Book Image

Clean Data

By : Megan Squire
Book Image

Clean Data

By: Megan Squire

Overview of this book

<p>Is much of your time spent doing tedious tasks such as cleaning dirty data, accounting for lost data, and preparing data to be used by others? If so, then having the right tools makes a critical difference, and will be a great investment as you grow your data science expertise.</p> <p>The book starts by highlighting the importance of data cleaning in data science, and will show you how to reap rewards from reforming your cleaning process. Next, you will cement your knowledge of the basic concepts that the rest of the book relies on: file formats, data types, and character encodings. You will also learn how to extract and clean data stored in RDBMS, web files, and PDF documents, through practical examples.</p> <p>At the end of the book, you will be given a chance to tackle a couple of real-world projects.</p>
Table of Contents (17 chapters)
Clean Data
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Summary


In this chapter, we looked at a wide variety of possibilities to share our cleaned data. We discussed various solutions and tradeoffs for different ways of packaging and distributing our data. We also reviewed the basics of providing documentation, including the most important things that your users need to know and how to communicate those items in a documentation file. We noticed that licenses and terms of use nearly always appear in documentation, but what do they mean and how should you choose one for your data? We reviewed some common terms of use for data projects, as well as the most common licensing schemes: Creative Commons, and ODbL. Finally, we brainstormed some ways for you to publicize your data, including data meta-collections, the Open Data Stack Exchange site, and data-centric hackathons.

At this point in the book, you have seen a complete beginning-to-end overview of data cleaning. The next two chapters consist of longer, more detailed projects that will give you...