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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.

R-CMD-check CRAN Status Badge License: MIT

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 cellsβ€”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: πŸ‘‰ 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:

Dual Engine Profile Selection

1. dtsmartr() β€” 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() β€” 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

πŸš€ Premium UX & UI Enhancements (v0.4.0)

πŸ†• Grid Layout Enhancements (v0.3.0)


πŸ“Š Core Data Engine Features


πŸ’» Code Export & Ingestion


βš™οΈ 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] 
    β”‚
    β–Ό  (Apache Arrow C++ Engine)
[Arrow RecordBatch Stream]
    β”‚
    β–Ό  (base64enc C-Library)
[Base64 Arrow IPC Payload] ---> Written directly into the HTMLWidget structure
                                    β”‚
                                    β–Ό (React App on Page Load)
                                [Uint8Array Decode]
                                    β”‚
                                    β–Ό (apache-arrow JS Library)
                                [Arrow Columnar Table]
                                    β”‚
                                    β–Ό
                                [Virtualized Grid View]

πŸ“¦ 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"
  )
)

πŸ“„ License

Licensed under the MIT License.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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