clouddrift.adapters.glad

This module defines functions used to adapt the Grand LAgrangian Deployment (GLAD) dataset as a ragged-array Xarray Dataset.

The dataset and its description are hosted at https://doi.org/10.7266/N7VD6WC8.

Example

>>> from clouddrift.adapters import glad
>>> ds = glad.to_xarray()

Reference

Özgökmen, Tamay. 2013. GLAD experiment CODE-style drifter trajectories (low-pass filtered, 15 minute interval records), northern Gulf of Mexico near DeSoto Canyon, July-October 2012. Distributed by: Gulf of Mexico Research Initiative Information and Data Cooperative (GRIIDC), Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7VD6WC8

Functions

get_dataframe()	Get the GLAD dataset as a pandas DataFrame.
to_xarray()	Return the GLAD data as a ragged-array Xarray Dataset.

clouddrift.adapters.glad.get_dataframe() → DataFrame

Get the GLAD dataset as a pandas DataFrame.

clouddrift.adapters.glad.to_xarray() → Dataset

Return the GLAD data as a ragged-array Xarray Dataset.