在 Pandas 数据框中通过多索引选择（子集）
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Selecting (subsetting) by multi index in pandas dataframe
提问by user3576212
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干净的方法可以基于多索引选择或子集 Pandas 数据帧。我的数据是这样的（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，而不是数据帧的子集。我也试过df.query()and df.ix()，但没有运气。
Thanks for your help!
谢谢你的帮助！
回答by Karl D.
You should be able to use .xsor .ixin 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
See herefor more information
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