ggplot2: Elegant Graphics for Data Analysis (Use R) Paperback - 2016
by Wickham, Hadley
- Used
Standard delivery: 5 to 9 days
Details
- Title ggplot2: Elegant Graphics for Data Analysis (Use R)
- Author Wickham, Hadley
- Binding Paperback
- Edition 2nd
- Condition Used - Very good
- Pages 260
- Volumes 1
- Language ENG
- Publisher Springer
- Publication date 2016-06-16
- Illustrated Yes
- Features Illustrated, Maps
- Bookseller's Inventory # K12R-00094
- ISBN 9783319242750 / 331924275X
- Weight 0.87 lbs (0.39 kg)
- Dimensions 9.21 x 6.14 x 0.58 in (23.39 x 15.60 x 1.47 cm)
- Category Computers - Other Applications
- Dewey Decimal Code 004
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From the publisher
From the rear cover
- produce handsome, publication-quality plots with automatic legends created from the plot specification
- superimpose multiple layers (points, lines, maps, tiles, box plots) 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 ggplot2 plot (or part thereof) for later modification or reuse
- create custom themes that capture in-house or journal style requirements and that can easily be appliedto multiple plots
- approach a graph from a visual perspective, thinking about how each component of the data is represented on the final plot
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). ggplot2 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 ggplot2 1.0, including major updates to the theme system
- New scales, stats and geoms added throughout
- Additional practice exercises
- A revisedintroduction that focuses on ggplot() instead of qplot()
- Updated chapters on data and modeling using tidyr, dplyr and broom