返回pandas单元格中每个单词的列表以及该单词在整个列中的总数

Question

我有一个pandas数据框，df，如下所示：

             column1
0   apple is a fruit
1        fruit sucks
2  apple tasty fruit
3   fruits what else
4      yup apple map
5   fire in the hole
6       that is true

我想生成一个column2，它是行中每个单词的列表以及整个列中每个单词的总数。所以输出应该是这样的。。。。在

^{pr2}$

我尝试使用sklearn，但未能达到上述目的。需要帮助。在

from sklearn.feature_extraction.text import CountVectorizer
v = CountVectorizer()
x = v.fit_transform(df['text'])

Answer 1

以下是一种给出您想要的结果的方法，尽管它完全避免了sklearn：

def counts(data, column):
    full_list = []
    datr = data[column].tolist()
    total_words = " ".join(datr).split(' ')
    # per rows
    for i in range(len(datr)):
        #first per row get the words
        word_list = re.sub("[^\w]", " ",  datr[i]).split()
        #cycle per word
        total_row = []
        for word in word_list:
            count = []
            count = total_words.count(word)
            val = (word, count)
            total_row.append(val)
        full_list.append(total_row)
    return full_list

df['column2'] = counts(df,'column1')
df
         column1                                    column2
0   apple is a fruit  [(apple, 3), (is, 2), (a, 1), (fruit, 3)]
1        fruit sucks                   [(fruit, 3), (sucks, 1)]
2  apple tasty fruit       [(apple, 3), (tasty, 1), (fruit, 3)]
3   fruits what else        [(fruits, 1), (what, 1), (else, 1)]
4      yup apple map           [(yup, 1), (apple, 3), (map, 1)]
5   fire in the hole  [(fire, 1), (in, 1), (the, 1), (hole, 1)]
6       that is true            [(that, 1), (is, 2), (true, 1)]