I started writing my first package as collection of various functions that I needed for (almost) daily work. Meanwhile, packages were growing and bit by bit I sourced out functions to put them into new packages. Although this means more work for CRAN members when they have more packages to manage on their network, from a user-perspective it is much better if packages have a clear focus and a well defined set of functions. That’s why I now released a new package on CRAN, sjlabelled, which contains all functions that deal with labelled data. These functions use to live in the sjmisc-package, where they now are deprecated and will be removed in a future update.
My aim is not only to provide packages with a clear focus, but also with a consistent design and philosophy, making it easier and more intuitive to use (see also here) – I prefer to follow the so called „tidyverse“-approach here. It is still work in progress, but so far I think I’m on a good way…
So, what are the packages I use for (almost) daily work?
- sjlabelled – reading, writing and working with labelled data (especially since I collaborate a lot with people who use Stata or SPSS)
- sjmisc – data and variable transformation utilities (the complement to dplyr and tidyr, when it comes down from data frames to variables within the data wrangling process)
- sjstats – out-of-the-box statistics that is not already provided by base R or packages
- sjPlot – to quickly generate tables and plot
- ggeffects – to visualize regression models
The next step is creating cheat sheets for my packages. I think if you can map the scope and idea of your package (functions) on a cheat sheet, its focus is probably well defined.
Btw, if you also use some of the above packages more or less regularly, you can install the „strengejacke“-package to load them all in one step. This package is not on CRAN, because its only purpose is to load other packages.
Disclaimer: Of course I use other packages everyday as well – this posting is just focussing on my packages that I created because I frequently needed these kind of functions.
Tagged: data visualization, ggplot, R, rstats, sjPlot, Statistik