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R Graphs Cookbook

Hrishi V. Mittal

Detailed hands-on recipes for creating the most useful types of graphs in R – starting from the simplest versions to more advanced applications
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Book Details

ISBN 139781849513067
Paperback272 pages

About This Book

  • Learn to draw any type of graph or visual data representation in R
  • Filled with practical tips and techniques for creating any type of graph you need; not just theoretical explanations
  • All examples are accompanied with the corresponding graph images, so you know what the results look like
  • Each recipe is independent and contains the complete explanation and code to perform the task as efficiently as possible

Who This Book Is For

This book is for readers already familiar with the basics of R who want to learn the best techniques and code to create graphics in R in the best way possible. It will also serve as an invaluable reference book for expert R users.


Height Map Topography




Table of Contents

Chapter 1: Basic Graph Functions
Creating scatter plots
Creating line graphs
Creating bar charts
Creating histograms and density plots
Creating box plots
Adjusting X and Y axes limits
Creating heat maps
Creating pairs plots
Creating multiple plot matrix layouts
Adding and formatting legends
Creating graphs with maps
Saving and exporting graphs
Chapter 2: Beyond the Basics: Adjusting Key Parameters
Setting colors of points, lines, and bars
Setting plot background colors
Setting colors for text elements: axis annotations, labels, plot titles, and legends
Choosing color combinations and palettes
Setting fonts for annotations and titles
Choosing plotting point symbol styles and sizes
Choosing line styles and width
Choosing box styles
Adjusting axis annotations and tick marks
Formatting log axes
Setting graph margins and dimensions
Chapter 3: Creating Scatter Plots
Grouping data points within a scatter plot
Highlighting grouped data points by size and symbol type
Labelling data points
Correlation matrix using pairs plot
Adding error bars
Using jitter to distinguish closely packed data points
Adding linear model lines
Adding non-linear model curves
Adding non-parametric model curves with lowess
Making three-dimensional scatter plots
How to make Quantile-Quantile plots
Displaying data density on axes
Making scatter plots with smoothed density representation
Chapter 4: Creating Line Graphs and Time Series Charts
Adding customized legends for multiple line graphs
Using margin labels instead of legends for multiple line graphs
Adding horizontal and vertical grid lines
Adding marker lines at specific X and Y values
Creating sparklines
Plotting functions of a variable in a dataset
Formatting time series data for plotting
Plotting date and time on the X axis
Annotating axis labels in different human readable time formats
Adding vertical markers to indicate specific time events
Plotting data with varying time averaging periods
Creating stock charts
Chapter 5: Creating Bar, Dot, and Pie Charts
Creating bar charts with more than one factor variable
Creating stacked bar charts
Adjusting the orientation of bars—horizontal and vertical
Adjusting bar widths, spacing, colors and borders
Displaying values on top of or next to the bars
Placing labels inside bars
Creating bar charts with vertical error bars
Modifying dot charts by grouping variables
Making better readable pie charts with clockwise-ordered slices
Labelling a pie chart with percentage values for each slice
Adding a legend to a pie chart
Chapter 6: Creating Histograms
Visualizing distributions as count frequencies or probability densities
Setting bin size and number of breaks
Adjusting histogram styles: bar colors, borders, and axes
Overlaying density line over a histogram
Multiple histograms along the diagonal of a pairs plot
Histograms in the margins of line and scatter plots
Chapter 7: Creating Box and Whisker Plots
Creating box plots with narrow boxes for a small number of variables
Grouping over a variable
Varying box widths by number of observations
Creating box plots with notches
Including or excluding outliers
Creating horizontal box plots
Changing box styling
Adjusting the extent of plot whiskers outside the box
Showing the number of observations
Splitting a variable at arbitrary values into subsets
Chapter 8: Creating Heat Maps and Contour Plots
Creating heat maps of single Z variable with scale
Creating correlation heat maps
Summarizing multivariate data in a heat map
Creating contour plots
Creating filled contour plots
Creating three-dimensional surface plots
Visualizing time series as calendar heat maps
Chapter 9: Creating Maps
Plotting global data by countries on a world map
Creating graphs with regional maps
Plotting data on Google maps
Creating and reading KML data
Working with ESRI shapefiles
Chapter 10: Finalizing graphs for publications and presentations
Exporting graphs in high resolution image formats: PNG, JPEG, BMP, TIFF
Exporting graphs in vector formats: SVG, PDF, PS
Adding mathematical and scientific notations (typesetting)
Adding text descriptions to graphs
Using graph templates
Choosing font families and styles under Windows, Mac OS X, and Linux
Choosing fonts for PostScripts and PDFs

What You Will Learn

  • Construct multiple graph matrix layouts
  • Summarize multivariate datasets with a single graph
  • Create custom graph functions to avoid code repetition
  • Make and re-use visual themes for graphs
  • Save and export graphs in various formats to print or publish
  • Learn to use fonts and annotations in graphs on Windows, Mac, and Linux
  • Combine different graph types to give a better visual summary of complex datasets
  • Present geographical data on maps
  • Use heatmaps to spot trends and anomalies in large datasets
  • Add scientific annotations and formulae to label graphs
  • Add text descriptions to create graph presentation handouts
  • Create beautiful color palettes and apply them to graphs

In Detail

With more than two million users worldwide, R is one of the most popular open source projects. It is a free and robust statistical programming environment with very powerful graphical capabilities. Analyzing and visualizing data with R is a necessary skill for anyone doing any kind of statistical analysis, and this book will help you do just that in the easiest and most efficient way possible.

Unlike other books on R, this book takes a practical, hands-on approach and you dive straight into creating graphs in R right from the very first page.

You want to harness the power of this open source programming language to visually present and analyze your data in the best way possible – and this book will show you how.

The R Graph Cookbook takes a practical approach to teaching how to create effective and useful graphs using R. This practical guide begins by teaching you how to make basic graphs in R and progresses through subsequent dedicated chapters about each graph type in depth. It will demystify a lot of difficult and confusing R functions and parameters and enable you to construct and modify data graphics to suit your analysis, presentation, and publication needs.

You will learn all about making graphics such as scatter plots, line graphs, bar charts, pie charts, dot plots, heat maps, histograms and box plots. In addition, there are detailed recipes on making various combinations and advanced versions of these graphs. Dedicated chapters on polishing and finalizing graphs will enable you to produce professional-quality graphs for presentation and publication. With R Graph Cookbook in hand, making graphs in R has never been easier.


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