xarray.DataArray.isel (original) (raw)

DataArray.isel(indexers=None, drop=False, missing_dims='raise', **indexers_kwargs)[source]#

Return a new DataArray whose data is given by selecting indexes along the specified dimension(s).

Parameters:

indexers (dict, optional) – A dict with keys matching dimensions and values given by integers, slice objects or arrays. indexer can be an integer, slice, array-like or DataArray. If DataArrays are passed as indexers, xarray-style indexing will be carried out. See Indexing and selecting data for the details. One of indexers or indexers_kwargs must be provided.
drop (bool, default: False) – If drop=True, drop coordinates variables indexed by integers instead of making them scalar.
missing_dims ({"raise", "warn", "ignore"}, default: "raise") – What to do if dimensions that should be selected from are not present in the DataArray: - “raise”: raise an exception - “warn”: raise a warning, and ignore the missing dimensions - “ignore”: ignore the missing dimensions
**indexers_kwargs ({dim: indexer, ...}, optional) – The keyword arguments form of indexers.

Returns:

Examples

da = xr.DataArray(np.arange(25).reshape(5, 5), dims=("x", "y")) da <xarray.DataArray (x: 5, y: 5)> Size: 200B array([[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [10, 11, 12, 13, 14], [15, 16, 17, 18, 19], [20, 21, 22, 23, 24]]) Dimensions without coordinates: x, y

tgt_x = xr.DataArray(np.arange(0, 5), dims="points") tgt_y = xr.DataArray(np.arange(0, 5), dims="points") da = da.isel(x=tgt_x, y=tgt_y) da <xarray.DataArray (points: 5)> Size: 40B array([ 0, 6, 12, 18, 24]) Dimensions without coordinates: points