teal.modules.general (version 0.3.0)

tm_g_response: teal module: Response plot

Description

Generates a response plot for a given response and x variables. This module allows users customize and add annotations to the plot depending on the module's arguments. It supports showing the counts grouped by other variable facets (by row / column), swapping the coordinates, show count annotations and displaying the response plot as frequency or density.

Usage

tm_g_response(
  label = "Response Plot",
  response,
  x,
  row_facet = NULL,
  col_facet = NULL,
  coord_flip = FALSE,
  count_labels = TRUE,
  rotate_xaxis_labels = FALSE,
  freq = FALSE,
  plot_height = c(600, 400, 5000),
  plot_width = NULL,
  ggtheme = c("gray", "bw", "linedraw", "light", "dark", "minimal", "classic", "void"),
  ggplot2_args = teal.widgets::ggplot2_args(),
  pre_output = NULL,
  post_output = NULL
)

Value

Object of class teal_module to be used in teal applications.

Arguments

label

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

response

(data_extract_spec or list of multiple data_extract_spec) Which variable to use as the response. You can define one fixed column by setting fixed = TRUE inside the select_spec.

The data_extract_spec must not allow multiple selection in this case.

x

(data_extract_spec or list of multiple data_extract_spec) Specifies which variable to use on the X-axis of the response plot. Allow the user to select multiple columns from the data allowed in teal.

The data_extract_spec must not allow multiple selection in this case.

row_facet

(data_extract_spec or list of multiple data_extract_spec) optional specification of the data variable(s) to use for faceting rows.

col_facet

(data_extract_spec or list of multiple data_extract_spec) optional specification of the data variable(s) to use for faceting columns.

coord_flip

(logical(1)) Indicates whether to flip coordinates between x and response. The default value is FALSE and it will show the x variable on the x-axis and the response variable on the y-axis.

count_labels

(logical(1)) Indicates whether to show count labels. Defaults to TRUE.

rotate_xaxis_labels

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

freq

(logical(1)) Indicates whether to display frequency (TRUE) or density (FALSE). Defaults to density (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.

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.

Examples

# general data example
library(teal.widgets)

data <- teal_data()
data <- within(data, {
  require(nestcolor)
  mtcars <- mtcars
  for (v in c("cyl", "vs", "am", "gear")) {
    mtcars[[v]] <- as.factor(mtcars[[v]])
  }
})
datanames(data) <- "mtcars"

app <- init(
  data = data,
  modules = modules(
    tm_g_response(
      label = "Response Plots",
      response = data_extract_spec(
        dataname = "mtcars",
        select = select_spec(
          label = "Select variable:",
          choices = variable_choices(data[["mtcars"]], c("cyl", "gear")),
          selected = "cyl",
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      x = data_extract_spec(
        dataname = "mtcars",
        select = select_spec(
          label = "Select variable:",
          choices = variable_choices(data[["mtcars"]], c("vs", "am")),
          selected = "vs",
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      ggplot2_args = ggplot2_args(
        labs = list(subtitle = "Plot generated by Response Module")
      )
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}

# CDISC data example
library(teal.widgets)

data <- teal_data()
data <- within(data, {
  require(nestcolor)
  ADSL <- rADSL
})
datanames(data) <- c("ADSL")
join_keys(data) <- default_cdisc_join_keys[datanames(data)]

app <- init(
  data = data,
  modules = modules(
    tm_g_response(
      label = "Response Plots",
      response = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variable:",
          choices = variable_choices(data[["ADSL"]], c("BMRKR2", "COUNTRY")),
          selected = "BMRKR2",
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      x = data_extract_spec(
        dataname = "ADSL",
        select = select_spec(
          label = "Select variable:",
          choices = variable_choices(data[["ADSL"]], c("SEX", "RACE")),
          selected = "RACE",
          multiple = FALSE,
          fixed = FALSE
        )
      ),
      ggplot2_args = ggplot2_args(
        labs = list(subtitle = "Plot generated by Response Module")
      )
    )
  )
)
if (interactive()) {
  shinyApp(app$ui, app$server)
}