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It is possible to sum columns based on a condition using the SUMIF() function in Excel. This function takes three arguments: range, criteria, and sum_range. The range is the range of cells to be evaluated, the criteria is the condition that must be met to be included in the sum, and the sum_range is the range of cells to be summed. This function allows you to quickly sum a column based on a given condition.
You can use the following syntax to sum the values of a column in a pandas DataFrame based on a condition:
df.loc[df['col1'] == some_value, 'col2'].sum()
This tutorial provides several examples of how to use this syntax in practice using the following pandas DataFrame:
import pandas as pd #create DataFrame df = pd.DataFrame({'team': ['A', 'A', 'A', 'B', 'B', 'C'], 'conference': ['East', 'East', 'East', 'West', 'West', 'East'], 'points': [11, 8, 10, 6, 6, 5], 'rebounds': [7, 7, 6, 9, 12, 8]}) #view DataFrame df team conference points rebounds 0 A East 11 7 1 A East 8 7 2 A East 10 6 3 B West 6 9 4 B West 6 12 5 C East 5 8
Example 1: Sum One Column Based on One Condition
The following code shows how to find the sum of the points for the rows where team is equal to ‘A’:
df.loc[df['team'] == 'A', 'points'].sum() 29
Example 2: Sum One Column Based on Multiple Conditions
The following code shows how to find the sum of the points for the rows where team is equal to ‘A’ and where conference is equal to ‘East’:
df.loc[(df['team'] == 'A') & (df['conference'] == 'East'), 'points'].sum() 29
Example 3: Sum One Column Based on One of Several Conditions
The following code shows how to find the sum of the points for the rows where team is equal to ‘A’ or ‘B’:
df.loc[df['team'].isin(['A', 'B']), 'points'].sum() 41
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