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

Found 237 packages in 0.02 seconds

ramify — by Brandon M. Greenwell, 10 months ago

Additional Matrix Functionality

Additional matrix functionality for R including: (1) wrappers for the base matrix function that allow matrices to be created from character strings and lists (the former is especially useful for creating block matrices), (2) better printing of large matrices via the generic "pretty" print function, and (3) a number of convenience functions for users more familiar with other scientific languages like 'Julia', 'Matlab'/'Octave', or 'Python'+'NumPy'.

readMDTable — by Jordan Bradford, a year ago

Read Markdown Tables into Tibbles

Efficient reading of raw markdown tables into tibbles. Designed to accept content from strings, files, and URLs with the ability to extract and read multiple tables from markdown for analysis.

gluedown — by Kiernan Nicholls, 2 years ago

Wrap Vectors in Markdown Formatting

Ease the transition between R vectors and markdown text. With 'gluedown' and 'rmarkdown', users can create traditional vectors in R, glue those strings together with the markdown syntax, and print those formatted vectors directly to the document. This package primarily uses GitHub Flavored Markdown (GFM), an offshoot of the unambiguous CommonMark specification by John MacFarlane (2019) < https://spec.commonmark.org/>.

iso8601 — by Jan van der Laan, a year ago

Working with ISO8601 Dates and Times

Functions to parse strings with ISO8601 dates, times, and date-times into R-objects. Additionally, there are functions to determine the type of ISO8601 string and to standardise ISO8601 strings.

re2 — by Girish Palya, a year ago

R Interface to Google RE2 (C++) Regular Expression Library

Pattern matching, extraction, replacement and other string processing operations using Google's RE2 < https://github.com/google/re2> regular-expression engine. Consistent interface (similar to 'stringr'). RE2 uses finite-automata based techniques, and offers a fast and safe alternative to backtracking regular-expression engines like those used in 'stringr', 'stringi' and other PCRE implementations.

tmcn — by Jian Li, 7 years ago

A Text Mining Toolkit for Chinese

A Text mining toolkit for Chinese, which includes facilities for Chinese string processing, Chinese NLP supporting, encoding detecting and converting. Moreover, it provides some functions to support 'tm' package in Chinese.

enderecobr — by Daniel Herszenhut, 4 months ago

Padronizador de Endereços Brasileiros (Brazilian Addresses Standardizer)

Padroniza endereços brasileiros a partir de diferentes critérios. Os métodos de padronização incluem apenas manipulações básicas de strings, não oferecendo suporte a correspondências probabilísticas entre strings. (Standardizes brazilian addresses using different criteria. Standardization methods include only basic string manipulation, not supporting probabilistic matches between strings.)

findPackage — by Amarnath Bose, 3 years ago

Find 'CRAN' Package by Topic

Finds 'CRAN' packages by the topic requested. The topic can be given as a character string or as a regular expression and will help users to locate 'CRAN' packages matching their specified requirement. findPackage() returns a data frame of packages with description containing the input string.

prqlr — by Tatsuya Shima, a year ago

R Bindings for the 'prqlc' Rust Library

Provides a function to convert 'PRQL' strings to 'SQL' strings. Combined with other R functions that take 'SQL' as an argument, 'PRQL' can be used on R.

omnibus — by Adam B. Smith, a year ago

Helper Tools for Managing Data, Dates, Missing Values, and Text

An assortment of helper functions for managing data (e.g., rotating values in matrices by a user-defined angle, switching from row- to column-indexing), dates (e.g., intuiting year from messy date strings), handling missing values (e.g., removing elements/rows across multiple vectors or matrices if any have an NA), text (e.g., flushing reports to the console in real-time); and combining data frames with different schema (copying, filling, or concatenating columns or applying functions before combining).