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47 lines
2.2 KiB
R
47 lines
2.2 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/availability.R
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\name{availability}
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\alias{availability}
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\title{Check Availability of Columns}
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\usage{
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availability(tbl, width = NULL)
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}
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\arguments{
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\item{tbl}{a \link{data.frame} or \link{list}}
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\item{width}{number of characters to present the visual availability, defaults to filling the width of the console}
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}
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\value{
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\link{data.frame} with column names of \code{tbl} as row names
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}
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\description{
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Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. \code{\link[=susceptibility]{susceptibility()}} and \code{\link[=resistance]{resistance()}}.
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}
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\details{
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The function returns a \link{data.frame} with columns \code{"resistant"} and \code{"visual_resistance"}. The values in that columns are calculated with \code{\link[=resistance]{resistance()}}.
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}
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\section{Stable Lifecycle}{
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\if{html}{\figure{lifecycle_stable.svg}{options: style=margin-bottom:"5"} \cr}
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The \link[=lifecycle]{lifecycle} of this function is \strong{stable}. In a stable function, major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; removing arguments or changing the meaning of existing arguments will be avoided.
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If the unlying code needs breaking changes, they will occur gradually. For example, an argument will be deprecated and first continue to work, but will emit a message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
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}
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\section{Read more on Our Website!}{
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On our website \url{https://msberends.github.io/AMR/} you can find \href{https://msberends.github.io/AMR/articles/AMR.html}{a comprehensive tutorial} about how to conduct AMR data analysis, the \href{https://msberends.github.io/AMR/reference/}{complete documentation of all functions} and \href{https://msberends.github.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
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}
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\examples{
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availability(example_isolates)
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\donttest{
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if (require("dplyr")) {
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example_isolates \%>\%
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filter(mo == as.mo("E. coli")) \%>\%
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select_if(is.rsi) \%>\%
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availability()
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}
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}
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}
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