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Pandas Series: mul() function

Get Multiplication of series in Pandas

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

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

Syntax:

Series.mul(self, other, level=None, fill_value=None, axis=0)
Pandas Series multiply() 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([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
Pandas Series multiply() function

Python-Pandas Code:

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

Output:

p    2.0
q    3.0
s    1.0
t    NaN
dtype: float64
Pandas Series multiply() function

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([2, 3, 1, np.nan], index=['p', 'q', 's', 't'])
x.multiply(y, fill_value=0)

Output:

p    6.0
q    6.0
r    0.0
s    0.0
t    NaN
dtype: float64

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Next: Floating division of series in Pandas



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