一列内唯一对的数量- pandas [英] Number of unique pairs within one column - pandas

问题描述

在为我的熊猫数据框生成统计信息时，我遇到了一些问题.我的数据框如下所示(我省略了索引):

I am having a little problem with producing statistics for my dataframe in pandas. My dataframe looks like this (I omit the index):

id    type  
1      A
2      B
3      A
1      B
3      B
2      C
4      B
4      C

重要的是，每个id都分配了两个type值，如上例所示.我想计算所有type组合的出现次数(因此，用给定的type组合来计算唯一id的数量)，所以我想获得这样的数据框:

What is important, each id has two type values assigned, as can be seen from the example above. I want to count all type combinations occurrences (so count number of unique id with given type combination), so I want to get such a dataframe:

type    count
A, B      2
A, C      0
B, C      2

我尝试了多种方式使用groupby，但徒劳无功.我可以使用for-loop和许多行代码来进行这种计数"，但是我认为必须有一个优雅且适当的解决方案(以python术语).

I tried using groupby in many ways, but in vain. I can do this kind of 'count' using for-loop and a number of lines of code, but I believe there has to be elegant and proper (in python terms) solution to this problem.

预先感谢您的提示.

推荐答案

将GroupBy + apply与value_counts一起使用:

from itertools import combinations

def combs(types):
    return pd.Series(list(combinations(sorted(types), 2)))

res = df.groupby('id')['type'].apply(combs).value_counts()

print(res)

(A, B)    2
(B, C)    2
Name: type, dtype: int64

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