Pandas dataframe.mul() function it is used to retrun the multiplication of dataframe and other element-wise. This function is equivalent to the DataFrame * but it can provide an additional support to the handle the missing values in one of input. It returns a DataFrame with the result of the multiplication operation.
Syntax
DataFrame.mul(other, axis=’columns’, level=None, fill_value=None)Parameter:
- other: It is a single or multiple data-structure or list-like object. It is a series sequence or dataframe.
- axis: It is used to represent the index which is '0' for index and '1' for the column, and in series input, axis to match Series index on.
- level: By Default None. It is used specify int or label to broadcast across a level, matching Index values on the passed MultiIndex level.
- fill_value: By Default None. It is used to fill missing values or any new elements for successful alignment of dataframe with this value before computation. If data in both the dataframe with the same location is missing then the result is also missing.
Return:
It returns dataframe which is result of Arithmetic operation.
Examples
using mul() function on whole DataFrame
import numpy as np
import pandas as pd
a = [11,21,35,46,57]
b = [10,30,50,40,60]
c = [33,45,67,76,55]
values = pd.DataFrame({'a':a,'b':b,'c':c})
print(values.mul(2))Output:
a b c
0 22 20 66
1 42 60 90
2 70 100 134
3 92 80 152
4 114 120 110When one DataFrame contains null values
x = [5,5,6,7,8]
y = [3,5,6,7,8]
z = [np.NaN,np.NaN,np.NaN,np.NaN,np.NaN]
values = pd.DataFrame({'x':x,'y':y,'z':z})
print(values.mul(20,fill_value=10))Output:
x y z
0 100 60 200.0
1 100 100 200.0
2 120 120 200.0
3 140 140 200.0
4 160 160 200.0