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R Graphics Cookbook von Winston Chang
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R Graphics Cookbook (2013. Auflage)

von Winston Chang

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This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R ́s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works. Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you ́re ready to get started. Use R ́s default graphics for quick exploration of data Create a variety of bar graphs, line graphs, and scatter plots Summarize data distributions with histograms, density curves, box plots, and other examples Provide annotations to help viewers interpret data Control the overall appearance of graphics Render data groups alongside each other for easy comparison Use colors in plots Create network graphs, heat maps, and 3D scatter plots Structure data for graphing… (mehr)
Mitglied:atbradley
Titel:R Graphics Cookbook
Autoren:Winston Chang
Info:O'Reilly Media (2013), Paperback, 416 pages
Sammlungen:Deine Bibliothek
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Tags:rstats, r, graphs, visualization, programming, software

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R Graphics Cookbook: Practical Recipes for Visualizing Data von Winston Chang

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Indeholder "Preface", " 0.1 Recipes", " 0.2 Software and Platform Notes", " 0.3 Conventions Used in This Book", " 0.4 Using Code Examples", " 0.5 How to Contact Us", " 0.6 Acknowledgments", "1. R Basics", " 1.1 Installing a Package", " 1.2 Loading a Package", " 1.3 Upgrading Packages", " 1.4 Loading a Delimited Text Data File", " 1.5 Loading Data from an Excel File", " 1.6 Loading Data from SPSS/SAS/Stata Files", " 1.7 Chaining Functions Together With %>%, the Pipe Operator", "2. Quickly Exploring Data", " 2.1 Creating a Scatter Plot", " 2.2 Creating a Line Graph", " 2.3 Creating a Bar Graph", " 2.4 Creating a Histogram", " 2.5 Creating a Box Plot", " 2.6 Plotting a Function Curve", "3. Bar Graphs", " 3.1 Making a Basic Bar Graph", " 3.2 Grouping Bars Together", " 3.3 Making a Bar Graph of Counts", " 3.4 Using Colors in a Bar Graph", " 3.5 Coloring Negative and Positive Bars Differently", " 3.6 Adjusting Bar Width and Spacing", " 3.7 Making a Stacked Bar Graph", " 3.8 Making a Proportional Stacked Bar Graph", " 3.9 Adding Labels to a Bar Graph", " 3.10 Making a Cleveland Dot Plot", "4. Line Graphs", " 4.1 Making a Basic Line Graph", " 4.2 Adding Points to a Line Graph", " 4.3 Making a Line Graph with Multiple Lines", " 4.4 Changing the Appearance of Lines", " 4.5 Changing the Appearance of Points", " 4.6 Making a Graph with a Shaded Area", " 4.7 Making a Stacked Area Graph", " 4.8 Making a Proportional Stacked Area Graph", " 4.9 Adding a Confidence Region", "5. Scatter Plots", " 5.1 Making a Basic Scatter Plot", " 5.2 Grouping Points Together using Shapes or Colors", " 5.3 Using Different Point Shapes", " 5.4 Mapping a Continuous Variable to Color or Size", " 5.5 Dealing with Overplotting", " 5.6 Adding Fitted Regression Model Lines", " 5.7 Adding Fitted Lines from an Existing Model", " 5.8 Adding Fitted Lines from Multiple Existing Models", " 5.9 Adding Annotations with Model Coefficients", " 5.10 Adding Marginal Rugs to a Scatter Plot", " 5.11 Labeling Points in a Scatter Plot", " 5.12 Creating a Balloon Plot", " 5.13 Making a Scatter Plot Matrix", "6. Summarized Data Distributions", " 6.1 Making a Basic Histogram", " 6.2 Making Multiple Histograms from Grouped Data", " 6.3 Making a Density Curve", " 6.4 Making Multiple Density Curves from Grouped Data", " 6.5 Making a Frequency Polygon", " 6.6 Making a Basic Box Plot", " 6.7 Adding Notches to a Box Plot", " 6.8 Adding Means to a Box Plot", " 6.9 Making a Violin Plot", " 6.10 Making a Dot Plot", " 6.11 Making Multiple Dot Plots for Grouped Data", " 6.12 Making a Density Plot of Two-Dimensional Data", "7. Annotations", " 7.1 Adding Text Annotations", " 7.2 Using Mathematical Expressions in Annotations", " 7.3 Adding Lines", " 7.4 Adding Line Segments and Arrows", " 7.5 Adding a Shaded Rectangle", " 7.6 Highlighting an Item", " 7.7 Adding Error Bars", " 7.8 Adding Annotations to Individual Facets", "8. Axes", " 8.1 Swapping X- and Y-Axes", " 8.2 Setting the Range of a Continuous Axis", " 8.3 Reversing a Continuous Axis", " 8.4 Changing the Order of Items on a Categorical Axis", " 8.5 Setting the Scaling Ratio of the X- and Y-Axes", " 8.6 Setting the Positions of Tick Marks", " 8.7 Removing Tick Marks and Labels", " 8.8 Changing the Text of Tick Labels", " 8.9 Changing the Appearance of Tick Labels", " 8.10 Changing the Text of Axis Labels", " 8.11 Removing Axis Labels", " 8.12 Changing the Appearance of Axis Labels", " 8.13 Showing Lines Along the Axes", " 8.14 Using a Logarithmic Axis", " 8.15 Adding Ticks for a Logarithmic Axis", " 8.16 Making a Circular Plot", " 8.17 Using Dates on an Axis", " 8.18 Using Relative Times on an Axis", "9. Controlling the Overall Appearance of Graphs", " 9.1 Setting the Title of a Graph", " 9.2 Changing the Appearance of Text", " 9.3 Using Themes", " 9.4 Changing the Appearance of Theme Elements", " 9.5 Creating Your Own Themes", " 9.6 Hiding Grid Lines", "10. Legends", " 10.1 Removing the Legend", " 10.2 Changing the Position of a Legend", " 10.3 Changing the Order of Items in a Legend", " 10.4 Reversing the Order of Items in a Legend", " 10.5 Changing a Legend Title", " 10.6 Changing the Appearance of a Legend Title", " 10.7 Removing a Legend Title", " 10.8 Changing the Labels in a Legend", " 10.9 Changing the Appearance of Legend Labels", " 10.10 Using Labels with Multiple Lines of Text", "11. Facets", " 11.1 Splitting Data into Subplots with Facets", " 11.2 Using Facets with Different Axes", " 11.3 Changing the Text of Facet Labels", " 11.4 Changing the Appearance of Facet Labels and Headers", "12. Using Colors in Plots", " 12.1 Setting the Colors of Objects", " 12.2 Representing Variables with Colors", " 12.3 Using a Colorblind-Friendly Palette", " 12.4 Using a Different Palette for a Discrete Variable", " 12.5 Using a Manually Defined Palette for a Discrete Variable", " 12.6 Using a Manually Defined Palette for a Continuous Variable", " 12.7 Coloring a Shaded Region Based on Value", "13. Miscellaneous Graphs", " 13.1 Making a Correlation Matrix", " 13.2 Plotting a Function", " 13.3 Shading a Subregion Under a Function Curve", " 13.4 Creating a Network Graph", " 13.5 Using Text Labels in a Network Graph", " 13.6 Creating a Heat Map", " 13.7 Creating a Three-Dimensional Scatter Plot", " 13.8 Adding a Prediction Surface to a Three-Dimensional Plot", " 13.9 Saving a Three-Dimensional Plot", " 13.10 Animating a Three-Dimensional Plot", " 13.11 Creating a Dendrogram", " 13.12 Creating a Vector Field", " 13.13 Creating a QQ Plot", " 13.14 Creating a Graph of an Empirical Cumulative Distribution Function", " 13.15 Creating a Mosaic Plot", " 13.16 Creating a Pie Chart", " 13.17 Creating a Map", " 13.18 Creating a Choropleth Map", " 13.19 Making a Map with a Clean Background", " 13.20 Creating a Map from a Shapefile", "14. Output for Presentation", " 14.1 Outputting to PDF Vector Files", " 14.2 Outputting to SVG Vector Files", " 14.3 Outputting to WMF Vector Files", " 14.4 Editing a Vector Output File", " 14.5 Outputting to Bitmap (PNG/TIFF) Files", " 14.6 Using Fonts in PDF Files", " 14.7 Using Fonts in Windows Bitmap or Screen Output", " 14.8 Combining Several Plots into the Same Graphic", "15. Getting Your Data into Shape", " 15.1 Creating a Data Frame", " 15.2 Getting Information About a Data Structure", " 15.3 Adding a Column to a Data Frame", " 15.4 Deleting a Column from a Data Frame", " 15.5 Renaming Columns in a Data Frame", " 15.6 Reordering Columns in a Data Frame", " 15.7 Getting a Subset of a Data Frame", " 15.8 Changing the Order of Factor Levels", " 15.9 Changing the Order of Factor Levels Based on Data Values", " 15.10 Changing the Names of Factor Levels", " 15.11 Removing Unused Levels from a Factor", " 15.12 Changing the Names of Items in a Character Vector", " 15.13 Recoding a Categorical Variable to Another Categorical Variable", " 15.14 Recoding a Continuous Variable to a Categorical Variable", " 15.15 Calculating New Columns From Existing Columns", " 15.16 Calculating New Columns by Groups", " 15.17 Summarizing Data by Groups", " 15.18 Summarizing Data with Standard Errors and Confidence Intervals", " 15.19 Converting Data from Wide to Long", " 15.20 Converting Data from Long to Wide", " 15.21 Converting a Time Series Object to Times and Values", "Appendix A. Understanding ggplot2", " A.1 Background", " A.2 Some Terminology and Theory", " A.3 Building a Simple Plot", " A.4 Printing", " A.5 Stats", " A.6 Themes", " A.7 End", "Index".

Super god kogebog til R og den ligger online, så man kan læse den gratis ved forlaget eller købe den til reolen. ( )
  bnielsen | Jun 2, 2021 |
This book is about leveraging R for all your graphical needs. It starts with the graphing functions in base R using the plot function. Starting chapter 3, ggplot2 takes over.

The provides great amount of detail on how to use the ggplot and geom_* functions for most types of graphs. I don't think the author expects us to learn the syntax in one go, so for me, it'll be a go-to reference book.

I would've preferred the appendix to be one of the early chapters. I think that would help understand the basics better. ( )
  nmarun | May 9, 2018 |
If you're ever fumbling around with data in R, you're probably familiar with the built-in, unattractive graphics. ggplot2's been increasingly recognized as a necessity for getting the most out of your imagery. It offers nearly complete control over your graphics output, building them layer by layer.

[N.B. This review includes images, and was formatted for my site, dendrobibliography -- located here.]

I spent a solid year learning and exploring R as a graduate student before I cracked open Winston Chang's R Graphics Cookbook and started learning ggplot2's little oddities. ggplot2 is itself almost like another language within R, but it's thankfully a very simple language -- far more simple and far more flexible, I feel, than the built-in graphics options.

Since you'll be printing your graphics step by step -- your boundaries before your lines; your lines separately from points; etc. -- it's easy to keep track of where every impact on the output image is occurring, allowing you to easily tweak the code and get immediate results. E.g., if annotations are not lining up where you want, or font size needs to be reduced.

Chang's cookbook is separated by what feature you need to either edit or create, making it easy to jump to what the reader needs. Full sections are devoted to bar graphs, line graphs, scatter plots, data distribution graphics, customizing annotations, axes, legends, color options, and cetera. Nearly 400 pages of text and images showing different ways of customizing and displaying every piece of your graphics. It's not a book you read cover to cover -- just the resource that 'cookbook' implies, meeting the reader's specific needs.

If you want to just jump into the code and see what you can do with your own data, there's no better place to start. Almost no time is devoted to unnecessary exercises or teaching you the fundamentals of the R programming language. Exploring the far reaches of the Internet is a free alternative that's likely just as helpful, but Chang's book serves as a great reference, and contains almost everything you need all in one.

I've uploaded examples of ggplot2 imagery produced for my thesis and an in-progress journal publication, including time series insect outbreak records (link), an arranged grid of superposed epoch analyses showing deviations in climate data around outbreak event years for our entire study region (link), a similar grid showing customized all the superposed epoch analyses for our individual sites (link), and -- just for fun -- a customized way to show outbreak dates as point data rather than time series (link). ( )
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This practical guide provides more than 150 recipes to help you generate high-quality graphs quickly, without having to comb through all the details of R ́s graphing systems. Each recipe tackles a specific problem with a solution you can apply to your own project, and includes a discussion of how and why the recipe works. Most of the recipes use the ggplot2 package, a powerful and flexible way to make graphs in R. If you have a basic understanding of the R language, you ́re ready to get started. Use R ́s default graphics for quick exploration of data Create a variety of bar graphs, line graphs, and scatter plots Summarize data distributions with histograms, density curves, box plots, and other examples Provide annotations to help viewers interpret data Control the overall appearance of graphics Render data groups alongside each other for easy comparison Use colors in plots Create network graphs, heat maps, and 3D scatter plots Structure data for graphing

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