对pandas的层次索引与取值的新方法详解

import numpy as np
import pandas as pd

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)

# Data 的层次索引
df1 = pd.Data ({
 \'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\']))

# # 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\'])

df1 = pd.Data ({
 \'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\'])