Separate a Data Frame by Normalization (unjoin)
Separate a data frame in two based on key columns. The function unjoin() provides an inside-out version of a nested data frame. This is used to identify duplication and normalize it (in the database sense) by linking two tables with the redundancy removed. This is a basic requirement for detecting topology within spatial structures that has motivated the need for this package as a building block for workflows within more applied projects.

Model Word Clouds (modelwordcloud)
Makes a word cloud of text, sized by the frequency of the word, and colored either by user-specified colors or colored by the strength of the coefficient of that text derived from a regression model.

Swarm Intelligence for Self-Organized Clustering (DatabionicSwarm)
Algorithms implementing populations of agents which interact with one another and sense their environment may exhibit emergent behavior such as self-organization and swarm intelligence. Here a swarm system, called databionic swarm (DBS), is introduced which is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method Pswarm, which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is a parameter-free high-dimensional data visualization technique, which generates projected points on a topographic map with hypsometric colors based on the generalized U-matrix. The third module is the clustering method itself with non-critical parameters. The clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. DBS enables even a non-professional in the field of data mining to apply its algorithms for visualization and/or clustering to data sets with completely different structures drawn from diverse research fields.

Estimate and Manage Empirical Distributions (distrr)
Tools to estimate and manage empirical distributions, which should work with survey data. One of the main features is the possibility to create data cubes of estimated statistics, that include all the combinations of the variables of interest (see for example functions dcc5() and dcc6()).

An Interface to Google Drive (googledrive)
Manage Google Drive files from R.