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This commit is contained in:
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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@ -138,13 +138,11 @@ At default, the names of antibiotics will be shown on the plots using \code{\lin
\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) +
@ -155,21 +153,18 @@ if (require("ggplot2") && require("dplyr")) {
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) \%>\%
@ -182,14 +177,12 @@ if (require("ggplot2") && require("dplyr")) {
)
}
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(
@ -202,7 +195,6 @@ if (require("ggplot2") && require("dplyr")) {
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()) \%>\%
@ -216,14 +208,12 @@ if (require("ggplot2") && require("dplyr")) {
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") \%>\%