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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

The basic syntax of ggplot2

Every phrase can be broken down into grammatical elements, such as subject, pronouns, and adjectives. When read together, words will make sense, forming a sentence and delivering a message. Likewise, as seen previously, there is a grammar for graphics as well, breaking the creation of a plot down into layers that can be added together to create a visual.

To understand the basics of how to write ggplot2 code, we will follow a set of questions to walk us through the process smoothly. Whenever there is a need to use the library, return to this template until the logic is absorbed and the coding becomes natural.

To create a basic plot in ggplot2, let us answer the following questions:

  • What is the dataset to be used?
  • What kind of graphic will be plotted?
  • What goes on the X axis and Y axis?
  • What is the graphic title?

These questions can be translated into the following code:

# What is the dataset to be used?
ggplot(data) +
...
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