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Pandas Series - add() function

The Pandas add() function returns addition 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.


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


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: Adding a scalar value to the Series

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

import pandas as pd
import numpy as np

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

print("The Series contains:")

#adding 3 to the Series
print("\nx.add(3) returns:")

The output of the above code will be:

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

x.add(3) returns:
0    13
1    23
2    33
3    43
4    53
dtype: int64

Example: Adding two Series

A series can be added to 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("\nThe y contains:")

#adding two Series
print("\nx.add(y, fill_value=0) returns:")
print(x.add(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.add(y, fill_value=0) returns:
A    11.0
B     2.0
C    33.0
D    40.0
dtype: float64

Example: Adding columns in a DataDrame

The add() function can be applied in a DataFrame to get the addition 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:")

#adding 'Bonus' and 'Salary' column
df['Total Salary'] = df['Salary'].add(df['Bonus'])

print("\nThe DataFrame is:")

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  Total Salary
John       5      60            65
Marry      3      62            65
Sam        2      65            67
Jo         4      59            63

❮ Pandas Series - Functions