Pandas Series - div() function

The Pandas div() function returns floating division of series and other, element-wise. It is equivalent to series / other, but with support to substitute a fill_value for missing data as one of the parameters.

Syntax

Series.div(other, level=None, fill_value=None)

Parameters

`other`	`Required.` Specify scalar value or Series.
`level`	`Optional.` Specify int or name to broadcast across a level, matching Index values on the passed MultiIndex level. Default is None.
`fill_value`	`Optional.` Specify value to fill existing missing (NaN) values, and any new element needed for successful Series alignment. If data in both corresponding Series locations is missing the result will be missing. Default is None.

Return Value

Returns the result of the arithmetic operation.

Example: Dividing the Series with a scalar value

In the example below, the div() function is used to divide the series with a given scalar value.

import pandas as pd
import numpy as np

x = pd.Series([10, 20, 30, 40, 50])

print("The Series contains:")
print(x)

#dividing the Series by 2
print("\nx.div(2) returns:")
print(x.div(2))

The output of the above code will be:

The Series contains:
0    10
1    20
2    30
3    40
4    50
dtype: int64

x.div(2) returns:
0     5.0
1    10.0
2    15.0
3    20.0
4    25.0
dtype: float64

Example: Dividing two Series

A series can be divided with another series in the similar fashion. Consider the following example:

import pandas as pd
import numpy as np

x = pd.Series([10, np.NaN, 30, 40], index=['A', 'B', 'C', 'D'])
y = pd.Series([1, 2, 3, np.NaN], index=['A', 'B', 'C', 'D'])

print("The x contains:")
print(x)

print("\nThe y contains:")
print(y)

#dividing x by y
print("\nx.div(y, fill_value=0) returns:")
print(x.div(y, fill_value=0))

The output of the above code will be:

The x contains:
A    10.0
B     NaN
C    30.0
D    40.0
dtype: float64

The y contains:
A    1.0
B    2.0
C    3.0
D    NaN
dtype: float64

x.div(y, fill_value=0) returns:
A    10.0
B     0.0
C    10.0
D     inf
dtype: float64

Example: Dividing columns in a DataDrame

The div() function can be applied in a DataFrame to get the division of two series/column element-wise. Consider the following example.

import pandas as pd
import numpy as np

df = pd.DataFrame({
  "Bonus": [5, 3, 2, 4],
  "Salary": [60, 62, 65, 59]},
  index= ["John", "Marry", "Sam", "Jo"]
)

print("The DataFrame is:")
print(df)

#dividing 'Bonus' by 'Salary' column
df['%Bonus'] = df['Bonus'].div(df['Salary'])
#converting into percentage
df['%Bonus'] = df['%Bonus'] * 100

print("\nThe DataFrame is:")
print(df)

The output of the above code will be:

The DataFrame is:
       Bonus  Salary
John       5      60
Marry      3      62
Sam        2      65
Jo         4      59

The DataFrame is:
       Bonus  Salary    %Bonus
John       5      60  8.333333
Marry      3      62  4.838710
Sam        2      65  3.076923
Jo         4      59  6.779661

❮ Pandas Series - Functions