#datamustread: Visualize This: The FlowingData Guide to Design, Visualization, and Statistics (2nd Edition) by Nathan Yau

A bookshelf neatly arranged with several books on data visualization and analytics: Displayed in the center is the 2nd edition of "Visualize This: The FlowingData Guide to Design, Visualization, and Statistics" by Nathan Yau. Surrounding this book are various other titles, including those by the Alexander Loth: "Decisively Digital", "Teach Yourself VISUALLY Power BI", "Visual Analytics with Tableau", "Datenvisualisierung mit Tableau", "Datenvisualisierung mit Power BI", and "KI für Content Creation." Other visible titles include "Rewired" and "Self-Service BI & Analytics." The arrangement highlights a strong focus on data visualization, analytics, and AI.
The 2nd edition of Visualize This by Nathan Yau, surrounded by several influential data and AI books, including my own works like Decisively Digital and Teach Yourself Visually Power BI.

While my latest book, KI für Content Creation, has just been reviewed by the renowned c’t magazine, I’m happy to continue reviewing books myself. Today, I’m reviewing the just-released second edition of a cornerstone of the data visualization community, Visualize This: The FlowingData Guide to Design, Visualization, and Statistics by Nathan Yau.

Visualize This: A Deep Dive into Data Visualization

Nathan Yau’s Visualize This has long been a staple for data enthusiasts, and the updated second edition brings fresh techniques, technologies, and examples that reflect the rapidly evolving landscape of data visualization.

Core Highlights of This Book

Data-First Approach: Yau emphasizes that effective visualizations start with a deep understanding of the data. This foundational principle ensures that the resulting graphics are not just visually appealing but also accurately convey the underlying information.

Diverse Toolkit: The book introduces a wide range of tools, including the latest R packages, Python libraries, JavaScript libraries, and illustration software. Yau’s pragmatic approach helps readers choose the right tool for the job without feeling overwhelmed by options.

Real-World Applications: With practical, hands-on examples using real-world datasets, readers learn to create meaningful visualizations. This experiential learning approach is particularly valuable for grasping the subtleties of data representation.

Comprehensive Tutorials: The step-by-step guides are a standout feature, covering statistical graphics, geographical maps, and information design. These tutorials provide clear, actionable instructions that make complex visualizations accessible.

Web and Print Design: Yau details how to create visuals suitable for various mediums, ensuring versatility in application whether for digital platforms or printed materials.

Personal Insights on Visualize This

Having taught data strategy and visualization for seven years, I find Visualize This to be an exceptional resource for a broad audience. Yau skillfully integrates scientific data visualization techniques with graphic design principles, providing practical advice along the way. The book’s toolkit is extensive, featuring R, Illustrator, XML, Python (with BeautifulSoup), JSON, and more, each with working code examples to demonstrate real-world applications.

The image shows an open page from the second edition of "Visualize This: The FlowingData Guide to Design, Visualization, and Statistics" by Nathan Yau. The page, from Chapter 5 titled "Visualizing Categories," features a colorful visualization titled "Cycle of Many," which depicts a 24-hour snapshot of daily activities based on data from the American Time Use Survey. This visual highlights how categories change over time and demonstrates the book's practical approach to data visualization.
Visualize This featuring a colorful 24-hour activity visualization based on data from the American Time Use Survey.

Even though I read the first edition years ago, I couldn’t put the second edition down all weekend. This book is a must-read for anyone who handles data or prepares data-based reports. Its beautiful presentation and careful consideration of every aspect—from typeface to page layout—make it a pleasure to read.

The book is user-friendly, offering a massive set of references and free tools for obtaining interesting datasets across various fields, from sports to politics to health. This breadth of resources is crucial for anyone looking to create impactful visualizations across different domains.

While the focus on Adobe Illustrator might be daunting due to its cost and learning curve, Yau’s examples show how Illustrator can enhance graphics created in other tools like SAS and R. I personally prefer the open-source Inkscape, but Yau’s insights helped me overcome my initial reluctance to use Illustrator, leading to more polished and professional visuals.

Yau uses R, Python, and Adobe Illustrator to demonstrate what can be achieved with imagination and creativity. Although some readers might desire more complex walkthroughs from raw data to final graphics, such material would require substantial foundational knowledge in R and Python. Including this would make the book significantly thicker and veer off from its focus on creating visually appealing graphics.

Conclusion: Visualize This is Essential Reading for Data Professionals

Visualize This (Amazon) is an indispensable guide for anyone serious about data visualization. Its methodical, data-first approach, combined with practical tutorials and a comprehensive toolkit, makes it a must-read for information designers, analysts, journalists, statisticians, and data scientists.

For those looking to refine their data visualization skills and create compelling, accurate graphics, this book offers invaluable insights and techniques.

Connect with me on LinkedIn and Twitter for more reviews and insights on the latest in data and AI! #datamustread

Unlocking the Power of Data Science with Excel: Discover the Book „Data Smart“

Exploring the depths of Data Science with Excel: A glimpse into 'Data Smart' by Jordan Goldmeier, a must-read for data enthusiasts.
Exploring the depths of Data Science with Excel: A glimpse into ‚Data Smart‘ by Jordan Goldmeier, a must-read for data enthusiasts.

Data Smart (Amazon) is an exceptional guide that creatively uses Microsoft Excel to teach data science, making complex concepts accessible to business professionals. This 2nd edition, masterfully updated by Jordan Goldmeier, arrives a decade after John Foreman’s highly acclaimed original version, bringing fresh perspectives and contemporary insights to the renowned first edition.

Whether you’re a novice or a seasoned analyst, this book provides valuable insight and skill enhancement without requiring extensive programming knowledge. The practical, problem-solving approach ensures that you not only understand the theory, but also how to apply it in real-world scenarios. That’s why I’ve chosen Data Smart as our latest pick for the #datamustread book club.

Why „Data Smart“ is a #datamustread

Data Smart stands out in the realm of data science literature. Its approachable and practical methodology is a breath of fresh air for business professionals and data enthusiasts alike. Here’s why this book is an indispensable resource:

1. Excel as Your Data Science Laboratory:
The use of Excel, a tool many of us are familiar with, to unravel data science concepts is nothing short of brilliant. This approach significantly flattens the learning curve, making complex techniques more digestible.

2. Practical Learning through Real Business Problems:
Each chapter of the book introduces a different data science technique via a relatable business scenario. This context-driven approach makes the learning experience tangible and immediately applicable.

3. No Programming, No Problem:
The author’s method of teaching data science without delving into programming languages makes the content accessible to a broader audience.

4. Excel Skills Elevated:
In addition to data science concepts, readers will enhance their Excel prowess with advanced tools like Power Query and Excel Tables.

5. A Spectrum of Techniques:
From cluster analysis to forecasting, the book covers a wide array of methods, making it a comprehensive toolkit for any aspiring data scientist.

6. Fresh Perspectives in the Second Edition:
Goldmeier’s updates are not just cosmetic; they incorporate the latest Excel features, ensuring the content remains relevant in today’s fast-paced tech landscape.

Bridging the Gap with „Teach Yourself VISUALLY Power BI“

While exploring Data Smart, you’ll find parallels with the insights shared in my own book, Teach Yourself VISUALLY Power BI. Both texts aim to make data analytics accessible and actionable, providing a solid foundation for anyone looking to make informed decisions based on data.

Your Journey into Data Science Awaits

Data Smart is a gateway to understanding data science through a familiar and powerful tool: Excel. Whether you’re a beginner or a seasoned analyst, this book will enhance your analytical skills and expand your understanding of data in the business world.

Order Data Smart today and support both the authors and my endeavors in bringing such valuable resources to our community. Let’s dive into this journey of discovery together, transforming data into actionable insights.

Join the Conversation

After delving into Data Smart, I’d love to hear your thoughts and takeaways. Share your insights and join the discussion in our vibrant #datamustread community on LinkedIn and Twitter:

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#datamustread Data Viz Essentials: The Must-Read Books to Master Data Visualization

#DataVizEssentials 2023: The Must-Read Books to Master Data Visualization
#DataVizEssentials 2023: The Must-Read Books to Master Data Visualization

Building on the previous #datamustread recommendations, I’m excited to present the data viz edition of #datamustread. In this post, we’re focusing on the indispensable skill of data visualization. Whether you’re a beginner or a seasoned pro, these five books will guide you to mastery:

  1. 📖 The Big Book of Dashboards
  2. 📖 Storytelling with Data
  3. 📖 The Truthful Art
  4. 📖 Show Me the Numbers
  5. 📖 Teach Yourself VISUALLY Power BI

The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios

A comprehensive guide filled with real-world solutions for building effective business dashboards across various industries and platforms. It’s a go-to resource for matching great dashboards with real-world scenarios.

Storytelling with Data: A Data Visualization Guide for Business Professionals

Cole Nussbaumer Knaflic shares practical guidance on creating compelling data stories. Learn how to make your data visually appealing, engaging, and resonant with your audience.

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Die Top 5 Bücher für erfolgreiche Data Science: Unverzichtbare Lektüre für angehende Data Scientists

Welche Data Science Bücher sollten Sie lesen um als Data Scientist erfolgreich zu sein? | Photo Credit: via Sebastian Sikora
Welche Data Science Bücher sollten Sie lesen um als Data Scientist erfolgreich zu sein? | Photo Credit: via Sebastian Sikora

Möchten Sie eine Karriere in Data Science verfolgen und fragen sich, welche Bücher Ihnen auf diesem Weg helfen können? In diesem Blogbeitrag präsentiere ich Ihnen die fünf entscheidenden Bücher, die für Ihre Ausbildung und Ihren beruflichen Werdegang in Data Science unerlässlich sind. 📚

1. Einstieg und Überblick: „Data Science in der Praxis“

Einstieg und Überblick: Data Science in der Praxis

Data Science in der Praxis von Tom Alby bietet Ihnen einen umfassenden Einstieg in die Welt der Daten. Dieses Buch vermittelt Ihnen nicht nur die Grundlagen von Data Science, sondern bietet auch praktische Beispiele und Fallstudien, die Ihnen helfen, das Gelernte anzuwenden und zu vertiefen.

2. Python Crashkurs: „Data Science mit Python“

Python Crashkurs: Data Science mit Python

Python ist die universelle Programmiersprache, die sich hervorragend zur Lösung von Data-Science-Fragestellungen eignet. Mit Data Science mit Python von Jake VanderPlas lernen Sie Python auf effiziente Weise und bereiten sich auf komplexere Data-Science-Aufgaben vor.

3. Der Statistikwerkzeugkasten: „Statistik I und II für Dummies“

Der Statistikwerkzeugkasten: Statistik I und II für Dummies

Statistik ist das Rückgrat von Data Science. Statistik für Dummies und Statisik II für Dummies von Deborah J. Rumsey bieten eine umfassende und leicht verständliche Einführung in die Statistik. Die Bücher decken eine Vielzahl von Themen ab, einschließlich Regression, Varianzanalyse, Chi-Quadrat-Tests und nichtparametrische Verfahren.

4. Für große Datenmengen: „Hadoop: The Definitive Guide“

Für große Datenmengen: Hadoop: The Definitive Guide

Hadoop: The Definitive Guide von Tom White ist unerlässlich, wenn Sie mit großen Datenmengen arbeiten. Dieses Buch führt Sie durch die Komplexitäten von Hadoop und hilft Ihnen, das Potenzial Ihrer Daten voll auszuschöpfen.

5. Mehrwert durch Data Science: „Data Science für Unternehmen“

Dieses #datamustread Buch von Foster Provost und Tom Fawcett zeigt auf, wie Data Science für Unternehmen Mehrwert schafft. Es erklärt die Grundlagen der Data Science und zeigt auf, wie Sie die Prinzipien auf reale Geschäftssituationen anwenden können.

Gewonnene Erkenntnisse visualisieren: Bücher zu Datenvisualisierung

Sie möchten Ihre mit Data Science gewonnenen Erkenntnisse visualisieren und interessieren sich für Bücher zum Thema Datenvisualisierung? Dann werfen Sie gerne einen Blick in meine Bücher!

Haben Sie andere Empfehlungen für Data Science Bücher? Teilen Sie Ihre Gedanken und Kommentare in diesem Tweet:

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Power BI Data Visualization Mastery: Unlocking Insights with „Teach Yourself VISUALLY Power BI“

Power BI Data Visualization Mastery with the book "Teach Yourself VISUALLY Power BI" by Alexander Loth
Power BI Data Visualization Mastery with the book „Teach Yourself VISUALLY Power BI“

If you’ve been on the lookout for a comprehensive guide to unlock the potential of data visualization using Microsoft’s Power BI, you’ve come to the right place. Our latest pick for the #DataMustRead book club is a special one – Teach Yourself VISUALLY Power BI (Amazon), which recently hit Amazon’s #1 New Release in Information Management. Authored by myself, this book is your pathway to understand and implement Power BI, regardless of whether you’re a beginner or a seasoned professional.

Why Choose „Teach Yourself VISUALLY Power BI“ for Your Power BI Journey?

Microsoft’s Power BI is a dynamic tool, breathing life into your company’s data through rich visuals and interactive dashboards. As powerful as it is, though, it can also present a daunting learning curve, especially if you’re new to data visualization. „Teach Yourself VISUALLY Power BI“ is designed to help you conquer this curve and emerge as a Power BI maestro.

This book is more than just a typical guide. It’s a visually-rich journey that transports you from Power BI basics to advanced features, equipping you with a strong foundation. Here’s a peek into what you can expect:

  1. Connect with Various Data Sources: Learn to prepare your data for visualization and connect seamlessly to multiple data sources.
  2. Transform and Process Data: Understand the transformation of raw data into valuable, decision-driving information.
  3. Create Customizable Charts and Graphs: Design visually striking, easy-to-understand charts and graphs with hands-on guidance.
  4. Apply Analytics and Machine Learning: Uncover the realm of analytics and machine learning, and learn how to apply these concepts in Power BI.
  5. Craft Interactive Dashboards: Master the creation of interactive dashboards that effectively narrate your data’s story.

Each topic is presented using full-color screenshots, step-by-step instructions, and practical tips, ensuring that you’ll be able to follow along no matter your current skill level.

The Data Visualization Guide for Any Power BI Project

The reviews for „Teach Yourself VISUALLY Power BI“ speak for themselves. Many readers have found the book to be an excellent resource, praising its unique approach to teaching both, data visualization and Power BI. From the detailed explanation of requirements gathering – a crucial step in any Power BI project – to providing insightful exploration of the current BI job market, this book aims to equip readers with a comprehensive understanding of Power BI and its practical applications.

Your Next Step in Power BI Mastery

Whether you’re a data rookie or a seasoned expert seeking to upskill, „Teach Yourself VISUALLY Power BI“ is a must-read. It doesn’t just enable you to understand Power BI, it inspires you to craft your own data visualizations and drive impactful decisions.

Are you ready to dive deep into Power BI? Order your copy here to support my future book projects. Happy reading, data enthusiasts!

I’m eager to hear your thoughts as you delve into this comprehensive guide to Power BI. Don’t forget to use the hashtag #datamustread to share your insights and experiences on LinkedIn or Twitter!

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