From a693a56459f74f9d51a4328de3867a6ed5b0d8a6 Mon Sep 17 00:00:00 2001 From: Glenn Johnson Date: Mon, 18 Jan 2021 12:53:23 -0600 Subject: add version 2.1.0 to r-janitor (#21120) --- .../repos/builtin/packages/r-janitor/package.py | 34 +++++++++++++--------- 1 file changed, 21 insertions(+), 13 deletions(-) (limited to 'var') diff --git a/var/spack/repos/builtin/packages/r-janitor/package.py b/var/spack/repos/builtin/packages/r-janitor/package.py index a64578ccc4..6166db41e0 100644 --- a/var/spack/repos/builtin/packages/r-janitor/package.py +++ b/var/spack/repos/builtin/packages/r-janitor/package.py @@ -7,30 +7,38 @@ from spack import * class RJanitor(RPackage): - """The main janitor functions can: perfectly format data.frame column - names; provide quick one- and two-variable tabulations (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 - Microsoft Excel. This package follows the principles of the "tidyverse" - and works well with the pipe function %>%. 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.""" + """Simple Tools for Examining and Cleaning Dirty Data + + The main janitor functions can: perfectly format data.frame column names; + provide quick one- and two-variable tabulations (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 Microsoft Excel. This package + follows the principles of the "tidyverse" and works well with the pipe + function %>%. 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.""" homepage = "https://github.com/sfirke/janitor" url = "https://cloud.r-project.org/src/contrib/janitor_0.3.0.tar.gz" list_url = "https://cloud.r-project.org/src/contrib/Archive/janitor" + version('2.1.0', sha256='d60615940fbe174f67799c8abc797f27928eca4ac180418527c5897a4aaad826') version('1.2.0', sha256='5e15a2292c65c5ddd6160289dec2604b05a813651a2be0d7854ace4548a32b8c') version('1.1.1', sha256='404b41f56e571fab4c95ef62e79cb4f3bb34d5bb6e4ea737e748ff269536176b') version('0.3.0', sha256='5e4d8ef895ed9c7b8fa91aeb93e25c009366b4c5faaf3d02265f64b33d4a45f4') depends_on('r@3.1.2:', type=('build', 'run')) depends_on('r-dplyr@0.7.0:', type=('build', 'run')) - depends_on('r-tidyr@0.7.0:', type=('build', 'run')) + depends_on('r-dplyr@1.0.0:', when='@2.1.0:', type=('build', 'run')) + depends_on('r-lifecycle', when='@2.1.0:', type=('build', 'run')) + depends_on('r-lubridate', when='@2.1.0:', type=('build', 'run')) depends_on('r-magrittr', type=('build', 'run')) - depends_on('r-snakecase@0.9.2:', when='@1.1.0:', type=('build', 'run')) depends_on('r-purrr', when='@1.1.0:', type=('build', 'run')) depends_on('r-rlang', when='@1.1.0:', type=('build', 'run')) + depends_on('r-stringi', when='@2.1.0:', type=('build', 'run')) + depends_on('r-stringr', when='@2.1.0:', type=('build', 'run')) + depends_on('r-snakecase@0.9.2:', when='@1.1.0:', type=('build', 'run')) + depends_on('r-tidyselect@1.0.0:', when='@2.1.0:', type=('build', 'run')) + depends_on('r-tidyr@0.7.0:', type=('build', 'run')) -- cgit v1.2.3-70-g09d2