Python 2.7 将多索引转换为列

我定义了一个多索引数据帧，例如：

import pandas as pd
import numpy as np

dates = pd.date_range('20130101',periods=3,freq='5s')
dates = dates.append(dates)

locations = list('AAABBB')
gascode = ['no2','o3','so2']*2

tup = pd.MultiIndex.from_tuples( zip(locations,gascode,dates), names=['Location','gas','Date'] )

data = pd.DataFrame(data=range(6),index=tup,columns=['val1'])

>>> data

Location gas Date                  val1         
A        no2 2013-01-01 00:00:00     0
         o3  2013-01-01 00:00:05     1
         so2 2013-01-01 00:00:10     2
B        no2 2013-01-01 00:00:00     3
         o3  2013-01-01 00:00:05     4
         so2 2013-01-01 00:00:10     5

仅从位置“A”保留数据：

data = data.xs(key='A',level='Location')

现在，我想根据“气体”索引创建新的列，以获得：

Date                   no2   o3   so2
2013-01-01 00:00:00     0    nan  nan
2013-01-01 00:00:05     nan  1    nan
2013-01-01 00:00:10     nan  nan  2

我试着围绕“日期”索引旋转，将“气体”放在列中，但失败了

data = data.pivot(index=data.index.get_level_values(level='date'),
                  columns=situ.index.get_level_values(level='gas'))

我不知道如何做到这一点；有人能推荐一个替代方案吗

您可以查看结果：

In [11]: data.xs(key='A', level='Location').unstack(0)
Out[11]: 
                     val1         
gas                   no2  o3  so2
Date                              
2013-01-01 00:00:00     0 NaN  NaN
2013-01-01 00:00:05   NaN   1  NaN
2013-01-01 00:00:10   NaN NaN    2

[3 rows x 3 columns]

您可以选择以下结果：

In [11]: data.xs(key='A', level='Location').unstack(0)
Out[11]: 
                     val1         
gas                   no2  o3  so2
Date                              
2013-01-01 00:00:00     0 NaN  NaN
2013-01-01 00:00:05   NaN   1  NaN
2013-01-01 00:00:10   NaN NaN    2

[3 rows x 3 columns]