Master EDA Platform V3

Overview

A comprehensive automated exploratory data analysis platform designed for MVP investor demos. This platform provides end-to-end data analysis capabilities through 14 sequential phases.

Architecture

• Backend: FastAPI + Python 3.11+
• Frontend: React 18+ + TypeScript + shadcn/ui
• Infrastructure: Docker + Docker Compose
• Storage: Local filesystem (no database required for MVP)

Project Structure

eda-platform/
├── backend/              # FastAPI backend service
├── frontend/             # React frontend application
├── docker-compose.yml    # Multi-container setup
├── .env.example         # Environment variables template
├── .gitignore           # Git ignore rules
└── README.md            # This file

Quick Start

Prerequisites

• Docker & Docker Compose
• Python 3.11+ (for local development)
• Node.js 18+ (for frontend development)

Using Docker (Recommended)

# Clone repository
git clone <repository-url>
cd eda-platform

# Start all services
docker-compose up --build

# Access applications
# Backend API: http://localhost:8000
# Frontend: http://localhost:3000
# API Docs: http://localhost:8000/api/docs

Local Development

# Backend
cd backend
pip install -r requirements.txt
uvicorn app.main:app --reload

# Frontend (separate terminal)
cd frontend
npm install
npm run dev

EDA Pipeline Phases

Phase	Name	Description	Status
0	Foundation & Architecture	Project setup and infrastructure	✅ Complete
1	Goal & KPIs Definition	Define business objectives	⏳ Pending
2	Data Ingestion	Upload and validate data files	⏳ Pending
3	Schema Discovery	Analyze data structure	⏳ Pending
4	Data Profiling	Generate comprehensive statistics	⏳ Pending
5	Missing Data Analysis	Identify missing data patterns	⏳ Pending
6	Data Standardization	Clean and standardize formats	⏳ Pending
7	Feature Engineering	Create derived features	⏳ Pending
7.5	Encoding & Scaling	Encode categorical variables	⏳ Pending
8	Data Merging	Combine multiple datasets	⏳ Pending
9	Correlation Analysis	Analyze variable relationships	⏳ Pending
9.5	Business Validation	Validate against business rules	⏳ Pending
10	Data Packaging	Prepare final dataset	⏳ Pending
10.5	Train/Test Split	Split data for modeling	⏳ Pending
11	Advanced Analytics	Perform advanced statistical analysis	⏳ Pending
11.5	Feature Selection	Select optimal features	⏳ Pending
12	Text Analysis	NLP analysis for text data	⏳ Pending
13	Monitoring & Reporting	Generate reports and monitoring	⏳ Pending

Supported Domains

• Finance
• Healthcare
• Retail
• Manufacturing
• Technology
• Education
• Government
• General

Supported File Formats

• CSV
• Excel (XLSX)
• Parquet
• JSON

API Documentation

• Swagger UI: http://localhost:8000/api/docs
• ReDoc: http://localhost:8000/api/redoc
• Health Check: http://localhost:8000/health

Documentation

• Full docs: see docs/README.md for Getting Started, Architecture, Phases, and more.

Development Guidelines

Phase Implementation

1. Each phase must be implemented sequentially
2. Run validation script before proceeding to next phase
3. All phases must pass validation checks
4. Follow the established project structure

Validation

# Validate current phase
python backend/validation_scripts/validate_phase0.py

Contributing

1. Follow the phase-by-phase implementation approach
2. Ensure all validation checks pass
3. Maintain backward compatibility
4. Document all changes

License

[Add your license here]

Support

For questions or issues, please refer to the project documentation or create an issue in the repository.