teal module: Univariate and bivariate visualizations — tm_g

Module enables the creation of univariate and bivariate plots, facilitating the exploration of data distributions and relationships between two variables.

Usage

tm_g_bivariate(
  label = "Bivariate Plots",
  x = teal.picks::picks(teal.picks::datasets(), teal.picks::variables(choices =
    is.numeric | teal.picks::is_categorical(min.len = 2, max.len = 10), selected = 1L),
    teal.picks::values()),
  y,
  row_facet,
  col_facet,
  facet,
  color = NULL,
  fill = NULL,
  size = NULL,
  use_density = FALSE,
  color_settings = FALSE,
  free_x_scales = FALSE,
  free_y_scales = FALSE,
  plot_height = c(600, 200, 2000),
  plot_width = NULL,
  rotate_xaxis_labels = FALSE,
  swap_axes = FALSE,
  ggtheme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"),
  ggplot2_args = teal.widgets::ggplot2_args(),
  pre_output = NULL,
  post_output = NULL,
  transformators = list(),
  decorators = list()
)

Arguments

label

(character(1)) Label shown in the navigation item for the module or module group. For modules() defaults to "root". See Details.

x

(picks) Variable specification for the x-axis. Created using teal.picks::picks(). Can be numeric, factor or character. No empty selections are allowed.

y

(picks) Variable specification for the y-axis. Created using teal.picks::picks(). Can be numeric, factor or character.

row_facet

(picks) optional, specification of the data variable(s) to use for faceting rows. Created using teal.picks::picks().

col_facet

(picks) optional, specification of the data variable(s) to use for faceting columns. Created using teal.picks::picks().

facet

(logical) optional, specifies whether the facet encodings ui elements are toggled on and shown to the user by default. Defaults to TRUE if either row_facet or column_facet are supplied.

color

(picks) optional, specification of the data variable(s) selected for the outline color inside the coloring settings. It will be applied when color_settings is set to TRUE. Created using teal.picks::picks().

fill

(picks) optional, specification of the data variable(s) selected for the fill color inside the coloring settings. It will be applied when color_settings is set to TRUE. Created using teal.picks::picks().

size

(picks) optional, specification of the data variable(s) selected for the size of geom_point plots inside the coloring settings. It will be applied when color_settings is set to TRUE. Created using teal.picks::picks().

use_density

(logical) optional, indicates whether to plot density (TRUE) or frequency (FALSE). Defaults to frequency (FALSE).

color_settings

(logical) Whether coloring, filling and size should be applied and UI tool offered to the user.

free_x_scales

(logical) optional, whether X scaling shall be changeable. Does not allow scaling to be changed by default (FALSE).

free_y_scales

(logical) optional, whether Y scaling shall be changeable. Does not allow scaling to be changed by default (FALSE).

plot_height

(numeric) optional, specifies the plot height as a three-element vector of value, min, and max intended for use with a slider UI element.

plot_width

(numeric) optional, specifies the plot width as a three-element vector of value, min, and max for a slider encoding the plot width.

rotate_xaxis_labels

(logical) optional, whether to rotate plot X axis labels. Does not rotate by default (FALSE).

swap_axes

(logical) optional, whether to swap X and Y axes. Defaults to FALSE.

ggtheme

(character) optional, ggplot2 theme to be used by default. Defaults to "gray".

ggplot2_args

(ggplot2_args) object created by teal.widgets::ggplot2_args() with settings for the module plot. The argument is merged with options variable teal.ggplot2_args and default module setup.

For more details see the vignette: vignette("custom-ggplot2-arguments", package = "teal.widgets")

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 like shiny::helpText() are useful.

transformators

(list of teal_transform_module) that will be applied to transform module's data input. To learn more check vignette("transform-input-data", package = "teal").

decorators

(named list of lists of teal_transform_module) optional, decorator for tables or plots included in the module output reported. The decorators are applied to the respective output objects.

Value

Object of class teal_module to be used in teal applications.

Details

This is a general module to visualize 1 & 2 dimensional data.

Note

For more examples, please see the vignette "Using bivariate plot" via vignette("using-bivariate-plot", package = "teal.modules.general").

Decorating Module

This module generates the following objects, which can be modified in place using decorators:

plot (ggplot)

A Decorator is applied to the specific output using a named list of teal_transform_module objects. The name of this list corresponds to the name of the output to which the decorator is applied. See code snippet below:

tm_g_bivariate(
   ..., # arguments for module
   decorators = list(
     plot = teal_transform_module(...) # applied to the `plot` output
   )
)

For additional details and examples of decorators, refer to the vignette vignette("decorate-module-output", package = "teal.modules.general").

To learn more please refer to the vignette vignette("transform-module-output", package = "teal") or the teal::teal_transform_module() documentation.

Reporting

This module returns an object of class teal_module, that contains a server function. Since the server function returns a teal_report object, this makes this module reportable, which means that the reporting functionality will be turned on automatically by the teal framework.

For more information on reporting in teal, see the vignettes:

vignette("reportable-shiny-application", package = "teal.reporter")
vignette("adding-support-for-reporting-to-custom-modules", package = "teal")

Examples in Shinylive

example-1: Open in Shinylive
example-2: Open in Shinylive

Examples

# general data example
data <- teal_data()
data <- within(data, {
  require(nestcolor)
  CO2 <- data.frame(CO2)
})

app <- init(
  data = data,
  modules = tm_g_bivariate(
    label = "Bivariate Plots",
    x = teal.picks::picks(
      datasets("CO2"),
      teal.picks::variables(selected = "conc")
    ),
    y = teal.picks::picks(
      datasets("CO2"),
      teal.picks::variables(selected = "uptake")
    ),
    row_facet = teal.picks::picks(
      datasets("CO2"),
      teal.picks::variables(selected = "Type")
    ),
    col_facet = teal.picks::picks(
      datasets("CO2"),
      teal.picks::variables(selected = "Treatment")
    )
  )
)
#> Warning: teal.picks::variables(selected = "conc")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
#> Initializing tm_g_bivariate
#> Warning: teal.picks::variables(selected = "uptake")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
#> Warning: teal.picks::variables(selected = "Type")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
#> Warning: teal.picks::variables(selected = "Treatment")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
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 = tm_g_bivariate(
    label = "Bivariate Plots",
    x = teal.picks::picks(
      datasets("ADSL"),
      teal.picks::variables(selected = "AGE")
    ),
    y = teal.picks::picks(
      datasets("ADSL"),
      teal.picks::variables(selected = "SEX")
    ),
    row_facet = teal.picks::picks(
      datasets("ADSL"),
      teal.picks::variables(selected = "ARM")
    ),
    col_facet = teal.picks::picks(
      datasets("ADSL"),
      teal.picks::variables(selected = "COUNTRY")
    )
  )
)
#> Warning: teal.picks::variables(selected = "AGE")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
#> Initializing tm_g_bivariate
#> Warning: teal.picks::variables(selected = "SEX")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
#> Warning: teal.picks::variables(selected = "ARM")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
#> Warning: teal.picks::variables(selected = "COUNTRY")
#>  - Setting explicit `selected` while `choices` are delayed (set using `tidyselect`) doesn't guarantee that `selected` is a subset of `choices`.
if (interactive()) {
  shinyApp(app$ui, app$server)
}