pyspark.pandas.Series.update

Series.update(other)

Modify Series in place using non-NA values from passed Series. Aligns on index.

Parameters

otherSeries

Examples

>>> from pyspark.pandas.config import set_option, reset_option
>>> set_option("compute.ops_on_diff_frames", True)
>>> s = ps.Series([1, 2, 3])
>>> s.update(ps.Series([4, 5, 6]))
>>> s.sort_index()
0    4
1    5
2    6
dtype: int64

>>> s = ps.Series(['a', 'b', 'c'])
>>> s.update(ps.Series(['d', 'e'], index=[0, 2]))
>>> s.sort_index()
0    d
1    b
2    e
dtype: object

>>> s = ps.Series([1, 2, 3])
>>> s.update(ps.Series([4, 5, 6, 7, 8]))
>>> s.sort_index()
0    4
1    5
2    6
dtype: int64

>>> s = ps.Series([1, 2, 3], index=[10, 11, 12])
>>> s
10    1
11    2
12    3
dtype: int64

>>> s.update(ps.Series([4, 5, 6]))
>>> s.sort_index()
10    1
11    2
12    3
dtype: int64

>>> s.update(ps.Series([4, 5, 6], index=[11, 12, 13]))
>>> s.sort_index()
10    1
11    4
12    5
dtype: int64

If other contains NaNs the corresponding values are not updated in the original Series.

>>> s = ps.Series([1, 2, 3])
>>> s.update(ps.Series([4, np.nan, 6]))
>>> s.sort_index()
0    4.0
1    2.0
2    6.0
dtype: float64

>>> reset_option("compute.ops_on_diff_frames")