Book Image

Python Web Scraping Cookbook

By : Michael Heydt
Book Image

Python Web Scraping Cookbook

By: Michael Heydt

Overview of this book

Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance scrapers and deal with crawlers, sitemaps, forms automation, Ajax-based sites, caches, and more. You'll explore a number of real-world scenarios where every part of the development/product life cycle will be fully covered. You will not only develop the skills needed to design and develop reliable performance data flows, but also deploy your codebase to AWS. If you are involved in software engineering, product development, or data mining (or are interested in building data-driven products), you will find this book useful as each recipe has a clear purpose and objective. Right from extracting data from the websites to writing a sophisticated web crawler, the book's independent recipes will be a godsend. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with Ajax websites, paginated items, and more. You will also learn to tackle problems such as 403 errors, working with proxy, scraping images, and LXML. By the end of this book, you will be able to scrape websites more efficiently and able to deploy and operate your scraper in the cloud.
Table of Contents (13 chapters)

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...