两个值与大 pandas 匹配时的累计计数 [英] Cumulative count when two values match pandas

问题描述

我正在尝试创建一个新的 Column ，它根据单独的列中的值显示一个累计计数.

I am trying to create a new Column that displays a cumulative count based off values in separate columns.

因此对于下面的代码，我试图基于 Cause 和 Answer Columns 创建两个新列.因此，对于 Column Answer 中的值，如果 In 位于 Column Cause 中，我想在新列中提供累积计数.

So for the code below, I'm trying to create two new columns based off Cause and Answer Columns. So for the values in Column Answer, if In is situated in Column Cause I want to provide a cumulative count in a new column.

import pandas as pd

d = ({
    'Cause' : ['In','','','In','','In','In'],
    'Answer' : ['Yes','No','Maybe','No','Yes','No','Yes'],
    })

df = pd.DataFrame(d)

输出:

  Answer Cause
0    Yes    In
1     No      
2  Maybe      
3     No    In
4    Yes      
5     No    In
6    Yes    In

预期输出:

  Answer Cause Count_No Count_Yes
0    Yes    In                  1
1     No                         
2  Maybe                         
3     No    In        1          
4    Yes                         
5     No    In        2          
6    Yes    In                  2

我尝试了以下操作，但出现错误.

I have tried the following but get an error.

df['cumsum'] = df.groupby(['Answer'])['Cause'].cumsum()

推荐答案

无for循环:-)

s=df.loc[df.Cause=='In'].Answer.str.get_dummies()
pd.concat([df,s.cumsum().mask(s!=1,'')],axis=1).fillna('')
Out[62]: 
  Answer Cause No Yes
0    Yes    In      1
1     No             
2  Maybe             
3     No    In  1    
4    Yes             
5     No    In  2    
6    Yes    In      2

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