Add visualization environment setup and helper tools #4
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- Create virtual environment with all required packages (NumPy, Matplotlib, Plotly, Pandas, SymPy, SciPy, NetworkX) - Add explore_visualizations.py to catalog and search 1000+ visualization scripts - Add run_visualization.sh helper script for easy execution - Add test_visualization.py to verify environment setup - Add .gitignore to exclude venv and Python artifacts The repository contains 1000 visualization scripts: - 724 3D visualizations - 51 2D visualizations - 44 electrical engineering visualizations - 29 physics simulations - 18 graph/network visualizations
Built a comprehensive system to visualize YOUR actual data from: - GitHub repositories (CSV, JSON, databases) - REST APIs - Live data streams (WebSocket, MQTT, Kafka) - Databases (PostgreSQL, MySQL, MongoDB, SQLite) New Files: - universal_data_visualizer.py: Scans all GitHub repos for data files and auto-generates visualizations - streaming_visualizer.py: Real-time visualization for live data streams - data_sources_config.json: Configuration for data sources - CUSTOM_VISUALIZATION_GUIDE.md: Complete guide for using the platform Features: ✅ Auto-discovers all data files in GitHub repos ✅ Automatically detects data types and creates appropriate visualizations ✅ Generates: time series, histograms, correlations, scatter plots, box plots ✅ Real-time streaming support with live dashboard updates ✅ Saves interactive HTML visualizations ✅ Configurable data sources via JSON config This replaces the 1000 static example scripts with a dynamic system that works with YOUR actual data!
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The repository contains 1000 visualization scripts: