Compiles and displays the available data sets regarding the Italian school system, with a focus on the infrastructural aspects.
    Input datasets are downloaded from the web, with the aim of updating everything to real time.  
    The functions are divided in four main modules, namely 
    'Get', to scrape raw data from the web
    'Util', various utilities needed to process raw data
    'Group', to aggregate data at the municipality or province level
    'Map', to visualize the output datasets.

Contains functions and datasets for math taught in school. A main focus is set to prime-calculation.

Offers a helping hand to psychologists and other behavioral scientists who routinely deal with experimental data from factorial experiments. It includes several functions to format output from other R functions according to the style guidelines of the APA (American Psychological Association). This formatted output can be copied directly into manuscripts to facilitate data reporting. These features are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious technician at the Department of Psychology III, University of Wuerzburg. For details on the implemented methods, see Roland Pfister and Markus Janczyk (2016) <doi: 10.20982/tqmp.12.2.p147>.

The complete scripts from the American version of the Office
    television show in tibble format. Use this package to analyze and have
    fun with text from the best series of all time.

A collection of useful functions and example code created and
    used by the Schloss Lab for reproducible microbiome research. Perform
    common tasks like read files created by mothur <https://mothur.org/>,
    tidy up your microbiome data, and format R Markdown documents for
    publication.  See the website <http://www.schlosslab.org/schtools/>
    for more information, documentation, and examples.

This is a shape preserving spline <doi:10.1137/0720057>
    which is guaranteed to be monotonic and concave or convex if the
    data is monotonic and concave or convex. It does not use any 
    optimisation and is therefore quick and smoothly converges to a 
    fixed point in economic dynamics problems including value function 
    iteration. It also automatically gives the first two derivatives 
    of the spline and options for determining behaviour when evaluated 
    outside the interpolation domain.