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Pandas Series: sub() function

Subtraction of series and other in Pandas

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

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

Syntax:

Series.sub(self, other, level=None, fill_value=None, axis=0)
Pandas Series subtract() 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([2, 1, 2, np.nan], index=['p', 'q', 'r', 's'])
x

Output:

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

Python-Pandas Code:

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

Output:

p    1.0
q    NaN
s    2.0
t    1.0
dtype: float64
Pandas Series subtract() function

Python-Pandas Code:

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

Output:

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

Previous: Addition of Pandas series and other
Next: Get Multiplication of series in Pandas



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