DataCamp DataCamp
Interactive Course

Interactive Data Visualization with Bokeh

Learn how to create versatile and interactive data visualizations using Bokeh.

  • 4 hours
  • 17 Videos
  • 63 Exercises
  • 27,339 Participants
  • 5,100 XP

Loved by learners at thousands of top companies:

mercedes-grey.svg
whole-foods-grey.svg
roche-grey.svg
uber-grey.svg
mls-grey.svg
intel-grey.svg

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.

  1. 1

    Basic 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.

  2. 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.

  1. 1

    Basic 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.

  2. 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.

  3. 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.

  4. 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.

What do other learners have to say?

Devon

“I've used other sites, but DataCamp's been the one that I've stuck with.”

Devon Edwards Joseph

Lloyd's Banking Group

Louis

“DataCamp is the top resource I recommend for learning data science.”

Louis Maiden

Harvard Business School

Ronbowers

“DataCamp is by far my favorite website to learn from.”

Ronald Bowers

Decision Science Analytics @ USAA

Bryan Van de Ven
Bryan Van de Ven

Software Engineer at Anaconda and Developer of Bokeh

Bryan is a developer of Bokeh and is a software engineer at Anaconda. 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.

See More
Icon Icon Icon professional info