How to Install and Uninstall r-cran-recipes Package on Ubuntu 20.10 (Groovy Gorilla)

Last updated: May 19,2024

1. Install "r-cran-recipes" package

Learn how to install r-cran-recipes on Ubuntu 20.10 (Groovy Gorilla)

$ sudo apt update $ sudo apt install r-cran-recipes

2. Uninstall "r-cran-recipes" package

Here is a brief guide to show you how to uninstall r-cran-recipes on Ubuntu 20.10 (Groovy Gorilla):

$ sudo apt remove r-cran-recipes $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-cran-recipes package on Ubuntu 20.10 (Groovy Gorilla)

Package: r-cran-recipes
Architecture: all
Version: 0.1.12+dfsg-2build1
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 1442
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-dplyr, r-cran-generics, r-cran-glue, r-cran-gower, r-cran-ipred, r-cran-lubridate, r-cran-magrittr, r-cran-matrix, r-cran-purrr (>= 0.2.3), r-cran-rlang (>= 0.4.0), r-cran-tibble, r-cran-tidyr (>= 0.8.3), r-cran-tidyselect (>= 0.2.5), r-cran-timedate, r-cran-withr
Recommends: r-cran-testthat (>= 2.1.0), r-cran-xml2, r-cran-ddalpha, r-cran-dimred, r-cran-fastica, r-cran-kernlab, r-cran-pls, r-cran-rcpproll, r-cran-rsample, r-cran-modeldata, r-cran-rspectra, r-cran-igraph, r-cran-rann
Suggests: r-cran-covr, r-cran-ggplot2, r-cran-knitr, r-cran-rmarkdown, r-cran-rpart
Filename: pool/universe/r/r-cran-recipes/r-cran-recipes_0.1.12+dfsg-2build1_all.deb
Size: 1082492
MD5sum: 785d2193df292574d320913efaf3fd80
SHA1: 562c1b0fb2b089591437784bccee69212d83a0ce
SHA256: 06bdad9f3ab9c044ebf7643e2ae90101429d938a21976718a135ff7b9e7e187c
SHA512: 34735444e1827d90cd3cf3d44af5949344c30c893c6dee140f5b36fead5977bcb45111888dc6dc5098072fa56c6540670f7175ff597f588d323d95e7443fdd4c
Homepage: https://cran.r-project.org/package=recipes
Description-en: GNU R preprocessing tools to create design matrices
This GNU R package provides an extensible framework to create and
preprocess design matrices. Recipes consist of one or more data
manipulation and analysis "steps". Statistical parameters for the steps
can be estimated from an initial data set and then applied to other data
sets. The resulting design matrices can then be used as inputs into
statistical or machine learning models.
Description-md5: cd7fdab093dd07718f27cfdb087cfce4