Book Image

The Data Wrangling Workshop - Second Edition

By : Brian Lipp, Shubhadeep Roychowdhury, Dr. Tirthajyoti Sarkar
Book Image

The Data Wrangling Workshop - Second Edition

By: Brian Lipp, Shubhadeep Roychowdhury, Dr. Tirthajyoti Sarkar

Overview of this book

While a huge amount of data is readily available to us, it is not useful in its raw form. For data to be meaningful, it must be curated and refined. If you’re a beginner, then The Data Wrangling Workshop will help to break down the process for you. You’ll start with the basics and build your knowledge, progressing from the core aspects behind data wrangling, to using the most popular tools and techniques. This book starts by showing you how to work with data structures using Python. Through examples and activities, you’ll understand why you should stay away from traditional methods of data cleaning used in other languages and take advantage of the specialized pre-built routines in Python. Later, you’ll learn how to use the same Python backend to extract and transform data from an array of sources, including the internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, the book teaches you how to handle missing or incorrect data, and reformat it based on the requirements from your downstream analytics tool. By the end of this book, you will have developed a solid understanding of how to perform data wrangling with Python, and learned several techniques and best practices to extract, clean, transform, and format your data efficiently, from a diverse array of sources.
Table of Contents (11 chapters)


The previous chapter covered how to create a successful data wrangling pipeline. In this chapter, we will build a web scraper that can be used by a data wrangling professional in their daily tasks using all of the techniques that we have learned so far. This chapter builds on the foundation of BeautifulSoup and introduces various methods for scraping a web page and using an API to gather data.

In today's connected world, one of the most valued and widely used skills for a data wrangling professional is the ability to extract and read data from web pages and databases hosted on the web. Most organizations host data on the cloud (public or private), and the majority of web microservices these days provide some kind of API for external users to access data. Let's take a look at the following diagram:

Figure 7.1: Data wrangling HTTP request and an XML/JSON reply

As we can see in the diagram, to fetch data from a web server or a database...