来自嵌套单词列表的共现矩阵 [英] Co-occurrence matrix from nested list of words

问题描述

我有一个名字列表，例如:

I have a list of names like:

names = ['A', 'B', 'C', 'D']

和一个文件列表，在每个文件中都提到了其中的一些名称.

and a list of documents, that in each documents some of these names are mentioned.

document =[['A', 'B'], ['C', 'B', 'K'],['A', 'B', 'C', 'D', 'Z']]

我想得到一个作为共现矩阵的输出，例如:

I would like to get an output as a matrix of co-occurrences like:

  A  B  C  D
A 0  2  1  1
B 2  0  2  1
C 1  2  0  1
D 1  1  1  0

在 R 中有一个解决方案(Creating co-occurrence matrix)，但我不能在 Python 中做到这一点.我想在 Pandas 上做，但没有进展！

There is a solution (Creating co-occurrence matrix) for this problem in R, but I couldn't do it in Python. I am thinking of doing it in Pandas, but yet no progress!

推荐答案

很明显，这可以根据您的目的进行扩展，但它执行的是一般操作:

Obviously this can be extended for your purposes, but it performs the general operation in mind:

import math

for a in 'ABCD':
    for b in 'ABCD':
        count = 0

        for x in document:
            if a != b:
                if a in x and b in x:
                    count += 1

            else:
                n = x.count(a)
                if n >= 2:
                    count += math.factorial(n)/math.factorial(n - 2)/2

        print '{} x {} = {}'.format(a, b, count)

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