python - 从Python的句子集中删除最常用词中的停用词

我在np.array中有5个句子，我想找到最常见的n个单词。例如，如果n=5我想要5个最常用的词。我有一个例子如下：

0    rt my mother be on school amp race
1    rt i am a red hair down and its a great
2    rt my for your every day and my chocolate
3    rt i am that red human being a man
4    rt my mother be on school and wear

以下是我用来获取最常见的n个单词的代码。

import numpy as np
from sklearn.feature_extraction.text import CountVectorizer

A = np.array(["rt my mother be on school amp race",
              "rt i am a red hair down and its a great",
              "rt my for your every day and my chocolate",
              "rt i am that red human being a man",
              "rt my mother be on school and wear"])

        n = 5
        vectorizer = CountVectorizer()
        X = vectorizer.fit_transform(A)

        vocabulary = vectorizer.get_feature_names()
        ind = np.argsort(X.toarray().sum(axis=0))[-n:]

        top_n_words = [vocabulary[a] for a in ind]

        print(top_n_words)

结果如下：

['school', 'am', 'and', 'my', 'rt']

但是，我想要的是从这些最常见的词中忽略停用词，例如'and'，'am'and'my'。我该怎么做？

最佳答案

您只需要在stop_words='english'中包含参数CountVectorizer()

vectorizer = CountVectorizer(stop_words='english')

您现在应该获得：

['wear', 'mother', 'red', 'school', 'rt']

请参阅此处的文档：https://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html

关于python - 从Python的句子集中删除最常用词中的停用词，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/57073029/