xorbits.pandas.DataFrame.unstack#

DataFrame.unstack(level: IndexLabel = - 1, fill_value=None, sort: bool = 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

level (int, str, or list of these, default -1 (last level)) – Level(s) of index to unstack, can pass level name.
fill_value (int, str or dict) – Replace NaN with this value if the unstack produces missing values.
sort (bool, default True) – Sort the level(s) in the resulting MultiIndex columns.

Return type

Series or DataFrame

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

Warning

This method has not been implemented yet. Xorbits will try to execute it with pandas.

This docstring was copied from pandas.core.frame.DataFrame.