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R Graphics Cookbook

ebook

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

  • Expand title description text
    Publisher: O'Reilly Media

    OverDrive Read

    • ISBN: 9781449363109
    • File size: 20038 KB
    • Release date: December 5, 2012

    EPUB ebook

    • ISBN: 9781449363109
    • File size: 20036 KB
    • Release date: December 5, 2012

    Formats

    OverDrive Read
    EPUB ebook

    Languages

    English

    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

  • Expand title description text