R for Everyone, 2nd

Use R for math: variable types, vectors, calling functions, and more
Exploit data structures, including data.frames, matrices, and lists
Create attractive, intuitive statistical graphics
Write user-defined functions
Control program flow with if, ifelse, and complex checks
Improve program efficiency with group manipulations
Combine and reshape multiple datasets
Manipulate strings using R’s facilities and regular expressions
Create normal, binomial, and Poisson probability distributions
Build linear, generalized linear, and nonlinear models
Program basic statistics: mean, standard deviation, and t-tests
Train machine learning models
Assess the quality of models and variable selection
Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods
Analyze univariate and multivariate time series data
Group data via K-means and hierarchical clustering
Prepare reports, slideshows, and web pages with knitr
Implement dashboards with Shiny