# pandas.Series.reindex_like¶

Return an object with matching indices as other object.

Conform the object to the same index on all axes. Optional filling logic, placing NaN in locations having no value in the previous index. A new object is produced unless the new index is equivalent to the current one and copy=False.

- param other
- Object of the same data type
Its row and column indices are used to define the new indices of this object.

- param method
- {None, ‘backfill’/’bfill’, ‘pad’/’ffill’, ‘nearest’}
Method to use for filling holes in reindexed DataFrame. Please note: this is only applicable to DataFrames/Series with a monotonically increasing/decreasing index.

None (default): don’t fill gaps

- pad / ffill: propagate last valid observation forward to next
valid

backfill / bfill: use next valid observation to fill gap

nearest: use nearest valid observations to fill gap

- param copy
- bool, default True
Return a new object, even if the passed indexes are the same.

- param limit
- int, default None
Maximum number of consecutive labels to fill for inexact matches.

- param 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`

.Tolerance may be a scalar value, which applies the same tolerance to all values, or list-like, which applies variable tolerance per element. List-like includes list, tuple, array, Series, and must be the same size as the index and its dtype must exactly match the index’s type.

New in version 0.21.0: (list-like tolerance)

- return
Series or DataFrame Same type as caller, but with changed indices on each axis.

Warning

This feature is currently unsupported by Intel Scalable Dataframe Compiler