Python 对熊猫系列中的多索引级别求和
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Summing over a multiindex level in a pandas series
提问by dylkot
Using the Pandas package in python, I would like to sum (marginalize) over one level in a series with a 3-level multiindex to produce a series with a 2 level multiindex. For example, if I have the following:
在 python 中使用 Pandas 包，我想对具有 3 级多索引的系列中的一个级别求和（边缘化）以生成具有 2 级多索引的系列。例如，如果我有以下内容：
ind = [tuple(x) for x in ['ABC', 'ABc', 'AbC', 'Abc', 'aBC', 'aBc', 'abC', 'abc']]
mi = pd.MultiIndex.from_tuples(ind)
data = pd.Series([264, 13, 29, 8, 152, 7, 15, 1], index=mi)
A B C 264
c 13
b C 29
c 8
a B C 152
c 7
b C 15
c 1
I would like to sum over the variable C to produce the following output:
我想对变量 C 求和以产生以下输出：
A B 277
b 37
a B 159
b 16
What is the best way in Pandas to do this?
Pandas 中执行此操作的最佳方法是什么？
采纳答案by chrisaycock
If you know you always want to aggregate over the first two levels, then this is pretty easy:
如果你知道你总是想聚合前两个级别，那么这很容易：
In [27]: data.groupby(level=[0, 1]).sum()
Out[27]:
A B 277
b 37
a B 159
b 16
dtype: int64
