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Python Web Scraping Cookbook

You're reading from   Python Web Scraping Cookbook Over 90 proven recipes to get you scraping with Python, microservices, Docker, and AWS

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781787285217
Length 364 pages
Edition 1st Edition
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Author (1):
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Michael Heydt Michael Heydt
Author Profile Icon Michael Heydt
Michael Heydt
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Table of Contents (13) Chapters Close

Preface 1. Getting Started with Scraping 2. Data Acquisition and Extraction FREE CHAPTER 3. Processing Data 4. Working with Images, Audio, and other Assets 5. Scraping - Code of Conduct 6. Scraping Challenges and Solutions 7. Text Wrangling and Analysis 8. Searching, Mining and Visualizing Data 9. Creating a Simple Data API 10. Creating Scraper Microservices with Docker 11. Making the Scraper as a Service Real 12. Other Books You May Enjoy

Calculating the frequency distributions of words

A frequency distribution counts the number of occurrences of distinct data values. These are of value as we can use them to determine which words or phrases within a document are most common, and from that infer those that have greater or lesser value.

Frequency distributions can be calculated using several different techniques. We will examine them using the facilities built into NLTK.

How to do it

NLTK provides a class, ntlk.probabilities.FreqDist, that allow us to very easily calculate the frequency distribution of values in a list. Let's examine using this class (code is in 07/freq_dist.py):

  1. To create a frequency distribution using NLTK, start by importing the...
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