Book Description
Extend your capabilities with R and learn to present data in graphical form. This comprehensive guide is designed to help you produce professional quality graphs by providing practical exercises for you to complete.
- 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
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.
Table of Contents
- R Graphs Cookbook
- R Graphs Cookbook
- Credits
- About the Author
- About the Reviewers
- www.PacktPub.com
- Preface
- 1. Basic Graph Functions
- Introduction
- 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
- 2. Beyond the Basics: Adjusting Key Parameters
- Introduction
- 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
- 3. Creating Scatter Plots
- Introduction
- 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
- 4. Creating Line Graphs and Time Series Charts
- Introduction
- 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
- 5. Creating Bar, Dot, and Pie Charts
- Introduction
- 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
- 6. Creating Histograms
- Introduction
- 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
- 7. Creating Box and Whisker Plots
- Introduction
- 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
- 8. Creating Heat Maps and Contour Plots
- 9. Creating Maps
- 10. Finalizing graphs for publications and presentations
- Introduction
- 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