Open Source · CRAN Package

gwalkr(data) = Interactive Data-Viz App in your RStudio

One line of R code. A full visual analytics experience.

Turn any R data frame into an interactive, drag-and-drop visualization app — right inside RStudio. No ggplot syntax to memorize, no Shiny app to build. Just call gwalkr() and start exploring.

700+
GitHub Stars
80K+
CRAN Downloads
Apache-2.0
Open Source
$install.packages("GWalkR")
GWalkR interface preview
Quick Start

Up and Running in 30 Seconds

Install from CRAN and call gwalkr() on any data frame. That's it.

01Install from CRAN

install.packages("GWalkR")

02Explore a dataset

library(GWalkR) data(iris) gwalkr(iris)

03Handle large data

gwalkr(large_df, kernelComputation = TRUE)
Why GWalkR

EDA Shouldn't Require 50 Lines of ggplot

R has the most powerful statistical computing ecosystem in the world. But exploratory visualization? That still means writing verbose ggplot code, tweaking aesthetics, and re-running scripts for every new angle. GWalkR changes that.

Zero Syntax Overhead

No aes(), no geom_*, no coord_flip(). Drag fields onto shelves and the chart renders instantly. Spend time thinking about your data, not your code.

Native RStudio Integration

GWalkR renders directly in the RStudio Viewer pane as an htmlwidget. It fits your existing R workflow — no external apps, no browser tabs, no context switching.

From Exploration to Presentation

Built charts are embeddable in R Markdown and Quarto documents. Go from initial exploration to shareable reports without rebuilding visualizations.

What You Can Do

Data overview
01

Data Profiling

Get an overview of your data frame under the Data tab. See column types, distributions, missing values, and summary statistics at a glance.

Drag and drop
02

Drag-and-Drop Charts

Create visualizations with simple drag-and-drop operations. Map columns to axes, colors, and sizes without writing any code.

Brush and zoom
03

Brush & Zoom

Brush and zoom to focus on interesting data points. Select regions to filter, drill down into subsets, and explore patterns interactively.

R notebook
04

R Markdown Export

Share insights in R Markdown with editable and explorable charts. Your audience can interact with the same visualizations you built.

How It Works

From Data Frame to Dashboard

1

Load Your Data

Read data from CSV, database, or any R source into a data frame. GWalkR works with any tabular data structure.

2

Call gwalkr()

Pass your data frame to gwalkr(). The interactive visualization app launches in the RStudio Viewer pane.

3

Explore Visually

Drag fields to build bar charts, scatter plots, line charts, heatmaps, and more. Apply filters, change aggregations, switch chart types — all interactively.

4

Export & Share

Save your visualization state, embed charts in R Markdown, or export to PNG/SVG. Your work is reproducible and shareable.

GWalkR vs Traditional R Visualization

Capabilityggplot2 / base RGWalkR
Time to first chartMinutes (write code)Seconds (drag & drop)
Learning curveSteep (grammar of graphics)Minimal (visual interface)
Interactive explorationRequires plotly/shinyBuilt-in
Chart type switchingRewrite codeOne click
Data filteringdplyr pipelineVisual filters
R Markdown supportStatic imagesInteractive widgets
Large dataset handlingManual optimizationKernel computation mode

Built for R Users

🎓

Academic Research

Explore experimental datasets, find patterns in survey data, and create publication-ready visuals without leaving RStudio.

👥

Data Science Teams

Rapidly prototype visualizations during analysis. Share interactive notebooks with collaborators who can explore the data themselves.

📚

Teaching & Workshops

Let students interact with data visually before learning ggplot syntax. GWalkR makes data intuition tangible.

📈

Business Analytics

Turn messy CSVs and database exports into interactive dashboards. No Shiny development cycle required.

Frequently Asked Questions

Is GWalkR free to use?

Yes. GWalkR is open-source under the Apache-2.0 license. It is free for personal, academic, and commercial use.

Does GWalkR work with large datasets?

Yes. For large datasets, use gwalkr(df, kernelComputation = TRUE) to enable server-side computation. This processes data in R while rendering only the visual output in the browser, handling millions of rows efficiently.

What chart types does GWalkR support?

GWalkR supports bar charts, line charts, area charts, scatter plots, histograms, heatmaps, box plots, tick plots, and more. You can switch between chart types with a single click.

Can I use GWalkR in R Markdown?

Yes. GWalkR outputs an htmlwidget that can be embedded directly in R Markdown documents and Quarto reports. The interactive charts remain fully functional in the rendered HTML output.

How does GWalkR compare to ggplot2?

GWalkR and ggplot2 serve different purposes. ggplot2 is ideal for creating precise, publication-quality static charts with code. GWalkR is designed for rapid interactive exploration — you drag and drop to build charts without writing any code. Many users use both: GWalkR for exploration, ggplot2 for final presentation.

Does GWalkR require an internet connection?

No. Once installed from CRAN, GWalkR works completely offline. All data processing happens locally in your R session, and the visualization renders in the RStudio Viewer pane.

What R version is required?

GWalkR requires R version 4.0 or later. It is compatible with RStudio, VS Code with R extension, and Jupyter with the R kernel.

Is my data sent to any server?

No. GWalkR processes everything locally. Your data stays in your R session and is never transmitted to any external server. It is completely private and secure.

Start Exploring Your Data

Install GWalkR from CRAN and turn any data frame into an interactive visualization — in one line of code.

R>install.packages("GWalkR")