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Python Natural Language Processing Cookbook

You're reading from   Python Natural Language Processing Cookbook Over 50 recipes to understand, analyze, and generate text for implementing language processing tasks

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Product type Paperback
Published in Mar 2021
Publisher Packt
ISBN-13 9781838987312
Length 284 pages
Edition 1st Edition
Languages
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Author (1):
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Zhenya Antić Zhenya Antić
Author Profile Icon Zhenya Antić
Zhenya Antić
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Toc

Table of Contents (10) Chapters Close

Preface 1. Chapter 1: Learning NLP Basics 2. Chapter 2: Playing with Grammar FREE CHAPTER 3. Chapter 3: Representing Text – Capturing Semantics 4. Chapter 4: Classifying Texts 5. Chapter 5: Getting Started with Information Extraction 6. Chapter 6: Topic Modeling 7. Chapter 7: Building Chatbots 8. Chapter 8: Visualizing Text Data 9. Other Books You May Enjoy

Visualizing parts of speech

As you saw in the Visualizing the dependency parse recipe, parts of speech are included in the dependency parse, so in order to see parts of speech for each word in a sentence, it is enough to do that. In this recipe, we will visualize part of speech counts. We will visualize the counts of past and present tense verbs in the book The Adventures of Sherlock Holmes.

Getting ready

We will use the spacy package for text analysis and the matplotlib package to create the graph. If you don't have matplotlib installed, install it using the following command:

pip install matplotlib

How to do it…

We will create a function that will count the number of verbs by tense and plot each on a bar graph:

  1. Import the necessary packages:
    import spacy
    import matplotlib.pyplot as plt
    from Chapter01.dividing_into_sentences import read_text_file
  2. Load the spacy engine and define the past and present tag sets:
    nlp = spacy.load("en_core_web_sm...
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