sentences=sentences.replace(',','') sentences=sentences.replace('.','')# 将句子里面的.去掉 sentences=sentences.split()# 将句子分开为单个的单词,分开后产生的是一个列表sentences # print(sentences) count_dict={} forsentenceinsentences: ifsentencenotincount_dict:# 判断是否不在统计的字典中 count_...
string = "Apple, Banana, Orange, Blueberry" print(string.split()) Output: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 ['Apple,', 'Banana,', 'Orange,', 'Blueberry'] 我们可以看到字符串没有很好地拆分,因为拆分的字符串包含 ,。我们可以使用 sep=',' 在有, 的地方进行拆分: 代码语...
Notice that this example is really a single sentence, reporting the speech of Mr. Lucian Gregory. However, the quoted speech contains several sentences, and these have been split into individual strings. This is reasonable behavior for most applications. Sentence segmentation is difficult because a ...
lines.append(line)print(" %i lines read from'%s' with size: %5.2f kb"%(len(lines),t,sys.getsizeof(lines)/1024.))# Constructa big stringofclean text text=" ".join(lineforlineinlines)# splitonsentences(period+space)delim=". "sentences=[_+delimfor_intext.split(delim)]#regexes are th...
split -> string -- 文档的词之间的分隔符 max_df -> integer -- 避免常用词,过滤超过该阈值的词 """ # 存放所有语料集信息 corpus = [] with open(tokenized_corpus_path, 'r', encoding='utf-8') as tokenized_corpus: flag = 0 for document in tokenized_corpus: ...
import string import random class Myclass: def __init__(self): self.a = seg.Segment() def tokenizer(self,allLines): b = self.a.process_paragraph(allLines,0,0) words = b.split() self.first = self.find_firstword_dict(words)
nlp=stanfordnlp.Pipeline()doc=nlp("Barack Obama was born in Hawaii.")forsentenceindoc.sentences:print(sentence.dependencies_string())# 打印依存关系 1. 2. 3. 4. 5. 6. 7. 解释: 这段代码展示了如何使用Stanford CoreNLP进行依存句法分析,输出句子内部词语之间的依存关系。
for sentence in doc.sentences: print(sentence.dependencies_string()) # 打印依存关系 解释: 这段代码展示了如何使用Stanford CoreNLP进行依存句法分析,输出句子内部词语之间的依存关系。 6. PyTorch Text 如果你对深度学习感兴趣,那么PyTorch Text绝对值得一试。它是基于PyTorch构建的,专为文本数据设计,可以方便地...
print(res['quiz']['sport']) # Dump data as string data = json.dumps(res) print(data) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 5读取 CSV 数据 import csv with open('test.csv','r') as csv_file: reader =csv.reader(csv_file) next(reader) # Skip first row for row ...
First 5 sentences in alice :- ["[Alice's Adventures in Wonderland by Lewis Carroll 1865]\n\nCHAPTER I.", "Down the Rabbit-Hole\n\nAlice was beginning to get very tired of sitting by her sister on the\nbank, and of having nothing to do: once or twice she had peeped into the\n...