pygmt.datasets.load_sample_data

pygmt.datasets.load_sample_data(name)[source]

Load an example dataset from the GMT server.

The data are downloaded to a cache directory (usually ~/.gmt/cache) the first time you invoke this function. Afterwards, it will load the data from the cache. So you’ll need an internet connection the first time around.

Parameters:: name (Literal['bathymetry', 'earth_relief_holes', 'fractures', 'hotspots', 'japan_quakes', 'mars_shape', 'maunaloa_co2', 'notre_dame_topography', 'ocean_ridge_points', 'rock_compositions', 'usgs_quakes']) – Name of the dataset to load.
Return type:: DataFrame | DataArray
Returns:: data – Sample dataset loaded as a pandas.DataFrame for tabular data or xarray.DataArray for raster data.

See also

list_sample_data: Report datasets available for tests and documentation examples.

Examples

>>> from pprint import pprint
>>> from pygmt.datasets import list_sample_data, load_sample_data
>>> # use list_sample_data to see the available datasets
>>> pprint(list_sample_data(), width=120)
{'bathymetry': 'Table of ship bathymetric observations off Baja California',
 'earth_relief_holes': 'Regional 20 arc-minutes Earth relief grid with holes',
 'fractures': 'Table of hypothetical fracture lengths and azimuths',
 'hotspots': 'Table of locations, names, and symbol sizes of hotpots from Müller et al. (1993)',
 'japan_quakes': 'Table of earthquakes around Japan from the NOAA NGDC database',
 'mars_shape': 'Table of topographic signature of the hemispheric dichotomy of Mars from Smith and Zuber (1996)',
 'maunaloa_co2': 'Table of CO2 readings from Mauna Loa',
 'notre_dame_topography': 'Table 5.11 in Davis: Statistics and Data Analysis in Geology',
 'ocean_ridge_points': 'Table of ocean ridge points for the entire world',
 'rock_compositions': 'Table of rock sample compositions',
 'usgs_quakes': 'Table of earthquakes from the USGS'}
>>> # Load the sample bathymetry dataset
>>> data = load_sample_data("bathymetry")