Combining multiple datasets, whether by stacking or joining, is commonly necessary as is changing the shape of data. The plyr and reshape2 packages offer good functions for accomplishing this in ...

A few years ago, I was the CTO and cofounder of a startup in the medical practice management software space. One of the problems we were trying to solve was how medical office visit schedules can ...

Introduction -- Why use R for your statistical work? -- Whom is this book for? -- My own background -- Getting started -- How to run R -- A first R session -- Introduction to functions -- Preview of ...

R is the most popular language used for data analysis, modelling and visualisation. It is great for linear and non-linear models, parametric and non-parametric tests, clustering and time-series models ...

For those who might be wondering, the programming language was created by Ross Ihaka and Robert Gentleman in 1993. Furthermore, note that most of the R libraries are written using R, but for others, C ...

This story contains interviews with David Smith, chief community officer at Revolution Analytics; Casey Herron, data scientist at Revolution Analytics; Tess Nesbitt, director of analytics at DataSong; ...

When it comes to choosing a programming language, there really are only two choices if you’re working with data. For data science, machine learning, statistics, IoT technology and even automation, the ...