xarray.auto_combine

xarray.auto_combine(datasets, concat_dim=’__infer_concat_dim__’, compat=’no_conflicts’)

Attempt to auto-magically combine the given datasets into one.

This method attempts to combine a list of datasets into a single entity by inspecting metadata and using a combination of concat and merge.

It does not concatenate along more than one dimension or sort data under any circumstances. It does align coordinates, but different variables on datasets can cause it to fail under some scenarios. In complex cases, you may need to clean up your data and use concat/merge explicitly.

auto_combine works well if you have N years of data and M data variables, and each combination of a distinct time period and set of data variables is saved its own dataset.

Parameters:

datasets : sequence of xarray.Dataset

Dataset objects to merge.

concat_dim : str or DataArray or Index, optional

Dimension along which to concatenate variables, as used by xarray.concat(). You only need to provide this argument if the dimension along which you want to concatenate is not a dimension in the original datasets, e.g., if you want to stack a collection of 2D arrays along a third dimension. By default, xarray attempts to infer this argument by examining component files. Set concat_dim=None explicitly to disable concatenation.

compat : {‘identical’, ‘equals’, ‘broadcast_equals’,

‘no_conflicts’}, optional

String indicating how to compare variables of the same name for potential conflicts:

  • ‘broadcast_equals’: all values must be equal when variables are broadcast against each other to ensure common dimensions.
  • ‘equals’: all values and dimensions must be the same.
  • ‘identical’: all values, dimensions and attributes must be the same.
  • ‘no_conflicts’: only values which are not null in both datasets must be equal. The returned dataset then contains the combination of all non-null values.
Returns:

combined : xarray.Dataset

See also

concat, Dataset.merge