Shiny: Highlighting DT Rows

2026-02-21 · Source: OR in an OB World · Field: Technology & Digital — Software Development & Engineering, Data Science & Analytics · Depth: Intermediate, quick

Summary

A Shiny application demonstration highlights rows in a DT data table based on user-selected criteria. The demo uses a portion of the `mtcars` dataset and allows users to select rows for highlighting via `checkboxGroupInput` controls. The implementation addresses challenges related to event observation and formatting persistence, specifically when no rows are selected. It employs an `observe()` function instead of `observeEvent()` to detect changes, including when all checkboxes are deselected, and utilizes an `if-else` structure within a `highlightRows()` function to conditionally apply formatting. The underlying DataTables library uses zero-based indexing for columns, which is reflected in the formatting code, and `reactiveVal()` is incorporated, though its necessity in the demo is noted as potentially optional.

Key takeaway

For Shiny developers building interactive data tables with conditional row highlighting, ensure your event observers correctly detect when all selection criteria are removed. Implement an `if-else` logic to explicitly apply or clear row formatting based on selection status. This prevents persistent highlighting when no rows should be marked, improving user experience and application responsiveness.

Key insights

Conditional row highlighting in Shiny DT tables requires careful event observation and zero-based indexing.

Principles

• DataTables uses zero-based indexing.
• Conditional formatting needs explicit clearing.

Method

Use `observe()` for `checkboxGroupInput` changes, and an `if-else` structure to apply row formatting only when selections exist, ensuring formatting clears when no rows are selected.

In practice

• Use `observe()` for `input$selected` changes.
• Apply `if-else` for conditional row formatting.
• Specify columns as `0:(ncol(df) - 1)`.

Topics

• Shiny Applications
• DT Library
• Row Highlighting
• Reactive Programming
• AI Code Assistance

Best for: Software Engineer, Data Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by OR in an OB World.