Dataset.reindex(indexers=None, method=None, copy=True, **kw_indexers)

Conform this object onto a new set of indexes, filling in missing values with NaN.


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.

method : {None, ‘nearest’, ‘pad’/’ffill’, ‘backfill’/’bfill’}, optional

Method to use for filling index values in indexers not found in this dataset:

  • default: don’t fill gaps
  • pad / ffill: propgate last valid index value forward
  • backfill / bfill: propagate next valid index value backward
  • nearest: use nearest valid index value (requires pandas>=0.16)

copy : bool, optional

If copy=True, the returned dataset contains only copied variables. If copy=False and no reindexing is required then original variables from this dataset are returned.

**kw_indexers : optional

Keyword arguments in the same form as indexers.


reindexed : Dataset

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