在pandas数据帧中通过多索引选择（子集化）

I was wondering if there is a clean way of selecting or subsetting a Pandas dataframe based on multi index. My data looks like this (id and date are index):

我想知道是否有一种基于多索引选择或子集Pandas数据帧的简洁方法。我的数据看起来像这样(id和date是索引):

                        values                  
id     date
10113  2010-07-21      24.7000
       2010-07-22      25.2600  
       2010-07-23      25.2800  
       2010-07-26      25.3700 
       2010-07-27      25.2900 
10223  2011-07-21      24.7000
       2011-07-22      25.2600  
       2011-07-23      25.2800  
       2011-07-26      25.3700 
       2011-07-27      25.2900

I want something like this:

我想要这样的东西:

df.xs[10223).xs('2011-07-21':'2011-07-30')

but above code doesn't work for the second xs(). xs() can only select a single row, not a subset of dataframe. I also tried df.query() and df.ix(), but no luck.

但上面的代码不适用于第二个xs()。 xs()只能选择一行,而不能选择数据帧的子集。我也试过df.query()和df.ix(),但没有运气。

Thanks for your help!

谢谢你的帮助!

1 个解决方案

#1

You should be able to use .xs or .ix in the following way:

您应该能够以下列方式使用.xs或.ix:

print df.ix[(10223,'2011-07-21'):(10223,'2011-07-30')]

                 values
id    date              
10223 2011-07-21   24.70
      2011-07-22   25.26
      2011-07-23   25.28
      2011-07-26   25.37
      2011-07-27   25.29

print df.xs(10223,level='id')

            values
date              
2011-07-21   24.70
2011-07-22   25.26
2011-07-23   25.28
2011-07-26   25.37
2011-07-27   25.29

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#1