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bokeh-visualization-guide

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Guide to Bokeh for interactive browser-based research visualizations

skills/analysis/dataviz/bokeh-visualization-guide/SKILL.md

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# Bokeh Visualization Guide

## Overview

Bokeh is a Python library for creating interactive visualizations for modern web browsers, with over 20K stars on GitHub. Developed and maintained by NumFocus, Bokeh generates standalone HTML documents or serves live interactive applications. Its architecture renders graphics in the browser using BokehJS, meaning the resulting visualizations are portable and can be shared as static HTML files without requiring Python on the viewer's end.

For researchers, Bokeh offers a unique advantage: its server-backed interactive applications allow real-time data exploration during analysis. Unlike static plotting libraries, Bokeh lets researchers build tools where they can brush-select data points, link multiple views of the same dataset, and stream live data from instruments or simulations. This makes it invaluable for exploratory data analysis in laboratory and computational research settings.

Bokeh provides multiple levels of API access. The high-level `bokeh.plotting` interface is comparable in convenience to matplotlib, while the low-level `bokeh.models` interface gives fine-grained control over every visual element. The library also integrates with HoloViews and Panel for building complex dashboards with minimal code.

## Getting Started with Bokeh

### Installation and Basic Setup
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