Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
R Programming By Example

You're reading from   R Programming By Example Practical, hands-on projects to help you get started with R

Arrow left icon
Product type Paperback
Published in Dec 2017
Publisher Packt
ISBN-13 9781788292542
Length 470 pages
Edition 1st Edition
Languages
Arrow right icon
Authors (2):
Arrow left icon
Omar Trejo Navarro Omar Trejo Navarro
Author Profile Icon Omar Trejo Navarro
Omar Trejo Navarro
Omar Trejo Navarro Omar Trejo Navarro
Author Profile Icon Omar Trejo Navarro
Omar Trejo Navarro
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Introduction to R 2. Understanding Votes with Descriptive Statistics FREE CHAPTER 3. Predicting Votes with Linear Models 4. Simulating Sales Data and Working with Databases 5. Communicating Sales with Visualizations 6. Understanding Reviews with Text Analysis 7. Developing Automatic Presentations 8. Object-Oriented System to Track Cryptocurrencies 9. Implementing an Efficient Simple Moving Average 10. Adding Interactivity with Dashboards 11. Required Packages

Creating a new dataset with what we've learned

What we have learned so far in this chapter is that age, education, and ethnicity are important factors in understanding the way people voted in the Brexit Referendum. Younger people with higher education levels are related with votes in favor of remaining in the EU. Older white people are related with votes in favor of leaving the EU. We can now use this knowledge to make a more succinct data set that incorporates this knowledge. First we add relevant variables, and then we remove non-relevant variables.

Our new relevant variables are two groups of age (adults below and above 45), two groups of ethnicity (whites and non-whites), and two groups of education (high and low education levels):

data$Age_18to44 <- (
    data$Age_18to19 +
    data$Age_20to24 +
    data$Age_25to29 +
    data$Age_30to44
)
data$Age_45plus <- (
 ...
You have been reading a chapter from
R Programming By Example
Published in: Dec 2017
Publisher: Packt
ISBN-13: 9781788292542
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image