Book Image

Practical Data Wrangling

By : Allan Visochek
Book Image

Practical Data Wrangling

By: Allan Visochek

Overview of this book

Around 80% of time in data analysis is spent on cleaning and preparing data for analysis. This is, however, an important task, and is a prerequisite to the rest of the data analysis workflow, including visualization, analysis and reporting. Python and R are considered a popular choice of tool for data analysis, and have packages that can be best used to manipulate different kinds of data, as per your requirements. This book will show you the different data wrangling techniques, and how you can leverage the power of Python and R packages to implement them. You’ll start by understanding the data wrangling process and get a solid foundation to work with different types of data. You’ll work with different data structures and acquire and parse data from various locations. You’ll also see how to reshape the layout of data and manipulate, summarize, and join data sets. Finally, we conclude with a quick primer on accessing and processing data from databases, conducting data exploration, and storing and retrieving data quickly using databases. The book includes practical examples on each of these points using simple and real-world data sets to give you an easier understanding. By the end of the book, you’ll have a thorough understanding of all the data wrangling concepts and how to implement them in the best possible way.
Table of Contents (16 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback


This chapter has provided an overall context for the purpose, subject matter, and programming languages in this book. In summary, data wrangling is important because data in its original raw format is rarely prepared for its end use to begin with. Data wrangling involves getting and reading data, cleaning data, merging and shaping data, and storing data. In this book, data wrangling will be conducted using the R and Python programming languages.

In the next chapter, I will dive into Python, with an introduction to Python programming. I will introduce basic principals of programming and features of the Python language that will be used throughout the rest of the book. If you are already familiar with Python, you may want to skip ahead or skim through the following chapter.

In Chapter 3Reading, Exploring, and Modifying Data - Part I, and Chapter 4Reading, Exploring, and Modifying Data - Part II, I will take a generalized programming approach to data wrangling. Chapter 3Reading, Exploring, and Modifying Data - Part I, and Chapter 4Reading, Exploring, and Modifying Data - Part II, will discuss how to use Python programming to read, write, and manipulate data using Python.