Interactive Data Visualization with Python: Present your data as an effective and compelling story , Second Edition

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Key benefits

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 real-world data

Description

With 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 non-interactive 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 non-interactive 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 go-to person for transforming data visualizations into engaging and interesting stories.

Who is this book for?

This 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 step-by-step 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.

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

What do you get with Print?

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Colour book shipped to your preferred address

Download this book in EPUB and PDF formats

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Frequently bought together

Interactive Data Visualization with Python

€36.99

€36.99

Hands-On Exploratory Data Analysis with Python

€59.99

Total € 133.97

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Robert Johnson May 15, 2020

I'm fairly new to Python. I bought this book to learn data visualization techniques with Python. It's well laid out with step by step instructions and explanations. There were a few sections that I couldn't get to work (Bokeh and Altair) but for the most part everything works and is correct. The Bokeh and Altair examples don't work for me but I suspect it's something to do with my setup (versions). I tried the author's downloaded code with the same result in case I had some weird syntax problem that I wasn't able to figure out. The other issue is more a problem with the Kindle version of the book. Depending on where it splits the page, it can make indentations hard to spot. But that's not really the fault of the author. Just something to be aware of.Using the techniques in the book, I was able to take some US COVID data and plot out maps with different visualizations (infections by county, infections per capita by county, time series tracking of growth by county). It was pretty cool to see it match up the professional sites. I did a per capita plot that showed a huge bubble in Tennessee, which I thought might have been a defect in the data. I googled the county and it turned out the data was correct due to a prison located in a sparse county which resulted in 1 in 9 people showing as infected.

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Dr. Bernd M. Feb 25, 2021

Ich mag das Buch, schaue immer wieder rein, wenn ich schnell mal paar Plots mit Seaborn, Bokeh, Plotly oder Altair erstellen möchte. Mich selber hat am Anfang vor allem die klare Beschreibung der Clustermaps von Seaborn beeindruckt, gibt es zwar auch im Internet, aber da wird man meistens von Details regelrecht erschlagen. Ich mag auch das Einführungskapitel zu Pandas, da ich bei der Bearbeitung/Umwandlung von Data-Frames immer wieder irgendwo was nachschlagen muss. Meiner Meinung nach ist es eine wirklich gute Mischung aus Lehrbuch und Nachschlagewerk.

Yifu Jan 13, 2021

This book is only good for complete beginners who have little or no experience in data visualizations with Python. The book covers basic usage of matplotlib, altair, bokeh and plotly but the topics covered are too simple. You could easily get better explanations or examples by searching online.If you have some or intermediate knowledge in data visualization, you could learn much more by just searching for tutorials or example gallery of those packages online.

Interactive Data Visualization with Python: Present your data as an effective and compelling story , Second Edition

What do you get with Print?