Seamless R and C++ Integration

The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about 'Rcpp' is provided by several vignettes included in this package, via the 'Rcpp Gallery' site at < https://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, ), the book by Eddelbuettel (2013, ) and the paper by Eddelbuettel and Balamuta (2018, ); see 'citation("Rcpp")' for details.

A 'dplyr' Back End for Databases

A 'dplyr' back end for databases that allows you to work with remote database tables as if they are in-memory data frames. Basic features work with any database that has a 'DBI' back end; more advanced features require 'SQL' translation to be provided by the package author.

Flexibly Reshape Data

Flexibly restructure and aggregate data using just two functions: melt and cast.

Functional Data Analysis

These functions were developed to support functional data analysis as described in Ramsay, J. O. and Silverman, B. W. (2005) Functional Data Analysis. New York: Springer and in Ramsay, J. O., Hooker, Giles, and Graves, Spencer (2009). Functional Data Analysis with R and Matlab (Springer). The package includes data sets and script files working many examples including all but one of the 76 figures in this latter book. Matlab versions are available by ftp from < https://www.psych.mcgill.ca/misc/fda/downloads/FDAfuns/>.

Data from Gapminder

An excerpt of the data available at Gapminder.org. For each of 142 countries, the package provides values for life expectancy, GDP per capita, and population, every five years, from 1952 to 2007.

Connecting to Various Database Platforms

An R 'DataBase Interface' ('DBI') compatible interface to various database platforms ('PostgreSQL', 'Oracle', 'Microsoft SQL Server', 'Amazon Redshift', 'Microsoft Parallel Database Warehouse', 'IBM Netezza', 'Apache Impala', 'Google BigQuery', 'Snowflake', 'Spark', 'SQLite', and 'InterSystems IRIS'). Also includes support for fetching data as 'Andromeda' objects. Uses either 'Java Database Connectivity' ('JDBC') or other 'DBI' drivers to connect to databases.

Classes for Relational Data

Tools to create and modify network objects. The network class can represent a range of relational data types, and supports arbitrary vertex/edge/graph attributes.

Standard Dataset Manager for Observational Medical Outcomes Partnership Common Data Model Sample Datasets

Facilitates access to sample datasets from the 'EunomiaDatasets' repository (< https://github.com/ohdsi/EunomiaDatasets>).

Methods to Convert R Data to YAML and Back

Implements the 'libyaml' 'YAML' 1.1 parser and emitter (< https://pyyaml.org/wiki/LibYAML>) for R.

A Tidy Tool for Phylogenetic Tree Data Manipulation

Phylogenetic trees contain components such as nodes, edges, branches, and associated data. As the core data manipulation tool in the 'ggtree' ecosystem, 'tidytree' provides tools for converting tree objects to tidy data frames and tidy interfaces for manipulating, analyzing, and visualizing tree data.