在与另一列Pandas中的唯一值相关联的列中查找值的交集 [英] Finding intersection of values in a column associated with unique values in another column Pandas

问题描述

如果我有一个像这样的DataFrame(非常简单的例子)

If I have a DataFrame like this (very minimal example)

  col1  col2
0    a     1
1    a     2
2    b     1
3    b     2
4    b     4
5    c     1
6    c     2
7    c     3

并且我想要所有col2值与其唯一的col1值相关的交集(因此，在这种情况下，交集为[1,2])，我该如何使用Pandas?另一种表达方式是col2中的值，该值对于col1中的每个唯一值都存在.

and I want the intersection of all col2 values when they are related to their unique col1 values (so in this case, the intersection would be [1,2]), how can I do so with Pandas? Another way to word this would be the values in col2 that exist for every unique value in col1.

我的( bad )解决方案是用unique获取唯一的col1元素，然后从col1中的每个唯一元素构建字典，然后采用这些字典的集合交集价值观.我觉得我应该使用一种机制将列关联在一起，但是这可以使这容易得多.

My (bad) solution was to get the unique col1 elements with unique, and then build dictionaries from each unique element in col1 and then take the set intersection of those dictionary values. I feel like there is a mechanism I should be using to relate the columns together however that could make this much easier.

推荐答案

一种方法是使用

One way is to use pivot_table:

In [11]: cross = df.pivot_table(index="col1", columns="col2", aggfunc='size') == 1

In [12]: cross
Out[12]:
col2     1     2      3      4
col1
a     True  True  False  False
b     True  True  False   True
c     True  True   True  False

In [13]: cross.all()
Out[13]:
col2
1     True
2     True
3    False
4    False
dtype: bool

In [14]: cross.columns[cross.all()]
Out[14]: Int64Index([1, 2], dtype='int64', name='col2')

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