Package 'visOmopResults' reference manual

Title:	Graphs and Tables for OMOP Results
Description:	Provides methods to transform omop_result objects into formatted tables and figures, facilitating the visualisation of study results working with the Observational Medical Outcomes Partnership (OMOP) Common Data Model.
Authors:	Martí Català [aut] (ORCID: <https://orcid.org/0000-0003-3308-9905>), Núria Mercadé-Besora [aut, cre] (ORCID: <https://orcid.org/0009-0006-7948-3747>), Yuchen Guo [ctb] (ORCID: <https://orcid.org/0000-0002-0847-4855>), Elin Rowlands [ctb] (ORCID: <https://orcid.org/0009-0007-6629-4661>), Marta Alcalde-Herraiz [ctb] (ORCID: <https://orcid.org/0009-0002-4405-1814>), Edward Burn [ctb] (ORCID: <https://orcid.org/0000-0002-9286-1128>)
Maintainer:	Núria Mercadé-Besora <[email protected]>
License:	Apache License (>= 2)
Version:	1.5.0
Built:	2026-05-22 10:21:33 UTC
Source:	https://github.com/darwin-eu/visomopresults

Create an alluvial plot visualisation from a data frame or a `⁠<summarised_result>⁠` object.

Description

Create an alluvial plot visualisation from a data frame or a ⁠<summarised_result>⁠ object.

Usage

alluvialPlot(result, x, y, colour = x, facet = NULL, style = NULL, type = NULL)
alluvialPlot(result, x, y, colour = x, facet = NULL, style = NULL, type = NULL)

Arguments

result

A ⁠<summarised_result>⁠ object.

x

A character vector of column names to use as alluvial axes, in order from left to right. Must contain at least 2 elements.

y

Column or estimate name that is used as y variable.

colour

Columns to use to determine the colours.

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

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.

Value

A plot object.

Examples

result <- dplyr::tibble(
  treatment_1 = c("A", "A", "A", "B", "B", "B", "C", "C"),
  treatment_2 = c("A", "A", "B", "A", "B", "B", "B", "C"),
  treatment_3 = c("A", "B", "B", "A", "A", "B", "B", "C"),
  count       = c(22, 3, 5, 7, 3, 17, 4, 12)
)

# basic alluvial plot with 3 axes
alluvialPlot(
  result = result,
  x = c("treatment_1", "treatment_2", "treatment_3"),
  y = "count"
)

# colour by first axis
alluvialPlot(
  result = result,
  x = c("treatment_1", "treatment_2", "treatment_3"),
  y = "count",
  colour = "treatment_1"
)

# colour by multiple variables
alluvialPlot(
  result = result,
  x = c("treatment_1", "treatment_2", "treatment_3"),
  y = "count",
  colour = c("treatment_1", "treatment_2")
)
result <- dplyr::tibble(
  treatment_1 = c("A", "A", "A", "B", "B", "B", "C", "C"),
  treatment_2 = c("A", "A", "B", "A", "B", "B", "B", "C"),
  treatment_3 = c("A", "B", "B", "A", "A", "B", "B", "C"),
  count       = c(22, 3, 5, 7, 3, 17, 4, 12)
)

# basic alluvial plot with 3 axes
alluvialPlot(
  result = result,
  x = c("treatment_1", "treatment_2", "treatment_3"),
  y = "count"
)

# colour by first axis
alluvialPlot(
  result = result,
  x = c("treatment_1", "treatment_2", "treatment_3"),
  y = "count",
  colour = "treatment_1"
)

# colour by multiple variables
alluvialPlot(
  result = result,
  x = c("treatment_1", "treatment_2", "treatment_3"),
  y = "count",
  colour = c("treatment_1", "treatment_2")
)

Create a bar plot visualisation from a data frame or a `⁠<summarised_result>⁠` object.

Description

Create a bar plot visualisation from a data frame or a ⁠<summarised_result>⁠ object.

Usage

barPlot(
  result,
  x,
  y,
  width = NULL,
  just = 0.5,
  position = "dodge",
  facet = NULL,
  colour = NULL,
  style = NULL,
  type = NULL,
  label = character()
)
barPlot(
  result,
  x,
  y,
  width = NULL,
  just = 0.5,
  position = "dodge",
  facet = NULL,
  colour = NULL,
  style = NULL,
  type = NULL,
  label = character()
)

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.

width

Bar width, as in geom_col() of the ggplot2 package.

just

Adjustment for column placement, as in geom_col() of the ggplot2 package.

position

Position of bars, can be either dodge or stack

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

type

label

Character vector with the columns to display interactively in plotly.

Value

A plot object.

Examples

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

barPlot(
  result = result,
  x = "cohort_name",
  y = "mean",
  facet = c("age_group", "sex"),
  colour = "sex")

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

barPlot(
  result = result,
  x = "cohort_name",
  y = "mean",
  facet = c("age_group", "sex"),
  colour = "sex")

Create a box plot visualisation from a data frame or a `⁠<summarised_result>⁠` object.

Description

Create a box plot visualisation from a data frame or a ⁠<summarised_result>⁠ object.

Usage

boxPlot(
  result,
  x,
  lower = "q25",
  middle = "median",
  upper = "q75",
  ymin = "min",
  ymax = "max",
  facet = NULL,
  colour = NULL,
  style = NULL,
  type = NULL,
  label = character()
)
boxPlot(
  result,
  x,
  lower = "q25",
  middle = "median",
  upper = "q75",
  ymin = "min",
  ymax = "max",
  facet = NULL,
  colour = NULL,
  style = NULL,
  type = NULL,
  label = character()
)

Arguments

result

A ⁠<summarised_result>⁠ object.

x

Column or estimate name that is used as x variable.

lower

Estimate name for the lower quantile of the box.

middle

Estimate name for the middle line of the box.

upper

Estimate name for the upper quantile of the box.

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.

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

type

label

Character vector with the columns to display interactively in plotly.

Value

A ggplot2 object.

Examples

dplyr::tibble(year = "2000", q25 = 25, median = 50, q75 = 75, min = 0, max = 100) |>
  boxPlot(x = "year")

dplyr::tibble(year = "2000", q25 = 25, median = 50, q75 = 75, min = 0, max = 100) |>
  boxPlot(x = "year")

Apply styling to text or column names

Description

This function styles character vectors or column names in a data frame. The styling function can be customised, or you can provide specific replacements for certain values.

Usage

customiseText(
  x,
  fun = function(x) stringr::str_to_sentence(gsub("_", " ", x)),
  custom = NULL,
  keep = NULL
)
customiseText(
  x,
  fun = function(x) stringr::str_to_sentence(gsub("_", " ", x)),
  custom = NULL,
  keep = NULL
)

Arguments

x

A character vector to style text.

fun

A styling function to apply to text in x. The default function converts snake_case to sentence case.

custom

A named character vector indicating custom names for specific values in x. If NULL, the styling function in fun is applied to all values.

keep

Either a character vector of names to keep unchanged. If NULL, all names will be styled.

Value

A character vector of styled text or a data frame with styled column names.

Examples

# Styling a character vector
customiseText(c("some_column_name", "another_column"))

# Custom styling for specific values
customiseText(x = c("some_column", "another_column"),
          custom = c("Custom Name" = "another_column"))

# Keeping specific values unchanged
customiseText(x = c("some_column", "another_column"), keep = "another_column")

# Styling column names and variables in a data frame
dplyr::tibble(
  some_column = c("hi_there", "rename_me", "example", "to_keep"),
  another_column = 1:4,
  to_keep = "as_is"
) |>
  dplyr::mutate(
    "some_column" = customiseText(some_column, custom = c("EXAMPLE" = "example"), keep = "to_keep")
  ) |>
  dplyr::rename_with(.fn = ~ customiseText(.x, keep = "to_keep"))
# Styling a character vector
customiseText(c("some_column_name", "another_column"))

# Custom styling for specific values
customiseText(x = c("some_column", "another_column"),
          custom = c("Custom Name" = "another_column"))

# Keeping specific values unchanged
customiseText(x = c("some_column", "another_column"), keep = "another_column")

# Styling column names and variables in a data frame
dplyr::tibble(
  some_column = c("hi_there", "rename_me", "example", "to_keep"),
  another_column = 1:4,
  to_keep = "as_is"
) |>
  dplyr::mutate(
    "some_column" = customiseText(some_column, custom = c("EXAMPLE" = "example"), keep = "to_keep")
  ) |>
  dplyr::rename_with(.fn = ~ customiseText(.x, keep = "to_keep"))

List of mock results

Description

List of mock results

Usage

data
data

Format

A list of mock results for quarto and shiny vignette examples

Returns an empty plot

Description

Returns an empty plot

Usage

emptyPlot(title = "No data to plot", subtitle = "", type = NULL, style = NULL)
emptyPlot(title = "No data to plot", subtitle = "", type = NULL, style = NULL)

Arguments

title

Title to use in the empty plot.

subtitle

Subtitle to use in the empty plot.

type

style

Value

An empty ggplot object

Examples

emptyPlot()

emptyPlot()

Returns an empty table

Description

Returns an empty table

Usage

emptyTable(type = NULL, style = NULL)
emptyTable(type = NULL, style = NULL)

Arguments

type

Character string specifying the desired output table format. See tableType() for supported table types. If type = NULL, global options (set via setGlobalTableOptions()) will be used if available; otherwise, a default 'gt' table is created.

style

Defines the visual formatting of the table. This argument can be provided in one of the following ways:

Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See tableStyle() for available options.
YAML file path: Provide the path to an existing .yml file defining a new style.
List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type. If style = NULL, the function will use global options (see setGlobalTableOptions()) or an existing ⁠_brand.yml⁠ file (if found); otherwise, the default style is applied. For more details, see the Styles vignette on the package website.

Value

An empty table of the class specified in type

Examples

emptyTable(type = "flextable")

emptyTable(type = "flextable")

Formats estimate_name and estimate_value column

Description

Formats estimate_name and estimate_value columns by changing the name of the estimate name and/or joining different estimates together in a single row.

Usage

formatEstimateName(
  result,
  estimateName = NULL,
  keepNotFormatted = TRUE,
  useFormatOrder = TRUE
)
formatEstimateName(
  result,
  estimateName = NULL,
  keepNotFormatted = TRUE,
  useFormatOrder = TRUE
)

Arguments

result

A ⁠<summarised_result>⁠.

estimateName

Named list of estimate name's to join, sorted by computation order. Indicate estimate_name's between <...>.

keepNotFormatted

Whether to keep rows not formatted.

useFormatOrder

Whether to use the order in which estimate names appear in the estimateName (TRUE), or use the order in the input dataframe (FALSE).

Value

A ⁠<summarised_result>⁠ object.

Examples

result <- mockSummarisedResult()
result |>
  formatEstimateName(
    estimateName = c(
      "N (%)" = "<count> (<percentage>%)", "N" = "<count>"
    ),
    keepNotFormatted = FALSE
  )

result <- mockSummarisedResult()
result |>
  formatEstimateName(
    estimateName = c(
      "N (%)" = "<count> (<percentage>%)", "N" = "<count>"
    ),
    keepNotFormatted = FALSE
  )

Formats the estimate_value column

Description

Formats the estimate_value column of ⁠<summarised_result>⁠ object by editing number of decimals, decimal and thousand/millions separator marks.

Usage

formatEstimateValue(
  result,
  decimals = c(integer = 0, numeric = 2, percentage = 1, proportion = 3),
  decimalMark = ".",
  bigMark = ","
)
formatEstimateValue(
  result,
  decimals = c(integer = 0, numeric = 2, percentage = 1, proportion = 3),
  decimalMark = ".",
  bigMark = ","
)

Arguments

result

A ⁠<summarised_result>⁠.

decimals

Number of decimals per estimate type (integer, numeric, percentage, proportion), estimate name, or all estimate values (introduce the number of decimals).

decimalMark

Decimal separator mark.

bigMark

Thousand and millions separator mark.

Value

A ⁠<summarised_result>⁠.

Examples

result <- mockSummarisedResult()

result |> formatEstimateValue(decimals = 1)

result |> formatEstimateValue(decimals = c(integer = 0, numeric = 1))

result |>
  formatEstimateValue(decimals = c(numeric = 1, count = 0))
result <- mockSummarisedResult()

result |> formatEstimateValue(decimals = 1)

result |> formatEstimateValue(decimals = c(integer = 0, numeric = 1))

result |>
  formatEstimateValue(decimals = c(numeric = 1, count = 0))

Create a header for gt and flextable objects

Description

Pivots a ⁠<summarised_result>⁠ object based on the column names in header, generating specific column names for subsequent header formatting in formatTable function.

Usage

formatHeader(
  result,
  header,
  delim = "\n",
  includeHeaderName = TRUE,
  includeHeaderKey = TRUE
)
formatHeader(
  result,
  header,
  delim = "\n",
  includeHeaderName = TRUE,
  includeHeaderKey = TRUE
)

Arguments

result

A ⁠<summarised_result>⁠.

Names of the variables to make headers.

delim

Delimiter to use to separate headers.

includeHeaderName

Whether to include the column name as header.

includeHeaderKey

Whether to include the header key (header, header_name, header_level) before each header type in the column names.

Value

A tibble with rows pivotted into columns with key names for subsequent header formatting.

Examples

result <- mockSummarisedResult()

result |>
  formatHeader(
    header = c(
      "Study cohorts", "group_level", "Study strata", "strata_name",
      "strata_level"
    ),
    includeHeaderName = FALSE
  )
result <- mockSummarisedResult()

result |>
  formatHeader(
    header = c(
      "Study cohorts", "group_level", "Study strata", "strata_name",
      "strata_level"
    ),
    includeHeaderName = FALSE
  )

To indicate which was the minimum cell counts where estimates have been suppressed.

Description

To indicate which was the minimum cell counts where estimates have been suppressed.

Usage

formatMinCellCount(result)
formatMinCellCount(result)

Arguments

result

A ⁠<summarised_result>⁠ object.

Examples

result <- mockSummarisedResult()
result |> formatMinCellCount()
result <- mockSummarisedResult()
result |> formatMinCellCount()

Creates a flextable or gt object from a dataframe

Description

Creates a flextable object from a dataframe using a delimiter to span the header, and allows to easily customise table style.

Usage

formatTable(
  x,
  type = NULL,
  delim = "\n",
  style = NULL,
  na = "–",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  groupColumn = NULL,
  groupAsColumn = FALSE,
  groupOrder = NULL,
  merge = "all_columns"
)
formatTable(
  x,
  type = NULL,
  delim = "\n",
  style = NULL,
  na = "–",
  title = NULL,
  subtitle = NULL,
  caption = NULL,
  groupColumn = NULL,
  groupAsColumn = FALSE,
  groupOrder = NULL,
  merge = "all_columns"
)

Arguments

x

A dataframe.

type

delim

Delimiter to separate headers.

style

Defines the visual formatting of the table. This argument can be provided in one of the following ways:

Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See tableStyle() for available options.
YAML file path: Provide the path to an existing .yml file defining a new style.
List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type. If style = NULL, the function will use global options (see setGlobalTableOptions()) or an existing ⁠_brand.yml⁠ file (if found); otherwise, the default style is applied. For more details, see the Styles vignette on the package website.

na

How to display missing values. Not used for "datatable" and "reactable".

title

Title of the table, or NULL for no title. Not used for "datatable".

subtitle

Subtitle of the table, or NULL for no subtitle. Not used for "datatable" and "reactable".

caption

Caption for the table, or NULL for no caption. Text in markdown formatting style (e.g. ⁠*Your caption here*⁠ for caption in italics). Not used for "reactable".

groupColumn

Columns to use as group labels, to see options use tableColumns(result). By default, the name of the new group will be the tidy* column names separated by ";". To specify a custom group name, use a named list such as: list("newGroupName" = c("variable_name", "variable_level")).

*tidy: The tidy format applied to column names replaces "_" with a space and converts to sentence case. Use rename to customise specific column names.

groupAsColumn

Whether to display the group labels as a column (TRUE) or rows (FALSE). Not used for "datatable" and "reactable"

groupOrder

Order in which to display group labels. Not used for "datatable" and "reactable".

merge

Names of the columns to merge vertically when consecutive row cells have identical values. Alternatively, use "all_columns" to apply this merging to all columns, or use NULL to indicate no merging. Not used for "datatable" and "reactable".

Value

A formatted table of the class selected in "type" argument.

Examples

# Example 1
mockSummarisedResult() |>
  formatEstimateValue(decimals = c(integer = 0, numeric = 1)) |>
  formatHeader(
    header = c("Study strata", "strata_name", "strata_level"),
    includeHeaderName = FALSE
  ) |>
  formatTable(
    type = "flextable",
    style = "default",
    na = "--",
    title = "fxTable example",
    subtitle = NULL,
    caption = NULL,
    groupColumn = "group_level",
    groupAsColumn = TRUE,
    groupOrder = c("cohort1", "cohort2"),
    merge = "all_columns"
  )

# Example 2
mockSummarisedResult() |>
  formatEstimateValue(decimals = c(integer = 0, numeric = 1)) |>
  formatHeader(header = c("Study strata", "strata_name", "strata_level"),
              includeHeaderName = FALSE) |>
  formatTable(
    type = "gt",
    style = list("header" = list(
      gt::cell_fill(color = "#d9d9d9"),
      gt::cell_text(weight = "bold")),
      "header_level" = list(gt::cell_fill(color = "#e1e1e1"),
                            gt::cell_text(weight = "bold")),
      "column_name" = list(gt::cell_text(weight = "bold")),
      "title" = list(gt::cell_text(weight = "bold"),
                     gt::cell_fill(color = "#c8c8c8")),
      "group_label" = gt::cell_fill(color = "#e1e1e1")),
    na = "--",
    title = "gtTable example",
    subtitle = NULL,
    caption = NULL,
    groupColumn = "group_level",
    groupAsColumn = FALSE,
    groupOrder = c("cohort1", "cohort2"),
    merge = "all_columns"
  )

# Example 1
mockSummarisedResult() |>
  formatEstimateValue(decimals = c(integer = 0, numeric = 1)) |>
  formatHeader(
    header = c("Study strata", "strata_name", "strata_level"),
    includeHeaderName = FALSE
  ) |>
  formatTable(
    type = "flextable",
    style = "default",
    na = "--",
    title = "fxTable example",
    subtitle = NULL,
    caption = NULL,
    groupColumn = "group_level",
    groupAsColumn = TRUE,
    groupOrder = c("cohort1", "cohort2"),
    merge = "all_columns"
  )

# Example 2
mockSummarisedResult() |>
  formatEstimateValue(decimals = c(integer = 0, numeric = 1)) |>
  formatHeader(header = c("Study strata", "strata_name", "strata_level"),
              includeHeaderName = FALSE) |>
  formatTable(
    type = "gt",
    style = list("header" = list(
      gt::cell_fill(color = "#d9d9d9"),
      gt::cell_text(weight = "bold")),
      "header_level" = list(gt::cell_fill(color = "#e1e1e1"),
                            gt::cell_text(weight = "bold")),
      "column_name" = list(gt::cell_text(weight = "bold")),
      "title" = list(gt::cell_text(weight = "bold"),
                     gt::cell_fill(color = "#c8c8c8")),
      "group_label" = gt::cell_fill(color = "#e1e1e1")),
    na = "--",
    title = "gtTable example",
    subtitle = NULL,
    caption = NULL,
    groupColumn = "group_level",
    groupAsColumn = FALSE,
    groupOrder = c("cohort1", "cohort2"),
    merge = "all_columns"
  )

A `⁠<summarised_result>⁠` object filled with mock data

Description

Creates an object of the class ⁠<summarised_result>⁠ with mock data for illustration purposes.

Usage

mockSummarisedResult()
mockSummarisedResult()

Value

An object of the class ⁠<summarised_result>⁠ with mock data.

Examples

mockSummarisedResult()


mockSummarisedResult()

Columns for the plot functions

Description

Names of the columns that can be used in the input arguments for the plot functions.

Usage

plotColumns(result)
plotColumns(result)

Arguments

result

A ⁠<summarised_result>⁠ object.

Value

A character vector of supported columns for plots.

Examples

result <- mockSummarisedResult()
plotColumns(result)

result <- mockSummarisedResult()
plotColumns(result)

Pre-defined styles are available for plots

Description

This function provides a list of pre-defined styles for plots that can then be used in the style argument of the plot functions.

Usage

plotStyle()
plotStyle()

Value

A character vector indicating the style names.

Examples

plotStyle()

plotStyle()

Supported plot types

Description

This function returns the supported plot types that can be used in the type argument of the plot functions.

Usage

plotType()
plotType()

Value

A character vector of supported plot types.

Examples

tableType()

tableType()

Create a scatter plot visualisation from a data frame or a `⁠<summarised_result>⁠` object.

Description

Create a scatter plot visualisation from a data frame or 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()
)
scatterPlot(
  result,
  x,
  y,
  line,
  point,
  ribbon,
  ymin = NULL,
  ymax = NULL,
  facet = NULL,
  colour = NULL,
  style = NULL,
  type = NULL,
  group = colour,
  label = character()
)

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.

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

type

group

Columns to use to determine the group.

label

Character vector with the columns to display interactively in plotly.

Value

A plot object.

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)

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)

Set format options for all subsequent plots

Description

Set format options for all subsequent plots unless state a different style in a specific function

Usage

setGlobalPlotOptions(style = NULL, type = NULL)
setGlobalPlotOptions(style = NULL, type = NULL)

Arguments

style

type

Set format options for all subsequent tables

Description

Set format options for all subsequent tables unless state a different style in a specific function

Usage

setGlobalTableOptions(style = NULL, type = NULL)
setGlobalTableOptions(style = NULL, type = NULL)

Arguments

style

Defines the visual formatting of the table. This argument can be provided in one of the following ways:

Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See tableStyle() for available options.
YAML file path: Provide the path to an existing .yml file defining a new style.
List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type. If style = NULL, the function will use global options (see setGlobalTableOptions()) or an existing ⁠_brand.yml⁠ file (if found); otherwise, the default style is applied. For more details, see the Styles vignette on the package website.

type

Examples

setGlobalTableOptions(style = "darwin", type = "tinytable")
result <- mockSummarisedResult()
result |>
  visOmopTable(
    estimateName = c("N%" = "<count> (<percentage>)",
                     "N" = "<count>",
                     "Mean (SD)" = "<mean> (<sd>)"),
    header = c("cohort_name"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = strataColumns(result)
  )
 # drop global options:
 setGlobalTableOptions(style = NULL, type = NULL)

setGlobalTableOptions(style = "darwin", type = "tinytable")
result <- mockSummarisedResult()
result |>
  visOmopTable(
    estimateName = c("N%" = "<count> (<percentage>)",
                     "N" = "<count>",
                     "Mean (SD)" = "<mean> (<sd>)"),
    header = c("cohort_name"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = strataColumns(result)
  )
 # drop global options:
 setGlobalTableOptions(style = NULL, type = NULL)

Columns for the table functions

Description

Names of the columns that can be used in the input arguments for the table functions.

Usage

tableColumns(result)
tableColumns(result)

Arguments

result

A ⁠<summarised_result>⁠ object.

Value

A character vector of supported columns for tables.

Examples

result <- mockSummarisedResult()
tableColumns(result)

result <- mockSummarisedResult()
tableColumns(result)

Additional table formatting options for `visOmopTable()` and `visTable()`

Description

This function provides a list of allowed inputs for the .option argument in visOmopTable() and visTable(), and their corresponding default values.

Usage

tableOptions()
tableOptions()

Value

A named list of default options for table customisation.

Examples

tableOptions()

tableOptions()

Pre-defined styles are available for tables

Description

This function provides a list of pre-defined styles for tables that can then be used in the style argument of the table functions.

Usage

tableStyle()
tableStyle()

Value

A character vector indicating the style names.

Examples

tableStyle()

tableStyle()

Supported table classes

Description

This function returns the supported table classes that can be used in the type argument of visOmopTable(), visTable(), and formatTable() functions.

Usage

tableType()
tableType()

Value

A character vector of supported table types.

Examples

tableType()

tableType()

Apply a pre-defined visOmopResults theme to a ggplot

Description

Apply a pre-defined visOmopResults theme to a ggplot

Usage

themeVisOmop(style = NULL, fontsizeRef = NULL)
themeVisOmop(style = NULL, fontsizeRef = NULL)

Arguments

style

fontsizeRef

An integer to use as reference when adjusting label fontsize.

Examples

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

barPlot(
  result = result,
  x = "cohort_name",
  y = "mean",
  facet = c("age_group", "sex"),
  colour = "sex"
) +
  themeVisOmop()

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

barPlot(
  result = result,
  x = "cohort_name",
  y = "mean",
  facet = c("age_group", "sex"),
  colour = "sex"
) +
  themeVisOmop()

Generate a formatted table from a `⁠<summarised_result>⁠`

Description

This function combines the functionalities of formatEstimateValue(), estimateName(), formatHeader(), and formatTable() into a single function specifically for ⁠<summarised_result>⁠ objects.

Usage

visOmopTable(
  result,
  estimateName = character(),
  header = character(),
  settingsColumn = character(),
  groupColumn = character(),
  rename = character(),
  type = NULL,
  hide = character(),
  columnOrder = character(),
  factor = list(),
  style = NULL,
  showMinCellCount = TRUE,
  .options = list()
)
visOmopTable(
  result,
  estimateName = character(),
  header = character(),
  settingsColumn = character(),
  groupColumn = character(),
  rename = character(),
  type = NULL,
  hide = character(),
  columnOrder = character(),
  factor = list(),
  style = NULL,
  showMinCellCount = TRUE,
  .options = list()
)

Arguments

result

A ⁠<summarised_result>⁠ object.

estimateName

A named list of estimate names to join, sorted by computation order. Use ⁠<...>⁠ to indicate estimate names.

A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. Elements in header can be:

Any of the columns returned by tableColumns(result) to create a header for these columns.
Any other input to create an overall header.

settingsColumn

A character vector with the names of settings to include in the table. To see options use settingsColumns(result).

groupColumn

*tidy: The tidy format applied to column names replaces "_" with a space and converts to sentence case. Use rename to customise specific column names.

rename

A named vector to customise column names, e.g., c("Database name" = "cdm_name"). The function renames all column names not specified here into a tidy* format.

type

hide

Columns to drop from the output table. By default, result_id and estimate_type are always dropped.

columnOrder

Character vector establishing the position of the columns in the formatted table. Columns in either header, groupColumn, or hide will be ignored.

factor

A named list where names refer to columns (see available columns in tableColumns()) and list elements are the level order of that column to arrange the results. The column order in the list will be used for arranging the result.

style

Defines the visual formatting of the table. This argument can be provided in one of the following ways:

Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See tableStyle() for available options.
YAML file path: Provide the path to an existing .yml file defining a new style.
List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type. If style = NULL, the function will use global options (see setGlobalTableOptions()) or an existing ⁠_brand.yml⁠ file (if found); otherwise, the default style is applied. For more details, see the Styles vignette on the package website.

showMinCellCount

If TRUE, suppressed estimates will be indicated with "<{min_cell_count}", otherwise, the default na defined in .options will be used.

.options

A named list with additional formatting options. visOmopResults::tableOptions() shows allowed arguments and their default values.

Value

A formatted table of the class selected in "type" argument.

Examples

result <- mockSummarisedResult()
result |>
  visOmopTable(
    estimateName = c("N%" = "<count> (<percentage>)",
                     "N" = "<count>",
                     "Mean (SD)" = "<mean> (<sd>)"),
    header = c("cohort_name"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = strataColumns(result)
  )
result |>
  visOmopTable(
    estimateName = c(
      "N%" = "<count> (<percentage>)",
      "N" = "<count>",
      "Mean (SD)" = "<mean> (<sd>)"
    ),
    header = c("cohort_name"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = strataColumns(result),
    type = "reactable"
  )

result <- mockSummarisedResult()
result |>
  visOmopTable(
    estimateName = c("N%" = "<count> (<percentage>)",
                     "N" = "<count>",
                     "Mean (SD)" = "<mean> (<sd>)"),
    header = c("cohort_name"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = strataColumns(result)
  )
result |>
  visOmopTable(
    estimateName = c(
      "N%" = "<count> (<percentage>)",
      "N" = "<count>",
      "Mean (SD)" = "<mean> (<sd>)"
    ),
    header = c("cohort_name"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = strataColumns(result),
    type = "reactable"
  )

Generate a formatted table from a `⁠<data.table>⁠`

Description

This function combines the functionalities of formatEstimateValue(), formatEstimateName(), formatHeader(), and formatTable() into a single function. While it does not require the input table to be a ⁠<summarised_result>⁠, it does expect specific fields to apply some formatting functionalities.

Usage

visTable(
  result,
  estimateName = character(),
  header = character(),
  groupColumn = character(),
  rename = character(),
  type = NULL,
  hide = character(),
  style = NULL,
  .options = list()
)
visTable(
  result,
  estimateName = character(),
  header = character(),
  groupColumn = character(),
  rename = character(),
  type = NULL,
  hide = character(),
  style = NULL,
  .options = list()
)

Arguments

result

A table to format.

estimateName

A named list of estimate names to join, sorted by computation order. Use ⁠<...>⁠ to indicate estimate names.

A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. The vector elements can be column names or labels for overall headers. The table must contain an estimate_value column to pivot the headers.

groupColumn

*tidy: The tidy format applied to column names replaces "_" with a space and converts to sentence case. Use rename to customise specific column names.

rename

A named vector to customise column names, e.g., c("Database name" = "cdm_name"). The function renames all column names not specified here into a tidy* format.

type

hide

Columns to drop from the output table.

style

Defines the visual formatting of the table. This argument can be provided in one of the following ways:

Pre-defined style: Use the name of a built-in style (e.g., "darwin"). See tableStyle() for available options.
YAML file path: Provide the path to an existing .yml file defining a new style.
List of custome R code: Supply a block of custom R code or a named list describing styles for each table section. This code must be specific to the selected table type. If style = NULL, the function will use global options (see setGlobalTableOptions()) or an existing ⁠_brand.yml⁠ file (if found); otherwise, the default style is applied. For more details, see the Styles vignette on the package website.

.options

A named list with additional formatting options. visOmopResults::tableOptions() shows allowed arguments and their default values.

Value

A formatted table of the class selected in "type" argument.

Examples

result <- mockSummarisedResult()
result |>
  visTable(
    estimateName = c("N%" = "<count> (<percentage>)",
                     "N" = "<count>",
                     "Mean (SD)" = "<mean> (<sd>)"),
    header = c("Estimate"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = c("strata_name", "strata_level"),
    hide = c("additional_name", "additional_level", "estimate_type", "result_type")
  )
result <- mockSummarisedResult()
result |>
  visTable(
    estimateName = c("N%" = "<count> (<percentage>)",
                     "N" = "<count>",
                     "Mean (SD)" = "<mean> (<sd>)"),
    header = c("Estimate"),
    rename = c("Database name" = "cdm_name"),
    groupColumn = c("strata_name", "strata_level"),
    hide = c("additional_name", "additional_level", "estimate_type", "result_type")
  )

Package 'visOmopResults'

Help Index

Create an alluvial plot visualisation from a data frame or a ⁠<summarised_result>⁠ object.

Description

Usage

Arguments

Value

Examples

Create a bar plot visualisation from a data frame or a ⁠<summarised_result>⁠ object.

Description

Usage

Arguments

Value

Examples

Create a box plot visualisation from a data frame or a ⁠<summarised_result>⁠ object.

Description

Usage

Arguments

Value

Examples

Apply styling to text or column names

Description

Usage

Arguments

Value

Examples

List of mock results

Description

Usage

Format

Returns an empty plot

Description

Usage

Arguments

Value

Examples

Returns an empty table

Description

Usage

Arguments

Value

Examples

Formats estimate_name and estimate_value column

Description

Usage

Arguments

Value

Examples

Formats the estimate_value column

Description

Usage

Arguments

Value

Examples

Create a header for gt and flextable objects

Description

Usage

Arguments

Value

Examples

To indicate which was the minimum cell counts where estimates have been suppressed.

Description

Usage

Arguments

Examples

Creates a flextable or gt object from a dataframe

Description

Usage

Arguments

Value

Examples

A ⁠<summarised_result>⁠ object filled with mock data

Description

Usage

Value

Examples

Columns for the plot functions

Description

Usage

Arguments

Create an alluvial plot visualisation from a data frame or a `⁠<summarised_result>⁠` object.

Create a bar plot visualisation from a data frame or a `⁠<summarised_result>⁠` object.

Create a box plot visualisation from a data frame or a `⁠<summarised_result>⁠` object.

A `⁠<summarised_result>⁠` object filled with mock data

Create a scatter plot visualisation from a data frame or a `⁠<summarised_result>⁠` object.

Additional table formatting options for `visOmopTable()` and `visTable()`

Generate a formatted table from a `⁠<summarised_result>⁠`

Generate a formatted table from a `⁠<data.table>⁠`