我是 Python 新手，在使用 Pandas 創(chuàng)建的數(shù)據(jù)幀上使用 SciLearn Kit 時遇到問題。下面是代碼：import numpy as npimport pandas as pdimport seaborn as snsimport matplotlib as pltimport json%matplotlib inlinedata = pd.read_json('C:/Users/Desktop/Machine Learning/yelp_academic_dataset_business.json', lines=True, orient='columns', encoding='utf-8')dataframe = pd.DataFrame(data)list(dataframe)subset_data = dataframe.loc[(dataframe.city == 'Toronto')]print(subset_data)documents = subset_data.to_dict('records')from sklearn.feature_extraction.text import TfidfVectorizer, CountVectorizerno_features = 1000# NMF is able to use tf-idftfidf_vectorizer = TfidfVectorizer(max_df=0.95, min_df=2, max_features=no_features, stop_words='english')tfidf = tfidf_vectorizer.fit_transform(documents)tfidf_feature_names = tfidf_vectorizer.get_feature_names()# LDA can only use raw term counts for LDA because it is a probabilistic graphical modeltf_vectorizer = CountVectorizer(max_df=0.95, min_df=2, max_features=no_features, stop_words='english')tf = tf_vectorizer.fit_transform(documents)tf_feature_names = tf_vectorizer.get_feature_names()下面是我得到的錯誤。AttributeError: 'dict' object has no attribute 'lower'數(shù)據(jù)集可在此處獲得：kaggle.com/yelp-dataset/yelp-dataset 數(shù)據(jù)集：yelp_academic_dataset_business.json任何幫助將不勝感激。謝謝你。