Question

This is the error I am getting.


AttributeError                            Traceback (most recent call last)
<ipython-input-28-913f9c114df8> in <module>
      2 Corpus['text'].dropna(inplace=True)
      3 # Step - b : Change all the text to lower case. This is required as python interprets 'dog' and 'DOG' differently
----> 4 Corpus['text'] = [entry.lower() for entry in Corpus['text']]
      5 # Step - c : Tokenization : In this each entry in the corpus will be broken into set of words
      6 Corpus['text']= [word_tokenize(entry) for entry in Corpus['text']]

<ipython-input-28-913f9c114df8> in <listcomp>(.0)
      2 Corpus['text'].dropna(inplace=True)
      3 # Step - b : Change all the text to lower case. This is required as python interprets 'dog' and 'DOG' differently
----> 4 Corpus['text'] = [entry.lower() for entry in Corpus['text']]
      5 # Step - c : Tokenization : In this each entry in the corpus will be broken into set of words
      6 Corpus['text']= [word_tokenize(entry) for entry in Corpus['text']]

**AttributeError: 'list' object has no attribute 'lower**

这是代码。我尝试在JUPITER笔记本中运行此代码。删除数据中的空白行（如果有）将所有文本更改为小写词标记化删除停用词删除非字母文字单词词法化

# Step - a: Remove blank rows if any.
Corpus['text'].dropna(inplace=True)
# Step - b : Change all the text to lower case. This is required as python interprets 'dog' and 'DOG' differently
Corpus['text'] = [entry.lower() for entry in Corpus['text']]
# Step - c : Tokenization : In this each entry in the corpus will be broken into set of words
Corpus['text']= [word_tokenize(entry) for entry in Corpus['text']]
# Step - d : Remove Stop words, Non-Numeric and perfom Word Stemming/Lemmenting.
# WordNetLemmatizer requires Pos tags to understand if the word is noun or verb or adjective etc. By default it is set to Noun
tag_map = defaultdict(lambda : wn.NOUN)
tag_map['J'] = wn.ADJ
tag_map['V'] = wn.VERB
tag_map['R'] = wn.ADV
for index,entry in enumerate(Corpus['text']):
    # Declaring Empty List to store the words that follow the rules for this step
    Final_words = []
    # Initializing WordNetLemmatizer()
    word_Lemmatized = WordNetLemmatizer()
    # pos_tag function below will provide the 'tag' i.e if the word is Noun(N) or Verb(V) or something else.
    for word, tag in pos_tag(entry):
        # Below condition is to check for Stop words and consider only alphabets
        if word not in stopwords.words('english') and word.isalpha():
            word_Final = word_Lemmatized.lemmatize(word,tag_map[tag[0]])
            Final_words.append(word_Final)
    # The final processed set of words for each iteration will be stored in 'text_final'
    Corpus.loc[index,'text_final'] = str(Final_words)

读取csv数据集和执行数据预处理时遇到问题

0 个答案: