Python Data Science Cheat Sheet: Bokeh

Python Data Science Cheat Sheet: Bokeh belongs to the widely circulated Python Data Science Cheat Sheet series, which traces back to the official cheat sheets released by DataCamp, an online data science education platform. Translated and compiled by Chinese translators, the series has spread widely in reader communities and covers topics including NumPy basics, Pandas basics and advanced usage, Matplotlib, Seaborn, Scikit-Learn, Keras, Jupyter Notebook, and Bokeh. This volume focuses specifically on Bokeh, Python's interactive visualization library, presenting its commonly used concepts and code patterns in a single-page cheat sheet so readers can look them up at any time while studying or working on projects. The defining feature of Bokeh is its ability to produce interactive charts and dashboards in the browser, so a cheat sheet of this kind typically revolves around glyph plotting, data source organization (such as ColumnDataSource), axis and legend configuration, figure layout and multi-plot composition, hover tooltips and widgets, and other interactive features. Brevity and a heavy reliance on code snippets and diagrams are the hallmarks of this volume; it is less a textbook than a quick-reference knowledge map, and true mastery requires pairing it with the official documentation and hands-on practice. This is not a systematic textbook and offers no step-by-step instruction. It suits readers who already have some Python and basic plotting experience and want to quickly fill gaps or get an overview of Bokeh's main APIs.