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Data Wrangling with R

You're reading from   Data Wrangling with R Load, explore, transform and visualize data for modeling with tidyverse libraries

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781803235400
Length 384 pages
Edition 1st Edition
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Author (1):
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Gustavo Santos Gustavo Santos
Author Profile Icon Gustavo Santos
Gustavo Santos
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Load and Explore Data
2. Chapter 1: Fundamentals of Data Wrangling FREE CHAPTER 3. Chapter 2: Loading and Exploring Datasets 4. Chapter 3: Basic Data Visualization 5. Part 2: Data Wrangling
6. Chapter 4: Working with Strings 7. Chapter 5: Working with Numbers 8. Chapter 6: Working with Date and Time Objects 9. Chapter 7: Transformations with Base R 10. Chapter 8: Transformations with Tidyverse Libraries 11. Chapter 9: Exploratory Data Analysis 12. Part 3: Data Visualization
13. Chapter 10: Introduction to ggplot2 14. Chapter 11: Enhanced Visualizations with ggplot2 15. Chapter 12: Other Data Visualization Options 16. Part 4: Modeling
17. Chapter 13: Building a Model with R 18. Chapter 14: Build an Application with Shiny in R 19. Conclusion 20. Other Books You May Enjoy

Creating two-variable plots

We learned in elementary school that graphics are composed of an x axis and a y axis. Ergo, when something happens in X, there is a resultant change in Y. Understanding this simple phrase helps us to understand that a bi-variate graphic will represent the relationship between two variables of our dataset. If the x variable goes up, what happens to the y variable? What if x is constant?

Those and so many other questions can be raised and answered by visualizations of two variables. The first one we will see is the scatterplot. Let’s move on.

Scatterplot

A scatterplot, also known as a points plot, is widely used for Data Science analysis, especially for regression analysis. Using this kind of plot, it is possible to see whether there is a linear relationship between x and y, for example, or to find another pattern in data. In the sequence of our exploration, we are interested in finding out the effect caused by the increase in horsepower on...

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