Hands-On Data Visualization with Bokeh : Interactive Web Plotting for Python Using Bokeh

Learn how to create interactive and visually aesthetic plots using the Bokeh package in Python Key Features A step by step approach to creating interactive plots with Bokeh Go from nstallation all the way to deploying your very own Bokeh application Work with a real time datasets to practice and create your very own plots and applications Book 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 learn Installing Bokeh and understanding its key concepts Creating plots using glyphs, the fundamental building blocks of Bokeh Creating plots using different data structures like NumPy and Pandas Using layouts and widgets to visually enhance your plots and add a layer of interactivity Building and hosting applications on the Bokeh server Creating advanced plots using spatial data Who 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. Table of Contents Bokeh installation and key concepts Plotting using glyphs Plotting with different data structures Using layouts for effective presentation Using annotations, widgets and visual attributes for visual enhancement Building and hosting applications using the Bokeh Server Advanced Plotting with Networks, Geo data, WebGL and Exporting plots The Bokeh Workflow: A case study Cover 1 Title Page 2 Copyright and Credits 3 Dedication 4 Packt Upsell 5 Contributors 6 Table of Contents 8 Preface 11 Chapter 1: Bokeh Installation and Key Concepts 16 Technical requirements 17 The difference between static and interactive plotting 17 Installing the Bokeh library 18 Installing Bokeh using a Python distribution 18 Verifying your installation 19 When things go wrong 21 Key concepts and the building blocks of Bokeh 21 Plot outputs 22 Summary 23 Chapter 2: Plotting using Glyphs 24 Technical requirements 24 What are glyphs? 25 Plotting with glyphs 25 Creating line plots 26 Creating bar plots 28 Creating patch plots 30 Creating scatter plots 32 Customizing glyphs 33 Summary 34 Chapter 3: Plotting with different Data Structures 35 Technical requirements 35 Creating plots using NumPy arrays 36 Creating line plots using NumPy arrays 36 Creating scatter plots using NumPy arrays 38 Creating plots using pandas DataFrames 40 Creating a time series plot using a pandas DataFrame 41 Creating scatter plots using a pandas DataFrame 43 Creating plots with ColumnDataSource 45 Creating a time series plot using the ColumnDataSource 45 Creating a scatter plot using the ColumnDataSource 47 Summary 49 Chapter 4: Using Layouts for Effective Presentation 50 Technical requirements 51 Creating multiple plots along the same row 51 Creating multiple plots in the same column 57 Creating multiple plots in a row and column 59 Creating multiple plots using a tabbed layout 61 Creating a robust grid layout 64 Linking multiple plots together 66 Summary 69 Chapter 5: Using Annotations, Widgets, and Visual Attributes for Visual Enhancement 70 Technical requirements 71 Creating annotations to convey supplemental information 71 Adding titles to plots 71 Adding legends to plots 74 Adding color maps to plots 76 Creating widgets to add interactivity to plots 78 Creating a button widget 78 Creating the checkbox widget 79 Creating a drop-down menu widget 79 Creating the radio button widget 80 Creating a slider widget 81 Creating a text input widget 82 Creating visual attributes to enhance style and interactivity 83 Attributes that add interactivity to the plot 83 Creating a hover tooltip 83 Creating selections 86 Attributes that enhance the visual style of the plot 88 Styling the title 88 Styling the background 91 Styling the outline of the plot 93 Styling the labels 95 Summary 97 Chapter 6: Building and Hosting Applications Using the Bokeh Server 98 Technical requirements 99 Introduction to the Bokeh Server 99 Building a Bokeh application 100 Creating a single slider application 101 Creating a multi-slider application 102 Combining the slider application with a scatter plot 103 Combining the slider application with a line plot 107 Creating an application with the select widget 109 Creating an application with the button widget 113 Creating an application to select different columns 116 Introduction to deploying the Bokeh application 119 Summary 119 Chapter 7: Advanced Plotting with Networks, Geo Data, WebGL, and Exporting Plots 120 Technical requirements 121 Using Bokeh to visualize networks 121 Visualizing networks with straight paths 122 Visualizing networks with explicit paths 131 Visualizing geographic data with Bokeh 136 Using WebGL to improve performance 141 Exporting plots as PNG images 144 Summary 146 Chapter 8: The Bokeh Workflow – A Case Study 147 Technical requirements 149 Asking the right question 149 The exploratory data analysis 150 Creating an insightful visualization 153 Creating the base plot 153 Mapping tech stocks 155 Adding a hover tool 157 Improving performance using WebGL 160 Presenting your results 161 Summary 162 Other Books You May Enjoy 163 Index 166 Learn How To Create Interactive And Visually Aesthetic Plots Using The Bokeh Package In Python Key Features A Step By Step Approach To Creating Interactive Plots With Bokeh Go From Installation All The Way To Deploying Your Very Own Bokeh Application Work With A Real Time Datasets To Practice And Create Your Very Own Plots And Applications Book 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 Learn Installing Bokeh And Understanding Its Key Concepts Creating Plots Using Glyphs, The Fundamental Building Blocks Of Bokeh Creating Plots Using Different Data Structures Like Numpy And Pandas Using Layouts And Widgets To Visually Enhance Your Plots And Add A Layer Of Interactivity Building And Hosting Applications On The Bokeh Server Creating Advanced Plots Using Spatial Data Who 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.