Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 7689 packages in 0.17 seconds

XML — by CRAN Team, 2 months ago

Tools for Parsing and Generating XML Within R and S-Plus

Many approaches for both reading and creating XML (and HTML) documents (including DTDs), both local and accessible via HTTP or FTP. Also offers access to an 'XPath' "interpreter".

lattice — by Deepayan Sarkar, a year ago

Trellis Graphics for R

A powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements. See ?Lattice for an introduction.

tibble — by Kirill Müller, 2 years ago

Simple Data Frames

Provides a 'tbl_df' class (the 'tibble') with stricter checking and better formatting than the traditional data frame.

markdown — by Yihui Xie, 8 months ago

Render Markdown with 'commonmark'

Render Markdown to full and lightweight HTML/LaTeX documents with the 'commonmark' package. This package has been superseded by 'litedown'.

mvtnorm — by Torsten Hothorn, a month ago

Multivariate Normal and t Distributions

Computes multivariate normal and t probabilities, quantiles, random deviates, and densities. Log-likelihoods for multivariate Gaussian models and Gaussian copulae parameterised by Cholesky factors of covariance or precision matrices are implemented for interval-censored and exact data, or a mix thereof. Score functions for these log-likelihoods are available. A class representing multiple lower triangular matrices and corresponding methods are part of this package.

e1071 — by David Meyer, 5 months ago

Misc Functions of the Department of Statistics, Probability Theory Group (Formerly: E1071), TU Wien

Functions for latent class analysis, short time Fourier transform, fuzzy clustering, support vector machines, shortest path computation, bagged clustering, naive Bayes classifier, generalized k-nearest neighbour ...

RCurl — by CRAN Team, 7 months ago

General Network (HTTP/FTP/...) Client Interface for R

A wrapper for 'libcurl' < https://curl.se/libcurl/> Provides functions to allow one to compose general HTTP requests and provides convenient functions to fetch URIs, get & post forms, etc. and process the results returned by the Web server. This provides a great deal of control over the HTTP/FTP/... connection and the form of the request while providing a higher-level interface than is available just using R socket connections. Additionally, the underlying implementation is robust and extensive, supporting FTP/FTPS/TFTP (uploads and downloads), SSL/HTTPS, telnet, dict, ldap, and also supports cookies, redirects, authentication, etc.

glue — by Jennifer Bryan, 5 months ago

Interpreted String Literals

An implementation of interpreted string literals, inspired by Python's Literal String Interpolation < https://www.python.org/dev/peps/pep-0498/> and Docstrings < https://www.python.org/dev/peps/pep-0257/> and Julia's Triple-Quoted String Literals < https://docs.julialang.org/en/v1.3/manual/strings/#Triple-Quoted-String-Literals-1>.

jsonlite — by Jeroen Ooms, 5 months ago

A Simple and Robust JSON Parser and Generator for R

A reasonably fast JSON parser and generator, optimized for statistical data and the web. Offers simple, flexible tools for working with JSON in R, and is particularly powerful for building pipelines and interacting with a web API. The implementation is based on the mapping described in the vignette (Ooms, 2014). In addition to converting JSON data from/to R objects, 'jsonlite' contains functions to stream, validate, and prettify JSON data. The unit tests included with the package verify that all edge cases are encoded and decoded consistently for use with dynamic data in systems and applications.

DiagrammeR — by Richard Iannone, a year ago

Graph/Network Visualization

Build graph/network structures using functions for stepwise addition and deletion of nodes and edges. Work with data available in tables for bulk addition of nodes, edges, and associated metadata. Use graph selections and traversals to apply changes to specific nodes or edges. A wide selection of graph algorithms allow for the analysis of graphs. Visualize the graphs and take advantage of any aesthetic properties assigned to nodes and edges.