pandas中groupby()函数参数as_index小结

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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。