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