pandas.Series.rpow#

Series.rpow(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 either one of the inputs.

Parameters

otherSeries or scalar value
levelint or name: Broadcast across a level, matching Index values on the passed MultiIndex level.
fill_valueNone 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 of filling (at that location) will be missing.
axis{0 or ‘index’}: Unused. Parameter needed for compatibility with DataFrame.

Returns

Series: The result of the operation.

See also

Series.pow: Element-wise Exponential power, see Python documentation for more details.

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