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Interactive Data Visualization with Bokeh

Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!

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4 Hours15 Videos53 Exercises
2,528 Learners

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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. 1

    Introduction to Bokeh

    Free

    Learn 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!

    Play Chapter Now
    Introduction to Bokeh
    50 xp
    When to use a scatter plot
    50 xp
    Blocks vs. rebounds
    100 xp
    Kevin Durant's performance across seasons
    100 xp
    Shooting ability by position
    100 xp
    Configuration tools
    50 xp
    The best tools for the job
    100 xp
    Setting tools
    100 xp
    Adding LassoSelectTool
    100 xp
    The HoverTool
    50 xp
    Adding a HoverTool
    100 xp
    Formatting the HoverTool
    100 xp
  2. 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!

    Play Chapter Now
    Adding style
    50 xp
    Colors, legend, and theme
    100 xp
    Customizing glyphs
    100 xp
    Customizing axes
    50 xp
    Average building size
    100 xp
    Sales over time
    100 xp
    Subplots
    50 xp
    Categorical column subplots
    100 xp
    Size, location, and price
    100 xp
    Using gridplot
    100 xp
    Changing size
    100 xp
    Visualizing categorical data
    50 xp
    High to low prices by region
    100 xp
    Creating nested categories
    100 xp
    Visualizing sales by period
    100 xp
  3. 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!

    Play Chapter Now
    Customizing glyph settings
    50 xp
    Shooting guards versus small forwards
    100 xp
    Big shooters
    100 xp
    Evolution of the point guard
    100 xp
    Highlighting and contrasting
    50 xp
    Highlighting by glyph size
    100 xp
    Steals vs. assists
    100 xp
    Adding a color bar
    100 xp
    Free throw percentage by position
    100 xp
    Communicating with text
    50 xp
    Sales by time and type of day
    100 xp
    Products sold by the time of day
    100 xp
    Adding annotations
    50 xp
    Box annotations for sales performance
    100 xp
    Setting up a polygon annotation
    100 xp
    Annotating Netflix stock price growth
    100 xp
  4. 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.

    Play Chapter Now
    Introduction to widgets
    50 xp
    Adding a Div
    100 xp
    Modifying glyph size with a widget
    100 xp
    Slider widgets
    50 xp
    Automotive stocks analysis
    100 xp
    Tech stock performance over time
    100 xp
    Select widgets
    50 xp
    Travel analysis
    100 xp
    Changing line plots with Select
    100 xp
    Congratulations!
    50 xp

Datasets

Bakery SalesStocksNBA Player StatisticsAustralia Property Market

Collaborators

Collaborator's avatar
James Chapman
Collaborator's avatar
Amy Peterson

Prerequisites

Data Manipulation with pandas
George Boorman HeadshotGeorge Boorman

Curriculum Manager, DataCamp

George is a Curriculum Manager at DataCamp. He holds a PGDip in Exercise for Health and BSc (Hons) in Sports Science and has experience in project management across public health, applied research, and not-for-profit sectors. George is passionate about sports, tech for good, and all things data science.
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