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ggplot2 : Elegant Graphics for Data Analysis / by Hadley Wickham
Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Use R | SpringerLink BücherPublisher: New York, NY : Springer-Verlag New York, 2009Description: Online-Ressource (VIII, 213 p, digital)ISBN:- 9780387981413
- 1282509918
- 9781282509917
- 001.4/226028566 006.686
- 519.5
- 510
- QA276-280
- QA90
Contents:
Summary: Getting started with qplot -- Mastering the grammar -- Build a plot layer by layer -- Toolbox -- Scales, axes and legends -- Positioning -- Polishing your plots for publication -- Manipulating data -- Reducing duplication.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.PPN: PPN: 1649895461Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SXMS | ZDB-2-SMA | ZDB-2-SEB
Contents; 1 Introduction; 1.1 Welcome to ggplot2; 1.2 Other resources; 1.3 What is the grammar of graphics?; 1.4 How does ggplot2 fit in with other R graphics?; 1.5 About this book; 1.6 Installation; 1.7 Acknowledgements; 2 Getting started with qplot; 2.1 Introduction; 2.2 Datasets; 2.3 Basic use; 2.4 Colour, size, shape and other aesthetic attributes; 2.5 Plot geoms; 2.5.1 Adding a smoother to a plot; 2.5.2 Boxplots and jittered points; 2.5.3 Histogram and density plots; 2.5.4 Bar charts; 2.5.5 Time series with line and path plots; 2.6 Faceting; 2.7 Other options; 2.8 Differences from plot
3 Mastering the grammar3.1 Introduction; 3.2 Fuel economy data; 3.3 Building a scatterplot; 3.4 A more complex plot; 3.5 Components of the layered grammar; 3.5.1 Layers; 3.5.2 Scales; 3.5.3 Coordinate system; 3.5.4 Faceting; 3.6 Data structures; 4 Build a plot layer by layer; 4.1 Introduction; 4.2 Creating a plot; 4.3 Layers; 4.4 Data; 4.5 Aesthetic mappings; 4.5.1 Plots and layers; 4.5.2 Setting vs. mapping; 4.5.3 Grouping; 4.5.4 Matching aesthetics to graphic objects; 4.6 Geoms; 4.7 Stat; 4.8 Position adjustments; 4.9 Pulling it all together; 4.9.1 Combining geoms and stats
4.9.2 Displaying precomputed statistics4.9.3 Varying aesthetics and data; 5 Toolbox; 5.1 Introduction; 5.2 Overall layering strategy; 5.3 Basic plot types; 5.4 Displaying distributions; 5.5 Dealing with overplotting; 5.6 Surface plots; 5.7 Drawing maps; 5.8 Revealing uncertainty; 5.9 Statistical summaries; 5.9.1 Individual summary functions; 5.9.2 Single summary function; 5.10 Annotating a plot; 5.11 Weighted data; 6 Scales, axes and legends; 6.1 Introduction; 6.2 How scales work; 6.3 Usage; 6.4 Scale details; 6.4.1 Common arguments; 6.4.2 Position scales; 6.4.3 Colour
6.4.4 The manual discrete scale6.4.5 The identity scale; 6.5 Legends and axes; 6.6 More resources; 7 Positioning; 7.1 Introduction; 7.2 Faceting; 7.2.1 Facet grid; 7.2.2 Facet wrap; 7.2.3 Controlling scales; 7.2.4 Missing faceting variables; 7.2.5 Grouping vs. faceting; 7.2.6 Dodging vs. faceting; 7.2.7 Continuous variables; 7.3 Coordinate systems; 7.3.1 Transformation; 7.3.2 Statistics; 7.3.3 Cartesian coordinate systems; 7.3.4 Non-Cartesian coordinate systems; 8 Polishing your plots for publication; 8.1 Themes; 8.1.1 Built-in themes; 8.1.2 Theme elements and element functions
8.2 Customising scales and geoms8.2.1 Scales; 8.2.2 Geoms and stats; 8.3 Saving your output; 8.4 Multiple plots on the same page; 8.4.1 Subplots; 8.4.2 Rectangular grids; 9 Manipulating data; 9.1 An introduction to plyr; 9.1.1 Fitting multiple models; 9.2 Converting data from wide to long; 9.2.1 Multiple time series; 9.2.2 Parallel coordinates plot; 9.3 !ggplot()! methods; 9.3.1 Linear models; 9.3.2 Writing your own; 10 Reducing duplication; 10.1 Introduction; 10.2 Iteration; 10.3 Plot templates; 10.4 Plot functions; Appendices; A Translating between different syntaxes; A.1 Introduction
A.2 Translating between qplot and ggplot
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