属性错误："单词列表"对象没有属性"拆分"

Question

在标记化我的"；脚本"；柱但是我得到一个AttributeError。我尝试了不同的

这是我的"；脚本"；列：

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

以及我尝试应用引理的代码：

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:UsersPCAppDataRoamingnltk_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()]))
~Anaconda3libsite-packagespandascoreseries.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_libslib.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，但不幸的是找不到有效的解决方案。谢谢你抽出时间。

Answer 1

您尝试执行的操作将不起作用，因为您正在将字符串函数(split(应用于单词列表。我会尝试使用nltk，并用我的标记化数据创建一个新的panda列：

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