- 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
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
What you will learn from this book
- 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
This hands-on guide cuts short the preamble and gets straight to the point - actually creating graphs, instead of just theoretical learning. Each recipe is specifically tailored to fulfill your appetite for visually representing you data in the best way possible.
Who this book is written 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.
Hrishi V. Mittal
Hrishi Mittal has been working with R for a few years in different capacities. He was introduced to the exciting world of data analysis with R when he was working as Senior Air Quality Scientist at King's College London, where he used R extensively to analyze large amounts of air pollution and traffic data for informing the London Mayor's Air Quality Strategy. He has experience in various other programming languages, but prefers R for data analysis and visualization. He is actively involved in various R mailing lists, forums and the development of some R packages.
In early 2010, he started Pretty Graph Limited (prettygraph.com), a software company specializing in web-based data visualization products. The company's flagship product Pretty Graph uses R as the backend engine for helping researchers and businesses visualize and analyze data. The goal is to bring the power of R to a wider audience by providing a modern graphical user interface which can be accessed by anyone and from anywhere simply using a web browser.