pandas.DataFrame.reindex_axis¶
- DataFrame.reindex_axis(labels, axis=0, method=None, level=None, copy=True, limit=None, fill_value=nan)¶
Conform input object 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
Parameters: labels : array-like
New labels / index to conform to. Preferably an Index object to avoid duplicating data
axis : {0, 1, ‘index’, ‘columns’}
method : {None, ‘backfill’/’bfill’, ‘pad’/’ffill’, ‘nearest’}, optional
- Method to use for filling holes in reindexed DataFrame:
- 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
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 number of consecutive elements to forward or backward fill
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.
New in version 0.17.0.
Returns: reindexed : DataFrame
See also
Examples
>>> df.reindex_axis(['A', 'B', 'C'], axis=1)