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Introduction to Data Visualization with Bokeh

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4 hours
5,100 XP
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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.
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  1. 1

    Basic plotting with Bokeh

    Free

    This 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.

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    Plotting with glyphs
    50 xp
    What are glyphs?
    50 xp
    A simple scatter plot
    100 xp
    A scatter plot with different shapes
    100 xp
    Customizing your scatter plots
    100 xp
    Additional glyphs
    50 xp
    Lines
    100 xp
    Lines and markers
    100 xp
    Patches
    100 xp
    Data formats
    50 xp
    Plotting data from NumPy arrays
    100 xp
    Plotting data from Pandas DataFrames
    100 xp
    The Bokeh ColumnDataSource
    50 xp
    The Bokeh ColumnDataSource (continued)
    100 xp
    Customizing glyphs
    50 xp
    Selection and non-selection glyphs
    100 xp
    Hover glyphs
    100 xp
    Colormapping
    100 xp
  2. 2

    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.

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    Introduction to layouts
    50 xp
    Creating rows of plots
    100 xp
    Creating columns of plots
    100 xp
    Nesting rows and columns of plots
    100 xp
    Advanced layouts
    50 xp
    Investigating the layout API
    50 xp
    Creating gridded layouts
    100 xp
    Starting tabbed layouts
    100 xp
    Displaying tabbed layouts
    100 xp
    Linking plots together
    50 xp
    Linked axes
    100 xp
    Linked brushing
    100 xp
    Annotations and guides
    50 xp
    How to create legends
    100 xp
    Positioning and styling legends
    100 xp
    Hover tooltips for exposing details
    50 xp
    Adding a hover tooltip
    100 xp
  3. 3

    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.

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    Introducing the Bokeh Server
    50 xp
    Understanding Bokeh apps
    50 xp
    Using the current document
    100 xp
    Add a single slider
    100 xp
    Multiple sliders in one document
    100 xp
    Connecting sliders to plots
    50 xp
    Adding callbacks to sliders
    50 xp
    How to combine Bokeh models into layouts
    100 xp
    Learn about widget callbacks
    100 xp
    Updating plots from dropdowns
    50 xp
    Updating data sources from dropdown callbacks
    100 xp
    Synchronize two dropdowns
    100 xp
    Buttons
    50 xp
    Button widgets
    100 xp
    Button styles
    100 xp
    Hosting applications for wider audiences
    50 xp
  4. 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 dataset.

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    Time to put it all together!
    50 xp
    Introducing the project dataset
    50 xp
    Some exploratory plots of the data
    100 xp
    Starting the app
    50 xp
    Beginning with just a plot
    100 xp
    Enhancing the plot with some shading
    100 xp
    Adding a slider to vary the year
    100 xp
    Customizing based on user input
    100 xp
    Adding more interactivity to the app
    50 xp
    Adding a hover tool
    100 xp
    Adding dropdowns to the app
    100 xp
    Congratulations!
    50 xp
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datasets

AAPL stockAutomobile miles per gallonGapminderBlood glucose levelsFemale literacy and birth rateOlympic medals (100m sprint)

prerequisites

Data Manipulation with pandas
Team Anaconda HeadshotTeam Anaconda

Data Science Training

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