pyspark.pandas.Series.pop¶

Series.pop(item: Union[Any, Tuple[Any, …]]) → Union[pyspark.pandas.series.Series, int, float, bool, str, bytes, decimal.Decimal, datetime.date, datetime.datetime, None][source]¶

Return item and drop from series.

Parameters

itemlabel: Label of index to be popped.

Returns

Value that is popped from series.

Examples

>>> s = ps.Series(data=np.arange(3), index=['A', 'B', 'C'])
>>> s
A    0
B    1
C    2
dtype: int64

>>> s.pop('A')
0

>>> s
B    1
C    2
dtype: int64

>>> s = ps.Series(data=np.arange(3), index=['A', 'A', 'C'])
>>> s
A    0
A    1
C    2
dtype: int64

>>> s.pop('A')
A    0
A    1
dtype: int64

>>> s
C    2
dtype: int64

Also support for MultiIndex

>>> midx = pd.MultiIndex([['lama', 'cow', 'falcon'],
...                       ['speed', 'weight', 'length']],
...                      [[0, 0, 0, 1, 1, 1, 2, 2, 2],
...                       [0, 1, 2, 0, 1, 2, 0, 1, 2]])
>>> s = ps.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3],
...               index=midx)
>>> s
lama    speed      45.0
        weight    200.0
        length      1.2
cow     speed      30.0
        weight    250.0
        length      1.5
falcon  speed     320.0
        weight      1.0
        length      0.3
dtype: float64

>>> s.pop('lama')
speed      45.0
weight    200.0
length      1.2
dtype: float64

>>> s
cow     speed      30.0
        weight    250.0
        length      1.5
falcon  speed     320.0
        weight      1.0
        length      0.3
dtype: float64

Also support for MultiIndex with several indexes.

>>> midx = pd.MultiIndex([['a', 'b', 'c'],
...                       ['lama', 'cow', 'falcon'],
...                       ['speed', 'weight', 'length']],
...                      [[0, 0, 0, 0, 0, 0, 1, 1, 1],
...                       [0, 0, 0, 1, 1, 1, 2, 2, 2],
...                       [0, 1, 2, 0, 1, 2, 0, 0, 2]]
...  )
>>> s = ps.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3],
...              index=midx)
>>> s
a  lama    speed      45.0
           weight    200.0
           length      1.2
   cow     speed      30.0
           weight    250.0
           length      1.5
b  falcon  speed     320.0
           speed       1.0
           length      0.3
dtype: float64

>>> s.pop(('a', 'lama'))
speed      45.0
weight    200.0
length      1.2
dtype: float64

>>> s
a  cow     speed      30.0
           weight    250.0
           length      1.5
b  falcon  speed     320.0
           speed       1.0
           length      0.3
dtype: float64

>>> s.pop(('b', 'falcon', 'speed'))
(b, falcon, speed)    320.0
(b, falcon, speed)      1.0
dtype: float64

pyspark.pandas.Series.keys

pyspark.pandas.Series.items