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

Chapter 9. Stack Overflow Project

This is the first of two full, chapter-length projects where we will put everything we have learned about data cleaning into practice. We can think of each project as a dinner party where we show off our best skills from our data science kitchen. To host a successful dinner party, we should of course have our menu and guest list planned in advance. However, the mark of a true expert is how we react when things do not go exactly according to plan. We have all had that moment when we forget to buy an important ingredient, despite our carefully prepared recipes and shopping lists. Will we be able to adjust our plan to meet the new challenges we meet along the way?

In this chapter, we will tackle some data cleaning using the publicly-released Stack Overflow database dump. Stack Overflow is part of the Stack Exchange family of question-and-answer websites. On these sites, writing good questions and answers can earn a user points and badges that accumulate over...