Pandas Series: rpow() function

Last update on September 15 2022 12:54:22 (UTC/GMT +8 hours)

Exponential power of Pandas series

The rpow() function is used to get exponential power of series and other, element-wise (binary operator rpow).

Syntax:

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

Parameters:

Name	Description	Type/Default Value	Required / Optional
other		Series or scalar value	Required
fill_value	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.	None or float value Default Value: None (NaN)	Required
level	Broadcast across a level, matching Index values on the passed MultiIndex level.	int or name	Required

Returns: Series
The result of the operation.

Example:

Python-Pandas Code:

import numpy as np
import pandas as pd
x = pd.Series([3, 2, 1, np.nan], index=['p', 'q', 'r', 's'])
x

Output:

p    3.0
q    2.0
r    1.0
s    NaN
dtype: float64

Python-Pandas Code:

import numpy as np
import pandas as pd
y = pd.Series([3, np.nan, 2, np.nan], index=['p', 'q', 's', 't'])
y

Output:

p    3.0
q    NaN
s    2.0
t    NaN
dtype: float64

Python-Pandas Code:

import numpy as np
import pandas as pd
x = pd.Series([3, 2, 1, np.nan], index=['p', 'q', 'r', 's'])
y = pd.Series([3, np.nan, 2, np.nan], index=['p', 'q', 's', 't'])
x.rpow(y, fill_value=0)

Output:

p    27.0
q     0.0
r     0.0
s     1.0
t     NaN
dtype: float64

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