pandas.DataFrame.reindex_axis¶
-
DataFrame.
reindex_axis
(labels, axis=0, method=None, level=None, copy=True, limit=None, fill_value=nan)[source]¶ 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 or ‘index’, 1 or ‘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
.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 0.17.0.
New in version 0.21.0: (list-like tolerance)
Returns: reindexed : DataFrame
See also
Examples
>>> df.reindex_axis(['A', 'B', 'C'], axis=1)