xarray.Dataset.reindex¶
-
Dataset.
reindex
(indexers=None, method=None, tolerance=None, copy=True, **indexers_kwargs)¶ Conform this object onto a new set of indexes, filling in missing values with 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 most 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. Ifcopy=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.**indexers_kwarg : {dim: indexer, …}, optional
Keyword arguments in the same form as
indexers
. One of indexers or indexers_kwargs must be provided.Returns: reindexed : Dataset
Another dataset, with this dataset’s data but replaced coordinates.
See also