DataFrame.unstack(level=-1, fill_value=None, sort=True)[source]#

Pivot a level of the (necessarily hierarchical) index labels.

Returns a DataFrame having a new level of column labels whose inner-most level consists of the pivoted index labels.

If the index is not a MultiIndex, the output will be a Series (the analogue of stack when the columns are not a MultiIndex).

levelint, str, or list of these, default -1 (last level)

Level(s) of index to unstack, can pass level name.

fill_valueint, str or dict

Replace NaN with this value if the unstack produces missing values.

sortbool, default True

Sort the level(s) in the resulting MultiIndex columns.

Series or DataFrame

If index is a MultiIndex: DataFrame with pivoted index labels as new inner-most level column labels, else Series.

See also


Pivot a table based on column values.


Pivot a level of the column labels (inverse operation from unstack).


Reference the user guide for more examples.


>>> index = pd.MultiIndex.from_tuples(
...     [("one", "a"), ("one", "b"), ("two", "a"), ("two", "b")]
... )
>>> s = pd.Series(np.arange(1.0, 5.0), index=index)
>>> s
one  a   1.0
     b   2.0
two  a   3.0
     b   4.0
dtype: float64
>>> s.unstack(level=-1)
     a   b
one  1.0  2.0
two  3.0  4.0
>>> s.unstack(level=0)
   one  two
a  1.0   3.0
b  2.0   4.0
>>> df = s.unstack(level=0)
>>> df.unstack()
one  a  1.0
     b  2.0
two  a  3.0
     b  4.0
dtype: float64