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Practical Data Wrangling

You're reading from   Practical Data Wrangling Expert techniques for transforming your raw data into a valuable source for analytics

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781787286139
Length 204 pages
Edition 1st Edition
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Author (1):
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Allan Visochek Allan Visochek
Author Profile Icon Allan Visochek
Allan Visochek
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Table of Contents (10) Chapters Close

Preface 1. Programming with Data FREE CHAPTER 2. Introduction to Programming in Python 3. Reading, Exploring, and Modifying Data - Part I 4. Reading, Exploring, and Modifying Data - Part II 5. Manipulating Text Data - An Introduction to Regular Expressions 6. Cleaning Numerical Data - An Introduction to R and RStudio 7. Simplifying Data Manipulation with dplyr 8. Getting Data from the Web 9. Working with Large Datasets

Logistical overview


All of the activities in this chapter will be conducted in a single R script. R scripts are files with the .R extension which are analogous to Python scripts. This chapter will make use of the RStudio IDE rather than a text editor for editing code, so you will be able to create this script from within RStudio (I will explain how to do this later in the chapter).

The R script containing the code for this chapter is called r_intro.R and is available in the code folder of the external resources. All external resources are available at the following link: https://goo.gl/8S58ra.

Data

The dataset for Chapter 6 will be the artificial_roads_by_region.csv dataset that was introduced in Chapter 4. It can be downloaded from the data folder of the external resources.

Directory structure

To follow along with the exercises in Chapter 6Cleaning Numerical Data - An Introduction to R and RStudio, create a project folder called ch6. The ch6 folder should have a folder called data, which should...

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