--- title: "Get Started" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Get Started} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ``` ```{r setup} library(shinydataviewer) library(shiny) library(bslib) ``` `shinydataviewer` provides a reusable Shiny module for viewing data with: - a `reactable` data viewer - a variable summary sidebar - Bootstrap 5 compatible styling via `bslib` The module supports data frames with numeric, integer, character, factor, logical, `Date`, and `POSIXct`/`POSIXt` columns. Non-finite numeric values such as `Inf`, `-Inf`, and `NaN` are excluded from numeric summary statistics and histogram bins. ## Interface preview ```{r, echo = FALSE, out.width = "100%", fig.cap = "The data viewer combines per-variable summary cards with a searchable table."} knitr::include_graphics("figures/screenshot.png") ``` ## Minimal module Use `data_viewer_ui()` when the viewer should manage its own table card. ```{r eval = FALSE} ui <- page_fillable( theme = bs_theme(version = 5), data_viewer_ui("viewer") ) server <- function(input, output, session) { data_viewer_server( "viewer", data = reactive(iris) ) } shinyApp(ui, server) ``` ## Embedded card Use `data_viewer_card_ui()` when the viewer belongs inside another layout. ```{r eval = FALSE} ui <- page_fillable( theme = bs_theme(version = 5), layout_columns( col_widths = c(4, 8), card( card_header("Context"), card_body("Supporting content") ), data_viewer_card_ui( "viewer", title = "Dataset", full_screen = FALSE ) ) ) server <- function(input, output, session) { data_viewer_server( "viewer", data = reactive(mtcars) ) } shinyApp(ui, server) ``` ## Summary helper The variable sidebar is backed by `summarize_columns()`. ```{r} summary_df <- summarize_columns(head(iris), top_n = 4) summary_df[c("var_name", "type", "n_missing", "n_unique")] ``` `summarize_columns()` returns one row per input column. Its `summary_stats` and `distribution_data` list-columns contain the precomputed payloads used by the viewer cards, including detail statistics, categorical top-level counts, and compact histogram metadata. ## Example app A runnable embedded example is included at `inst/examples/embedded-card-example.R`.