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:
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 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) |
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Returns: |
reindexed : DataFrame |
See also
>>> df.reindex_axis(['A', 'B', 'C'], axis=1)
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http://pandas.pydata.org/pandas-docs/version/0.22.0/generated/pandas.DataFrame.reindex_axis.html