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Hands-On Exploratory Data Analysis with R

You're reading from  Hands-On Exploratory Data Analysis with R

Product type Book
Published in May 2019
Publisher Packt
ISBN-13 9781789804379
Pages 266 pages
Edition 1st Edition
Languages
Authors (2):
Radhika Datar Radhika Datar
Profile icon Radhika Datar
Harish Garg Harish Garg
Profile icon Harish Garg
View More author details

Table of Contents (17) Chapters

Preface 1. Section 1: Setting Up Data Analysis Environment
2. Setting Up Our Data Analysis Environment 3. Importing Diverse Datasets 4. Examining, Cleaning, and Filtering 5. Visualizing Data Graphically with ggplot2 6. Creating Aesthetically Pleasing Reports with knitr and R Markdown 7. Section 2: Univariate, Time Series, and Multivariate Data
8. Univariate and Control Datasets 9. Time Series Datasets 10. Multivariate Datasets 11. Section 3: Multifactor, Optimization, and Regression Data Problems
12. Multi-Factor Datasets 13. Handling Optimization and Regression Data Problems 14. Section 4: Conclusions
15. Next Steps 16. Other Books You May Enjoy

Advanced graphics grammar of ggplot2

ggplot2 is considered one of the primary R packages used for producing statistical or data graphics, and is completely different from other graphics packages. This package functions under grammar called the grammar of graphics, which is made up of a set of independent components that can be composed in many ways. Grammar of graphics is the only thing that makes ggplot2 very powerful, because the user is not limited to a set of prespecified graphics that are used in other libraries. The grammar includes a simple set of core principles that render ggplot2 relatively easy to learn.

In 2005, Wilkinson coined the concept of grammar of graphics in order to describe the deep features that underpin all statistical graphics. The concept focuses on the primacy of layers, which includes adapting features embedded with R. So, what does the grammar of graphics...

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