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

Handling shapefiles to map Afghanistan health facilities


This recipe is wonderful because it's teaching so many things at once. The main goal is to teach you how to read and handle shapefiles. Additionally it also teaches how to download files directly from the console, how to create temporary files and directories, and reinforce the use of polygons and points to draw maps using ggplot2.

A little disclaimer: this code is big. However, do not feel intimidated by it, there is much to learn from this recipe. Much of it is not restricted to maps, it can be generalized to the handling of web-available data. Relying on data available on the internet makes your codes more reproducible and less local-file dependent. Upload your data and code. Tet the community help out. Now let's plot Afghanistan districts and highlight health facilities.

Getting ready

Make sure to have an internet connection. This is a not only a requirement for the packages we may need to install but also to get that. That will be...