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Introduction to Data Visualization with Bokeh
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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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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.
Plotting with glyphs50 xpWhat are glyphs?50 xpA simple scatter plot100 xpA scatter plot with different shapes100 xpCustomizing your scatter plots100 xpAdditional glyphs50 xpLines100 xpLines and markers100 xpPatches100 xpData formats50 xpPlotting data from NumPy arrays100 xpPlotting data from Pandas DataFrames100 xpThe Bokeh ColumnDataSource50 xpThe Bokeh ColumnDataSource (continued)100 xpCustomizing glyphs50 xpSelection and non-selection glyphs100 xpHover glyphs100 xpColormapping100 xp - 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.
Introduction to layouts50 xpCreating rows of plots100 xpCreating columns of plots100 xpNesting rows and columns of plots100 xpAdvanced layouts50 xpInvestigating the layout API50 xpCreating gridded layouts100 xpStarting tabbed layouts100 xpDisplaying tabbed layouts100 xpLinking plots together50 xpLinked axes100 xpLinked brushing100 xpAnnotations and guides50 xpHow to create legends100 xpPositioning and styling legends100 xpHover tooltips for exposing details50 xpAdding a hover tooltip100 xp - 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.
Introducing the Bokeh Server50 xpUnderstanding Bokeh apps50 xpUsing the current document100 xpAdd a single slider100 xpMultiple sliders in one document100 xpConnecting sliders to plots50 xpAdding callbacks to sliders50 xpHow to combine Bokeh models into layouts100 xpLearn about widget callbacks100 xpUpdating plots from dropdowns50 xpUpdating data sources from dropdown callbacks100 xpSynchronize two dropdowns100 xpButtons50 xpButton widgets100 xpButton styles100 xpHosting applications for wider audiences50 xp - 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.
Time to put it all together!50 xpIntroducing the project dataset50 xpSome exploratory plots of the data100 xpStarting the app50 xpBeginning with just a plot100 xpEnhancing the plot with some shading100 xpAdding a slider to vary the year100 xpCustomizing based on user input100 xpAdding more interactivity to the app50 xpAdding a hover tool100 xpAdding dropdowns to the app100 xpCongratulations!50 xp
Datasets
AAPL stockAutomobile miles per gallonGapminderBlood glucose levelsFemale literacy and birth rateOlympic medals (100m sprint)Prerequisites
Data Manipulation with pandasTeam Anaconda
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