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R Data Visualization Recipes

R Data Visualization Recipes

By : Bianchi Lanzetta
4 (1)
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R Data Visualization Recipes

R Data Visualization Recipes

4 (1)
By: 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 (13 chapters)
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Zooming in on the map


If you want to analyze a specific region better, you might want to zoom in on the map. By doing this, a more detailed and better looking map is achieved. It's not hard to take the previous choropleth and zoom it. Although it's easy to obtain such a result, trusting the wrong tools leads to lame outcomes, so it's important to keep it straight.

With this recipe, we will zoom in on the tri-state area (New York, New Jersey, and Connecticut). Besides zooming in, we will outline them by coloring the outer states with grey. For now, go ahead and check the requirements.

Getting ready

This recipe requires the choropleth and merged_data objects created by the last recipe, Crafting choropleth using ggplot2, hence automatically requesting the same requirements from it.  Having ggplot2 installed, the choropleth object and merged_data in your environment would be enough.

How to do it...

We can zoom into the map as follows:

  1. Manipulate data using the %in% operator to create data that will...
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