xarray.Dataset.reindex¶

Dataset.reindex(indexers = None, method = None, tolerance = None, copy = True, fill_value = <NA>, **indexers_kwargs) → xarray.core.dataset.Dataset¶

Conform this object onto a new set of indexes, filling in missing values with fill_value. The default fill value is NaN.

Parameters

indexers (dict. optional) – Dictionary with keys given by dimension names and values given by arrays of coordinates tick labels. Any mis-matched coordinate values will be filled in with NaN, and any mis-matched dimension names will simply be ignored. One of indexers or indexers_kwargs must be provided.
method ({None, 'nearest', 'pad'/'ffill', 'backfill'/'bfill'}, optional) –
Method to use for filling index values in indexers not found in this dataset:
- None (default): don’t fill gaps
- pad / ffill: propagate last valid index value forward
- backfill / bfill: propagate next valid index value backward
- nearest: use nearest valid index value (requires pandas>=0.16)
tolerance (optional) – Maximum distance between original and new labels for inexact matches. The values of the index at the matching locations must satisfy the equation abs(index[indexer] - target) <= tolerance. Requires pandas>=0.17.
copy (bool, optional) – If copy=True, data in the return value is always copied. If copy=False and reindexing is unnecessary, or can be performed with only slice operations, then the output may share memory with the input. In either case, a new xarray object is always returned.
fill_value (scalar, optional) – Value to use for newly missing values
**indexers_kwarg ({dim: indexer, ..}, optional) – Keyword arguments in the same form as indexers. One of indexers or indexers_kwargs must be provided.

Returns

reindexed – Another dataset, with this dataset’s data but replaced coordinates.

Return type

Dataset