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Hands-On Data Visualization with Bokeh

更新時間：2021-06-25 20:50:37

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ThisbookiswellsuitedfordatascientistsanddataanalystswhowanttoperforminteractivedatavisualizationontheirwebbrowsersusingBokeh.SomeexposuretoPythonprogrammingwillbehelpful,butpriorexperiencewithBokehisnotrequired.

目錄(119章)

倒序

封面
版權信息
Dedication
Packt Upsell
Why subscribe?
PacktPub.com
Contributors
About the author
About the reviewer
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Code in action
Conventions used
Get in touch
Reviews
Bokeh Installation and Key Concepts
Technical requirements
The difference between static and interactive plotting
Installing the Bokeh library
Installing Bokeh using a Python distribution
Verifying your installation
When things go wrong
Key concepts and the building blocks of Bokeh
Plot outputs
Summary
Plotting using Glyphs
Technical requirements
What are glyphs?
Plotting with glyphs
Creating line plots
Creating bar plots
Creating patch plots
Creating scatter plots
Customizing glyphs
Summary
Plotting with different Data Structures
Technical requirements
Creating plots using NumPy arrays
Creating line plots using NumPy arrays
Creating scatter plots using NumPy arrays
Creating plots using pandas DataFrames
Creating a time series plot using a pandas DataFrame
Creating scatter plots using a pandas DataFrame
Creating plots with ColumnDataSource
Creating a time series plot using the ColumnDataSource
Creating a scatter plot using the ColumnDataSource
Summary
Using Layouts for Effective Presentation
Technical requirements
Creating multiple plots along the same row
Creating multiple plots in the same column
Creating multiple plots in a row and column
Creating multiple plots using a tabbed layout
Creating a robust grid layout
Linking multiple plots together
Summary
Using Annotations Widgets and Visual Attributes for Visual Enhancement
Technical requirements
Creating annotations to convey supplemental information
Adding titles to plots
Adding legends to plots
Adding color maps to plots
Creating widgets to add interactivity to plots
Creating a button widget
Creating the checkbox widget
Creating a drop-down menu widget
Creating the radio button widget
Creating a slider widget
Creating a text input widget
Creating visual attributes to enhance style and interactivity
Attributes that add interactivity to the plot
Creating a hover tooltip
Creating selections
Attributes that enhance the visual style of the plot
Styling the title
Styling the background
Styling the outline of the plot
Styling the labels
Summary
Building and Hosting Applications Using the Bokeh Server
Technical requirements
Introduction to the Bokeh Server
Building a Bokeh application
Creating a single slider application
Creating a multi-slider application
Combining the slider application with a scatter plot
Combining the slider application with a line plot
Creating an application with the select widget
Creating an application with the button widget
Creating an application to select different columns
Introduction to deploying the Bokeh application
Summary
Advanced Plotting with Networks Geo Data WebGL and Exporting Plots
Technical requirements
Using Bokeh to visualize networks
Visualizing networks with straight paths
Visualizing networks with explicit paths
Visualizing geographic data with Bokeh
Using WebGL to improve performance
Exporting plots as PNG images
Summary
The Bokeh Workflow – A Case Study
Technical requirements
Asking the right question
The exploratory data analysis
Creating an insightful visualization
Creating the base plot
Mapping tech stocks
Adding a hover tool
Improving performance using WebGL
Presenting your results
Summary
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Leave a review - let other readers know what you think 更新時間：2021-06-25 20:50:37

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Hands-On Data Visualization with Bokeh