shinydataviewer provides a reusable Shiny module for viewing tabular data with a searchable table and a variable summary sidebar inspired by the Positron data viewer.

Installation
Install shinydataviewer from CRAN:
install.packages("shinydataviewer")You can install the development version from GitHub:
pak::pak("Ryan-W-Harrison/shinydataviewer")Package interface
shinydataviewer is designed to be used as a reusable Shiny module. The main exported functions are:
data_viewer_ui(id)data_viewer_server(id, data)data_viewer_card_ui(id, title = NULL)summarize_columns(df)
data should be a reactive expression that returns a data.frame. Supported column classes are numeric, integer, character, factor, logical, Date, and POSIXct/POSIXt.
Minimal module example
Use the module directly when you want the viewer layout to manage its own main table region:
library(shiny)
library(bslib)
library(shinydataviewer)
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 example
Use data_viewer_card_ui() when the viewer needs to live inside a larger dashboard or reporting layout:
library(shiny)
library(bslib)
library(shinydataviewer)
ui <- page_fillable(
theme = bs_theme(version = 5),
layout_columns(
col_widths = c(4, 8),
card(
card_header("Context"),
card_body("Supporting content goes here.")
),
card(
card_header("Dataset"),
card_body(
fill = TRUE,
data_viewer_card_ui("viewer", title = NULL, full_screen = FALSE)
)
)
)
)
server <- function(input, output, session) {
data_viewer_server(
"viewer",
data = reactive(mtcars)
)
}
shinyApp(ui, server)An additional runnable example is included at inst/examples/embedded-card-example.R.
Theming and branding
The viewer styles are attached as a package dependency and use Bootstrap 5 theme variables instead of fixed colors. In practice, that means the module will follow the active bslib theme and should pick up branding supplied through bs_theme() or a brand.yml-driven theme without additional module-specific configuration.
ui <- page_fillable(
theme = bs_theme(
version = 5,
brand = "brand.yml"
),
data_viewer_card_ui("viewer")
)Data summary helper
If you want access to the same summary data used by the module’s variable panel, you can call summarize_columns() directly:
summarize_columns(iris)The returned data frame has one row per input column. Its summary_stats and distribution_data list-columns contain the same precomputed payloads used by the sidebar cards, including compact statistics, histogram bins, and top-level categorical counts.
