API Reference

This page provides detailed information about all functions and classes in the IGRA Toolkit.

Data Access

Data Processing

Visualization

Data Types

The toolkit works with two main data formats:

  1. Pandas DataFrame * Contains columns for each variable * Includes metadata in column names and attributes * Easy to manipulate and analyze

  2. NetCDF Dataset * Multi-dimensional arrays for each variable * Includes metadata in attributes * Efficient for large datasets

Common Parameters

  • station_id: Station identifier (e.g., “USM00072520”)

  • file_type: Output format (‘df’ or ‘netcdf’)

  • start_date: Start date for filtering (YYYY-MM-DD)

  • end_date: End date for filtering (YYYY-MM-DD)

  • variables: List of variables to include

  • lat_range: Tuple of (min_lat, max_lat)

  • lon_range: Tuple of (min_lon, max_lon)

Return Values

Most functions return either:

  • A pandas DataFrame

  • An xarray Dataset

  • None (if an error occurs)

Error Handling

Functions handle errors by:

  1. Printing informative error messages

  2. Returning None for failed operations

  3. Providing detailed error information in exceptions