Data Visualization App Documentation - Master File

Created by sphinx-quickstart on Sun Feb 4 15:16:39 2024. Adapted to include AI model integration (Gemini/Claude).

This project is a data analysis and visualization platform for cleaning, analyzing, and visualizing data with AI-driven insights. Under Master AI & Data Science by Wissal Ben Othmen & Bilel Guembri.

This documentation provides a comprehensive guide to the Data Visualization App, a Flask-based tool for data upload, cleaning, analysis, and visualization.

Contents:

• AI Model Integration
  • API Key Configuration
  • Model Selection
• utils.py API
  • analyze_data()
  • apply_fixes_to_data()
  • create_dataset_summary()
  • exec_code_to_generate_plot()
  • filter_data_by_top_variables()
  • fix_json()
  • generate_graph_interpretation_claude()
  • generate_graph_interpretation_gemini()
  • get_plot_suggestion_from_claude()
  • get_plot_suggestion_from_gemini()
  • get_top_n_variables()
  • handle_graph_communication_claude()
  • handle_graph_communication_gemini()
• app.py API

Key Features:

• Data Upload: Supports multiple file formats (CSV, Excel, JSON, etc.).

• Data Quality Checks: Automatic detection of missing values, duplicates, and data type issues.

• Data Cleaning: Tools for handling missing data and removing duplicate entries.

• Interactive Visualizations: Creation of various customizable plots based on your data.

• AI-Powered Insights: Integration with Gemini or Claude language models for: * Visualization Suggestions: The AI model analyzes your data and recommends appropriate visualizations. * Data Interpretation: The AI model provides textual descriptions and insights based on the generated visualizations. * Automated Analysis (Future Enhancement): Potential for the AI to perform more complex statistical analyses and generate reports.

• User-Friendly Interface: Designed for intuitive use, regardless of data analysis expertise.

Note

This is a basic documentation structure. Expand this to include sections for:

• Getting Started: Installation, initial setup, and basic usage.

• User Guide: Detailed instructions on using each feature of the app.

• AI Model Integration: Specific details on how to use the Gemini/Claude features, including API keys, configuration, and limitations.

• Troubleshooting: Common issues and solutions.

• API Reference: Comprehensive documentation of the ai_model, utils_api, and app_api modules.

• Contributing: Guidelines for contributing to the project.

• Examples: Showcase different use cases and provide sample data and visualizations.

• Advanced Usage: Coverage of power-user features and customizations.

• Release Notes / Changelog: Track updates and new features