Plot the result of summariseCohortCount.

Usage

plotCohortCount(
  result,
  x = NULL,
  facet = c("cdm_name"),
  colour = NULL,
  style = NULL
)

Arguments

result

A summarised_result object.

x

Variables to use in x axis.

facet

Columns to facet by. See options with availablePlotColumns(result). Formula is also allowed to specify rows and columns.

colour

Columns to color by. See options with availablePlotColumns(result).

style

Visual theme to apply. Character, or NULL. If a character, this may be either the name of a built-in style (see plotStyle()), or a path to a .yml file that defines a custom style. If NULL, the function will use the explicit default style, unless a global style option is set (see setGlobalPlotOptions()), or a ⁠_brand.yml⁠ file is present (in that order). Refer to the package vignette on styles to learn more.

Value

A ggplot.

Examples

# \donttest{
library(CohortCharacteristics)
library(PatientProfiles)
library(dplyr, warn.conflicts = FALSE)

cdm <- mockCohortCharacteristics(numberIndividuals = 100)
#> Warning: There are observation period end dates after the current date: 2025-12-09
#> ℹ The latest max observation period end date found is 2032-03-12

counts <- cdm$cohort2 |>
  addSex() |>
  addAge(ageGroup = list(c(0, 29), c(30, 59), c(60, Inf))) |>
  summariseCohortCount(strata = list("age_group", "sex", c("age_group", "sex"))) |>
  filter(variable_name == "Number subjects")
#> ℹ summarising data
#> ℹ summarising cohort cohort_1
#> ℹ summarising cohort cohort_2
#> ℹ summarising cohort cohort_3
#> ✔ summariseCharacteristics finished!

counts |>
  plotCohortCount(
    x = "sex",
    facet = cohort_name ~ age_group,
    colour = "sex"
  )


# }