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ggDescription2 Elegant Graphics for Data Analysis


ggDescription2 Elegant Graphics for Data Analysis
ggDescription2: Elegant Graphics for Data Analysis by Hadley Wickham
English | PDF (True) | 2016 | 266 Pages | ISBN : 331924275X | 24.6 MB
This new edition to the classic book by ggDescription2 creator Hadley Wickham highlights compatibility with knitr and RStudio. ggDescription2 is a data visualization package for R that helps users create data graphics, including those that are multi-layered, with ease. With ggDescription2, it's easy to:


* produce handsome, publication-quality Descriptions with automatic legends created from the Description specification
* superimpose multiple layers (points, lines, maps, tiles, box Descriptions) from different data sources with automatically adjusted common scales
* add customizable smoothers that use powerful modeling capabilities of R, such as loess, linear models, generalized additive models, and robust regression
* save any ggDescription2 Description (or part thereof) for later modification or reuse
* create custom themes that capture in-house or journal style requirements and that can easily be applied to multiple Descriptions
* approach a graph from a visual perspective, thinking about how each component of the data is represented on the final Description
This book will be useful to everyone who has struggled with displaying data in an informative and attractive way. Some basic knowledge of R is necessary (e.g., importing data into R). ggDescription2 is a mini-language specifically tailored for producing graphics, and you'll learn everything you need in the book. After reading this book you'll be able to produce graphics customized precisely for your problems, and you'll find it easy to get graphics out of your head and on to the screen or page. New to this edition:<
* Brings the book up-to-date with ggDescription2 1.0, including major updates to the theme system
* New scales, stats and geoms added throughout
* Additional practice exercises
* A revised introduction that focuses on ggDescription() instead of qDescription()
* Updated chapters on data and modeling using tidyr, dplyr and broom

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