The three most common open source technologies for writing data science programs are Python, SciLab, and R. Here's how to write program-defined functions in R. There's no clear definition of the term ...
R packages are great for organizing your own work, not only sharing with others. See how to create an R package in a few simple steps, thanks to packages like devtools, usethis, and roxygen2 When you ...
Writing RStudio addins is easy, is fun, and takes just a few minutes! Well, that’s what Hao Zhu from the Marcus Institute for Aging Research told the RStudio Conference recently. It hadn’t even ...
Let's explore factor analysis again, this time using the R ability to tap into OOP, but we won't use the RC model. The R language was created primarily to perform statistical analyses in an ...
Almost every R user knows about popular packages like dplyr and ggplot2. But with 10,000+ packages on CRAN and yet more on GitHub, it’s not always easy to unearth libraries with great R functions. One ...
The table below shows my favorite go-to R packages for data import, wrangling, visualization and analysis — plus a few miscellaneous tasks tossed in. The package names in the table are clickable if ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results