mirror of https://github.com/msberends/AMR.git
59 lines
2.1 KiB
R
59 lines
2.1 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/guess_ab_col.R
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\name{guess_ab_col}
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\alias{guess_ab_col}
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\title{Guess antibiotic column}
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\usage{
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guess_ab_col(x = NULL, search_string = NULL, verbose = FALSE)
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}
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\arguments{
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\item{x}{a \code{data.frame}}
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\item{search_string}{a text to search \code{x} for, will be checked with \code{\link{as.ab}} if this value is not a column in \code{x}}
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\item{verbose}{a logical to indicate whether additional info should be printed}
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}
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\value{
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A column name of \code{x}, or \code{NULL} when no result is found.
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}
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\description{
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This tries to find a column name in a data set based on information from the \code{\link{antibiotics}} data set. Also supports WHONET abbreviations.
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}
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\details{
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You can look for an antibiotic (trade) name or abbreviation and it will search \code{x} and the \code{\link{antibiotics}} data set for any column containing a name or code of that antibiotic. \strong{Longer columns names take precendence over shorter column names.}
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}
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\section{Read more on our website!}{
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On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a tutorial} about how to conduct AMR analysis, the \href{https://msberends.gitlab.io/AMR/reference}{complete documentation of all functions} (which reads a lot easier than here in R) and \href{https://msberends.gitlab.io/AMR/articles/WHONET.html}{an example analysis using WHONET data}.
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}
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\examples{
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df <- data.frame(amox = "S",
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tetr = "R")
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guess_ab_col(df, "amoxicillin")
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# [1] "amox"
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guess_ab_col(df, "J01AA07") # ATC code of tetracycline
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# [1] "tetr"
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guess_ab_col(df, "J01AA07", verbose = TRUE)
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# Note: Using column `tetr` as input for "J01AA07".
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# [1] "tetr"
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# WHONET codes
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df <- data.frame(AMP_ND10 = "R",
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AMC_ED20 = "S")
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guess_ab_col(df, "ampicillin")
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# [1] "AMP_ND10"
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guess_ab_col(df, "J01CR02")
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# [1] "AMC_ED20"
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guess_ab_col(df, as.ab("augmentin"))
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# [1] "AMC_ED20"
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# Longer names take precendence:
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df <- data.frame(AMP_ED2 = "S",
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AMP_ED20 = "S")
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guess_ab_col(df, "ampicillin")
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# [1] "AMP_ED20"
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}
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