teal.transform (version 0.5.0)

data_extract_ui: teal data extraction module user-interface

Description

Usage

data_extract_ui(id, label, data_extract_spec, is_single_dataset = FALSE)

Value

Shiny shiny::selectInputs that allow to define how to extract data from a specific dataset. The input elements will be returned inside a shiny::div container.

Arguments

id

(character) shiny input unique identifier.

label

(character) Label above the data extract input.

data_extract_spec

(list of data_extract_spec) This is the outcome of listing data_extract_spec() constructor calls.

is_single_dataset

(logical) FALSE to display the dataset widget.

Details

There are three inputs that will be rendered

1. Dataset select Optional. If more than one data_extract_spec is handed over to the function, a shiny shiny::selectInput will be rendered. Else just the name of the dataset is given.

2. Filter Panel Optional. If the data_extract_spec contains a filter element a shiny shiny::selectInput will be rendered with the options to filter the dataset.

3. Select panel A shiny shiny::selectInput to select columns from the dataset to go into the analysis.

The output can be analyzed using data_extract_srv(...).

This functionality should be used in the encoding panel of your teal app. It will allow app-developers to specify a data_extract_spec() object. This object should be used to teal module variables being filtered data from CDISC datasets.

You can use this function in the same way as any shiny module UI. The corresponding server module can be found in data_extract_srv().

Examples

library(shiny)
library(teal.widgets)

adtte_filters <- filter_spec(
  vars = c("PARAMCD", "CNSR"),
  sep = "-",
  choices = c("OS-1" = "OS-1", "OS-0" = "OS-0", "PFS-1" = "PFS-1"),
  selected = "OS-1",
  multiple = FALSE,
  label = "Choose endpoint and Censor"
)

response_spec <- data_extract_spec(
  dataname = "ADTTE",
  filter = adtte_filters,
  select = select_spec(
    choices = c("AVAL", "BMRKR1", "AGE"),
    selected = c("AVAL", "BMRKR1"),
    multiple = TRUE,
    fixed = FALSE,
    label = "Column"
  )
)
# Call to use inside your teal module UI function
standard_layout(
  output = tableOutput("table"),
  encoding = div(
    data_extract_ui(
      id = "regressor",
      label = "Regressor Variable",
      data_extract_spec = response_spec
    )
  )
)