Data Management in R: A Guide for Social Scientists¶
Elff, Martin. 2020. Data Management with R: A Guide for Social Scientists. London: SAGE Publications.
This page provides material to accompany my recent book Data Management in R: A Guide for Social Scientists, which is being published by Sage Publications. The material is organised into different pages each corresponding to a chapter of the book:
The material consists, firstly, of R-scripts and, where possible, R-data files that allow to run the code shown in the book. Unfortunately not all data sets used in the examples in the book can be made available here, because of restrictions on redistribution. In some instances redistribution is prohibited by the data providers and downloaders have to assure that they agree to this. In some other cases, downloading the data requires registration with the data providers, which indicates that they do not agree to redistribution of the data by third parties. In these cases, the supporting material indicates how to obtain the data sets from the relevant data providers.
The R-scripts on the following pages are accompanied by Jupyter
https://jupyter.org), which contains input and output
that will be created by running the script. Each notebook is rendered as a page
of this website, which if applicable contains information how to obtain the data
used in the script and the notebook. Each rendered notebook also contains a link
to a dedicated container in
the code in the notebook can be interactively run. The link is marked
by this icon:
It is also possible to run RStudio on the notebook server, using the link
allows to run the R-scripts in a virtual computing enviroment. To do this
successrully one needs to make the directory in which the R-script is the
working directory. To make this easy, each directory (
.Rproj file which can be clicked on in the files pane of
In order to access the notebook container you have to log in via ORCID. See https://info.orcid.org/what-is-orcid/ to get an idea what ORCID is about.
The sources of the R-scripts and notebooks (as well as R-markdown files), are
available in the GitHub repository
ZIP-file with the contents of the repository can be downloaded from