visOmopResults (version 1.4.0)

scatterPlot: Create a scatter plot visualisation from a <summarised_result> object

Description

Create a scatter plot visualisation from a <summarised_result> object

Usage

scatterPlot(
  result,
  x,
  y,
  line,
  point,
  ribbon,
  ymin = NULL,
  ymax = NULL,
  facet = NULL,
  colour = NULL,
  style = NULL,
  type = NULL,
  group = colour,
  label = character()
)

Value

A plot object.

Arguments

result

A <summarised_result> object.

x

Column or estimate name that is used as x variable.

y

Column or estimate name that is used as y variable.

line

Whether to plot a line using geom_line.

point

Whether to plot points using geom_point.

ribbon

Whether to plot a ribbon using geom_ribbon.

ymin

Lower limit of error bars, if provided is plot using geom_errorbar.

ymax

Upper limit of error bars, if provided is plot using geom_errorbar.

facet

Variables to facet by, a formula can be provided to specify which variables should be used as rows and which ones as columns.

colour

Columns to use to determine the colours.

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.

type

Character string indicating the output plot format. See plotType() for the list of supported plot types. If type = NULL, the function will use the global setting defined via setGlobalPlotOptions() (if available); otherwise, a standard ggplot2 plot is produced by default.

group

Columns to use to determine the group.

label

Character vector with the columns to display interactively in plotly.

Examples

result <- mockSummarisedResult() |>
  dplyr::filter(variable_name == "age")

scatterPlot(
  result = result,
  x = "cohort_name",
  y = "mean",
  line = TRUE,
  point = TRUE,
  ribbon = FALSE,
  facet = age_group ~ sex)