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Showing content from https://pandas.pydata.org/docs/dev/user_guide/../reference/api/pandas.DataFrame.unstack.html below:

pandas.DataFrame.unstack — pandas 3.0.0.dev0+2231.g4f2aa4d2be documentation

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.

Returns:

Series or DataFrame

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

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

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