english_features = vectorizer_en.fit_transform(df['English']).toarray() # 向量化中文特征 chinese_features = vectorizer_cn.fit_transform(df['Chinese']).toarray() # 将中英文特征组合起来 combined_features = hstack([english_features, chinese_features]) # 显示组合后的特征 print(combined_features, vectorizer_en.get_feature_names_out(), vectorizer_cn.g...
import nltk from nltk.corpus import stopwords from nltk.tokenize import word_tokenize text = "This is a sample sentence. It contains some words." stop_words = set(stopwords.words('english')) # 停用词列表 word_list = [w.lower() for w in word_tokenize(text) if w.lower() not...
在 word 上使用 .casefold() 可以忽略 word 中字母的大小写。因为 stopwords.words('english') 仅包含...
然后,您将完成两个不同的编程项目:一个存储多个文本字符串的简单剪贴板和一个自动完成格式化文本片段的枯燥工作的程序。 使用字符串 让我们看看 Python 允许你在代码中编写、打印和访问字符串的一些方法。 字符串字面值 用Python 代码键入字符串值相当简单:它们以单引号开始和结束。但是你怎么能在字符串中使用引号呢...
translator= Translator(to_lang="english") translation = translator.translate("数据") print(translation) 1. 2. 3. 4. 输出的结果还是“数据” 1.4 有道在线翻译 Reference: https://pypi.org/project/pytranslator/ 1.4.1 安装软件包
A slightly richer kind of lexical resource is a table (or spreadsheet 电子表格), containing a word plus some properties in each row. NLTK includes the CMU Pronouncing Dictionary for U.S. English, which was designed for use by speech synthesizers. ...
NLTK是由宾夕法尼亚大学计算机和信息科学使用python语言实现的一种自然语言工具包，其收集的大量公开数据...
words = englishtxt.split() counts = {} # 统计单词出现次数 for word in words: counts[word] = counts.get(word, 0 ) + 1 items = list (counts.items()) # 将字典转换为记录列表 items.sort( key = lambda x:x[ 1 ], reverse = true ) #...
for word in udhr.words(lang + '-Latin1')) cfd.plot() #为两种语言和长度少于 10 个字符的词汇绘制累计频率数据表 cfd.tabulate(conditions=['English', 'German_Deutsch'], samples=range(10), cumlative=True) 1. 2. 3. 4. 5. 6.
As an example, we’ll build a dictionary that maps from English to Spanish words, so the keys and the values are all strings. The functiondictcreates a new dictionary with no items. Becausedictis the name of a built-in function, you should avoid using it as a variable name. ...