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Python Bokeh Tutorial | Create Interactive Plots, Multiplots & Grid Layouts

Course link: https://aicourse.thinkific.com/courses/data-understanding-and-data-visualization-with-python
00:00 – Introduction to Bokeh
04:19 – Bokeh Multiplots Markers
11:12 – Bokeh Multiplots Grid Plot
In this Python Bokeh tutorial, you will learn how to create powerful interactive plots, multiplots, and grid layouts for data visualization. Unlike static libraries such as Matplotlib and Seaborn, Bokeh enables you to zoom, pan, reset, and interact with plots directly in your browser or Jupyter Notebook. We start with the basics of Bokeh by importing essential functions, setting output options, and creating simple line plots. Then, we move on to customizing plots with titles, axis labels, colors, markers (circle, triangle, square, etc.), and legends. Finally, we explore how to build multiplots and arrange them into grid plots, similar to subplots in Matplotlib, for side-by-side interactive visualization. By the end of this tutorial, you’ll have a complete understanding of how to use Bokeh in Python for interactive data visualization.

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