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gnu: Add r-janitor.

* gnu/packages/cran.scm (r-janitor): New variable.
master
Ricardo Wurmus 2022-07-04 13:19:22 +02:00
parent 12d206901a
commit 4aee04819e
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@ -28942,6 +28942,46 @@ novels, ready for text analysis. These novels are \"Sense and Sensibility\",
and \"Persuasion\".")
(license license:expat)))
(define-public r-janitor
(package
(name "r-janitor")
(version "2.1.0")
(source (origin
(method url-fetch)
(uri (cran-uri "janitor" version))
(sha256
(base32
"09nqm957m2f54y2l30619b58x4i7gxwvr2lwg5kly5xy1ya1a1nn"))))
(properties `((upstream-name . "janitor")))
(build-system r-build-system)
(propagated-inputs
(list r-dplyr
r-lifecycle
r-lubridate
r-magrittr
r-purrr
r-rlang
r-snakecase
r-stringi
r-stringr
r-tidyr
r-tidyselect))
(native-inputs (list r-knitr))
(home-page "https://github.com/sfirke/janitor")
(synopsis "Simple tools for examining and cleaning dirty data")
(description
"The main janitor functions can: perfectly format @code{data.frame column}
names; provide quick counts of variable combinations (i.e., frequency tables
and crosstabs); and isolate duplicate records. Other janitor functions nicely
format the tabulation results. These tabulate-and-report functions
approximate popular features of SPSS and Excel. This package follows the
principles of the \"tidyverse\" and works well with the pipe function
@code{%>%}. janitor was built with beginning-to-intermediate R users in mind
and is optimized for user-friendliness. Advanced R users can already do
everything covered here, but with janitor they can do it faster and save their
thinking for the fun stuff.")
(license license:expat)))
(define-public r-tokenizers
(package
(name "r-tokenizers")