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Pandas Series: rsub() function

Element-wise subtraction of series and other in Pandas

The rsub() function is used to get Subtraction of series and other, element-wise (binary operator rsub).

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

Syntax:

Series.rsub(self, other, level=None, fill_value=None, axis=0)
Pandas Series rsub() function

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([1, 2, 2, np.nan], index=['p', 'q', 'r', 's'])
x

Output:

p    1.0
q    2.0
r    2.0
s    NaN
dtype: float64
Pandas Series rsub() function

Python-Pandas Code:

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

Output:

p    2.0
q    NaN
s    2.0
t    NaN
dtype: float64
Pandas Series rsub() function

Python-Pandas Code:

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

Output:

p    1.0
q   -2.0
r   -2.0
s    2.0
t    NaN
dtype: float64

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Next: Multiplication of Pandas series and other, element-wise



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