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RStudio IDE (or RStudio) is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser .
rstudio::conf 2019 Website: January 27 - January 30, 2020 San Francisco, CA: rstudio::conf 2020 Website: January 21, 2021 Online rstudio::global(2021) Website: Online conference due to COVID-19 pandemic: July 25 - July 28, 2022 Washington D.C. rstudio::conf(2022) Talks: RStudio rebrands to Posit [13] [18] September 17 - September 20, 2023 ...
Shiny is a web framework for developing web applications (apps), originally in R and since 2022 in python. It is free and open source. [2] It was announced by Joe Cheng, CTO of Posit, formerly RStudio, in 2012. [3] One of the uses of Shiny has been in fast prototyping. [4] In 2022, a separate implementation Shiny for Python was announced. [5]
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R is a programming language for statistical computing and data visualization.It has been adopted in the fields of data mining, bioinformatics and data analysis. [9]The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data.
It is distributed as free and open-source software under the Apache License 2.0, and is developed mainly by Microsoft. [2] The first version released was 0.3 on March 5, 2016, and the current (version 1.0) was released in 2017. [3] However, the project is described as "not actively supported" since February 2019. [4]
With the release of version 0.3.0 in April 2016 [4] the use in production and research environments became more widespread. The package was reviewed several months later on the R blog The Beginner Programmer as "R provides a simple and very user friendly package named rnn for working with recurrent neural networks.", [5] which further increased usage.
R logo. R packages are extensions to the R statistical programming language.R packages contain code, data, and documentation in a standardised collection format that can be installed by users of R, typically via a centralised software repository such as CRAN (the Comprehensive R Archive Network).