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)


This chapter of our data journey is focused on Relational Database Management System (RDBMS) and Structured Query Language (SQL). In the previous chapter, we stored and read data from a file. In this chapter, we will read structured data, design access to the data, and create query interfaces for databases.

For years, the RDBMS format has been the conventional way to store data. An RDBMS is one of the safest ways to store, manage, and retrieve data. It is backed by a solid mathematical foundation (relational algebra and calculus) and exposes an efficient and intuitive declarative language – SQL – for easy interaction. Almost every language has a rich set of libraries to interact with different RDBMS, and the tricks and methods of using them are well tested and well understood.

Scaling an RDBMS is a pretty well-understood task, and there is a group of well trained, experienced professionals to do this job (DBAs, or database administrators).

So, it...