Calculate the percentage of a categorical column using conditional groupby and count in Python

Question

I want to calculate a percentage, for each id, of True values from all rows of the id. Here an example of my data: id col1 1 True 1 True 1 False 1 True 2 False 2 False The new column should look like this: id col1 num_true 1 True 0.75 1 True 0.75 1 False 0.75 1 True 0.75 2 False 0 2 False 0 This is what I tried to do: df['num_true']= df[df['col1'] == 'True'].groupby('id')['col1'].count() df['num_col1_id']= df.groupby('id')['col1'].transform('count') df['perc_true']= df.num_true/df.num_col1_id Select the correct answer from above options

Answer 1

Use groupby and apply transform to get the mean df['num_true']=df.groupby('id').col1.transform('mean') id col1 num_true 0 1 True 0.75 1 1 True 0.75 2 1 False 0.75 3 1 True 0.75 4 2 False 0.00 5 2 False 0.00 Learn Python for Data Science Course to improve your technical knowledge.