📅 Create interactive timeline visualizations in R
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ThreeAudio helps you create music visualizations in Three.js or tQuery.
Beautiful and interactive visualizations for your ruby web pages powered by ApexCharts.JS. :bar_chart:
- ruby
- charts
- apexcharts
- heatmap-chart
Application of music theory in audio reactive visualizations
Flare is an ActionScript library for creating visualizations that run in the Adobe Flash Player. From basic charts and graphs to complex interactive graphics, the toolkit supports data management, visual encoding, animation, and interaction techniques.
Creating interactive visualizations with Python
Components for interactive scientific writing, reactive documents and explorable explanations.
- webcomponents
- writing
- explorable-explanations
- exploratory-data-visualizations
React components for declaratively composing animated, interactive visualizations.
Interactive details-on-demand data visualizations at scale
- visualization-tools
- visualization-grammar
- interactive-visualizations
- postgresql
Plotly for C++. A C++ interface to the Plotly.js figure spec, for creating interactive data visualizations.
TranslatedBuild your own Minecraft-inspired 3D personal website.
Visualizing GTFS data.
Package with useful functions to create geo-spatial visualizations from a GTFS.
A plugin for d3.js that allows you to easy use context-menus in your visualizations.
A lightweight component abstraction for D3.js.
an R package that automates performance testing of ML models and summarizes the results in a dashboard w/ rad visualizations
Magic to display dynamic call graphs of Python function calls
- jupyter-notebook-extension
- ipython-magic
- python
- education
Tools for drawing 2d and 3d interactive visualizations using Jupyter proxy widgets
Data and code for "When (ish) is My Bus? User-centered Visualizations of Uncertainty in Everyday, Mobile Predictive Systems" (CHI 2016)
Modern, interactive charts for Jupyter notebooks with Apache ECharts
- apache
- apache-echarts
- data-visualization
- echarts
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.
- art-history
- color-analysis
- color-extraction
- color-palette