This package arranges data by a set of methods. It uses rearrangers to reorder data points and mutators to change their values. From basic utilities, to centering the greatest value, to swirling in 3-dimensional space, rearrr enables creativity when plotting and experimenting with data.

Create and customize interactive maps using the Leaflet JavaScript library and the htmlwidgets package. These maps can be used directly from the R console, from RStudio, in Shiny applications and R Markdown documents.

This package provides airline on-time data for all flights departing NYC in 2013. It also includes useful metadata on airlines, airports, weather, and planes.

This package provides common functionality for the dynverse packages. dynverse is created to support the development, execution, and benchmarking of trajectory inference methods.

This package provides a set of simple functions that transforms longitudinal data to estimate the cosinor linear model as described in Tong (1976). Methods are given to summarize the mean, amplitude and acrophase, to predict the mean annual outcome value, and to test the coefficients.

For tree ensembles such as random forests, regularized random forests and gradient boosted trees, this package provides functions for: extracting, measuring and pruning rules; selecting a compact rule set; summarizing rules into a learner; calculating frequent variable interactions; formatting rules in latex code. Reference: Interpreting tree ensembles with inTrees (Houtao Deng, 2019, <doi:10.1007/s41060-018-0144-8>).

The ggcorrplot package can be used to visualize easily a correlation matrix using ggplot2. It provides a solution for reordering the correlation matrix and displays the significance level on the plot. It also includes a function for computing a matrix of correlation p-values.

This package contains a simple SMTP client which provides a portable solution for sending email, including attachments, from within R.

This package performs estimation of physical activity and sedentary behavior variables from activPAL events files.

This package provides logicless templating, with a syntax that is not limited to R.

This package provides a scripting and command-line front-end is provided by r (aka littler) as a lightweight binary wrapper around the GNU R language and environment for statistical computing and graphics. While R can be used in batch mode, the r binary adds full support for both shebang-style scripting (i.e. using a hash-mark-exclamation-path expression as the first line in scripts) as well as command-line use in standard pipelines. In other words, r provides the R language without the environment.

This package provides bindings to GnuPG for working with OpenGPG (RFC4880) cryptographic methods. It includes utilities for public key encryption, creating and verifying digital signatures, and managing your local keyring. Some functionality depends on the version of GnuPG that is installed on the system.

This package provides various R programming tools for data manipulation, including:

• medical unit conversions

• combining objects

• character vector operations

• factor manipulation

• obtaining information about R objects

• generating fixed-width format files

• extricating components of date and time objects

• operations on columns of data frames

• matrix operations

• operations on vectors and data frames

• value of last evaluated expression

• wrapper for sample that ensures consistent behavior for both scalar and vector arguments

This package provides classes and methods for handling genetic data. It includes classes to represent genotypes and haplotypes at single markers up to multiple markers on multiple chromosomes. Function include allele frequencies, flagging homo/heterozygotes, flagging carriers of certain alleles, estimating and testing for Hardy-Weinberg disequilibrium, estimating and testing for linkage disequilibrium, ...

mlr3 enables efficient, object-oriented programming on the building blocks of machine learning. It provides R6 objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While mlr3 focuses on the core computational operations, add-on packages provide additional functionality.

This package contains a function that imports data from a CSV file, or uses manually entered data from the format (x, y, weight) and plots the appropriate ACC vs LOI graph and LMA graph. The main function is plotLMA (source file, header) that takes a data set and plots the appropriate LMA and ACC graphs. If no source file (a string) was passed, a manual data entry window is opened. The header parameter indicates by TRUE/FALSE (false by default) if the source CSV file has a header row or not. The dataset should contain only one independent variable (x) and one dependent variable (y) and can contain a weight for each observation.

Many models contain tuning parameters (i.e. parameters that cannot be directly estimated from the data). These tools can be used to define objects for creating, simulating, or validating values for such parameters.

This package implements a data structure similar to hashes in Perl and dictionaries in Python but with a purposefully R flavor. For objects of appreciable size, access using hashes outperforms native named lists and vectors.

This package adds distinctive yet unobtrusive geometric patterns where solid color fills are normally used. Patterned figures look just as professional when viewed by colorblind readers or when printed in black and white. The dozen included patterns can be customized in terms of scale, rotation, color, fill, line type, and line width. It is compatible with the ggplot2 package as well as grid graphics.

This package provides alluvial plots for ggplot2. Alluvial plots use variable-width ribbons and stacked bar plots to represent multi-dimensional or repeated-measures data with categorical or ordinal variables.

This is a package for visualizing data quality of partially accruing data.

This package provides tools for measuring inequality, concentration, and poverty measures. It provides both empirical and theoretical Lorenz curves.

This package lets you plot model surfaces for a wide variety of models using partial dependence plots and other techniques. Also plot model residuals and other information on the model.

This package generates ROC plots. Most ROC curve plots obscure the cutoff values and inhibit interpretation and comparison of multiple curves. This attempts to address those shortcomings by providing plotting and interactive tools. Functions are provided to generate an interactive ROC curve plot for web use, and print versions. A Shiny application implementing the functions is also included.