Book Image

R Data Visualization Recipes

By : Vitor Bianchi Lanzetta
Book Image

R Data Visualization Recipes

By: Vitor Bianchi Lanzetta

Overview of this book

R is an open source language for data analysis and graphics that allows users to load various packages for effective and better data interpretation. Its popularity has soared in recent years because of its powerful capabilities when it comes to turning different kinds of data into intuitive visualization solutions. This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization using R. It starts off with the basics of ggplot2, ggvis, and plotly visualization packages, along with an introduction to creating maps and customizing them, before progressively taking you through various ggplot2 extensions, such as ggforce, ggrepel, and gganimate. Using real-world datasets, you will analyze and visualize your data as histograms, bar graphs, and scatterplots, and customize your plots with various themes and coloring options. The book also covers advanced visualization aspects such as creating interactive dashboards using Shiny By the end of the book, you will be equipped with key techniques to create impressive data visualizations with professional efficiency and precision.
Table of Contents (19 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Installing car package and getting familiar to data


Before getting our hands dirty, let's conduct a brief data examination. Theirisdata set could be used from the beginning to the end of this chapter, as it displays simultaneously discrete (Species) and continuous variables (petal lengths/widths, sepallengths/widths), but let's get some fresh air.

Data set Salaries coming from the car package shows information about nine-month salary for professors in a college in the  U.S. between 2008 and 2009. It holds exactly the kind of data that we need. This recipe will look for car package among the already installed packages. If it's already installed, recipe proceeds to a quick data exploration, otherwise it installs car at the first place. 

How to do it...

We proceed with the recipe as follows:

  1. Use an if statement to check and install the car package:
> if(!require(car)){ install.packages('car') }
  1. Load the package and use ? to call for data set documentation:
> library(car)
> ?Salaries
  1. Check...