<p style="margin:0px">With the open source R programming language and its immense library of packages, you can perform virtually any data analysis task. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to import, manipulate, summarize, model, and plot data with R, formalize analytical code; and build powerful R packages using current best practices. Each short, easy lesson builds on all that's come before: you'll learn all of R's essentials as you create real R solutions. <b>R in 24 hours, Sams Teach Yourself </b>covers the entire data analysis workflow from the viewpoint of professionals whose code must be efficient, reproducible and suitable for sharing with others. You'll learn all this, and much more:</p><ul><li><div style="margin:0px">Installing and configuring the R environment</div></li><li><div style="margin:0px">Creating single-mode and multi-mode data structures</div></li><li><div style="margin:0px">Working with dates, times, and factors</div></li><li><div style="margin:0px">Using common R functions, and writing your own</div></li><li><div style="margin:0px">Importing, exporting, manipulating, and transforming data</div></li><li><div style="margin:0px">Handling data more efficiently, and writing more efficient R code</div></li><li><div style="margin:0px">Plotting data with ggplot2 and Lattice graphics</div></li><li><div style="margin:0px">Building the most common types of R models</div></li><li><div style="margin:0px">Building high-quality packages, both simple and complex - complete with data and documentation</div></li><li><div style="margin:0px">Writing R classes: S3, S4, and beyond</div></li><li><div style="margin:0px">Using R to generate automated reports</div></li><li><div style="margin:0px">Building web applications with Shiny</div></li></ul><p style="margin:0px">Step-by-step instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; &quot;Did You Know?&quot; tips offer insider advice and shortcuts; and &quot;Watch Out!&quot; alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable going beyond the book to solve a wide spectrum of analytical and statistical problems with R.</p>