teal
module: Stack plots of variables and show association with reference variable
Source: R/tm_g_association.R
tm_g_association.Rd
Module provides functionality for visualizing the distribution of variables and their association with a reference variable. It supports configuring the appearance of the plots, including themes and whether to show associations.
Usage
tm_g_association(
label = "Association",
ref,
vars,
show_association = TRUE,
plot_height = c(600, 400, 5000),
plot_width = NULL,
distribution_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic",
"void"),
association_theme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic",
"void"),
pre_output = NULL,
post_output = NULL,
ggplot2_args = teal.widgets::ggplot2_args(),
decorators = NULL
)
Arguments
- label
(
character(1)
) Label shown in the navigation item for the module or module group. Formodules()
defaults to"root"
. SeeDetails
.- ref
(
data_extract_spec
orlist
of multipledata_extract_spec
) Reference variable, must accepts adata_extract_spec
withselect_spec(multiple = FALSE)
to ensure single selection option.- vars
(
data_extract_spec
orlist
of multipledata_extract_spec
) Variables to be associated with the reference variable.- show_association
(
logical
) optional, whether show association ofvars
with reference variable. Defaults toTRUE
.- plot_height
(
numeric
) optional, specifies the plot height as a three-element vector ofvalue
,min
, andmax
intended for use with a slider UI element.- plot_width
(
numeric
) optional, specifies the plot width as a three-element vector ofvalue
,min
, andmax
for a slider encoding the plot width.- distribution_theme, association_theme
(
character
) optional,ggplot2
themes to be used by default. Default to"gray"
.- pre_output
(
shiny.tag
) optional, text or UI element to be displayed before the module's output, providing context or a title. with text placed before the output to put the output into context. For example a title.- post_output
(
shiny.tag
) optional, text or UI element to be displayed after the module's output, adding context or further instructions. Elements likeshiny::helpText()
are useful.- ggplot2_args
-
(
ggplot2_args
) optional, object created byteal.widgets::ggplot2_args()
with settings for all the plots or named list ofggplot2_args
objects for plot-specific settings. The argument is merged with options variableteal.ggplot2_args
and default module setup.List names should match the following:
c("default", "Bivariate1", "Bivariate2")
.For more details see the vignette:
vignette("custom-ggplot2-arguments", package = "teal.widgets")
. - decorators
-
(
list
ofteal_transform_module
, namedlist
ofteal_transform_module
orNULL
) optional, if notNULL
, decorator for tables or plots included in the module. When a named list ofteal_transform_module
, the decorators are applied to the respective output objects.Otherwise, the decorators are applied to all objects, which is equivalent as using the name
default
.See section "Decorating
tm_g_association
" below for more details.
Note
For more examples, please see the vignette "Using association plot" via
vignette("using-association-plot", package = "teal.modules.general")
.
Decorating tm_g_association
This module generates the following objects, which can be modified in place using decorators:
plot
(grob
created withggplot2::ggplotGrob()
)
For additional details and examples of decorators, refer to the vignette
vignette("decorate-modules-output", package = "teal")
or the teal::teal_transform_module()
documentation.
Examples
# general data example
data <- teal_data()
data <- within(data, {
require(nestcolor)
CO2 <- CO2
factors <- names(Filter(isTRUE, vapply(CO2, is.factor, logical(1L))))
CO2[factors] <- lapply(CO2[factors], as.character)
})
app <- init(
data = data,
modules = modules(
tm_g_association(
ref = data_extract_spec(
dataname = "CO2",
select = select_spec(
label = "Select variable:",
choices = variable_choices(data[["CO2"]], c("Plant", "Type", "Treatment")),
selected = "Plant",
fixed = FALSE
)
),
vars = data_extract_spec(
dataname = "CO2",
select = select_spec(
label = "Select variables:",
choices = variable_choices(data[["CO2"]], c("Plant", "Type", "Treatment")),
selected = "Treatment",
multiple = TRUE,
fixed = FALSE
)
)
)
)
)
#> Initializing tm_g_association
#> Initializing reporter_previewer_module
if (interactive()) {
shinyApp(app$ui, app$server)
}
# CDISC data example
data <- teal_data()
data <- within(data, {
require(nestcolor)
ADSL <- teal.data::rADSL
})
join_keys(data) <- default_cdisc_join_keys[names(data)]
app <- init(
data = data,
modules = modules(
tm_g_association(
ref = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variable:",
choices = variable_choices(
data[["ADSL"]],
c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
),
selected = "RACE",
fixed = FALSE
)
),
vars = data_extract_spec(
dataname = "ADSL",
select = select_spec(
label = "Select variables:",
choices = variable_choices(
data[["ADSL"]],
c("SEX", "RACE", "COUNTRY", "ARM", "STRATA1", "STRATA2", "ITTFL", "BMRKR2")
),
selected = "BMRKR2",
multiple = TRUE,
fixed = FALSE
)
)
)
)
)
#> Initializing tm_g_association
#> Initializing reporter_previewer_module
if (interactive()) {
shinyApp(app$ui, app$server)
}