Bokeh Data Visualization

Bokeh is an interactive visualization library for Python that targets modern web browsers for presentation, enabling elegant and versatile construction of expressive graphics with high performance over large or streaming datasets. Maintained by NumFOCUS and developed by a global community of contributors, the library produces output as standalone HTML documents, server backed applications, or Jupyter notebook cells. Core capabilities include a flexible glyph system for rendering scatter plots, lines, bars, patches, wedges, hex tiles, and custom glyphs with vectorized properties for color, size, and alpha. The layout system supports grid plots, row and column arrangements, tabbed panels, and responsive sizing modes. Interactive features include linked brushing and panning across multiple plots, hover tools with customizable tooltips, box and lasso selection, range sliders, dropdown menus, and custom JavaScript callbacks triggered by user interactions. The Bokeh Server architecture enables real time streaming plots, periodic callbacks, and interactive applications that synchronize Python state with the browser. Visual styling provides fine grained control over every visual attribute including fill color, line width, font size, and tick formatting. The library integrates with Pandas DataFrames, NumPy arrays, and ColumnDataSource for efficient data handling. Notable adopters include Netflix, the Sant energy research organization, and numerous scientific institutions for data exploration.