sjmisc - Data Transformation and Labelled Data Utility Functions
This package contains utility functions that are useful when carrying out data analysis, performing common recode and data transformation tasks or working with labelled data (especially intended for people coming from 'SPSS', 'SAS' or 'Stata' and/or who are new to R).
Basically, this package covers two domains of functionality:
- reading and writing data between other statistical packages (like 'SPSS') and R, based on the haven and foreign packages; hence, this package also includes functions to make working with labelled data easier
- frequently applied recoding and variable transformation tasks, also with support for labelled data
The functions of sjmisc are designed to work together seamlessly with other packes from the tidyverse, like dplyr. For instance, you can use the functions from sjmisc both within a pipe-worklflow to manipulate data frames, or to create new variables with mutate(). See vignette("design_philosophy", "sjmisc") for more details.
Installation
Latest development build
To install the latest development snapshot (see latest changes below), type following commands into the R console:
library(devtools)
devtools::install_github("strengejacke/sjmisc")Officiale, stable release
To install the latest stable release from CRAN, type following command into the R console:
install.packages("sjmisc")References, documentation and examples
Citation
In case you want / have to cite my package, please use citation('sjmisc') for citation information.