R Graphs cookbook : over 70 recipes for building and customizing publication-quality visualizations of powerful and stunning R graphs

Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: R Graphics; Base graphics using the default package; Trellis graphs using lattice; Graphs inspired by Grammar of Graphics; Chapter 2: 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.;Targeted at those with an existing familiarity with R programming, this practical guide will appeal directly to programmers interested in learning effective data visualization techniques with R and a wide-range of its associated libraries. Cover Copyright Credits About the Authors About the Reviewers www.PacktPub.com Table of Contents Preface Chapter 1: R Graphics Base graphics using the default package Trellis graphs using lattice Graphs inspired by Grammar of Graphics Chapter 2: 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 graphsChapter 3: 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 Chapter 4: Creating Scatter Plots Introduction. Grouping data points within a scatter plotHighlighting grouped data points by size and symbol type Labeling data points Correlation matrix using pairs plots Adding error bars Using jitter to distinguish closely packed data points Adding linear model lines Adding nonlinear model curves Adding nonparametric model curves with lowess Creating three-dimensional scatter plots Creating Quantile-Quantile plots Displaying the data density on axes Creating scatter plots with a smoothed density representation Chapter 5: Creating Line Graphs and Time Series Charts Introduction. Adding customized legends for multiple-line graphsUsing margin labels instead of legends for multiple-line graphs Adding horizontal and vertical grid lines Adding marker lines at specific x and y values using abline Creating sparklines Plotting functions of a variable in a dataset Formatting time series data for plotting Plotting the date or time variable 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 6: Creating Bar, Dot, and Pie ChartsIntroduction 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 Labeling a pie chart with percentage values for each slice Adding a legend to a pie chart.

Data visualization is one of the most important tasks in the data science track. Through effective visualization, we can easily uncover underlying patterns among variables without doing any sophisticated statistical analysis.

Starting with a high-level overview of the R graphics system and then moving through this practical cookbook, you will leverage powerful default R graphics and utilize advanced graphics systems such as lattice and ggplot2, the grammar of graphics. Through inspecting large datasets using tableplot and stunning three-dimensional visualizations, you will know how to produce, customize, and publish advanced visualizations using this popular, and powerful, framework.

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