BPt.Dataset.unstack#

Dataset.unstack(level=- 1, fill_value=None)[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_valueint, str or dict: Replace NaN with this value if the unstack produces missing values.

Returns

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