| # Tools for IFVI Value Factors Dataset | |
| This directory contains tools and utilities for working with the IFVI Value Factors dataset. | |
| ## Directory Structure | |
| - `conversion/`: Tools for converting between different data formats | |
| - `analysis/`: Scripts and notebooks for analyzing the value factors | |
| - `visualization/`: Tools for visualizing the value factors | |
| ## Conversion Tools | |
| The `conversion/` directory contains tools for converting between different data formats: | |
| - JSON to CSV conversion | |
| - CSV to Parquet conversion | |
| - Data validation tools | |
| ## Analysis Tools | |
| The `analysis/` directory contains scripts and notebooks for analyzing the value factors: | |
| - Data loading and exploration | |
| - Statistical analysis | |
| - Comparative analysis across regions and impact types | |
| ## Visualization Tools | |
| The `visualization/` directory contains tools for visualizing the value factors: | |
| - Geographic visualizations | |
| - Comparative charts and graphs | |
| - Interactive dashboards | |
| ## Usage | |
| Each tool directory contains its own README with specific usage instructions. Generally, tools can be run using Python: | |
| ```bash | |
| python tools/analysis/load_data.py | |
| ``` | |
| ## Requirements | |
| Most tools require Python 3.6+ and the following packages: | |
| - pandas | |
| - numpy | |
| - matplotlib | |
| - pyarrow (for Parquet files) | |
| A `requirements.txt` file is provided in each tool directory with specific dependencies. | |
| ## Contributing | |
| Contributions of additional tools are welcome. Please ensure that all tools are well-documented and include: | |
| 1. A clear description of what the tool does | |
| 2. Required dependencies | |
| 3. Usage examples | |
| 4. Expected output | |