Create a ggplot from the output of summariseCharacteristics.

Usage

plotCharacteristics(
  result,
  plotType = "barplot",
  facet = NULL,
  colour = NULL,
  style = NULL,
  plotStyle = lifecycle::deprecated()
)

Arguments

result

A summarised_result object.

plotType

Either barplot, scatterplot or boxplot. If barplot or scatterplot subset to just one estimate.

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.

plotStyle

deprecated.

Value

A ggplot.

Examples

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

cdm <- mockCohortCharacteristics()

results <- summariseCharacteristics(
  cohort = cdm$cohort1,
  ageGroup = list(c(0, 19), c(20, 39), c(40, 59), c(60, 79), c(80, 150)),
  tableIntersectCount = list(
    tableName = "visit_occurrence", window = c(-365, -1)
  ),
  cohortIntersectFlag = list(
    targetCohortTable = "cohort2", window = c(-365, -1)
  )
)
#> ℹ adding demographics columns
#> ℹ adding tableIntersectCount 1/1
#> window names casted to snake_case:
#> • `-365 to -1` -> `365_to_1`
#> ℹ adding cohortIntersectFlag 1/1
#> window names casted to snake_case:
#> • `-365 to -1` -> `365_to_1`
#> ℹ summarising data
#> ℹ summarising cohort cohort_1
#> ℹ summarising cohort cohort_2
#> ℹ summarising cohort cohort_3
#> ✔ summariseCharacteristics finished!

results |>
  filter(
    variable_name == "Cohort2 flag -365 to -1", estimate_name == "percentage"
  ) |>
  plotCharacteristics(
    plotType = "barplot",
    colour = "variable_level",
    facet = c("cdm_name", "cohort_name")
  )


results |>
  filter(variable_name == "Age", estimate_name == "mean") |>
  plotCharacteristics(
    plotType = "scatterplot",
    facet = "cdm_name"
  )


results |>
  filter(variable_name == "Age", group_level == "cohort_1") |>
  plotCharacteristics(
    plotType = "boxplot",
    facet = "cdm_name",
    colour = "cohort_name"
  )
#> Ignoring unknown labels:
#> • fill : "Cohort name"
#> Warning: `label` cannot be a <ggplot2::element_blank> object.


# }