NOTE: Before running this notebook, place a copy of your downloaded RomeoAndJuliet.txt file in the same folder with this notebook.

## 12.2.11 Word Frequencies¶

- Various techniques for detecting similarity between documents rely on word frequencies
- `TextBlob` can count word frequencies for you
- When you read a file with `Path`’s `read_text` method, it closes the file immediately after it finishes reading the file

In [1]:

    from pathlib import Path

In [2]:

    from textblob import TextBlob

In [3]:

    blob = TextBlob(Path('RomeoAndJuliet.txt').read_text())

- Access the word frequencies through the `TextBlob`’s `word_counts` dictionary

In [4]:

    blob.word_counts['juliet']

Out[4]:

    190

In [5]:

    blob.word_counts['romeo']

Out[5]:

    315

In [6]:

    blob.word_counts['thou']

Out[6]:

    278

- If you already have tokenized a `TextBlob` into a `WordList`, you can count specific words in the list via the `count` method

In [7]:

    blob.words.count('joy')

Out[7]:

    14

In [8]:

    blob.noun_phrases.count('lady capulet')

Out[8]:

    46

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