Customization

library(shinydataviewer)
library(shiny)
library(bslib)
#> 
#> Attaching package: 'bslib'
#> The following object is masked from 'package:utils':
#> 
#>     page
library(reactable)

The module exposes a small set of customization hooks intended to balance drop-in defaults with downstream flexibility.

Table behavior

data_viewer_server() exposes first-class arguments for common table controls:

• searchable
• filterable
• sortable
• default_page_size
• page_size_options

For lower-level reactable() overrides, use reactable_args.

default_page_size must be one of the values supplied in page_size_options, and page_size_options must contain positive integers.

data_viewer_server(
  "viewer",
  data = reactive(mtcars),
  searchable = TRUE,
  filterable = FALSE,
  sortable = TRUE,
  default_page_size = 25,
  page_size_options = c(25, 50, 100),
  reactable_args = list(
    showPageInfo = FALSE
  )
)

Table controls position

The UI helpers support top or bottom table controls:

data_viewer_card_ui(
  "viewer",
  table_controls_position = "bottom"
)

Custom summary cards

Use summary_card_fn to replace the default variable card renderer while keeping the module’s summary computation and table logic.

The custom function must accept at least summary_row and index, where summary_row is a one-row data frame produced by summarize_columns().

custom_summary_card <- function(summary_row, index) {
  htmltools::tags$div(
    class = "custom-summary-card",
    htmltools::tags$strong(summary_row$var_name[[1]]),
    htmltools::tags$span(sprintf(" (%s)", summary_row$type[[1]]))
  )
}

data_viewer_server(
  "viewer",
  data = reactive(iris),
  summary_card_fn = custom_summary_card
)

A typical use case is treating identifier-like columns differently from ordinary categorical fields, for example by suppressing the mini chart and showing a “High cardinality” badge instead.

The module validates unsupported column classes early, so custom summary-card logic can assume the incoming summary_row corresponds to one of the supported viewer types.

Theme integration

The module styles use Bootstrap variables, so they follow the active bslib theme and brand.yml values automatically.

ui <- page_fillable(
  theme = bs_theme(version = 5, brand = "brand.yml"),
  data_viewer_card_ui("viewer")
)