P281424/AMR
1
0
Fork 0
mirror of https://github.com/msberends/AMR.git synced 2025-07-11 23:01:56 +02:00
Code Releases Activity

(v2.1.1.9235) New website!

Browse Source
This commit is contained in:
dr. M.S. (Matthijs) Berends
2025-04-08 15:54:30 +01:00
parent a905303296
commit 36fd99e1f4
172 changed files with 2003 additions and 5522 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
R/amr_selectors.R
View File

@ -24,7 +24,7 @@
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# how to conduct AMR data analysis: https://amr-for-r.org/ #
# ==================================================================== #
#' Antimicrobial Selectors
@ -47,7 +47,7 @@
#' @details
#' These functions can be used in data set calls for selecting columns and filtering rows. They work with base \R, the Tidyverse, and `data.table`. They are heavily inspired by the [Tidyverse selection helpers][tidyselect::language] such as [`everything()`][tidyselect::everything()], but are not limited to `dplyr` verbs. Nonetheless, they are very convenient to use with `dplyr` functions such as [`select()`][dplyr::select()], [`filter()`][dplyr::filter()] and [`summarise()`][dplyr::summarise()], see *Examples*.
#'
#' All selectors can also be used in `tidymodels` packages such as `recipe` and `parsnip`. See for more info [our tutorial](https://msberends.github.io/AMR/articles/AMR_with_tidymodels.html) on using antimicrobial selectors for predictive modelling.
#' All selectors can also be used in `tidymodels` packages such as `recipe` and `parsnip`. See for more info [our tutorial](https://amr-for-r.org/articles/AMR_with_tidymodels.html) on using antimicrobial selectors for predictive modelling.
#'
#' All columns in the data in which these functions are called will be searched for known antimicrobial names, abbreviations, brand names, and codes (ATC, EARS-Net, WHO, etc.) according to the [antimicrobials] data set. This means that a selector such as [aminoglycosides()] will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
#'