如何将一列中的一条字符串分成两条字符串熊猫

Question

我有两个字符串数据，每个数据都被命名为数据集和口语。

数据口语表：

|**wrong**  | **correct** |    
|sheis      | she is      |    
|taht       | that        |    
|diedwhen   | died when   |    

第二个dataframe是具有特定列的dataset，我使用的列如下所示：

数据集“‘review”：

review    
[shewas, wrong, but, her, intentions, are, good]     
[is, taht, you]     
[he, diedwhen, he, was, young]    

我想要改变数据集‘’review‘中的错误单词为正确的单词根据数据口语。我用这个：

normalizad_word = pd.read_excel("colloquial.xlsx")    

normalizad_word_dict = {}    

for index, row in normalizad_word.iterrows():    
    if row[0] not in normalizad_word_dict:    
        normalizad_word_dict[row[0]] = row[1]     

def normalized_term(document):    
    return [normalizad_word_dict[term] if term in normalizad_word_dict else term for term in document]     

dataset['review_normalized'] = dataset['review'].apply(normalized_term)     

dataset['review_normalized']    

但结果是：

review_normalized    
[she was, wrong, but, her, intentions, are, good]    
[is, that, you]    
[he, died when, he, was, young]    

我想要这样：

review_normalized    
[she, was, wrong, but, her, intentions, are, good]    
[is, that, you]    
[he, died, when, he, was, young]    

Answer 1

更改normalized_term函数：

def normalized_term(document):
    result = []
    for term in document:
        if term in normalizad_word_dict:
            for word in normalizad_word_dict[term].split(' '):
                result.append(word)
        else:
            result.append(term)
    return result

或者如果您想使用内联循环：

import itertools    
def normalized_term(document):
    return list(itertools.chain(*[normalizad_word_dict[term].split() if term in normalizad_word_dict else term.split() for term in document]))