Pandas DataFrame: reindex_like() function

Last update on August 19 2022 21:50:33 (UTC/GMT +8 hours)

DataFrame - reindex_like() function

The reindex_like() function is used to return an object with matching indices as other object.

Syntax:

DataFrame.reindex_like(self, other, method=None, copy=True, limit=None, tolerance=None)

Parameters:

Name	Description	Type/Default Value	Required / Optional
other	Its row and column indices are used to define the new indices of this object.	Object of the same data type	Required
method	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	{None, ‘backfill’/’bfill’, ‘pad’/’ffill’, ‘nearest’}	Required
copy	Return a new object, even if the passed indexes are the same.	bool Default Value: True	Required
limit	Maximum number of consecutive labels to fill for inexact matches.	int Default Value: None	Required
tolerance	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.		Optional

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

Example:

Download the Pandas DataFrame Notebooks from here.

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