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

Hacking ggvis add_axis() function to operate as a title function


Version 0.4.3 of ggvisdoes not have a function to add titles to plots, but still there is a known way to hack the add_axis() function to work as a title function. If a user expects to explore this device many times, it's advised to wrap it into a function. Besides making the code more readable, it's a quicker way to address the problem.

Getting ready

This recipe does not only teach how to craft the hack function but also to experiment it on the previous plot, so make sure to have sca3 from the earlier recipe loaded into your environment. Alternatively, you can use another ggvis object of your own.

How to do it...

  1. Wrap the add_axis() function with several arguments declared to work as a title function:
> library(ggvis)
> ggvis_title <- function(vis, plot_title, title_size = 18, shift = 0, ...){ 
    add_axis(vis, 'x', ticks = 0, orient = 'top', 
             properties = axis_props( axis = list(strokeWidth = 0),
       ...