visOmopResults (version 1.3.1)

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 = "default",
  type = "ggplot",
  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

A character string defining the visual theme to apply to the plot. You can set this to NULL to apply the standard ggplot2 default style, or provide a name for one of the package's pre-defined styles. Refer to the plotStyle() function for all available style pre-defined themes. For further customization, you can always modify the returned ggplot object directly.

type

The desired format of the output plot. See plotType() for supported plot types.

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)