I'm working on a text-mining use case in python. These are the sentences of interest:
As a result may continue to be adversely impacted, by fluctuations in foreign currency exchange rates. Certain events such as the threat of additional tariffs on imported consumer goods from China, have increased. Stores are primarily located in shopping malls and other shopping centers.
How can I extract the sentence with the keyword "China"? I do need a sentence before and after that, actually atleast two sentences before and after.
I've tried the below, as was answered here:
import nltk
from nltk.tokenize import word_tokenize
sents = nltk.sent_tokenize(text)
my_sentences = [sent for sent in sents if 'China' in word_tokenize(sent)]
Please help!
Use sent_tokenize, keep track of the index where the focus word and window the sentences to get the desired result.
from itertools import chain
from nltk import sent_tokenize, word_tokenize
from nltk.tokenize.treebank import TreebankWordDetokenizer
word_detokenize = TreebankWordDetokenizer().detokenize
text = """As a result may continue to be adversely impacted, by fluctuations in foreign currency exchange rates. Certain events such as the threat of additional tariffs on imported consumer goods from China, have increased global economic and political uncertainty and caused volatility in foreign currency exchange rates. Stores are primarily located in shopping malls and other shopping centers, certain of which have been experiencing declines in customer traffic."""
tokenized_text = [word_tokenize(sent) for sent in sent_tokenize(text)]
sent_idx_with_china = [idx for idx, sent in enumerate(tokenized_text)
if 'China' in sent or 'china' in sent]
window = 2 # If you want 2 sentences before and after.
for idx in sent_idx_with_china:
start = max(idx - window, 0)
end = min(idx+window, len(tokenized_text))
result = ' '.join(word_detokenize(sent) for sent in tokenized_text[start:end])
print(result)
Another example, pip install wikipedia first:
from itertools import chain
from nltk import sent_tokenize, word_tokenize
from nltk.tokenize.treebank import TreebankWordDetokenizer
word_detokenize = TreebankWordDetokenizer().detokenize
import wikipedia
text = wikipedia.page("Winnie The Pooh").content
tokenized_text = [word_tokenize(sent) for sent in sent_tokenize(text)]
sent_idx_with_china = [idx for idx, sent in enumerate(tokenized_text)
if 'China' in sent or 'china' in sent]
window = 2 # If you want 2 sentences before and after.
for idx in sent_idx_with_china:
start = max(idx - window, 0)
end = min(idx+window, len(tokenized_text))
result = ' '.join(word_detokenize(sent) for sent in tokenized_text[start:end])
print(result)
print()
[out]:
Ashdown Forest in England where the Pooh stories are set is a popular tourist attraction, and includes the wooden Pooh Bridge where Pooh and Piglet invented Poohsticks. The Oxford University Winnie the Pooh Society was founded by undergraduates in 1982. == Censorship in China == In the People's Republic of China, images of Pooh were censored in mid-2017 from social media websites, when internet memes comparing Chinese president Xi Jinping to Pooh became popular. The 2018 film Christopher Robin was also denied a Chinese release.