版权声明:本文为博主原创文章,未经博主允许不得转载。 https://blog.csdn.net/buside/article/details/86597764
在官方网站中对as_index有以下介绍:
as_index : boolean, default True
For aggregated output, return object with group labels as the index. Only relevant for DataFrame input. as_index=False is effectively “SQL-style” grouped output
翻译过来就是说as_index 的默认值为True, 对于聚合输出,返回以组标签作为索引的对象。仅与DataFrame输入相关。as_index = False实际上是“SQL风格”的分组输出。举例如下
# -*- coding: UTF-8 -*-
import pandas as pd
df = pd.DataFrame(data={'books':['bk1','bk1','bk1','bk2','bk2','bk3'], 'price':
[12,12,12,15,15,17]})
print df
print('................1..........................')
df0 = df.groupby('books', as_index=True).sum()
print df0
print(df0.loc['bk1'])
# print(df0.loc[0])
print('....................2......................')
df1 = df.groupby('books', as_index=False).sum()
print df1
# print(df1.loc['bk1'])
print(df1.loc[df1.books=='bk1'])
print('....................3......................')
print(df1.loc[0])
输出结果如下
books price
0 bk1 12
1 bk1 12
2 bk1 12
3 bk2 15
4 bk2 15
5 bk3 17
................1..........................
price
books
bk1 36
bk2 30
bk3 17
price 36
Name: bk1, dtype: int64
....................2......................
books price
0 bk1 36
1 bk2 30
2 bk3 17
books price
0 bk1 36
....................3......................
books bk1
price 36
Name: 0, dtype: object
代码中注释的两段代码报错,分析可以看到,当as_index=True时,df0没有显示索引项,而是以第一列组标签为索引值,故不能通过df0.loc[0]取值,可以通过df0.loc[‘bk1’]取值;当as_index=False时,df1显示索引项,此时可以通过df0.loc[0]取得值。因此as_index的作用是控制聚合输出是否以组标签为索引值。