dtsmartr

An interactive, ultra-responsive, and high-fidelity data explorer widget for clinical programming (CDISC SDTM/ADaM) and general R data frames, built on a virtualized React grid backend.

dtsmartr is a premium, Kaggle-style data browser package for R. Leveraging a virtualized React rendering engine and a custom Base64 Apache Arrow IPC serialization pipeline, it delivers instantaneous rendering and fluid scrolling on tables containing millions of cells—directly inside the RStudio/Positron Viewer pane, embedded in Shiny, or exported as offline-capable HTML reports.

🌐 Documentation & Live Website

For step-by-step installation guides, API reference sheets, and feature articles, visit our official documentation site: 👉 https://wagh-nikhil.github.io/dtsmartr/

🏎️ Dual-Engine Profiles: Choose Your Mode

Depending on the scale of your dataset and analytical needs, dtsmartr offers two tailored frontend engines:

1. dtsmartr() — Full Analytics Mode (Default)

Enables the complete suite of analytical features, designed for deep exploration: * Micro-Dashboard Headers: Live histograms, stacked categorical bars, and data completeness progress bars. * Insights Drawer: Interactive SVG distribution histograms and Pareto charts. * Query Builder: Multi-rule, nested Boolean logic filters (AND/OR). * Code Export: Code generation for Base R, dplyr, SQL, and Apache Arrow.

2. dtsmart_lite() — Minimalist Viewer Mode

Forces a compact, ultra-clean grid layout optimized for raw scrolling performance and minimal memory footprint: * Flat Headers: Hides distributions, progress bars, and stats from column headers to maximize visible grid space. * Analytics Disabled: Hides the Advanced Query Builder, Insights Drawer, and Code Export controls. * High Refresh Rate: Streamlines the DOM footprint to ensure maximum scrolling velocity on huge data structures.

🎨 Comprehensive Feature Matrix

🚀 Premium UX & UI Enhancements (v0.4.0)

• Responsive Header & Row Density Modes: Toggle header sizing (≡ Min / ≡ Auto / ≡ Detail) and row padding (Compact / Standard / Comfort) directly in the toolbar. Row height scales dynamically (24px → 32px → 40px), doubling screen layout capacity. Density modes can also be configured programmatically from R.
• Smart Sparkline & Badge Sizing: Low-variance, constant, and binary columns automatically display clean descriptive summary badges (🔒 Constant, ⚖️ CV) or binary stacked bars instead of full histograms to maximize screen estate.
• Collapsible Right-Sidebar Filter Drawer: Replaces the blocking full-screen advanced filter modal with a 350px right-sidebar drawer. Features Live Preview Highlighting (rows matching draft rules highlighted in yellow in real-time) and live match counters.
• Shift+Click Multi-Column Sorting: Chain sort conditions directly by clicking headers (Shift+Click) showing priority badges (1️⃣ ↑, 2️⃣ ↓) and a toolbar sort chain display.
• Compact Toolbar Icon Buttons: Replaced large text-based buttons with clean SVG icons for label toggle, filter sidebar, query code, and column picker.
• Keyboard Shortcuts Cheatsheet: Press ? to open the overlay cheatsheet modal. Shortcuts include Ctrl+Alt+F for filter, Ctrl+Shift+[ / ] for density, and Ctrl+Shift+F to clear.

🆕 Grid Layout Enhancements (v0.3.0)

• Interactive Column Freezing & Anchoring (⚓): Click the anchor symbol in any column header to freeze that column and all columns to its left. Sticky cells remain fixed on the left while you scroll horizontally.
• Visual Freeze Divider: Draws a prominent vertical blue line (3px solid #3b82f6) along the frozen boundary across the header and all body cells.
• HTML5 Drag-and-Drop Column Reordering: Grab any column header and drag it horizontally to reposition it dynamically. The virtualized body cells and headers rerender instantly.
• Clean Control Isolation: Separated sorting controls (⇅) from quick-filter popovers (≡) on header cards to prevent accidental clicks.

📊 Core Data Engine Features

• Auto-Sniffing Data Badges: Headers automatically identify and display data types (e.g., # for numeric, a for character, L for logical, 📅 for date-time).
• Variable Metadata Label Overlays: Automatically extracts R variable label attributes (highly common in CDISC SDTM/ADaM datasets) and renders them as clear sub-headers.
• Advanced Boolean Query Builder (AND/OR): Build complex, nested filter conditions using searchable checkbox checklists for categorical variables, calendar pickers for date-time fields, and numeric range inputs.
• Auto Text-Wrapping: Text wraps neatly within cell boundaries to ensure complete data visibility without manual column widening.
• Sticky Row Pinning (📌): Click any row to lock it to the top of the grid with a soft-gold highlight, keeping key subjects or records visible.

💻 Code Export & Ingestion

• Universal Reproducible Code Generator: Converts your interactive grid filters into copy-pasteable, production-ready code with a single click:
  • Base R: df[df$AGE > 50 & df$SEX == "F", ]
  • dplyr: df %>% filter(AGE > 50, SEX == "F")
  • SQL: SELECT * FROM df WHERE AGE > 50 AND SEX = 'F'
  • Apache Arrow: df |> filter(AGE > 50) |> collect()
• dtsmart_launch() Data Ingestion Wizard: Start a local uploader wizard to drag-and-drop local Excel, CSV, RDS, or SAS (.sas7bdat) files directly into the grid.
• 50,000+ Row Safety Guardrail: Prevents IDE viewer pane freezes. If a dataset exceeds 50,000 rows during an interactive session, it automatically redirects the explorer to an external web browser.

⚙️ High-Performance Architecture Roadmap

Our serialization protocol is engineered for speed. In version 0.3.0, dtsmartr transitioned to a high-speed Apache Arrow IPC Binary Stream Serialization pipeline:

[R Data Frame] 
    │
    ▼  (Apache Arrow C++ Engine)
[Arrow RecordBatch Stream]
    │
    ▼  (base64enc C-Library)
[Base64 Arrow IPC Payload] ---> Written directly into the HTMLWidget structure
                                    │
                                    ▼ (React App on Page Load)
                                [Uint8Array Decode]
                                    │
                                    ▼ (apache-arrow JS Library)
                                [Arrow Columnar Table]
                                    │
                                    ▼
                                [Virtualized Grid View]

• Instant Load Times: Replaces slow JSON formatting with a binary stream. Large datasets load up to 10x faster.
• Columnar Layout Alignment: Keeps columns stored sequentially in memory, enabling lightning-fast virtualized data projection and filtering.
• Minimal Memory Overhead: Eliminates the double-memory allocation typical of nested JSON arrays.

📦 Installation & Quick Start

Installation

Install the package directly from GitHub using remotes:

# Install remotes if needed
if (!requireNamespace("remotes", quietly = TRUE)) {
  install.packages("remotes")
}

# Install the latest dev version
remotes::install_github("wagh-nikhil/dtsmartr")

Quick Start

Fire up the grid on standard datasets in one line:

library(dtsmartr)

# 1. Full Analytics Mode (Default)
dtsmartr(mtcars)

# 2. Minimalist Viewer Mode (Clean, compact layout)
dtsmart_lite(iris, title = "Iris Compact View")

# 3. Custom configurations (Dark theme, pre-hidden variables)
dtsmartr(
  data = mtcars,
  options = dtsmartr_options(
    theme = "dark",
    hidden_columns = c("cyl", "hp"),
    na_string = "Missing"
  )
)

📄 License

Licensed under the MIT License.

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