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47,133 repositories indexed
1–22 of 22 · Most stars
A collection of composable React components for building interactive data visualizations
:bar_chart: A D3-based reusable chart library
Learning Convolutional Neural Networks with Interactive Visualization.
- deep-learning
- visualization
- interactive-visualizations
- visual-learning
Business intelligence as code: build fast, interactive data visualizations in SQL and markdown
📊 Re-usable, easy interface JavaScript chart library based on D3.js, with SVG and Canvas rendering support
Plotting library for IPython/Jupyter notebooks
- visualizations
- jupyter
- ipython
Interactive visualizations of time series using JavaScript and the HTML canvas tag
- dygraphs
- visualization
- charting-library
- timeseries
Library for animated data visualizations and data stories.
A javascript library that extends D3.js to enable fast and beautiful visualizations.
Composable Svelte chart components to build a large variety of visualizations
Compose complex, data-driven visualizations from reusable charts and components with d3
📅 Create interactive timeline visualizations in R
Beautiful and interactive visualizations for your ruby web pages powered by ApexCharts.JS. :bar_chart:
- ruby
- charts
- apexcharts
- heatmap-chart
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.
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
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