Title
Interactive Data Visualization with Python: Present your data as an effective and compelling story, 2nd Edition,Used
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Create your own clear and impactful interactive data visualizations with the powerful data visualization libraries of Python Key Features Study and use Python interactive libraries, such as Bokeh and Plotly Explore different visualization principles and understand when to use which one Create interactive data visualizations with realworld data Book DescriptionWith so much data being continuously generated, developers, who can present data as impactful and interesting visualizations, are always in demand. Interactive Data Visualization with Python sharpens your data exploration skills, tells you everything there is to know about interactive data visualization in Python.You'll begin by learning how to draw various plots with Matplotlib and Seaborn, the noninteractive data visualization libraries. You'll study different types of visualizations, compare them, and find out how to select a particular type of visualization to suit your requirements. After you get a hang of the various noninteractive visualization libraries, you'll learn the principles of intuitive and persuasive data visualization, and use Bokeh and Plotly to transform your visuals into strong stories. You'll also gain insight into how interactive data and model visualization can optimize the performance of a regression model.By the end of the course, you'll have a new skill set that'll make you the goto person for transforming data visualizations into engaging and interesting stories. What you will learn Explore and apply different interactive data visualization techniques Manipulate plotting parameters and styles to create appealing plots Customize data visualization for different audiences Design data visualizations using interactive libraries Use Matplotlib, Seaborn, Altair and Bokeh for drawing appealing plots Customize data visualization for different scenarios Who this book is forThis book intends to provide a solid training ground for Python developers, data analysts and data scientists to enable them to present critical data insights in a way that best captures the user's attention and imagination. It serves as a simple stepbystep guide that demonstrates the different types and components of visualization, the principles, and techniques of effective interactivity, as well as common pitfalls to avoid when creating interactive data visualizations. Students should have an intermediate level of competency in writing Python code, as well as some familiarity with using libraries such as pandas. Table of Contents Introduction to Visualization with PythonBasic and Customized Plotting Static Visualization Global Patterns and Summary Statistics From Static to Dynamic Visualization Interactive Visualization of Data across Strata Interactive Visualization of Data across Time Interactive Visualization of Data across Geographical Regions Avoiding Common Pitfalls to Create Interactive Visualization
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This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the main focus of 'Interactive Data Visualization with Python - Second Edition'? A: The book focuses on creating clear and impactful interactive data visualizations using Python's powerful libraries such as Bokeh and Plotly. It teaches how to effectively present data as engaging stories.
- Q: Who is the target audience for this book? A: The book is aimed at Python developers, data analysts, and data scientists who have an intermediate level of Python competency and want to enhance their skills in data visualization.
- Q: What programming libraries will I learn about in this book? A: Readers will learn to use several libraries including Matplotlib, Seaborn, Bokeh, Plotly, and Altair for creating various types of visualizations.
- Q: How many pages does the book contain? A: The book contains a total of 362 pages.
- Q: Is this book suitable for beginners in Python? A: No, this book is intended for individuals with an intermediate understanding of Python programming. A basic familiarity with libraries such as pandas is also recommended.
- Q: What are some key features of this book? A: Key features include exploring various interactive visualization techniques, customizing plots for different audiences, and learning the principles of effective data storytelling.
- Q: When was 'Interactive Data Visualization with Python - Second Edition' published? A: The book was published on April 13, 2020.
- Q: What can I expect to learn from this book? A: You can expect to learn how to create appealing interactive visualizations, manipulate plotting parameters, and apply different visualization principles effectively.
- Q: What edition is this book? A: This is the second edition of the book.
- Q: What is the condition of the book being sold? A: The book is in new condition.