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Interactive Data Visualization with Python - Second Edition

You're reading from Interactive Data Visualization with Python - Second Edition

Product type Book

Published in Apr 2020

Publisher

ISBN-13 9781800200944

Pages 362 pages

Edition 2nd Edition

Languages

Concepts

Data Visualization

Authors (4):

Abha Belorkar

Sharath Chandra Guntuku

Shubhangi Hora

Anshu Kumar

View More author details

Table of Contents (9) Chapters

Preface

About the Book

1. Introduction to Visualization with Python – Basic and Customized Plotting

2. Static Visualization – Global Patterns and Summary Statistics

3. From Static to Interactive Visualization

4. Interactive Visualization of Data across Strata

5. Interactive Visualization of Data across Time

6. Interactive Visualization of Geographical Data

7. Avoiding Common Pitfalls to Create Interactive Visualizations

Appendix

Introduction

The previous chapters of this book have progressed from static to interactive data visualizations and described various interactive features (such as sliders and hover tools) and types of plots (such as grouped bar graphs, line plots, and choropleth world maps) pertaining to specific types of data, such as temporal and geographical. This chapter lists and explains the possible mistakes and errors that are made during various stages of the data visualization process – such as visualizing uncorrelated elements from a dataset to display a relationship or creating an inapt interactive feature – and discusses how to ensure that the final visualization is appropriate, informative, and simple. Additionally, there is a cheat sheet at the end of this chapter that describes the libraries and the types of visualizations you should use when performing data visualization.

The process of data visualization may seem simple – take some data, plot some graphs...

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Authors (4)

Abha Belorkar

Abha Belorkar is an educator and researcher in computer science. She received her bachelor's degree in computer science from Birla Institute of Technology and Science Pilani, India and her Ph.D. from the National University of Singapore. Her current research work involves the development of methods powered by statistics, machine learning, and data visualization techniques to derive insights from heterogeneous genomics data on neurodegenerative diseases.

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Sharath Chandra Guntuku

Sharath Chandra Guntuku is a researcher in natural language processing and multimedia computing. He received his bachelor's degree in computer science from Birla Institute of Technology and Science, Pilani, India and his Ph.D. from Nanyang Technological University, Singapore. His research aims to leverage large-scale social media image and text data to model social health outcomes and psychological traits. He uses machine learning, statistical analysis, natural language processing, and computer vision to answer questions pertaining to health and psychology in individuals and communities.

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Shubhangi Hora

Shubhangi Hora is a data scientist, Python developer, and published writer. With a background in computer science and psychology, she is particularly passionate about healthcare-related AI, including mental health. Shubhangi is also a trained musician.

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Anshu Kumar

Anshu Kumar is a data scientist with over 5 years of experience in solving complex problems in natural language processing and recommendation systems. He has an M.Tech. from IIT Madras in computer science. He is also a mentor at SpringBoard. His current interests are building semantic search, text summarization, and content recommendations for large-scale multilingual datasets.

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