在 Python 中计算单词

本文介绍了在 Python 中计算单词的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述

我在 python 中有一个字符串列表.

I have a list of strings in python.

list = [ "Sentence1.Sentence2...", "Sentence1.Sentence2...",...]

我想删除停用词并计算所有不同字符串组合的每个词的出现次数.有什么简单的方法吗?

I want to remove stop words and count occurrence of each word of all different strings combined. Is there a simple way to do it?

我目前正在考虑使用 scikit 中的 CountVectorizer()，而不是对每个单词进行迭代并组合结果

I am currently thinking of using CountVectorizer() from scikit and than iterating for each word and combining the results

推荐答案

如果你不介意安装一个新的 python 库，我建议你使用 gensim.第一个教程完全符合您的要求:

If you don't mind installing a new python library, I suggest you use gensim. The first tutorial does exactly what you ask:

# remove common words and tokenize stoplist = set('for a of the and to in'.split()) texts = [[word for word in document.lower().split() if word not in stoplist] for document in documents]

然后您需要为您的文档语料库创建字典并创建词袋.

You will then need to create the dictionary for your corpus of document and create the bag-of-words.

dictionary = corpora.Dictionary(texts) dictionary.save('/tmp/deerwester.dict') # store the dictionary, for future print(dictionary)

您可以使用 tf-idf 和其他东西对结果进行加权，然后很容易地进行 LDA.

You can weight the result using tf-idf and stuff and do LDA quite easily after.

查看教程 1 此处