Interactive Data Visualization with Bokeh
Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!
Start Course for Free4 Hours15 Videos53 Exercises4500 XP
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Course Description
Bokeh is a powerful Python package for interactive data visualization, enabling you to go beyond static plots and allow stakeholders to modify your visualizations! In this interactive data visualization with Bokeh course, you'll work with a range of datasets, including stock prices, basketball player statistics, and Australian real-estate sales data. Through hands-on exercises, you’ll build and customize a range of plots, including scatter, bar, line, and grouped bar plots. You'll also get to grips with configuration tools to change how viewers interact with your plot, discover Bokeh's custom themes, learn how to generate subplots, and even how to add widgets to your plots!
- 1
Introduction to Bokeh
FreeLearn about the fundamentals of the Bokeh library in this course, which will enable you to level up your Python data visualization skills by building interactive plots. You’ll see how to set up configuration tools, including the HoverTool, providing various opportunities for stakeholders to interact with your plots!
Introduction to Bokeh50 xpWhen to use a scatter plot50 xpBlocks vs. rebounds100 xpKevin Durant's performance across seasons100 xpShooting ability by position100 xpConfiguration tools50 xpThe best tools for the job100 xpSetting tools100 xpAdding LassoSelectTool100 xpThe HoverTool50 xpAdding a HoverTool100 xpFormatting the HoverTool100 xp - 2
Customizing Visualizations
For this chapter, you’ll learn how to customize axes, create and enhance a legend, modify glyph settings, and apply Bokeh's custom themes!
Adding style50 xpColors, legend, and theme100 xpCustomizing glyphs100 xpCustomizing axes50 xpAverage building size100 xpSales over time100 xpSubplots50 xpCategorical column subplots100 xpSize, location, and price100 xpUsing gridplot100 xpChanging size100 xpVisualizing categorical data50 xpHigh to low prices by region100 xpCreating nested categories100 xpVisualizing sales by period100 xp - 3
Storytelling with Visualizations
Learn how to use various elements to communicate with stakeholders. You’ll produce grouped bar plots with categorical data, build multiple subplots, add annotations, and modify the text to make your Bokeh visualizations even more striking!
Customizing glyph settings50 xpShooting guards versus small forwards100 xpBig shooters100 xpEvolution of the point guard100 xpHighlighting and contrasting50 xpHighlighting by glyph size100 xpSteals vs. assists100 xpAdding a color bar100 xpFree throw percentage by position100 xpCommunicating with text50 xpSales by time and type of day100 xpProducts sold by the time of day100 xpAdding annotations50 xpBox annotations for sales performance100 xpSetting up a polygon annotation100 xpAnnotating Netflix stock price growth100 xp - 4
Introduction to Widgets
Discover Bokeh's widgets and how they enable users to modify Python visualizations! You’ll learn about Spinners, which allow viewers to change the size of glyphs. We’ll discuss Sliders, which can be used to change axis ranges. Lastly, we’ll introduce the Select widget, which will enable plot updates based on dropdown options.
James Chapman
Amy PetersonPrerequisites
Data Manipulation with pandas
George Boorman
Core Curriculum Manager, DataCamp
George is a Core Curriculum Manager at DataCamp. He has experience in project management across public health, applied research, and not-for-profit sectors. George is passionate about health technologies and all things data science.
What do other learners have to say?
I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.
Devon Edwards Joseph
Lloyds 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
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