Pandas groupby agg returns multiindex columns how to remove multiindex?-CodePudding

I am trying to understand how to remove multiindex columns after applying groupby and agg - see below, last command returns (Target, count), (Target, sum) multiindex columns but I want a data frame without multiindex

# Sample Data Creation
lst_Purchase_Date = ['2022-02-28','2022-02-28','2022-02-28','2022-03-01','2022-03-01']
lst_Target = [0,0,1,1,1]
df_test = pd.DataFrame(list(zip(lst_Purchase_Date,lst_Target)),columns=['Purchase_Date','Target'])
df_test.head()

    Purchase_Date   Target
0   2022-02-28        0
1   2022-02-28        0
2   2022-02-28        1
3   2022-03-01        1
4   2022-03-01        1

Using groupby and agg results in column multi-index

result = df_test.groupby('Purchase_Date').agg(['sum','count'])
result = result.reset_index()
result.head()

    Purchase_Date   Target
                   sum  count
0   2022-02-28       1  3
1   2022-03-01       2  2

I need result like below

Purchase_Date Target_Sum Target_Count
2022-02-28       1            3
2022-03-01       2            2

CodePudding user response：

You can use a more verbose syntax for agg where you get to specify the column names on the left, then the column to operate on, then the function to apply

import pandas as pd

df = pd.DataFrame(
    {'Purchase_Date': 
     {0: '2022-02-28',
      1: '2022-02-28',
      2: '2022-02-28',
      3: '2022-03-01',
      4: '2022-03-01'},
 'Target': {0: 0, 1: 0, 2: 1, 3: 1, 4: 1}}
)

result = df.groupby('Purchase_Date').agg(
    Target_Sum = ('Target','sum'),
    Target_Count = ('Target','count'),
)

result