pandas.Series.rpow

Series.rpow(self, other, level=None, fill_value=None, axis=0) [source]

Return Exponential power of series and other, element-wise (binary operator rpow).

Equivalent to other ** series, but with support to substitute a fill_value for missing data in one of the inputs.

Parameters:

other : Series or scalar value fill_value : None or float value, default None (NaN) Fill existing missing (NaN) values, and any new element needed for successful Series alignment, with this value before computation. If data in both corresponding Series locations is missing the result will be missing. level : int or name Broadcast across a level, matching Index values on the passed MultiIndex level.

Returns:

Series The result of the operation.

See also

Series.pow

Examples

>>> a = pd.Series([1, 1, 1, np.nan], index=['a', 'b', 'c', 'd'])
>>> a
a    1.0
b    1.0
c    1.0
d    NaN
dtype: float64
>>> b = pd.Series([1, np.nan, 1, np.nan], index=['a', 'b', 'd', 'e'])
>>> b
a    1.0
b    NaN
d    1.0
e    NaN
dtype: float64
>>> a.pow(b, fill_value=0)
a    1.0
b    1.0
c    1.0
d    0.0
e    NaN
dtype: float64