创建由单词对组成的元组

Question

我有一个字符串（或单词列表）。我想创建每个可能的单词对组合的元组，以便将它们传递给 Counter 以进行字典创建和频率计算。频率按以下方式计算：如果该对存在于一个字符串中（无论顺序如何，或者它们之间是否有任何其他单词），频率 = 1（即使 word1 的频率为 7，word2 的频率为 3）一对 word1 和 word2 仍然是 1)

我正在使用循环创建所有对的元组但卡住了

tweetList = ('I went to work but got delayed at other work and got stuck in a traffic and I went to drink some coffee but got no money and asked for money from work', 'We went to get our car but the car was not ready. We tried to expedite our car but were told it is not ready')

words = set(tweetList.split())
n = 10
for tweet in tweetList:

    for word1 in words:
        for word2 in words:
            pairW = [(word1, word2)]

            c1 = Counter(pairW for pairW in tweet)

c1.most_common(n)

但是，输出很奇怪：

[('k', 1)]

它似乎不是单词而是迭代字母

如何解决这个问题？使用 split() 将字符串转换为单词列表？

另一个问题：如何避免创建重复的元组，例如：（word1，word2）和（word2，word1）？枚举？

作为输出，我希望有一个字典，其中键 = 所有单词对（但请参阅重复的注释），值 = 列表中一对的频率

谢谢！

Answer 1

我想知道这是不是你想要的：

import itertools, collections

tweets = ['I went to work but got delayed at other work and got stuck in a traffic and I went to drink some coffee but got no money and asked for money from work',
          'We went to get our car but the car was not ready. We tried to expedite our car but were told it is not ready']

words = set(word.lower() for tweet in tweets for word in tweet.split())
_pairs = list(itertools.permutations(words, 2))
# We need to clean up similar pairs: sort words in each pair and then convert
# them to tuple so we can convert whole list into set.
pairs = set(map(tuple, map(sorted, _pairs)))

c = collections.Counter()

for tweet in tweets:
    for pair in pairs:
        if pair[0] in tweet and pair[1] in tweet:
            c.update({pair: 1})

print c.most_common(10)

结果是：[(('a', 'went'), 2), (('a', 'the'), 2), (('but', 'i'), 2), (('i', 'the'), 2), (('but', 'the'), 2), (('a', 'i'), 2), (('a', 'we'), 2), (('but', 'we'), 2), (('no', 'went'), 2), (('but', 'went'), 2)]

Answer 2

tweet 是一个字符串，因此Counter(pairW for pairW in tweet) 将计算tweet 中字母的频率，这可能不是您想要的。