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

Understanding computer memory

To make sense of why processing large files requires a new approach, I will briefly discuss computer memory and databases here. Feel free to skip ahead if you are familiar with how memory and databases work. 

In computer hardware, memory is the medium that stores data, programs, and files. The hardware for computer memory is split into primary storage, which generally takes the form of RAM (random access memory), and secondary storage, which generally takes the form of a hard drive. Primary storage is used for storing the machine code and the data of active programs, while secondary storage is used for storing all data and files not currently in use. This division in memory usage reflects a few differences in the hardware used for each.

The first difference is that RAM (used for primary storage) is cleared when the computer is shut down, while data stored on hard drives (used for secondary storage) persists. The second difference is that data stored on RAM is...