Pandas Series: rdiv() function

Last update on September 15 2022 12:56:45 (UTC/GMT +8 hours)

Floating division of Pandas series

The rdiv() function is used to get floating division of series and other, element-wise (binary operator rtruediv).

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

Syntax:

Series.rdiv(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([2, 2, 2, np.nan], index=['p', 'q', 'r', 's'])
x

Output:

p    2.0
q    2.0
r    2.0
s    NaN
dtype: float64

Python-Pandas Code:

import numpy as np
import pandas as pd
y = pd.Series([1, 1, 1, np.nan], index=['p', 'q', 's', 't'])
y

Output:

p    1.0
q    1.0
s    1.0
t    NaN
dtype: float64

Python-Pandas Code:

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

Output:

p    0.5
q    0.5
r    0.0
s    inf
t    NaN
dtype: float64

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