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

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: