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The Statistics and Machine Learning with R Workshop

You're reading from   The Statistics and Machine Learning with R Workshop Unlock the power of efficient data science modeling with this hands-on guide

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781803240305
Length 516 pages
Edition 1st Edition
Languages
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Author (1):
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Liu Peng Liu Peng
Author Profile Icon Liu Peng
Liu Peng
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Table of Contents (20) Chapters Close

Preface 1. Part 1:Statistics Essentials
2. Chapter 1: Getting Started with R FREE CHAPTER 3. Chapter 2: Data Processing with dplyr 4. Chapter 3: Intermediate Data Processing 5. Chapter 4: Data Visualization with ggplot2 6. Chapter 5: Exploratory Data Analysis 7. Chapter 6: Effective Reporting with R Markdown 8. Part 2:Fundamentals of Linear Algebra and Calculus in R
9. Chapter 7: Linear Algebra in R 10. Chapter 8: Intermediate Linear Algebra in R 11. Chapter 9: Calculus in R 12. Part 3:Fundamentals of Mathematical Statistics in R
13. Chapter 10: Probability Basics 14. Chapter 11: Statistical Estimation 15. Chapter 12: Linear Regression in R 16. Chapter 13: Logistic Regression in R 17. Chapter 14: Bayesian Statistics 18. Index 19. Other Books You May Enjoy

Understanding the grammar of graphics

The previous example contained the three essential layers that need to be specified when plotting a graph: data, aesthetics, and geometries. The primary purpose of each layer is listed as follows:

  • The data layer specifies the dataset to be plotted. This corresponds to the mtcars dataset we specified earlier.
  • The aesthetics layer specifies the scale-related items that map the variables to the visual properties of the plot. Examples include the variables to be shown for the x axis and y axis, the size and color, and other plot aesthetics. This corresponds to the cyl and mpg variables we specified earlier.
  • The geometry layer specifies the visual elements used for the data, such as presenting the data via points, lines, or other forms. The geom_point() command we set in the previous example tells the plot to be shown as a scatter plot.

Other layers, such as the theme layer, also help beautify the plot, which we will cover later...

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