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ggplot2: elegant graphics for data analysis

By: Wickham, Hadley.
Series: Use R!. Publisher: Dordrecht Springer 2009Description: viii, 212 p.ISBN: 9780387981406.Subject(s): Graphic methods | R (Computer program language) | Datan analysis | Graphische Darstellung | Plot (Graphische Darstellung) | R (Programm) | VisualisierungDDC classification: 001.4226028566 Summary: This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkison's Grammar of Graphics to create a powerful and flexible system for creating data graphics. With ggplot2, it's easy to: produce handsome, publication-quality plots, with automatic legends created from the plot specification superpose multiple layers (points, lines, maps, tiles, box plots to name a few) from different data sources, with automatically adjusted common scales add customisable smoothers that use the powerful modelling capabilities of R, such as loess, linear models, generalised 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 applied to multiple plots approach your 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 their data in an informative and attractive way. You will need some basic knowledge of R (i.e. you should be able to get your data into R), but 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. Hadley Wickham is an Assistant Professor of Statistics at Rice University, and is interested in developing computational and cognitive tools for making data preparation, visualization, and analysis easier. He has developed 15 R packages and in 2006 he won the John Chambers Award for Statistical Computing for his work on the ggplot and reshape R packages.
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Books Vikram Sarabhai Library
Slot 5 (0 Floor, West Wing) Non-fiction 001.4226028566 W4G4 (Browse shelf) Available 179643

This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkison's Grammar of Graphics to create a powerful and flexible system for creating data graphics. With ggplot2, it's easy to:
produce handsome, publication-quality plots, with automatic legends created from the plot specification
superpose multiple layers (points, lines, maps, tiles, box plots to name a few) from different data sources, with automatically adjusted common scales
add customisable smoothers that use the powerful modelling capabilities of R, such as loess, linear models, generalised 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 applied to multiple plots
approach your 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 their data in an informative and attractive way. You will need some basic knowledge of R (i.e. you should be able to get your data into R), but 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.
Hadley Wickham is an Assistant Professor of Statistics at Rice University, and is interested in developing computational and cognitive tools for making data preparation, visualization, and analysis easier. He has developed 15 R packages and in 2006 he won the John Chambers Award for Statistical Computing for his work on the ggplot and reshape R packages.

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