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Data Wrangling with R

You're reading from  Data Wrangling with R

Product type Book
Published in Feb 2023
Publisher Packt
ISBN-13 9781803235400
Pages 384 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Gustavo R Santos Gustavo R Santos
Profile icon Gustavo R Santos

Table of Contents (21) Chapters

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