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Döbler Mario - Data Visualization with Python: Create an impact with meaningful data insights using interactive and engaging visuals

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Understand, explore, and effectively present data using the powerful data visualization techniques of Python programming.Key Features Study key visualization tools and techniques with real-world data Explore industry-standard plotting libraries, including Matplotlib and Seaborn Breathe life into your visuals with exciting widgets and animations using Bokeh Book DescriptionData Visualization with Python reviews the spectrum of data visualization and its importance. Designed for beginners, itll help you learn about statistics by computing mean, median, and variance for certain numbers.In the first few chapters, youll be able to take a quick tour of key NumPy and Pandas techniques, which include indexing, slicing, iterating, filtering, and grouping. The book keeps pace with your learning needs, introducing you to various visualization libraries. As you work through chapters on Matplotlib and Seaborn, youll discover how to create visualizations in an easier way. After a lesson on these concepts, you can then brush up on advanced visualization techniques like geoplots and interactive plots.Youll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful visualizations. Whats more? Youll study how to plot geospatial data on a map using Choropleth plot and understand the basics of Bokeh, extending plots by adding widgets and animating the display of information.By the end of this book, youll be able to put your learning into practice with an engaging activity, where you can work with a new dataset to create an insightful capstone visualization.What you will learn Understand and use various plot types with Python Explore and work with different plotting libraries Learn to create effective visualizations Improve your Python data wrangling skills Hone your skill set by using tools like Matplotlib, Seaborn, and Bokeh Reinforce your knowledge of various data formats and representations Who this book is forData Visualization with Python is designed for developers and scientists, who want to get into data science or want to use data visualizations to enrich their personal and professional projects. You do not need any prior experience in data analytics and visualization, however, itll help you to have some knowledge of Python and familiarity with high school level mathematics. Even though this is a beginner level course on data visualization, experienced developers will be able to improve their Python skills by working with real-world data.Table of Contents The Importance of Data Visualization and Data Exploration All You Need to Know about Plots A Deep Dive into Matplotlib Simplifying Visualizations Using Seaborn Plotting Geospatial Data Making Things Interactive with Bokeh Combining What We Have Learned

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Data Visualization with Python

Create an impact with meaningful data insights using interactive and engaging visuals

Mario Dbler and Tim Gromann

Data Visualization with Python

Copyright 2019 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 author, 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.

Author: Mario Dbler and Tim Gromann

Reviewer: Jos Espaa

Managing Editor: Aditya Shah and Bhavesh Bangera

Acquisitions Editor: Kunal Sawant

Production Editor: Shantanu Zagade

Editorial Board: David Barnes, Ewan Buckingham, Shivangi Chatterji, Simon Cox, Manasa Kumar, Alex Mazonowicz, Douglas Paterson, Dominic Pereira, Shiny Poojary, Saman Siddiqui, Erol Staveley, Ankita Thakur and Mohita Vyas

First Published: February 2019

Production Reference: 2100419

ISBN: 978-1-78995-646-7

Table of Contents
Chapter 1:
Chapter 2:
Chapter 3:
Chapter 4:
Chapter 5:
Chapter 6:
Chapter 7:
Preface
About

This section briefly introduces the author, the coverage of this book, the technical skills you'll need to get started, and the hardware and software requirements required to complete all of the included activities and exercises.

About the Book

You'll begin Data Visualization with Python with an introduction to data visualization and its importance. Then, you'll learn about statistics by computing mean, median, and variance for some numbers, and observing the difference in their values. You'll also learn about key NumPy and Pandas techniques, such as indexing, slicing, iterating, filtering, and grouping. Next, you'll study different types of visualizations, compare them, and find out how to select a particular type of visualization using this comparison. You'll explore different plots, including custom creations.

After you get a hang of the various visualization libraries, you'll learn to work with Matplotlib and Seaborn to simplify the process of creating visualizations. You'll also be introduced to advanced visualization techniques, such as geoplots and interactive plots. You'll learn how to make sense of geospatial data, create interactive visualizations that can be integrated into any webpage, and take any dataset to build beautiful and insightful visualizations. You'll study how to plot geospatial data on a map using Choropleth plot, and study the basics of Bokeh, extending plots by adding widgets and animating the display of information.

This book ends with an interesting activity in which you will be given a new dataset and you must apply all that you've learned to create an insightful capstone visualization.

About the Author

Mario Dbler is a Ph.D. student with focus in deep learning at the University of Stuttgart. He previously interned at the Bosch Center for Artificial Intelligence in Silicon Valley in the field of deep learning, using state-of-the-art algorithms to develop cutting-edge products. In his master thesis, he dedicated himself to apply deep learning to medical data to drive medical applications.

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