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The Data Wrangling Workshop

You're reading from   The Data Wrangling Workshop Create your own actionable insights using data from multiple raw sources

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781839215001
Length 576 pages
Edition 2nd Edition
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Authors (3):
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Dr. Tirthajyoti Sarkar Dr. Tirthajyoti Sarkar
Author Profile Icon Dr. Tirthajyoti Sarkar
Dr. Tirthajyoti Sarkar
Shubhadeep Roychowdhury Shubhadeep Roychowdhury
Author Profile Icon Shubhadeep Roychowdhury
Shubhadeep Roychowdhury
Brian Lipp Brian Lipp
Author Profile Icon Brian Lipp
Brian Lipp
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Toc

Table of Contents (11) Chapters Close

Preface
1. Introduction to Data Wrangling with Python 2. Advanced Operations on Built-In Data Structures 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. Applications in Business Use Cases and Conclusion of the Course Appendix

The Requests and BeautifulSoup Libraries

We will take advantage of two Python libraries in this chapter: requests and BeautifulSoup. To avoid dealing with HTTP methods at a lower level, we will use the requests library. It is an API built on top of pure Python web utility libraries, which makes placing HTTP requests easy and intuitive.

BeautifulSoup is one of the most popular HTML parser packages. It parses the HTML content you pass on and builds a detailed tree of all the tags and markup within the page for easy and intuitive traversal. This tree can be used by a programmer to look for certain markup elements (for example, a table, a hyperlink, or a blob of text within a particular div ID) to scrape useful data.

We are going to do a couple of exercises in order to demonstrate how to use the requests library and decode the contents of the response received when data is fetched from the server.

Exercise 7.01: Using the Requests Library to Get a Response from the Wikipedia Home...

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