I am trying to solve a problem some what very similar to: https://platform.stratascratch.com/coding/10362-top-monthly-sellers?code_type=2

here I data frame as :

         product  seller  market   total_sales

         books      s1      de     10     
         books      s2      jp     20
         books      s3      in     30
         books      s1      de     25     
         books      s5      in     15
         books      s1      us     12
         books      s2      uk     10
      clothing      s1      de     11
      clothing      s2      de     18
      clothing      s1      uk     55
      clothing      s3      in     31
      clothing      s1      de     14
      clothing      s2      de     10
      clothing      s1      de     35
  electronics      s1       us     18
  electronics      s1       de     12
  electronics      s2       in     16
  electronics      s3       uk     24
  electronics      s1       us     37      
  electronics      s4       jp     27
  electronics      s3       uk     26
  electronics      s1       us     15      

I want to get top three product category sales in the world.

Expected output is:

product seller market total_sales

books s1 de 35
books s3 in 30
books s2 jp 20
Clothing s1 de 60
Clothing s1 uk 55
Clothing s2 de 28
electronics s1 us 70
electronics s3 uk 50
electronics s4 jp 27

I was able to aggregate total sales basing on product,seller & group them. After grouping I am able to sort it by total_sales per group.
But, I was not able to get only the top-3 total_sale rows per [‘product’] group. Cany anyone help on this.

import pandas as pd

df = df.groupby([‘product’, ‘seller’,’market’], as_index = False).agg({‘total_sales’:sum})

df = df.sort_values([‘product’,’seller’,’market’,’total_sales’],ascending=False).groupby([‘product’, ‘seller’,’market’,],as_index = False).aggregate(lambda x: ‘,’.join(map(str, x)))

print(df)