aframexr 1.0.0b1

Python library to visualize data in Virtual and Extended Reality using Aframe components.

AFrameXR

AFrameXR is a declarative Python library for building immersive 3D and XR data visualizations — directly in your browser, with no 3D experience required.

Inspired by Vega-Altair and Vega-Lite, AFrameXR lets you define interactive 3D charts using a simple grammar, and render them directly in the browsers and XR devices — without low-level 3D programming.

Live Demos

https://davidlab20.github.io/TFG/examples/index.html

Features

• Declarative API — Define charts using a high-level grammar
• XR Visualization — Explore charts in immersive environments
• Notebook Integration — Works with Jupyter and Marimo
• Browser Rendering — Visualize charts directly in the browser
• Interactive Exploration — Navigate and interact with your data

Why AFrameXR?

AFrameXR brings the declarative visualization paradigm to 3D and XR environments.

• No need to learn complex 3D engines
• Inspired by proven visualization tools like Vega-Lite
• Built for the web and XR from the ground up
• Clean and concise API for rapid prototyping

Installation

pip install aframexr

Simple example

import aframexr
from aframexr.datasets import data

# Load dataset
cars = data.cars()

# Create a 3D chart
aframexr.Chart(
    cars,
    position="0 2 -5"
).mark_bar().encode(
    x="model",
    y="sales",
    z="doors:N",  # :N indicates a categorical (nominal) field
    color="motor"
)

Supported Environments

• Jupyter Notebook
• Marimo Notebooks
• Modern web browsers (Chrome, Firefox)
• XR devices

Documentation

Full documentation: https://davidlab20.github.io/TFG/

User Study

Try AFrameXR in a short usability study (~10–15 min).

If you'd like to participate: Go to experiment instructions

What you'll do

• Complete a few small visualization tasks
• No prior 3D experience required

Your feedback is extremely valuable!