You can use the following methods to calculate the mean value by group in pandas:
Method 1: Calculate Mean of One Column Grouped by One Column
df.groupby(['group_col'])['value_col'].mean()
Method 2: Calculate Mean of Multiple Columns Grouped by One Column
df.groupby(['group_col'])['value_col1', 'value_col2'].mean()
Method 3: Calculate Mean of One Column Grouped by Multiple Columns
df.groupby(['group_col1', 'group_col2'])['value_col'].mean()
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({'team': ['A', 'A', 'A', 'A', 'B', 'B', 'B', 'B'], 'position': ['G', 'F', 'F', 'G', 'F', 'F', 'G', 'G'], 'points': [30, 22, 19, 14, 14, 11, 20, 28], 'assists': [4, 3, 7, 7, 12, 15, 8, 4]}) #view DataFrame print(df) team position points assists 0 A G 30 4 1 A F 22 3 2 A F 19 7 3 A G 14 7 4 B F 14 12 5 B F 11 15 6 B G 20 8 7 B G 28 4
Example 1: Calculate Mean of One Column Grouped by One Column
The following code shows how to calculate the mean value of the points column, grouped by the team column:
#calculate mean of points grouped by team
df.groupby('team')['points'].mean()
team
A 21.25
B 18.25
Name: points, dtype: float64
From the output we can see:
- The mean points value for team A is 21.25.
- The mean points value for team B is 18.25.
Example 2: Calculate Mean of Multiple Columns Grouped by One Column
The following code shows how to calculate the mean value of the points column and the mean value of the assists column, grouped by the team column:
#calculate mean of points and mean of assists grouped by team
df.groupby('team')[['points', 'assists']].mean()
points assists
team
A 21.25 5.25
B 18.25 9.75
The output displays the mean points value and mean assists value for each team.
Example 3: Calculate Mean of One Column Grouped by Multiple Columns
The following code shows how to calculate the mean value of the points column, grouped by the team and position columns:
#calculate mean of points, grouped by team and position
df.groupby(['team', 'position'])['points'].mean()
team position
A F 20.5
G 22.0
B F 12.5
G 24.0
Name: points, dtype: float64
From the output we can see:
- The mean points value for players on team A and position F is 20.5.
- The mean points value for players on team A and position G is 22.
- The mean points value for players on team B and position F is 12.5.
- The mean points value for players on team B and position G is 24.
Additional Resources
The following tutorials explain how to perform other common functions in pandas:
How to Find the Max Value by Group in Pandas
How to Find Sum by Group in Pandas
How to Calculate Quantiles by Group in Pandas