*29*

You can use the following methods to find the sum of a specific set of columns in a pandas DataFrame:

**Method 1: Find Sum of All Columns**

#find sum of all columns df['sum'] = df.sum(axis=1)

**Method 2: Find Sum of Specific Columns**

#specify the columns to sum cols = ['col1', 'col4', 'col5'] #find sum of columns specified df['sum'] = df[cols].sum(axis=1)

The following examples show how to use each method in practice with the following pandas DataFrame:

import pandas as pd #create DataFrame df = pd.DataFrame({'points': [18, 22, 19, 14, 14, 11, 20, 28], 'assists': [5, 7, 7, 9, 12, 9, 9, 4], 'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]}) #view DataFrame print(df) points assists rebounds 0 18 5 11 1 22 7 8 2 19 7 10 3 14 9 6 4 14 12 6 5 11 9 5 6 20 9 9 7 28 4 12

**Example 1: Find Sum of All Columns**

The following code shows how to sum the values of the rows across all columns in the DataFrame:

#define new column that contains sum of all columns df['sum_stats'] = df.sum(axis=1) #view updated DataFrame df points assists rebounds sum_stats 0 18 5 11 34 1 22 7 8 37 2 19 7 10 36 3 14 9 6 29 4 14 12 6 32 5 11 9 5 25 6 20 9 9 38 7 28 4 12 44

The **sum_stats** column contains the sum of the row values across all columns.

For example, here’s how the values were calculated:

- Sum of row 0: 18 + 5 + 11 =
**34** - Sum of row 1: 22 + 7 + 8 =
**37** - Sum of row 2: 19 + 7 + 10 =
**36**

And so on.

**Example 2: Find Sum of Specific Columns**

The following code shows how to sum the values of the rows across all columns in the DataFrame:

#specify the columns to sum cols = ['points', 'assists'] #define new column that contains sum of specific columns df['sum_stats'] = df[cols].sum(axis=1) #view updated DataFrame df points assists rebounds sum_stats 0 18 5 11 23 1 22 7 8 29 2 19 7 10 26 3 14 9 6 23 4 14 12 6 26 5 11 9 5 20 6 20 9 9 29 7 28 4 12 32

The **sum_stats** column contains the sum of the row values across the ‘points’ and ‘assists’ columns.

For example, here’s how the values were calculated:

- Sum of row 0: 18 + 5 + 11 =
**23** - Sum of row 1: 22 + 7 =
**29** - Sum of row 2: 19 + 7 =
**26**

And so on.

**Additional Resources**

The following tutorials explain how to perform other common operations in pandas:

How to Perform a SUMIF Function in Pandas

How to Perform a GroupBy Sum in Pandas

How to Sum Columns Based on a Condition in Pandas