Bokeh is an accessible and easy-to-use Python library which allows even novice programmers to build complex, interactive visualizations in an intuitive manner. Learn how to build interactive plots to support business decision making with Bokeh.
Organizations have huge datasets, usually in a raw format. Visualization of this data is critical in order to understand what is significant before diving into data analysis. In this course, Building Interactive Visualizations Using Bokeh, you'll learn how to use Bokeh to build tweakable visualizations on the web which allows for easy exploration of data without in-depth coding knowledge. First, you'll explore the internals of how Bokeh works and the basic building blocks of Bokeh plots by working with glyphs, plots, tables, arbitrary shapes, and visual layouts. Then, you'll delve into specialized plots in Bokeh, such as plots which work with categorical data, network graphs, and geographical data. Next, you'll discover how to build geo-plots using built-in Bokeh maps and the Google Maps API, along with Bokeh's huge sample dataset to prototype some interesting plots. Finally, you'll learn some advanced features in Bokeh such as integrating with Bokeh plot tools to enhance plot interactivity and working with the Bokeh server which offers a model-view-controller paradigm to manipulate data in Python and view it using a browser. By the end of this course, you'll have the necessary knowledge to effectively work with Bokeh plots and features to extract insights from your own data in the real world.
A problem solver at heart, Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework.