AMR/man/antibiotic_class_selectors.Rd

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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ab_class_selectors.R
\name{antibiotic_class_selectors}
\alias{antibiotic_class_selectors}
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\alias{ab_class}
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\alias{aminoglycosides}
\alias{carbapenems}
\alias{cephalosporins}
\alias{cephalosporins_1st}
\alias{cephalosporins_2nd}
\alias{cephalosporins_3rd}
\alias{cephalosporins_4th}
\alias{cephalosporins_5th}
\alias{fluoroquinolones}
\alias{glycopeptides}
\alias{macrolides}
\alias{penicillins}
\alias{tetracyclines}
\title{Antibiotic class selectors}
\usage{
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ab_class(ab_class)
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aminoglycosides()
carbapenems()
cephalosporins()
cephalosporins_1st()
cephalosporins_2nd()
cephalosporins_3rd()
cephalosporins_4th()
cephalosporins_5th()
fluoroquinolones()
glycopeptides()
macrolides()
penicillins()
tetracyclines()
}
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\arguments{
\item{ab_class}{an antimicrobial class, like \code{"carbapenems"}. The columns \code{group}, \code{atc_group1} and \code{atc_group2} of the \link{antibiotics} data set will be searched (case-insensitive) for this value.}
}
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\description{
Use these selection helpers inside any function that allows \href{https://tidyselect.r-lib.org/reference/language.html}{Tidyverse selections}, like \code{dplyr::select()} or \code{tidyr::pivot_longer()}. They help to select the columns of antibiotics that are of a specific antibiotic class, without the need to define the columns or antibiotic abbreviations.
}
\details{
All columns will be searched for known antibiotic names, abbreviations, brand names and codes (ATC, EARS-Net, WHO, etc.). This means that a selector like e.g. \code{\link[=aminoglycosides]{aminoglycosides()}} will pick up column names like 'gen', 'genta', 'J01GB03', 'tobra', 'Tobracin', etc.
These functions only work if the \code{tidyselect} package is installed, that comes with the \code{dplyr} package. An error will be thrown if \code{tidyselect} package is not installed, or if the functions are used outside a function that allows Tidyverse selections like \code{select()} or \code{pivot_longer()}.
}
\examples{
if (require("dplyr")) {
# this will select columns 'IPM' (imipenem) and 'MEM' (meropenem):
example_isolates \%>\%
select(carbapenems())
# this will select columns 'mo', 'AMK', 'GEN', 'KAN' and 'TOB':
example_isolates \%>\%
select(mo, aminoglycosides())
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# this will select columns 'mo' and all antimycobacterial drugs ('RIF'):
example_isolates \%>\%
select(mo, ab_class("mycobact"))
# get bug/drug combinations for only macrolides in Gram-positives:
example_isolates \%>\%
filter(mo_gramstain(mo) \%like\% "pos") \%>\%
select(mo, macrolides()) \%>\%
bug_drug_combinations() \%>\%
format()
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data.frame(irrelevant = "value",
J01CA01 = "S") \%>\% # ATC code of ampicillin
select(penicillins()) # so the 'J01CA01' column is selected
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}
}
\seealso{
\code{\link[=filter_ab_class]{filter_ab_class()}} for the \code{filter()} equivalent.
}