Popular Courses
Intro to Python
Intro to R
Intro to SQL
Popular Searches
SQL
Interactive Data Visualization with Bokeh
Learn how to create versatile and interactive data visualizations using Bokeh.
- 4 hours
- 17 Videos
- 63 Exercises
- 35,281 Participants
- 5,100 XP
Create Your Free Account
By pressing Continue you accept the Terms of Use and Privacy Policy. You also accept that you are aware that your data will be stored outside of the EU and that you are above the age of 16.
Loved by learners at thousands of top companies:
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 create rich, interactive visualizations.
-
1
Basic plotting with Bokeh
FreeThis chapter provides 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.
-
Building interactive apps with Bokeh
Bokeh server applications allow you to connect all of the powerful Python libraries for data science and analytics, such as NumPy and pandas to create 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.
-
Layouts, Interactions, and Annotations
Learn how to combine multiple Bokeh plots into different kinds of layouts on a page, how to easily link different plots together, and how to add annotations such as legends and hover tooltips.
-
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 dataset.
-
1
Basic plotting with Bokeh
FreeThis chapter provides 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.
-
Layouts, Interactions, and Annotations
Learn how to combine multiple Bokeh plots into different kinds of layouts on a page, how to easily link different plots together, and how to add annotations such as legends and hover tooltips.
-
Building interactive apps with Bokeh
Bokeh server applications allow you to connect all of the powerful Python libraries for data science and analytics, such as NumPy and pandas to create 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 dataset.
What do other learners have to say?
“I've used other sites, but DataCamp's been the one that I've stuck with.”
Devon Edwards Joseph
Lloyd's Banking Group
“DataCamp is the top resource I recommend for learning data science.”
Louis Maiden
Harvard Business School
“DataCamp is by far my favorite website to learn from.”
Ronald Bowers
Decision Science Analytics @ USAA
Team Anaconda
Data Science Training
This course was created in collaboration with Anaconda. With over 6 million users, the open source Anaconda Distribution is the fastest and easiest way to do Python data science and machine learning. It's the industry standard for developing, testing, and training on a single machine.
See MoreCollaborators
-
Yashas Roy
-
Hugo Bowne-Anderson