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 summary, the dplyr package builds on the R language to make an even more expressive and concise language for data manipulation. In this chapter, the estimate for the total road length in 2011 is the same as in the previous chapter, but the code used to get there is more concise and easier to follow. This can mean less time spent on navigating numerous processing steps and variable names, and more time spent organizing the data.

This concludes the second section of this book, which dealt with a more formulated approach to data wrangling. If you've read up to this point, congratulations! You now have a broad understanding of the tools, approaches, and skills involved in manipulating data.

In the remaining part of the book, I will discuss advanced methods for retrieving and storing data. First, large sources of data are often made available through web interfaces called APIs. I will discuss how to use APIs to retrieve data in the next chapter.

Second, working with large amounts of data...