使用代码进行编辑以重新创建

Question

我有DataFrame MultiIndex。索引字段为OptionSymbol（级别0）和QuoteDatetime（级别1）。我已对DataFrame进行索引和排序，如下所示：

sorted = df.sort_values(
    ['OptionSymbol', 'QuoteDatetime'], 
    ascending=[False, True]
)

indexed = sorted.set_index(
    ['OptionSymbol', 'QuoteDatetime'],
    drop=True
)

这导致以下结果：

                                      Id  Strike Expiration OptionType
OptionSymbol       QuoteDatetime                                      
ZBYMZ              2013-09-02     234669   170.0 2011-01-22        put
                   2013-09-03     234901   170.0 2011-01-22        put
                   2013-09-04     235133   170.0 2011-01-22        put
  ...                     ...        ...     ...        ...        ...
YBWNA              2010-02-12     262202    95.0 2010-02-20       call
                   2010-02-16     262454    95.0 2010-02-20       call
                   2010-02-17     262707    95.0 2010-02-20       call
  ...                     ...        ...     ...        ...        ...
XWNAX              2012-07-12     262201    90.0 2010-02-20       call
                   2012-07-16     262453    90.0 2010-02-20       call
                   2012-07-17     262706    90.0 2010-02-20       call
  ...                     ...        ...     ...        ...        ...
WWWAX              2012-04-12     262201    90.0 2010-02-20       call
                   2012-04-16     262453    90.0 2010-02-20       call
                   2012-04-17     262706    90.0 2010-02-20       call
  ...                     ...        ...     ...        ...        ...

正如预期的那样，首先按OptionSymbol的降序排序，然后在OptionSymbol组中按升序排序。

我需要做的是现在使用QuoteDatetime中的第一个值，因此结果如下所示：

Id Strike Expiration OptionType OptionSymbol QuoteDatetime XBWNA 2010-02-12 262202 95.0 2010-02-20 call 2010-02-16 262454 95.0 2010-02-20 call 2010-02-17 262707 95.0 2010-02-20 call ... ... ... ... ... ... NWWAX 2012-04-12 262201 90.0 2010-02-20 call 2012-04-16 262453 90.0 2010-02-20 call 2012-04-17 262706 90.0 2010-02-20 call ... ... ... ... ... ... BWNAX 2012-07-12 262201 90.0 2010-02-20 call 2012-07-16 262453 90.0 2010-02-20 call 2012-07-17 262706 90.0 2010-02-20 call ... ... ... ... ... ... XBYMZ 2013-09-02 234669 170.0 2011-01-22 put 2013-09-03 234901 170.0 2011-01-22 put 2013-09-04 235133 170.0 2011-01-22 put ... ... ... ... ... ...

我尝试过各种各种方法来索引= 1然后我失去了OptionSymbol组。我怎么做这种呢？

使用代码进行编辑以重新创建

from collections import OrderedDict df = OrderedDict(( ('OptionSymbol', pd.Series(['ZBYMZ', 'ZBYMZ', 'ZBYMZ', 'YBWNA', 'YBWNA', 'YBWNA', 'XWNAX', 'XWNAX', 'XWNAX', 'WWWAX', 'WWWAX', 'WWWAX', ])), ('QuoteDatetime', pd.Series(['2013-09-02', '2013-09-03', '2013-09-04', '2010-02-12', '2010-02-16', '2010-02-17', '2012-07-12', '2012-07-16', '2012-07-17', '2012-04-12', '2012-04-16', '2012-04-17'])), ('Id', pd.Series(np.random.randn(12,))), ('Strike', pd.Series(np.random.randn(12,))), ('Expiration', pd.Series(np.random.randn(12,))), ('OptionType', pd.Series(np.random.randn(12,))) ))

在这种情况下使用df.sort_index(level=1)的奇怪工作可以解决我的完整数据集（20多列），但我失去了OptionSymbol分组。

Answer 1

IIUC您只需按第二级排序索引：

In [27]: df.sort_index(level=1)
Out[27]:
                                Id  Strike  Expiration OptionType
OptionSymbol QuoteDatetime
YBWNA        2010-02-12     262202    95.0  2010-02-20       call
             2010-02-16     262454    95.0  2010-02-20       call
             2010-02-17     262707    95.0  2010-02-20       call
WWWAX        2012-04-12     262201    90.0  2010-02-20       call
             2012-04-16     262453    90.0  2010-02-20       call
             2012-04-17     262706    90.0  2010-02-20       call
XWNAX        2012-07-12     262201    90.0  2010-02-20       call
             2012-07-16     262453    90.0  2010-02-20       call
             2012-07-17     262706    90.0  2010-02-20       call
ZBYMZ        2013-09-02     234669   170.0  2011-01-22        put
             2013-09-03     234901   170.0  2011-01-22        put
             2013-09-04     235133   170.0  2011-01-22        put

如何通过二级采用MultiIndex DataFrame

使用代码进行编辑以重新创建

1 个答案: