Grouped subsets iteration loop

Task:Calculate how many months it takes for each sales representative to reach the sales amount of 50k.

Python

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 import pandas as pd

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 sale_file = "E:/txt/orders_i.csv"
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 sale_data = pd.read_csv(sale_file,sep=‘\t’)

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 sale_g = sale_data.groupby(‘sellerid‘)

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 breach50_list = []

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 for index,group in sale_g:

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     amount=0

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     group = group.sort_values(‘month’)

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     for row in group.itertuples():

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         amount+=getattr(row, ‘amount’)

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         if amount>=500000:

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             breach50_list.append([index,getattr(row, ‘month’),])

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             break

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 breach50_df = pd.DataFrame(breach50_list,columns=[‘sellerid‘,‘month’])

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 print(breach50_df)

esProc

 

 A

 
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E:/txt/orders_i.csv

 
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=file(A1).import@t()

 
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=A2.group(sellerid;(~.iterate((x=month,~~+amount),0,~~>500000),x):breach50)

 

esProc retains grouped subsets and uses the iterative function to realize the iteration.