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
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

 Summary


In this chapter, we went through the basics of Python programming, but we've also started to cover conceptually some of the fundamentals to create, store, and work with data. If you've made it this far, give yourself a pat on the back. You've successfully created your first program and learned the syntax of the Python programming language.

In the next chapter, you will take some of these principals to the next level to continue your data wrangling journey. I will talk first about modules, which allow you to add previously written code with additional functionality to our program. You will use modules to read from and write to different files, or conduct file I/O. I will cover the usage of for statements to iterate through the entries of a dataset, and basic methods to analyze and modify the data. Finally, I will cover functions that allow us to create blocks of code that we can run several times.