按组计算正值的比率

Question

I'm working with a Pandas DataFrame having the following structure:

import pandas as pd
​
df = pd.DataFrame({'brand' : ['A', 'A', 'B', 'B', 'C', 'C'], 
                   'target' : [0, 1, 0, 1, 0, 1], 
                   'freq' : [5600, 220, 5700, 90, 5000, 100]})
​
print(df)
  brand  target  freq
0     A       0  5600
1     A       1   220
2     B       0  5700
3     B       1    90
4     C       0  5000
5     C       1   100

For each brand, I would like to calculate the ratio of positive targets, eg for brand A, the percentage of positive target is 220/(220+5600) = 0.0378.

My resulting DataFrame should look like the following:

  brand  target  freq   ratio
0     A       0  5600  0.0378
1     A       1   220  0.0378
2     B       0  5700  0.0156
3     B       1    90  0.0156
4     C       0  5000  0.0196
5     C       1   100  0.0196

I know that I should group my DataFrame by brand and then apply some function to each group (since I want to keep all rows in my final result I think I should use transform here). I tested a couple of things but without any success. Any help is appreciated.

Answer 1

First sorting columns by brand and target for last 1 row per group and then divide in GroupBy.transform with lambda function:

df = df.sort_values(['brand','target'])
df['ratio'] = df.groupby('brand')['freq'].transform(lambda x: x.iat[-1] / x.sum())
print (df)
  brand  target  freq     ratio
0     A       0  5600  0.037801
1     A       1   220  0.037801
2     B       0  5700  0.015544
3     B       1    90  0.015544
4     C       0  5000  0.019608
5     C       1   100  0.019608

Or divide Series created by functions GroupBy.last and GroupBy.sum :

df = df.sort_values(['brand','target'])
g = df.groupby('brand')['freq']
df['ratio'] = g.transform('last').div(g.transform('sum'))