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R Data Visualization Recipes
R Data Visualization Recipes

R Data Visualization Recipes: A cookbook with 65+ data visualization recipes for smarter decision-making

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R Data Visualization Recipes

Installation and Introduction

Following recipes are covered in this chapter:

  • Installing and loading graphics packages
  • Using ggplot2, plotly, and ggvis
  • Making plots using primitives
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Key benefits

  • Use R's popular packages—such as ggplot2, ggvis, ggforce, and more—to create custom, interactive visualization solutions.
  • Create, design, and build interactive dashboards using Shiny
  • A highly practical guide to help you get to grips with the basics of data visualization techniques, and how you can implement them using R

Description

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.

Who is this book for?

If you are looking to create custom data visualization solutions using the R programming language and are stuck somewhere in the process, this book will come to your rescue. Prior exposure to packages such as ggplot2 would be useful but not necessary. However, some R programming knowledge is required.

What you will learn

  • Get to know various data visualization libraries available in R to represent data
  • Generate elegant codes to craft graphics using ggplot2, ggvis and plotly
  • Add elements, text, animation, and colors to your plot to make sense of data
  • Deepen your knowledge by adding bar-charts, scatterplots, and time series plots using ggplot2
  • Build interactive dashboards using Shiny.
  • Color specific map regions based on the values of a variable in your data frame
  • Create high-quality journal-publishable scatterplots
  • Create and design various three-dimensional and multivariate plots

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 22, 2017
Length: 366 pages
Edition : 1st
Language : English
ISBN-13 : 9781788394079
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Product Details

Publication date : Nov 22, 2017
Length: 366 pages
Edition : 1st
Language : English
ISBN-13 : 9781788394079
Category :
Languages :
Tools :

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Table of Contents

12 Chapters
Installation and Introduction Chevron down icon Chevron up icon
Plotting Two Continuous Variables Chevron down icon Chevron up icon
Plotting a Discrete Predictor and a Continuous Response Chevron down icon Chevron up icon
Plotting One Variable Chevron down icon Chevron up icon
Making Other Bivariate Plots Chevron down icon Chevron up icon
Creating Maps Chevron down icon Chevron up icon
Faceting Chevron down icon Chevron up icon
Designing Three-Dimensional Plots Chevron down icon Chevron up icon
Using Theming Packages Chevron down icon Chevron up icon
Designing More Specialized Plots Chevron down icon Chevron up icon
Making Interactive Plots Chevron down icon Chevron up icon
Building Shiny Dashboards Chevron down icon Chevron up icon

Customer reviews

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Amazon Customer Jan 16, 2018
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
A clear and compelling read, and a great way to get a handle on the major methods of data visualization in R.
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