# xarray.Dataset.isel_points¶

Dataset.isel_points(dim='points', **indexers)

Returns a new dataset with each array indexed pointwise along the specified dimension(s).

This method selects pointwise values from each array and is akin to the NumPy indexing behavior of arr[[0, 1], [0, 1]], except this method does not require knowing the order of each array’s dimensions.

Parameters: dim : str or DataArray or pandas.Index or other list-like object, optional Name of the dimension to concatenate along. If dim is provided as a string, it must be a new dimension name, in which case it is added along axis=0. If dim is provided as a DataArray or Index or list-like object, its name, which must not be present in the dataset, is used as the dimension to concatenate along and the values are added as a coordinate. **indexers : {dim: indexer, ...} Keyword arguments with names matching dimensions and values given by array-like objects. All indexers must be the same length and 1 dimensional. obj : Dataset A new Dataset with the same contents as this dataset, except each array and dimension is indexed by the appropriate indexers. With pointwise indexing, the new Dataset will always be a copy of the original.