pandas.DataFrame.unstack#

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).

Parameters:

levelint, str, or list of these, default -1 (last level): Level(s) of index to unstack, can pass level name.
fill_valuescalar: Replace NaN with this value if the unstack produces missing values.
sortbool, default True: Sort the level(s) in the resulting MultiIndex columns. This also orders the rows of the result: sorted by the remaining levels if True, in order of first appearance if False.

Returns:

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

See also

DataFrame.pivot: Pivot a table based on column values.
DataFrame.stack: Pivot a level of the column labels (inverse operation from unstack).

Notes

Reference the user guide for more examples.

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