To quickly analyze text, including determining its sentiment, tokenization, noun phrase and word frequency analysis, and spelling correction, use TextBlob.

To use TextBlob, start with creating a new instance of the TextBlob class with the text “Today is a beautiful day”.

from textblob import TextBlob

text = "Today is a beautiful day"
blob = TextBlob(text)

Tokenize words:

blob.words

WordList(['Today', 'is', 'a', 'beautiful', 'day'])

Extract noun phrases:

blob.noun_phrases

WordList(['beautiful day'])

Analyze sentiment:

blob.sentiment

Sentiment(polarity=0.85, subjectivity=1.0)

Count words:

blob.word_counts

defaultdict(int, {'today': 1, 'is': 1, 'a': 1, 'beautiful': 1, 'day': 1})

Correct spelling:

text = "Today is a beutiful day"
blob = TextBlob(text)
blob.correct()

TextBlob("Today is a beautiful day")

Link to TextBlob.

Run in Google Colab.