Title

6.7 选择单行、单列、单值、多行多列

分层索引切片，就是通过切片DataFrame或者Series的分层索引达到选择数据的目的。分层索引的切片方式与单层索引切片完全相同，只是单层索引标签一般是标量值，而分层索引标签是由元组构成。

1、选择单行

单行选择直接将分层索引的每层标签写入元组，返回结果是Series数据

2、选择单列

单列选择将分层索引的每层标签写入元组，返回结果也是Series数据

3、选择单值

指定单行单列的交叉点是一个单值，也就是在loc中指定单行分层索引标与单列分层索引标签

import pandas as pd

df=pd.read_excel(r "D:\Pyobject2023\object\测试\素材\测试素材.多层索引区域选择.xlsx" , header =[ 0,1,2 ], index_col =[ 0,1,2 ])

print (df)

import pandas as pd

df=pd.read_excel(r "D:\Pyobject2023\object\测试\素材\测试素材.多层索引区域选择.xlsx" , header =[ 0,1,2 ], index_col =[ 0,1,2 ])

s1=df.loc[( "上海","销售1部","B" )]

s2=df.loc[:,( "硬件","配件","主板" )]

print (s1)

print ("--------------------------------")

print (s2)

Name: (上海, 销售1部, B), dtype: int64

--------------------------------

Name: (硬件, 配件, 主板), dtype: int64

import pandas as pd

df=pd.read_excel(r "D:\Pyobject2023\object\测试\素材\测试素材.多层索引区域选择.xlsx" , header =[ 0,1,2 ], index_col =[ 0,1,2 ])

df.sort_index(level=[ "地区","部门","代号" ], inplace = True )

df=df.loc[( "上海","销售1部","A" ):( "北京","销售1部","B" ),( "硬件","配件","主板" ):( "软件","编程","Python" )]

print (df)