Interactive Data Visualization With Python _ present your data as an

Interactive Data Visualization with Python Second Edition Present your data as an effective and compelling story Abha Belorkar Sharath Chandra Guntuku Shubhangi Hora Anshu Kumar Interactive Data Visualization with Python Second Edition Copyright © 2020 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 Every effort has been made in the preparation of this book to ensure the accuracy of the information presented However, the information contained in this book is sold without warranty, either express or implied Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book 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 Authors: Abha Belorkar, Sharath Chandra Guntuku, Shubhangi Hora, and Anshu Kumar Technical Reviewer: Saurabh Dorle Managing Editor: Ranu Kundu Acquisitions Editor: Kunal Sawant Production Editor: Shantanu Zagade Editorial Board: Shubhopriya Banerjee, Bharat Botle, Ewan Buckingham, Mahesh Dhyani, Manasa Kumar, Alex Mazonowicz, Bridget Neale, Dominic Pereira, Shiny Poojary, Abhisekh Rane Erol Staveley, Ankita Thakur, Nitesh Thakur, and Jonathan Wray First published: October 2019 Second edition: April 2020 Production Reference: 1130420 ISBN: 978-1-80020-094-4 Published by Packt Publishing Ltd Livery Place, 35 Livery Street Birmingham B3 2PB, UK Table of Contents Preface   i Chapter 1: Introduction to Visualization with Python – Basic and Customized Plotting   1 Introduction   2 Handling Data with pandas DataFrame   3 Reading Data from Files  . 3 Exercise 1: Reading Data from Files   3 Observing and Describing Data   4 Exercise 2: Observing and Describing Data  . 4 Selecting Columns from a DataFrame  . 8 Adding New Columns to a DataFrame  . 8 Exercise 3: Adding New Columns to the DataFrame   9 Applying Functions on DataFrame Columns   10 Exercise 4: Applying Functions on DataFrame columns   11 Exercise 5: Applying Functions on Multiple Columns   13 Deleting Columns from a DataFrame  . 14 Exercise 6: Deleting Columns from a DataFrame   14 Writing a DataFrame to a File   16 Exercise 7: Writing a DataFrame to a File   16 Plotting with pandas and seaborn   18 Creating Simple Plots to Visualize a Distribution of Variables   18 Exercise 8: Plotting and Analyzing a Histogram    19 Bar Plots  . 25 Exercise 9: Creating a Bar Plot and Calculating the Mean Price Distribution    25 Exercise 10: Creating Bar Plots Grouped by a Specific Feature   30 Tweaking Plot Parameters   31 Exercise 11: Tweaking the Plot Parameters of a Grouped Bar Plot   32 Annotations  . 35 Exercise 12: Annotating a Bar Plot   36 Activity 1: Analyzing Different Scenarios and Generating the Appropriate Visualization   39 Summary   45 Chapter 2: Static Visualization – Global Patterns and Summary Statistics   47 Introduction   48 Creating Plots that Present Global Patterns in Data   48 Scatter Plots  . 49 Exercise 13: Creating a Static Scatter Plot  . 50 Hexagonal Binning Plots   51 Exercise 14: Creating a Static Hexagonal Binning Plot   51 Contour Plots  . 53 Exercise 15: Creating a Static Contour Plot   53 Line Plots   54 Exercise 16: Creating a Static Line Plot   55 Exercise 17: Presenting Data across Time with multiple Line Plots   58 Heatmaps   60 Exercise 18: Creating and Exploring a Static Heatmap   60 The Concept of Linkage in Heatmaps  . 66 Exercise 19: Creating Linkage in Static Heatmaps   66 Creating Plots That Present Summary Statistics of Your Data   71 Histogram Revisited   71 Example 1: Histogram Revisited  . 72 Box Plots   73 Exercise 20: Creating and Exploring a Static Box Plot   73 Violin Plots   76 Exercise 21: Creating a Static Violin Plot   77 Activity 2: Design Static Visualization to Present Global Patterns and Summary Statistics   78 Summary   83 Chapter 3: From Static to Interactive Visualization   85 Introduction    86 Static versus Interactive Visualization   88 Applications of Interactive Data Visualizations    93 Getting Started with Interactive Data Visualizations   95 Interactive Data Visualization with Bokeh   98 Exercise 22: Preparing Our Dataset   99 Exercise 23: Creating the Base Static Plot for an Interactive Data Visualization   104 Exercise 24: Adding a Slider to the Static Plot   107 Exercise 25: Adding a Hover Tool   108 Interactive Data Visualization with Plotly Express   113 Exercise 26: Creating an Interactive Scatter Plot   113 Activity 3: Creating Different Interactive Visualizations Using Plotly Express   117 Summary   119 Chapter 4: Interactive Visualization of Data across Strata   121 Introduction   122 Interactive Scatter Plots   122 Exercise 27: Adding Zoom-In and Zoom-Out to a Static Scatter Plot   124 Exercise 28: Adding Hover and Tooltip Functionality to a Scatter Plot   127 Exercise 29: Exploring Select and Highlight Functionality on a Scatter Plot   130 Exercise 30: Generating a Plot with Selection, Zoom, and Hover/Tooltip Functions   133 Selection across Multiple Plots   136 Exercise 31: Selection across Multiple Plots   137 Selection Based on the Values of a Feature   140 Exercise 32: Selection Based on the Values of a Feature   141 Other Interactive Plots in altair   143 Exercise 33: Adding a Zoom-In and Zoom-Out Feature and Calculating the Mean on a Static Bar Plot    144 Exercise 34: An Alternative Shortcut for Representing the Mean on a Bar Plot   150 Exercise 35: Adding a Zoom Feature on a Static Heatmap   153 Exercise 36: Creating a Bar Plot and a Heatmap Next to Each Other   157 Exercise 37: Dynamically Linking a Bar Plot and a Heatmap   160 Activity 4: Generate a Bar Plot and a Heatmap to Represent Content Rating Types in the Google Play Store Apps Dataset   163 Summary   166 Chapter 5: Interactive Visualization of Data across Time   169 Introduction   170 Temporal Data   170 Types of Temporal Data   171 Why Study Temporal Visualization?   172 Understanding the Relation between Temporal Data and Time‑Series Data   174 Examples of Domains That Use Temporal Data   175 Visualization of Temporal Data   176 How Time-Series Data Is Manipulated and Visualized   179 Date/Time Manipulation in pandas   181 Building a DateTime Index   182 Choosing the Right Aggregation Level for Temporal Data   183 Exercise 38: Creating a Static Bar Plot and Calculating the Mean and Standard Deviation in Temporal Data   185 Exercise 39: Calculating zscore to Find Outliers in Temporal Data   190 Resampling in Temporal Data   194 Common Pitfalls of Upsampling and Downsampling   194 Exercise 40: Upsampling and Downsampling in Temporal Data   194 Using shift and tshift to Introduce a Lag in Time-Series Data   199 Exercise 41: Using shift and tshift to Shift Time in Data   199 Autocorrelation in Time Series   201 Interactive Temporal Visualization   203 Bokeh Basics   204 Advantages of Using Bokeh   204 Exercise 42: Adding Interactivity to Static Line Plots Using Bokeh   206 Exercise 43: Changing the Line Color and Width on a Line Plot   208 Exercise 44: Adding Box Annotations to Find Anomalies in a Dataset   210 Interactivity in Bokeh   212 Activity 5: Create an Interactive Temporal Visualization    214 Summary   215 Chapter 6: Interactive Visualization of Geographical Data   217 Introduction   218 Choropleth Maps   218 Worldwide Choropleth Maps    219 Exercise 45: Creating a Worldwide Choropleth Map   220 Exercise 46: Tweaking a Worldwide Choropleth Map   223 Exercise 47: Adding Animation to a Choropleth Map   227 USA State Maps   231 Exercise 48: Creating a USA State Choropleth Map   232 Plots on Geographical Maps   235 Scatter Plots   235 Exercise 49: Creating a Scatter Plot on a Geographical Map   235 Bubble Plots   237 Exercise 50: Creating a Bubble Plot on a Geographical Map   238 Line Plots on Geographical Maps   244 Exercise 51: Creating Line Plots on a Geographical Map   245 Activity 6: Creating a Choropleth Map to Represent Total Renewable Energy Production and Consumption across the World   250 Summary   255 Chapter 7: Avoiding Common Pitfalls to Create Interactive Visualizations   257 Introduction   258 Data Formatting and Interpretation   258 Avoiding Common Pitfalls while Dealing with Dirty Data   259 Outliers   259 Exercise 52: Visualizing Outliers in a Dataset with a Box Plot   261 Exercise 53: Dealing with Outliers   266 Missing Data   269 Exercise 54: Dealing with Missing Values   269 Duplicate Instances and/or Features   275 Bad Feature Selection   276 Activity 7: Determining Which Features to Visualize on a Scatter Plot   276 Data Visualization    279 Choosing a Visualization    279 Common Pitfalls While Visualizing Data   282 Exercise 55: Creating a Confusing Visualization   283 Activity 8: Creating a Bar Graph for Improving a Visualization   286 Cheat Sheet for the Visualization Process   288 Summary   290 Appendix   293 Index   335 ... TrainingByPackt /Interactive- Data- Visualization- with- Python/ tree/master/Graphics/ Lesson1 Handling Data with pandas DataFrame | Handling Data with pandas DataFrame The pandas library is an extremely resourceful... "https://raw.githubusercontent.com/TrainingByPackt/ Interactive- Data- Visualization- with- Python/ master/datasets/diamonds csv" Handling Data with pandas DataFrame | Read files from the URL into the pandas DataFrame: #Yes, we can read files.. .Interactive Data Visualization with Python Second Edition Present your data as an effective and compelling story Abha Belorkar Sharath Chandra Guntuku Shubhangi Hora Anshu Kumar Interactive Data