比较两个 pandas 列并从第 2 列中删除第 1 列中出现的标记

Question

我正在尝试比较 pandas 数据框中的两列。我想要的是从正文中删除用户名

raw_data = {
'user_name': ['name1 name2', 'nameX nameY '],
'text_body': ['this is the text were i should delete name1 and name2', 
'this is the text were i should delete nameX and nameY']}
df_a = pd.DataFrame(raw_data, columns = ['user_name', 'text_body'])
df_a

我将两个 pd 列分隔为标记，以遍历我应该删除单词的第二列。

def sent_to_words(sentences):
    # function to transforms a sentence into tokens
    tokens = [nltk.word_tokenize(sent) for sent in sentences]
    return tokens

def remover_user_name(text_body,user_name): 
    #sent_to_words is a function that transforms the raw data into small tokens 
    user_name_token = sent_to_words(user_name)
    for row in dataset.itertuples(index=True, name='Pandas'):
        for user in user_name_token:
            dataset['user_clean'] = data.apply(lambda x: data.str.strip(user) for user in user_name_token)
    return dataset['user_clean'].tolist()



data = dataset['Textemsg'].apply(lambda x: clean_data(x))
user_name = to_lower(dataset['user_name'])
dataaa = remover_user_name(data,user_name)
print(dataaa)

这是我得到的错误：

---

TypeError                                 Traceback (most recent call last)
<ipython-input-104-9b39af043e09> in <module>()
      1 data = dataset['Textemsg'].apply(lambda x: clean_data(x))
      2 user_name = to_lower(dataset['user_name'])
----> 3 dataaa = remover_user_name(data,user_name)
      4 print(dataaa)

<ipython-input-103-0a5a8bce7b52> in remover_user_name(data, user_name)
      3     for row in dataset.itertuples(index=True, name='Pandas'):
      4         for user in user_name_token:
----> 5             dataset['user_clean'] = data.apply(lambda x: data.str.strip(user) for user in user_name_token)
      6     return dataset['user_clean'].tolist()

/opt/conda/lib/python3.6/site-packages/pandas/core/series.py in apply(self, func, convert_dtype, args, **kwds)
   3192             else:
   3193                 values = self.astype(object).values
-> 3194                 mapped = lib.map_infer(values, f, convert=convert_dtype)
   3195 
   3196         if len(mapped) and isinstance(mapped[0], Series):

pandas/_libs/src/inference.pyx in pandas._libs.lib.map_infer()

TypeError: 'generator' object is not callable

Answer 1

在这里，我删除了 text_body 中的所有单词，而该单词在 user_name 中。

def remove_words_from_text_body(row):
    # Seperate the words to remove by the space between them
    words_to_remove = row['user_name'].split(" ")

    # Get the text_body as a starting template
    text_body = row['text_body']

    # For each word that we want to remove, replace it with "" (blank)
    for word in words_to_remove:
        text_body = text_body.replace(word, "")

    return text_body

所以当你运行时：
df_a['cleaned_text'] = df_a.apply(remove_words_from_text_body, axis=1)

你会得到：

      user_name                                          text_body                                 cleaned_text
0   name1 name2  this is the text were i should delete name1 an...  this is the text were i should delete  and 
1  nameX nameY   this is the text were i should delete nameX an...  this is the text were i should delete  and