import spacy, en_core_web_sm
nlp = en_core_web_sm.load()
doc = nlp(u"I will go to the mall")
chk_set = set(['VERB'])
print chk_set.issubset(t.pos_ for t in doc)
上面的代码返回True if POS = verb
存在。
现在我想扩展此代码以读取存储在Excel工作表中的句子列表。为了检查句子中是否存在标点符号,我可以使用下面的代码实现它。
问题是如何扩展下面的代码以包含上面的动词检查。
from pandas import read_excel
import pandas as pd
import xlsxwriter
my_sheet_name = 'Metrics'
df = read_excel('sentence.xlsx', sheet_name = my_sheet_name)
df['.']=df['Sentence'].str.contains('.')
# df['VERB']=df['Sentence'].str.contains('.')
writer = pd.ExcelWriter('sentence.xlsx', engine='xlsxwriter')
df.to_excel(writer, sheet_name='Metrics')
writer.save()
预期结果:
Sentence Verb
I will go to the mall True
the mall False
I may be here tomorrow. True
您可以使用NLTK
执行以下操作:
import nltk
import pandas as pd
df = pd.DataFrame({'sent': ['I will go to the mall', 'the mall', 'I may be here tomorrow.']})
def tag_verb(sent):
words = nltk.word_tokenize(sent)
tags = nltk.pos_tag(words)
for t in tags:
if t[1] == 'VB':
return True
return False
df['verb'] = df['sent'].apply(lambda x: tag_verb(x))
输出:
sent verb
0 I will go to the mall True
1 the mall False
2 I may be here tomorrow. True