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You're reading from  Python Web Scraping Cookbook

Product typeBook
Published inFeb 2018
Reading LevelBeginner
PublisherPackt
ISBN-139781787285217
Edition1st Edition
Languages
Python
Tools
Scrapy
Concepts
Data Mining
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Michael Heydt
Michael Heydt
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Michael Heydt

Michael Heydt is an independent consultant, programmer, educator, and trainer. He has a passion for learning and sharing his knowledge of new technologies. Michael has worked in multiple industry verticals, including media, finance, energy, and healthcare. Over the last decade, he worked extensively with web, cloud, and mobile technologies and managed user experiences, interface design, and data visualization for major consulting firms and their clients. Michael's current company, Seamless Thingies , focuses on IoT development and connecting everything with everything. Michael is the author of numerous articles, papers, and books, such as D3.js By Example, Instant Lucene. NET, Learning Pandas, and Mastering Pandas for Finance, all by Packt. Michael is also a frequent speaker at .NET user groups and various mobile, cloud, and IoT conferences and delivers webinars on advanced technologies.
Read more about Michael Heydt

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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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Python Web Scraping Cookbook
Published in: Feb 2018Publisher: PacktISBN-13: 9781787285217
© 2018 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Michael Heydt

Michael Heydt is an independent consultant, programmer, educator, and trainer. He has a passion for learning and sharing his knowledge of new technologies. Michael has worked in multiple industry verticals, including media, finance, energy, and healthcare. Over the last decade, he worked extensively with web, cloud, and mobile technologies and managed user experiences, interface design, and data visualization for major consulting firms and their clients. Michael's current company, Seamless Thingies , focuses on IoT development and connecting everything with everything. Michael is the author of numerous articles, papers, and books, such as D3.js By Example, Instant Lucene. NET, Learning Pandas, and Mastering Pandas for Finance, all by Packt. Michael is also a frequent speaker at .NET user groups and various mobile, cloud, and IoT conferences and delivers webinars on advanced technologies.
Read more about Michael Heydt

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