From 5488d08db1b2c956f05f52d9a2b6aee073984b5c Mon Sep 17 00:00:00 2001 From: Vinta Chen Date: Sat, 15 Aug 2026 14:39:53 +0800 Subject: [PATCH] prune: sweep Data Visualization to the shortlist cap Per ADR-0001. No restructure needed: Plotting caps to matplotlib, plotly, seaborn plus altair as Challenger (listed last per the Challenger-ordering rule); Specialized (cartopy, graphify, pygraphviz) and Dashboards and Apps (gradio, streamlit) already fit. Removed (downloads are PyPI last-month via pypistats, 2026-08-14/15): - bokeh (8.4M/month): Plotting at cap; interactive plotting job covered by plotly - plotnine (3.1M/month): below the shortlist bar - vispy (1.4M/month): below the shortlist bar - pyqtgraph (1.0M/month): below the shortlist bar - bqplot (381K/month): below the shortlist bar - pygal: legacy; downloads fetch failed - ultraplot (3.9K/month): no adoption Co-Authored-By: Claude --- README.md | 9 +-------- 1 file changed, 1 insertion(+), 8 deletions(-) diff --git a/README.md b/README.md index 1d95a66c..2d189b92 100644 --- a/README.md +++ b/README.md @@ -520,17 +520,10 @@ _Libraries for validating data. Used for forms in many cases._ _Libraries for visualizing data. Also see [awesome-javascript](https://github.com/sorrycc/awesome-javascript#data-visualization)._ - Plotting - - [altair](https://github.com/vega/altair) - Declarative statistical visualization library for Python. - - [bokeh](https://github.com/bokeh/bokeh) - Interactive Web Plotting for Python. - - [bqplot](https://github.com/bqplot/bqplot) - Interactive Plotting Library for the Jupyter Notebook. - [matplotlib](https://github.com/matplotlib/matplotlib) - A Python 2D plotting library. - [plotly](https://github.com/plotly/plotly.py) - Interactive graphing library for Python. - - [plotnine](https://github.com/has2k1/plotnine) - A grammar of graphics for Python based on ggplot2. - - [pygal](https://github.com/Kozea/pygal) - A Python SVG Charts Creator. - - [pyqtgraph](https://github.com/pyqtgraph/pyqtgraph) - Interactive and realtime 2D/3D/Image plotting and science/engineering widgets. - [seaborn](https://github.com/mwaskom/seaborn) - Statistical data visualization using Matplotlib. - - [ultraplot](https://github.com/ultraplot/UltraPlot) - Matplotlib wrapper for publication-ready scientific figures with minimal code. Includes advanced subplot management, panel layouts, and batteries-included geoscience plotting. - - [vispy](https://github.com/vispy/vispy) - High-performance scientific visualization based on OpenGL. + - [altair](https://github.com/vega/altair) - Declarative statistical visualization library for Python. - Specialized - [cartopy](https://github.com/SciTools/cartopy) - A cartographic python library with matplotlib support. - [graphify](https://github.com/safishamsi/graphify) - Turn any folder of code, SQL schemas, docs, papers, images, or videos into a queryable knowledge graph.