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Data Wrangling with R

You're reading from   Data Wrangling with R Load, explore, transform and visualize data for modeling with tidyverse libraries

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781803235400
Length 384 pages
Edition 1st Edition
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Concepts
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Author (1):
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Gustavo Santos Gustavo Santos
Author Profile Icon Gustavo Santos
Gustavo Santos
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Table of Contents (21) Chapters Close

Preface 1. Part 1: Load and Explore Data
2. Chapter 1: Fundamentals of Data Wrangling FREE CHAPTER 3. Chapter 2: Loading and Exploring Datasets 4. Chapter 3: Basic Data Visualization 5. Part 2: Data Wrangling
6. Chapter 4: Working with Strings 7. Chapter 5: Working with Numbers 8. Chapter 6: Working with Date and Time Objects 9. Chapter 7: Transformations with Base R 10. Chapter 8: Transformations with Tidyverse Libraries 11. Chapter 9: Exploratory Data Analysis 12. Part 3: Data Visualization
13. Chapter 10: Introduction to ggplot2 14. Chapter 11: Enhanced Visualizations with ggplot2 15. Chapter 12: Other Data Visualization Options 16. Part 4: Modeling
17. Chapter 13: Building a Model with R 18. Chapter 14: Build an Application with Shiny in R 19. Conclusion 20. Other Books You May Enjoy

Map plots

We live in the information era. Enormous amounts of data are created each day, from all parts of the world. Part of that data has location information attached to it (latitude and longitude), enabling the data scientists that have access to it to create visualizations using maps. Anaysis of store sales by city, state taxes collection, tourism destinations, and internet access by country are only a few examples of a large spectrum of possibilities. That is enough reason to learn how to use ggplot2 to create plots using maps.

A side note before we jump into the action is that map plots are a vast domain as well, being part of the spatial data analysis domain, which is out of the scope of this book. Here, the intention is to show the capabilities of ggplot2. To learn in more depth about map plotting, there is some material available in the Further reading section.

To plot a map, the geometry used is geom_map(). But before we can plot anything, ggplot2 requires us to load...

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