How to use NLP with TextBlob?
TextBlob is a Python library for processing textual data. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more.
Code sample
# import nltk
# nltk.download('punkt')
# https://stackoverflow.com/questions/13965823/resource-corpora-wordnet-not-found-on-heroku
from textblob import TextBlob
text = "Today is a beautiful day"
blob = TextBlob(text)
# Word tokenization
blob.words
"""WordList(['Today', 'is', 'a', 'beautiful', 'day'])"""
# Noun phrase extraction
blob.noun_phrases
"""WordList(['beautiful day'])"""
# sentiment analysis
blob.sentiment
"""Sentiment(polarity=0.85, subjectivity=1.0)"""
# word counts
blob.word_counts
"""defaultdict(int, {'today': 1, 'is': 1, 'a': 1, 'beautiful': 1, 'day': 1})"""
# Spelling corection
text = "Today is a beutiful day"
blob = TextBlob(text)
blob.correct()
"""TextBlob("Today is a beautiful day")"""
