如何将pandas数据透视表转换为数据帧

Question

我想使用数据透视表来汇总数据集,然后能够访问数据透视表中的信息,就像它是一个DataFrame一样.

考虑一个分层数据集,患者在医院和位于地区的医院接受治疗:

import pandas as pd

example_data = {'patient' : ['p1','p2','p3','p4','p5','p6','p7','p8','p9','p10','p11','p12','p13','p14','p15','p16','p17','p18','p19','p20','p21','p22','p23','p24','p25','p26','p27','p28','p29','p30','p31','p32','p33','p34','p35','p36','p37','p38','p39','p40','p41','p42','p43','p44','p45','p46','p47','p48','p49','p50','p51','p52','p53','p54','p55','p56','p57','p58','p59','p60','p61','p62','p63'], 
                'hospital' : ['h1','h1','h1','h2','h2','h2','h2','h3','h3','h3','h3','h3','h4','h4','h4','h4','h4','h4','h5','h5','h5','h5','h5','h5','h5','h6','h6','h6','h6','h6','h6','h6','h6','h7','h7','h7','h7','h7','h7','h7','h7','h7','h8','h8','h8','h8','h8','h8','h8','h8','h8','h8','h9','h9','h9','h9','h9','h9','h9','h9','h9','h9','h9'], 
                'region' : ['r1','r1','r1','r1','r1','r1','r1','r1','r1','r1','r1','r1','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r2','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3','r3'] }

example_dataframe = pd.DataFrame(example_data)

print example_dataframe

这产生如下的简单输出:

   hospital patient region
0        h1      p1     r1
1        h1      p2     r1
2        h1      p3     r1
3        h2      p4     r1
4        h2      p5     r1
5        h2      p6     r1
6        h2      p7     r1
7        h3      p8     r1
8        h3      p9     r1
9        h3     p10     r1
10       h3     p11     r1
11       h3     p12     r1
12       h4     p13     r2
13       h4     p14     r2
14       h4     p15     r2
15       h4     p16     r2
16       h4     p17     r2
etc.

现在我想总结使用数据透视表,只计算每家医院的患者数量:

example_pivot_table = pd.pivot_table(example_dataframe, values='patient', rows=['hospital','region'], aggfunc='count')

print example_pivot_table

这会产生以下输出:

hospital  region
h1        r1         3
h2        r1         4
h3        r1         5
h4        r2         6
h5        r2         7
h6        r2         8
h7        r3         9
h8        r3        10
h9        r3        11
Name: patient, dtype: int64

据我了解,这实际上是一个多索引系列.

我如何使用这些数据来找出医院h7所在的区域？如果hospital,region并且患者计数数据是DataFrame中的单独列,则很容易.但我认为医院和地区是指数.我已经尝试过很多东西,但却无法让它发挥作用.

Answer 1

您可以使用get_level_values获取医院列。您可以传递级别编号或级别名称，即0或hospital

然后你可以通过以下方式得到你想要的：

In [38]: example_pivot_table[ example_pivot_table.index.get_level_values('hospital') == 'h7' ]
Out[38]: 
hospital  region
h7        r3        9
Name: patient, dtype: int64

更新

要获取区域，您可以这样做

example_pivot_table[ example_pivot_table.index.get_level_values('hospital') == 'h7' ]['regions']