Welcome to pandas!

6.2 分层索引的设置

1、创建时指定Series索引

import pandas as pd

l=[[ "A组","A组","B组","B组" ],[ "1","2","3","4" ]]

s=pd.Series([ "张三","李四","王麻子","小曾" ], index =l)

print (s)

返回：

dtype: object

import pandas as pd

l=[[ "A组","A组","B组","B组" ],[ "1","2","3","4" ]]

s=pd.Series([ "张三","李四","王麻子","小曾" ], index =l)

s.index.names=[ "组名","工号" ] #索引标题["组名","工号"]

print (s)

返回：

dtype: object

2、重置已存在Series索引

import pandas as pd

l=[[ "A组","A组","B组","B组" ],[ "1","2","3","4" ]]

s=pd.Series([ "张三","李四","王麻子","小曾" ]) #如Series是通过切片生成

s.index=l #如Series是通过切片生成,则可以通过s.index指定索引

s.index.names=[ "组名","工号" ] #指定索引标题["组名","工号"]

print (s)

返回结果和上列是一样的。

3、DataFrame行索引

import pandas as pd,numpy as np

l=[[ "A组","A组","B组","B组" ],[ "1","2","3","4" ]]

arr=np.arange( 2000,2020 ).reshape( 4,5 )

df=pd.DataFrame(arr, index =l)

df.index.names=[ "组名","工号" ]

print (df)

返回：

4、DataFrame列索引

import pandas as pd,numpy as np

l=[[ "A组","A组","B组","B组","C组" ],[ "1","2","3","4","5" ]]

arr=np.arange( 2000,2020 ).reshape( 4,5 )

df=pd.DataFrame(arr, columns =l)

df.columns.names=[ "组名","工号" ]

print (df)

返回：