pandas.DataFrame.reindex_axis

DataFrame.reindex_axis(labels, axis=0, method=None, level=None, copy=True, limit=None, fill_value=nan)

Conform DataFrame to new index with optional filling logic, placing NA/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

index : array-like, optional

New labels / index to conform to. Preferably an Index object to avoid duplicating data

axis : {0, 1}

0 -> index (rows) 1 -> columns

method : {‘backfill’, ‘bfill’, ‘pad’, ‘ffill’, None}, default None

Method to use for filling holes in reindexed DataFrame pad / ffill: propagate last valid observation forward to next valid backfill / bfill: use NEXT valid observation to fill gap

copy : boolean, default True

Return a new object, even if the passed indexes are the same

level : int or name

Broadcast across a level, matching Index values on the passed MultiIndex level

limit : int, default None

Maximum size gap to forward or backward fill

>>> df.reindex_axis(['A', 'B', 'C'], axis=1)

DataFrame.reindex, DataFrame.reindex_like

reindexed : same type as calling instance