python - 如何将 group by Keys 应用于相关组

Question

我有一个数据框，我使用 group by 对它们进行分组，如下所示

Name      Nationality    age
Peter     UK             28
John      US             29 
Wiley     UK             28 
Aster     US             29 

grouped = self_ex_df.groupby([Nationality, age])

1. 现在我想为每个值附加一个唯一 ID

我正在尝试这个，但不确定它是否有效？

uniqueID = 'ID_'+ grouped.groups.keys().astype(str)

    uniqueID    Name      Nationality    age
     ID_UK28    Peter       UK             28
     ID_US29    John        US             29 
     ID_UK28    Wiley       UK             28 
     ID_US29    Aster       US             29 

1. 我现在想将它组合成一个新的 DF，类似于这样

    uniqueID   Nationality    age   Text
     ID_UK28     UK           28    Peter and Whiley have a combined age of 56
     ID_US_29    US           29    John and Aster have a combined age of 58
   

我如何实现上述目标？

Answer 1

希望足够接近，无法得到平均年龄:

import pandas as pd

#create dataframe
df = pd.DataFrame({'Name': ['Peter', 'John', 'Wiley', 'Aster'], 'Nationality': ['UK', 'US', 'UK', 'US'], 'age': [28, 29, 28, 29]})

#make uniqueID
df['uniqueID'] = 'ID_' + df['Nationality'] + df['age'].astype(str)

#groupby has agg method that can take dict and preform multiple aggregations
df = df.groupby(['uniqueID', 'Nationality']).agg({'age': 'sum', 'Name': lambda x: ' and '.join(x)})

#to get text you just combine new Name and sum of age
df['Text'] = df['Name'] + ' have a combined age of ' + df['age'].astype(str)