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dr. M.S. (Matthijs) Berends
2023-01-23 15:01:21 +01:00
parent af139a3c82
commit 19fd0ef121
57 changed files with 2864 additions and 2739 deletions
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10
R/ggplot_sir.R
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@ -71,13 +71,11 @@
#' @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_sir()
#' }
#' if (require("ggplot2") && require("dplyr")) {
#'
#' # prettify the plot using some additional functions:
#' df <- example_isolates %>% select(AMX, NIT, FOS, TMP, CIP)
#' ggplot(df) +
@ -88,21 +86,18 @@
#' theme_sir()
#' }
#' 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_sir()
#' }
#' if (require("ggplot2") && require("dplyr")) {
#'
#' # get only proportions and no counts:
#' example_isolates %>%
#' select(AMX, NIT, FOS, TMP, CIP) %>%
#' ggplot_sir(datalabels = FALSE)
#' }
#' if (require("ggplot2") && require("dplyr")) {
#'
#' # add other ggplot2 arguments as you like:
#' example_isolates %>%
#' select(AMX, NIT, FOS, TMP, CIP) %>%
@ -115,14 +110,12 @@
#' )
#' }
#' if (require("ggplot2") && require("dplyr")) {
#'
#' # you can alter the colours with colour names:
#' example_isolates %>%
#' select(AMX) %>%
#' ggplot_sir(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(
@ -135,7 +128,6 @@
#' scale_sir_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()) %>%
@ -149,14 +141,12 @@
#' ggplot_sir(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_sir(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") %>%