AttributeError：'WordList‘对象没有属性’拆分‘

Question

在标记我的“脚本”列之后，我尝试应用Lemmatization。但我得到了一个AttributeError。我尝试了不同的方法

这是我的“脚本”专栏：

df_toklem["script"][0:5]
---------------------------------------------------------------------------
type(df_toklem["script"])

输出：

id
1    [ext, street, day, ups, man, big, pot, belly, ...
2    [credits, still, life, tableaus, lawford, n, h...
3    [fade, ext, convent, day, whispering, nuns, pr...
4    [fade, int, c, hercules, turbo, prop, night, e...
5    [open, theme, jaws, plane, busts, clouds, like...
Name: script, dtype: object
---------------------------------------------------------------------------
pandas.core.series.Series

以及我试图应用Lemmatization的代码：

from textblob import Word
nltk.download("wordnet")
df_toklem["script"].apply(lambda x: " ".join([Word(word).lemmatize() for word in x.split()]))

错误：

[nltk_data] Downloading package wordnet to
[nltk_data]     C:\Users\PC\AppData\Roaming\nltk_data...
[nltk_data]   Package wordnet is already up-to-date!
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-72-dbc80c619ec5> in <module>
      1 from textblob import Word
      2 nltk.download("wordnet")
----> 3 df_toklem["script"].apply(lambda x: " ".join([Word(word).lemmatize() for word in x.split()]))

~\Anaconda3\lib\site-packages\pandas\core\series.py in apply(self, func, convert_dtype, args, **kwds)
   4198             else:
   4199                 values = self.astype(object)._values
-> 4200                 mapped = lib.map_infer(values, f, convert=convert_dtype)
   4201 
   4202         if len(mapped) and isinstance(mapped[0], Series):

pandas\_libs\lib.pyx in pandas._libs.lib.map_infer()

<ipython-input-72-dbc80c619ec5> in <lambda>(x)
      1 from textblob import Word
      2 nltk.download("wordnet")
----> 3 df_toklem["script"].apply(lambda x: " ".join([Word(word).lemmatize() for word in x.split()]))

AttributeError: 'WordList' object has no attribute 'split'

我尝试了不同的方法，但不幸的是没有找到一个有效的解决方案。谢谢您抽时间见我。

Answer 1

您要做的工作将无法工作，因为您正在将字符串函数(拆分)应用到一个单词列表中。我会尝试使用nltk，然后用我的标记化数据创建一个新的熊猫列：

import nltk
df_toklem['tokenized'] = df_toklem.apply(lambda row: nltk.word_tokenize(row['script']))