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- Herausgeber: Packt Publishing
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
Learn how to create interactive and visually aesthetic plots using the Bokeh package in Python
Key FeaturesA step by step approach to creating interactive plots with BokehGo from installation all the way to deploying your very own Bokeh applicationWork with a real time datasets to practice and create your very own plots and applicationsBook Description
Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free. This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization.
The book starts out by helping you understand how Bokeh works internally and how you can set up and install the package in your local machine. You then use a real world data set which uses stock data from Kaggle to create interactive and visually stunning plots. You will also learn how to leverage Bokeh using some advanced concepts such as plotting with spatial and geo data. Finally you will use all the concepts that you have learned in the previous chapters to create your very own Bokeh application from scratch.
By the end of the book you will be able to create your very own Bokeh application. You will have gone through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with interactive and visually aesthetic plots.
What you will learnInstalling Bokeh and understanding its key conceptsCreating plots using glyphs, the fundamental building blocks of BokehCreating plots using different data structures like NumPy and PandasUsing layouts and widgets to visually enhance your plots and add a layer of interactivityBuilding and hosting applications on the Bokeh serverCreating advanced plots using spatial dataWho this book is for
This book is well suited for data scientists and data analysts who want to perform interactive data visualization on their web browsers using Bokeh. Some exposure to Python programming will be helpful, but prior experience with Bokeh is not required.
As a formally educated data scientist with a master’s degree in data science from the prestigious King’s College London, Kevin works as a data scientist with a digital healthcare startup - Connido Limited in London where he is primarily involved with building the descriptive, diagnostic and predictive analytic pipelines. He is also the founder of LinearData- a leading online resource in the field of data science which has over 30,000 unique website hits.
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Seitenzahl: 118
Veröffentlichungsjahr: 2018
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Hands-On Data Visualization with Bokeh
Copyright © 2018 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
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Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
Commissioning Editor: Amey VarangaonkarAcquisition Editor: Noyonika DasContent Development Editor: Aditi GourTechnical Editor: Jinesh TopiwalaCopy Editor: Safis EditingProject Coordinator: Hardik BhindeProofreader: Safis EditingIndexer: Aishwarya GangawaneGraphics: Jason MonteiroProduction Coordinator: Nilesh Mohite
First published: June 2018
Production reference: 1120618
Published by Packt Publishing Ltd. Livery Place 35 Livery Street Birmingham B3 2PB, UK.
ISBN 978-1-78913-540-4
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Contributors
About the author
As a formally educated data scientist with a master’s degree in data science from the prestigious King’s College London, Kevin works as a data scientist with a digital healthcare startup - Connido Limited in London where he is primarily involved with building the descriptive, diagnostic and predictive analytic pipelines.
He is also the founder of LinearData—a leading online resource in the field of data science which has over 30,000 unique website hits.
About the reviewer
Zaim Awang, who is from Malaysia, has been an oil and gas engineer for more than 20 years—but a data scientist at heart for just as long. A graduate from the University of Texas in Austin, he used to work for Shell and other companies in different regions. He enjoys solving technical problems. His latest discovery is a new algorithm for pattern prediction that works much better than traditional deep learning for structured data. He is now leading a team at Invigour Energy developing AiSara (for solution approximation with robust algorithms). He welcomes contact at his twitter handle, @zaim_awang.
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Table of Contents
Title Page
Copyright and Credits
Hands-On Data Visualization with Bokeh
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
Other Books You May Enjoy
Leave a review - let other readers know what you think
Preface
Bokeh is an open source, interactive, data visualization package in Python that allows users to create interactive and beautiful visualizations that are both statistically significant and aesthetically pleasing.
This book aims to provide you with the tools needed to get started with Bokeh and to create plots that can tell a story through interaction.
Who this book is for
This book is well suited for data scientists and data analysts who wish to perform interactive data visualization on their web browsers using the Bokeh library.
A basic knowledge of Python is required in order to understand the content of this book.
What this book covers
Chapter 1, Bokeh Installation and Key Concepts, looks at how to install Bokeh on your PC and how to understand the fundamental concepts that are needed to progress with the rest of the book.
Chapter 2, Plotting Using Glyphs, will teach you how to create visualizations using the building block of Bokeh—Glyphs.
Chapter 3, Plotting with Different Data Structures, explains how to create visualizations using data structures that are found ubiquitously, such as the Pandas DataFrame and the NumPy array.
Chapter 4, Using Layouts for Effective Presentation, explores how to use layouts in order to enhance the aesthetic appeal of your visualizations.
Chapter 5, Using Annotations, Widgets, and Visual Attributes for Visual Enhancement, will teach you how to enhance your plot's interactivity as well as its aesthetics.
Chapter 6, Building and Hosting Applications on the Bokeh Server, goes through how to create and deploy applications that can host interactive visualizations.
Chapter 7, Advanced Plotting with Networks, Geo Data, WebGL, and Exporting Plots, dives into the advanced topics of Bokeh and sheds light on some of the ways in which you can enhance your interactive plotting experience.
Chapter 8, The Bokeh Workflow – A Case Study, comprises a case study that will have you explore data and build an interactive visualization by following a workflow that is tailored for Bokeh!
To get the most out of this book
A basic knowledge of Python is essential. Knowledge of importing packages, and experience of working with NumPy, Pandas, and DataFrames, will help the reader get the most out of this book.
Download the example code files
You can download the example code files for this book from your account at www.packtpub.com. If you purchased this book elsewhere, you can visit www.packtpub.com/support
