pandas calculate mean by groups
# Basic syntax: df.groupby('column_name').mean() # Where this will return the mean of each group with the same values in # the column "column_name" # Example usage: import pandas as pd import numpy as np df = pd.DataFrame({'A': [1, 1, 2, 1, 2], 'B': [np.nan, 2, 3, 4, 5], 'C': [1, 2, 1, 1, 2]}, columns=['A', 'B', 'C']) print(df) A B C 0 1 NaN 1 1 1 2.0 2 2 2 3.0 1 3 1 4.0 1 4 2 5.0 2 # Calculate the mean of columns B and C grouped by the values in column A df.groupby('A').mean() # Returns: B C A 1 3.0 1.333333 2 4.0 1.500000 # Calculate the mean of column C grouped by the values in columns A and B df.groupby(['A', 'B']).mean() # Returns: C A B 1 2.0 2 4.0 1 2 3.0 1 5.0 2