--- title: "Using cross table" author: "NEST CoreDev" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Using cross table} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- # `teal` application to use cross table with various datasets types This vignette will guide you through the four parts to create a `teal` application using various types of datasets using the cross table module `tm_t_crosstable()`: 1. Load libraries 2. Create data sets 3. Create an `app` variable 4. Run the app ## 1 - Load libraries ```{r library, echo=TRUE, message=FALSE, warning=FALSE, results="hide"} library(teal.modules.general) # used to create the app library(dplyr) # used to modify data sets library(rtables) ``` ## 2 - Create data sets Inside this app 2 datasets will be used 1. `ADSL` A wide data set with subject data 2. `ADLB` A long data set with lab measurements for each subject ```{r data, echo=TRUE, message=FALSE, warning=FALSE, results="hide", echo=2:6} data <- teal_data() data <- within(data, { ADSL <- teal.modules.general::rADSL ADLB <- teal.modules.general::rADLB %>% mutate(CHGC = as.factor(case_when( CHG < 1 ~ "N", CHG > 1 ~ "P", TRUE ~ "-" ))) }) join_keys(data) <- default_cdisc_join_keys[names(data)] ``` ## 3 - Create an `app` variable This is the most important section. We will use the `teal::init()` function to create an app. The data will be handed over using `teal.data::teal_data()`. The app itself will be constructed by multiple calls of `tm_t_crosstable()` using different combinations of data sets. ```{r app, echo=TRUE, message=FALSE, warning=FALSE, results="hide"} # configuration for the single wide dataset mod1 <- tm_t_crosstable( label = "Single wide dataset", x = data_extract_spec( "ADSL", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADSL"]]), selected = names(data[["ADSL"]])[5], multiple = TRUE, fixed = FALSE, ordered = TRUE ) ), y = data_extract_spec( "ADSL", select = select_spec( label = "Select variable:", choices = variable_choices(data[["ADSL"]]), selected = names(data[["ADSL"]])[6], multiple = FALSE, fixed = FALSE ) ) ) # configuration for the same long datasets (different subsets) mod2 <- tm_t_crosstable( label = "Same long datasets (different subsets)", x = data_extract_spec( dataname = "ADLB", filter = filter_spec( vars = "PARAMCD", choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"), selected = levels(data[["ADLB"]]$PARAMCD)[1], multiple = FALSE ), select = select_spec( choices = variable_choices(data[["ADLB"]]), selected = "AVISIT", multiple = TRUE, fixed = FALSE, ordered = TRUE, label = "Select variable:" ) ), y = data_extract_spec( dataname = "ADLB", filter = filter_spec( vars = "PARAMCD", choices = value_choices(data[["ADLB"]], "PARAMCD", "PARAM"), selected = levels(data[["ADLB"]]$PARAMCD)[1], multiple = FALSE ), select = select_spec( choices = variable_choices(data[["ADLB"]]), selected = "LOQFL", multiple = FALSE, fixed = FALSE, label = "Select variable:" ) ) ) # initialize the app app <- init( data = data, modules = modules( modules( label = "Cross table", mod1, mod2 ) ) ) ``` ## 4 - Run the app A simple `shiny::shinyApp()` call will let you run the app. Note that app is only displayed when running this code inside an `R` session. ```{r shinyapp, echo=TRUE, results="hide", eval=base::interactive()} shinyApp(app$ui, app$server, options = list(height = 1024, width = 1024)) ``` ## 5 - Try it out in Shinylive ```{r shinylive_url, echo = FALSE, results = 'asis', eval = requireNamespace("roxy.shinylive", quietly = TRUE)} code <- paste0(c( knitr::knit_code$get("library"), knitr::knit_code$get("data"), knitr::knit_code$get("app"), knitr::knit_code$get("shinyapp") ), collapse = "\n") url <- roxy.shinylive::create_shinylive_url(code) cat(sprintf("[Open in Shinylive](%s)\n\n", url)) ``` ```{r shinylive_iframe, echo = FALSE, out.width = '150%', out.extra = 'style = "position: relative; z-index:1"', eval = requireNamespace("roxy.shinylive", quietly = TRUE) && knitr::is_html_output() && identical(Sys.getenv("IN_PKGDOWN"), "true")} knitr::include_url(url, height = "800px") ```