Bokeh Basics: Setup and Interactive Data Visualization

Tired of static graphs? Python's Bokeh library allows you to create dynamic, interactive data visualizations that can be easily embedded into web applications and dashboards. This course provides a complete foundational guide to setting up your environment and using Bokeh to transform raw data into rich, web-ready plots, enabling deeper data exploration and communication. What you'll learn: * Understand the core concepts of Bokeh, including models, glyphs, and the ColumnDataSource data structure. * Configure a modern Python virtual environment and install Bokeh and necessary data handling dependencies. * Build foundational plots like scatter plots, line charts, and bar graphs using the basic plotting interface. * Apply interactive tools and widgets, such as hover tools, panning, and linking plots for dynamic user experiences. * Practice structuring data efficiently using Bokeh's specialized data sources for optimal rendering performance. We begin with essential terminology and environment configuration, then move step-by-step through creating basic visualizations, adding interactive elements, and preparing plots for deployment. This course is designed for absolute beginners in data visualization or Python users looking to add interactive plotting capabilities. No prior experience with Bokeh is required. Start building powerful, web-enabled data stories today.