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Data Wrangling with Python

You're reading from   Data Wrangling with Python Creating actionable data from raw sources

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789800111
Length 452 pages
Edition 1st Edition
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Authors (2):
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Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Author Profile Icon Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Author Profile Icon Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
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Table of Contents (12) Chapters Close

Data Wrangling with Python
Preface
1. Introduction to Data Wrangling with Python 2. Advanced Data Structures and File Handling FREE CHAPTER 3. Introduction to NumPy, Pandas, and Matplotlib 4. A Deep Dive into Data Wrangling with Python 5. Getting Comfortable with Different Kinds of Data Sources 6. Learning the Hidden Secrets of Data Wrangling 7. Advanced Web Scraping and Data Gathering 8. RDBMS and SQL 9. Application of Data Wrangling in Real Life Appendix

Introduction to Beautiful Soup 4 and Web Page Parsing


The ability to read and understand web pages is one of paramount interest for a person collecting and formatting data. For example, consider the task of gathering data about movies and then formatting it for a downstream system. Data for the movies is best obtained by the websites such as IMDB and that data does not come pre-packaged in nice forms(CSV, JSON< and so on), so you need to know how to download and read web page.

Furthermore, you also need to be equipped with the knowledge of the structure of a web page so that you can design a system that can search for (query) a particular piece of information from a whole web page and get the value of it. This involves understanding the grammar of markup languages and being able to write something that can parse them. Doing this, and keeping all the edge cases in mind, for something like HTML is already incredibly complex, and if you extend the scope of the bespoke markup language to include...

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