:
Detailed Data Profiling (Missing values, numeric stats, categorical stats).
At-a-glance overview visuals (Data types, missing data heatmap, correlation matrix).
Interactive deep-dive tools for exploring individual features.
π οΈ Tech Stack
This project leverages a modern, powerful stack for data science and web applications:
Backend & Data Analysis: Python, Pandas, NumPy, scikit-learn, statsmodels
Web Framework & UI: Gradio
AI Integration: Google Generative AI (Gemini)
Visualization: Plotly, Matplotlib, WordCloud
π Getting Started
You can get your own instance of CognitiveEDA running in just two steps.
1. Prerequisites
Python 3.9 or higher.
A Google Gemini API Key. You can get a free key from Google AI Studio.
2. Installation & Launch
First, clone the repository to your local machine:
Generated bash
git clone https://github.com/your-repo/CognitiveEDA.git
cd CognitiveEDA
Use code with caution.
Bash
Next, install all the required dependencies using the requirements.txt file. It's highly recommended to do this within a Python virtual environment.
Generated bash
# Create and activate a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
# Install all dependencies
pip install -r requirements.txt
Use code with caution.
Bash
Finally, run the application:
Generated bash
python app.py
Use code with caution.
Bash
The application will start and provide a local URL (e.g., http://127.0.0.1:7860) that you can open in your web browser.
π How to Use
Launch the application and open the URL in your browser.
Upload your data file using the "Upload Data File" component. Supported formats are .csv, .xlsx, and .xls.
Enter your Google Gemini API Key in the provided text field.
Click "Build My Dashboard".
Explore! The application will process your data and build a custom dashboard. The standard tabs (AI Narrative, Profile, Overview) will be populated, and any relevant specialized tabs (Time-Series, Text, Clustering) will automatically appear.
Interact with the dropdowns and sliders in each tab to perform deep-dive analyses.
π‘ Future Roadmap & Contributions
CognitiveEDA is an evolving platform. We welcome contributions from the community!
Potential Future Enhancements:
Geospatial Analysis Module: Automatically detect latitude/longitude or location names and generate map-based visualizations.
Interactive HTML Report Export: Export a single, beautiful, and fully interactive HTML file with embedded Plotly charts.
Database Connectors: Allow users to connect directly to PostgreSQL, MySQL, or BigQuery.
Background Job Processing: For extremely large datasets, allow full analysis to run as a background task with progress updates.
Advanced Caching: Implement more sophisticated caching to speed up re-analysis of the same data.
How to Contribute
Fork the repository.
Create a new branch for your feature (git checkout -b feature/AmazingNewFeature).
Commit your changes (git commit -m 'Add some AmazingNewFeature').
Push to the branch (git push origin feature/AmazingNewFeature).
Open a Pull Request.
π License
This project is licensed under the MIT License - see the LICENSE file for details. |