1、层次索引

1.1 定义

在某一个方向拥有多个（两个及两个以上）索引级别，就叫做层次索引。

通过层次化索引，pandas能够以较低维度形式处理高纬度的数据

通过层次化索引，可以按照层次统计数据

层次索引包括Series层次索引和DataFrame层次索引

1.2 Series的层次索引

import numpy as npimport pandas as pds1 = pd.Series(data=[99, 80, 76, 80, 99], index=[['2017', '2017', '2018', '2018', '2018'], ['张伊曼', '张巧玲', '张诗诗', '张思思', '张可可']])print(s1)

1.3 DataFrame的层次索引

# DataFrame的层次索引df1 = pd.DataFrame({ 'year': [2016, 2016, 2017, 2017, 2018], 'fruit': ['apple', 'banana', 'apple', 'banana', 'apple'], 'production': [10, 30, 20, 70, 100], 'profits': [40, 30, 60, 80,10],})print("df1===================================")print(df1)df2 = df1.set_index(['year', 'fruit'])print("df2===================================")print(df2)print("df2.index===================================")print(df2.index)print("df2.sum(level='year')===================================")print(df2.sum(level='year'))print("df2.mean(level='fruit')===================================")print(df2.mean(level='fruit'))print("df2.sum(level=['year', 'fruit'])===================================")print(df2.sum(level=['year', 'fruit']))

2、取值的新方法

ix是比较老的方法 新方式是使用iloc loc

iloc 对下标值进行操作 Series与DataFrame都可以操作

loc 对索引值进行操作 Series与DataFrame都可以操作

2.1 Series

# # 取值的新方法s1 = pd.Series(data=[99, 80, 76, 80, 99], index=[['2017', '2017', '2018', '2018', '2018'], ['张伊曼', '张巧玲', '张诗诗', '张思思', '张可可']])print("s1=================================")print(s1)print("s1.iloc[2]=================================")print(s1.iloc[2])print("s1.loc['2018']['张思思']=================================")print(s1.loc['2018']['张思思'])

2.2 DataFrame

df1 = pd.DataFrame({ 'year': [2016, 2016, 2017, 2017, 2018], 'fruit': ['apple', 'banana', 'apple', 'banana', 'apple'], 'production': [10, 30, 20, 70, 100], 'profits': [40, 30, 60, 80,10],})print("df1===================================")print(df1)print("旧方法获取值===================================")print("df1['year'][0]===================================")print(df1['year'][0])print("df1.ix[0]['year']===================================")print(df1.ix[0]['year'])print("新方法获取值===================================")print("df1.iloc[0][3]===================================")print(df1.iloc[0][3])print("df1.loc[0]['year']===================================")print(df1.loc[0]['year'])

以上这篇对pandas的层次索引与取值的新方法详解就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。