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

Chapter 3. Reading, Exploring, and Modifying Data - Part I

Even if you are new to programming, opening, modifying and saving files within programs should be a relatively familiar process. You have likely opened and edited a document with a word processor or entered data into an Excel spread sheet.

Like a computer program, a dataset can be represented using a text file with a specific syntactical structure. The text in a data file specifies both the information contained in the data and the structure in which that information is placed. In a sense, writing a program to process data files is a similar to the process of editing a document or a spreadsheet. First, the content of a file is opened, observed, and modified, and then the result is saved.


Another general strategy to store and retrieve digital data is to use a database. Databases are organized collections of data that allow for efficient storage, retrieval, and modification. I will revisit databases in Chapter 9, Working with Large...