premium course
Interactive Data Visualization with Bokeh
Start Course For Free Play Trailer- 20 Videos
- 75 Exercises
- 4 hours
- 4,535 Participants
- 6100 XP
Instructor(s):
Bryan Van de Ven
Bryan is a developer of Bokeh and is a software engineer at Continuum Analytics. He received undergraduate degrees in Computer Science and Mathematics from UT Austin, and a Master's degree in physics from UCLA. He has worked at the Applied Research Labs, developing software for sonar feature detection and classification systems on US Naval submarine platforms. He also spent time at Enthought, where he worked on problems in financial risk modeling and fluid mixing simulation, and also contributed to the Chaco visualization library. He has also worked on an assortment of iOS projects as an independent consultant.
Hugo Bowne-Anderson
Yashas Roy
Course Description
Bokeh is an interactive data visualization library for Python (and other languages!) that targets modern web browsers for presentation. It can create versatile, data-driven graphics, and connect the full power of the entire Python data-science stack to rich, interactive visualizations.
1Basic plotting with Bokeh Free
An introduction to basic plotting with Bokeh. You will create your first plots, learn about different data formats Bokeh understands, and make visual customizations for selections and mouse hovering.
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Plotting with glyphs
50 xp
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What are glyphs?
50 xp
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A simple scatter plot
100 xp
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A scatter plot with different shapes
100 xp
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Customizing your scatter plots
100 xp
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Additional glyphs
50 xp
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Lines
100 xp
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Lines and markers
100 xp
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Patches
100 xp
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Data formats
50 xp
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Plotting data from NumPy arrays
100 xp
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Plotting data from Pandas DataFrames
100 xp
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The Bokeh ColumnDataSource
50 xp
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The Bokeh ColumnDataSource (continued)
100 xp
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Customizing glyphs
50 xp
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Selection and non-selection glyphs
100 xp
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Hover glyphs
100 xp
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Colormapping
100 xp
Layouts, Interactions, and Annotations
Learn how to combine mutiple Bokeh plots into different kinds of layouts on a page, how to easily link different plots together in various ways, and how to add annotations such as legends and hover tooltips.
High-level Charts
In addition to versatile data-driven glyphs, Bokeh comes with a variety of high-level statistical chart types built in, so that you can get quick exploratory charts with very little code.
Building interactive apps with Bokeh
Bokeh server applications let you connect all of the powerful Python libraries for analytics and data science, such as NumPy and Pandas, to rich interactive Bokeh visualizations. Learn about Bokeh's built-in widgets, how to add them to Bokeh documents alongside plots, and how to connect everything to real python code using the Bokeh server.
Putting It All Together! A Case Study
In this final chapter, you'll build a more sophisticated Bokeh data exploration application from the ground up, based on the famous Gapminder data set.