Python 将多索引数据帧的行合并到逗号分隔的列表中
给定一个多索引数据帧,我想组合重复的索引对,并将它们的值列为逗号分隔的列表。例如,输入:Python 将多索引数据帧的行合并到逗号分隔的列表中,python,pandas,dataframe,multi-index,Python,Pandas,Dataframe,Multi Index,给定一个多索引数据帧,我想组合重复的索引对,并将它们的值列为逗号分隔的列表。例如,输入: df = pd.DataFrame({'Last Name' : ['Deere','Deere','Foo' ,'Foo' ,'Man' ], 'First Name': ['John' ,'Jane' ,'Kung' ,'Kung' ,'Karate'], 'Value1': [ 1 , 2
df = pd.DataFrame({'Last Name' : ['Deere','Deere','Foo' ,'Foo' ,'Man' ],
'First Name': ['John' ,'Jane' ,'Kung' ,'Kung' ,'Karate'],
'Value1': [ 1 , 2 , 3 , 4 , 5 ],
'Value2': ['Green','Blue' ,'Yellow','Black','Purple']})
df.set_index(['Last Name','First Name'],inplace=True)
规定:
Value1 Value2
Last Name First Name
Deere John 1 Green
Jane 2 Blue
Foo Kung 3 Yellow
Kung 4 Black
Man Karate 5 Purple
我想将其转换为以下数据帧:
Value1 Value2
Last Name First Name
Deere John 1 Green
Jane 2 Blue
Foo Kung 3,4 Yellow,Black
Man Karate 5 Purple
您可以先将列
Value1
转换为string
by,然后使用join
按级别Last Name
和first Name
:
df['Value1'] = df['Value1'].astype(str)
result = df.groupby(level=['Last Name','First Name'], sort=False).agg( ','.join)
print result
Value1 Value2
Last Name First Name
Deere John 1 Green
Jane 2 Blue
Foo Kung 3,4 Yellow,Black
Man Karate 5 Purple