% Generated by roxygen2: do not edit by hand % Please edit documentation in R/ggplot_rsi.R \name{ggplot_rsi} \alias{ggplot_rsi} \alias{geom_rsi} \alias{facet_rsi} \alias{scale_y_percent} \alias{scale_rsi_colours} \alias{theme_rsi} \alias{labels_rsi_count} \title{AMR Plots with \code{ggplot2}} \usage{ ggplot_rsi( data, position = NULL, x = "antibiotic", fill = "interpretation", facet = NULL, breaks = seq(0, 1, 0.1), limits = NULL, translate_ab = "name", combine_SI = TRUE, minimum = 30, language = get_AMR_locale(), nrow = NULL, colours = c(S = "#3CAEA3", SI = "#3CAEA3", I = "#F6D55C", IR = "#ED553B", R = "#ED553B"), datalabels = TRUE, datalabels.size = 2.5, datalabels.colour = "grey15", title = NULL, subtitle = NULL, caption = NULL, x.title = "Antimicrobial", y.title = "Proportion", ... ) geom_rsi( position = NULL, x = c("antibiotic", "interpretation"), fill = "interpretation", translate_ab = "name", minimum = 30, language = get_AMR_locale(), combine_SI = TRUE, ... ) facet_rsi(facet = c("interpretation", "antibiotic"), nrow = NULL) scale_y_percent(breaks = seq(0, 1, 0.1), limits = NULL) scale_rsi_colours(..., aesthetics = "fill") theme_rsi() labels_rsi_count( position = NULL, x = "antibiotic", translate_ab = "name", minimum = 30, language = get_AMR_locale(), combine_SI = TRUE, datalabels.size = 3, datalabels.colour = "grey15" ) } \arguments{ \item{data}{a \link{data.frame} with column(s) of class \code{\link{rsi}} (see \code{\link[=as.rsi]{as.rsi()}})} \item{position}{position adjustment of bars, either \code{"fill"}, \code{"stack"} or \code{"dodge"}} \item{x}{variable to show on x axis, either \code{"antibiotic"} (default) or \code{"interpretation"} or a grouping variable} \item{fill}{variable to categorise using the plots legend, either \code{"antibiotic"} (default) or \code{"interpretation"} or a grouping variable} \item{facet}{variable to split plots by, either \code{"interpretation"} (default) or \code{"antibiotic"} or a grouping variable} \item{breaks}{a \link{numeric} vector of positions} \item{limits}{a \link{numeric} vector of length two providing limits of the scale, use \code{NA} to refer to the existing minimum or maximum} \item{translate_ab}{a column name of the \link{antibiotics} data set to translate the antibiotic abbreviations to, using \code{\link[=ab_property]{ab_property()}}} \item{combine_SI}{a \link{logical} to indicate whether all values of S and I must be merged into one, so the output only consists of S+I vs. R (susceptible vs. resistant), defaults to \code{TRUE}} \item{minimum}{the minimum allowed number of available (tested) isolates. Any isolate count lower than \code{minimum} will return \code{NA} with a warning. The default number of \code{30} isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see \emph{Source}.} \item{language}{language of the returned text, defaults to system language (see \code{\link[=get_AMR_locale]{get_AMR_locale()}}) and can also be set with \code{getOption("AMR_locale")}. Use \code{language = NULL} or \code{language = ""} to prevent translation.} \item{nrow}{(when using \code{facet}) number of rows} \item{colours}{a named vactor with colour to be used for filling. The default colours are colour-blind friendly.} \item{datalabels}{show datalabels using \code{\link[=labels_rsi_count]{labels_rsi_count()}}} \item{datalabels.size}{size of the datalabels} \item{datalabels.colour}{colour of the datalabels} \item{title}{text to show as title of the plot} \item{subtitle}{text to show as subtitle of the plot} \item{caption}{text to show as caption of the plot} \item{x.title}{text to show as x axis description} \item{y.title}{text to show as y axis description} \item{...}{other arguments passed on to \code{\link[=geom_rsi]{geom_rsi()}} or, in case of \code{\link[=scale_rsi_colours]{scale_rsi_colours()}}, named values to set colours. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red. See \emph{Examples}.} \item{aesthetics}{aesthetics to apply the colours to, defaults to "fill" but can also be (a combination of) "alpha", "colour", "fill", "linetype", "shape" or "size"} } \description{ Use these functions to create bar plots for AMR data analysis. All functions rely on \link[ggplot2:ggplot]{ggplot2} functions. } \details{ At default, the names of antibiotics will be shown on the plots using \code{\link[=ab_name]{ab_name()}}. This can be set with the \code{translate_ab} argument. See \code{\link[=count_df]{count_df()}}. \subsection{The Functions}{ \code{\link[=geom_rsi]{geom_rsi()}} will take any variable from the data that has an \code{\link{rsi}} class (created with \code{\link[=as.rsi]{as.rsi()}}) using \code{\link[=rsi_df]{rsi_df()}} and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis. \code{\link[=facet_rsi]{facet_rsi()}} creates 2d plots (at default based on S/I/R) using \code{\link[ggplot2:facet_wrap]{ggplot2::facet_wrap()}}. \code{\link[=scale_y_percent]{scale_y_percent()}} transforms the y axis to a 0 to 100\% range using \code{\link[ggplot2:scale_continuous]{ggplot2::scale_y_continuous()}}. \code{\link[=scale_rsi_colours]{scale_rsi_colours()}} sets colours to the bars (green for S, yellow for I, and red for R). with multilingual support. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red. \code{\link[=theme_rsi]{theme_rsi()}} is a [ggplot2 theme][\code{\link[ggplot2:theme]{ggplot2::theme()}} with minimal distraction. \code{\link[=labels_rsi_count]{labels_rsi_count()}} print datalabels on the bars with percentage and amount of isolates using \code{\link[ggplot2:geom_text]{ggplot2::geom_text()}}. \code{\link[=ggplot_rsi]{ggplot_rsi()}} is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (\verb{\%>\%}). See \emph{Examples}. } } \examples{ \donttest{ if (require("ggplot2") && require("dplyr")) { # get antimicrobial results for drugs against a UTI: ggplot(example_isolates \%>\% select(AMX, NIT, FOS, TMP, CIP)) + geom_rsi() } if (require("ggplot2") && require("dplyr")) { # prettify the plot using some additional functions: df <- example_isolates \%>\% select(AMX, NIT, FOS, TMP, CIP) ggplot(df) + geom_rsi() + scale_y_percent() + scale_rsi_colours() + labels_rsi_count() + theme_rsi() } if (require("ggplot2") && require("dplyr")) { # or better yet, simplify this using the wrapper function - a single command: example_isolates \%>\% select(AMX, NIT, FOS, TMP, CIP) \%>\% ggplot_rsi() } if (require("ggplot2") && require("dplyr")) { # get only proportions and no counts: example_isolates \%>\% select(AMX, NIT, FOS, TMP, CIP) \%>\% ggplot_rsi(datalabels = FALSE) } if (require("ggplot2") && require("dplyr")) { # add other ggplot2 arguments as you like: example_isolates \%>\% select(AMX, NIT, FOS, TMP, CIP) \%>\% ggplot_rsi( width = 0.5, colour = "black", size = 1, linetype = 2, alpha = 0.25 ) } if (require("ggplot2") && require("dplyr")) { # you can alter the colours with colour names: example_isolates \%>\% select(AMX) \%>\% ggplot_rsi(colours = c(SI = "yellow")) } if (require("ggplot2") && require("dplyr")) { # but you can also use the built-in colour-blind friendly colours for # your plots, where "S" is green, "I" is yellow and "R" is red: data.frame( x = c("Value1", "Value2", "Value3"), y = c(1, 2, 3), z = c("Value4", "Value5", "Value6") ) \%>\% ggplot() + geom_col(aes(x = x, y = y, fill = z)) + scale_rsi_colours(Value4 = "S", Value5 = "I", Value6 = "R") } if (require("ggplot2") && require("dplyr")) { # resistance of ciprofloxacine per age group example_isolates \%>\% mutate(first_isolate = first_isolate()) \%>\% filter( first_isolate == TRUE, mo == as.mo("Escherichia coli") ) \%>\% # age_groups() is also a function in this AMR package: group_by(age_group = age_groups(age)) \%>\% select(age_group, CIP) \%>\% ggplot_rsi(x = "age_group") } if (require("ggplot2") && require("dplyr")) { # a shorter version which also adjusts data label colours: example_isolates \%>\% select(AMX, NIT, FOS, TMP, CIP) \%>\% ggplot_rsi(colours = FALSE) } if (require("ggplot2") && require("dplyr")) { # it also supports groups (don't forget to use the group var on `x` or `facet`): example_isolates \%>\% filter(mo_is_gram_negative(), ward != "Outpatient") \%>\% # select only UTI-specific drugs select(ward, AMX, NIT, FOS, TMP, CIP) \%>\% group_by(ward) \%>\% ggplot_rsi( x = "ward", facet = "antibiotic", nrow = 1, title = "AMR of Anti-UTI Drugs Per Ward", x.title = "Ward", datalabels = FALSE ) } } }