These 3 books may change your way of visualizing the data!

Data visualization is a method to visualize statistical data to communicate the insights and patterns behind the data. However, plotting the various charts with statistical plots only makes sense sometimes.
Good data analysts/data scientists used to open the secret behind the data with their expertise. However, beginners also gain that expertise through reading well-written books from experienced Authors.
I used to upgrade my data visualization skills by reading various books, and Here are some of my recommendations to upgrade your skills in data visualization.
1. How to Choose the Right Data Visualization by Mike Yi ✍️

If you need to outline your data using visualization but aren’t sure what kind of visualization to use, this book will recommend chart types to try.
In this book, chart types have been divided into seven major categories based on visualization roles. such as,
- Display the data (Raw Numbers) in a Single value chart, Single value with indicator, Bullet chart, and Table.
- Charts showing change over time are explained in Line Charts, Sparkling, Connected Scatter plots, Bar charts, and Box plots.
- Charts for showing part-to-whole composition described by Pie charts, Doughnut charts, Waffle charts/Grid Plots, Stacked Bar charts, Stacked Area charts, and Steam graphs.
- Charts depicting flows and processes explain Funnel Chart, Parallel Sets Chart, Sankey Diagram, and Gantt chart.
- Data distributions are explained by Bar charts, histograms, Density curves, Box plots, Letter-Value plots, and Violin plots.
- Comparing values between groups include Bar Chart, Grouped Bar Chart, Lollipop Chart, Dot Plot, Line Chart, Sparkling, RidgeLine, Box Plot, Letter-Value Plot, and Violin Plot.
- Observing relationships between variables include Scatter Plots, Bubble charts, Connected Scatter plots, Dual-axis bar line Plots, Grouped Bar charts, Heatmap, 2-d density Curves, and Dendrogram.
- Examining geographical data include Scatter maps, Bubble maps, 2-d histograms, Isopleth/contour maps, Connection maps, Choropleths, and cartograms.
Download the book 📕 using this link.
2. Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic ✍️

If you are a newbie in visualization and want to generate good charts and ethics on fundamentals of storytelling in a business circumstance, this is an important book to start learning the primary principles. Specifically, you’ll learn about
- The importance of context
- Choosing an effective visual
- Clutter is your enemy!
- Focus your audience’s attention
- Think like a designer
- Dissecting model visuals
- Lessons in storytelling
Through this book 📖 you can improve reasoning and analytical 🧐 skills for Data Visualization.
My favorite is chapter -6, which explains the dissecting model visuals. In this chapter, you will learn the importance of fascinating model visuals.
Overall this book is to best Visualise raw numbers.
Here is the link to purchase this book – Amazon Site
3. Good Charts Workbook: Tips, Tools, and Exercises for Making Better Data Visualizations by Scott Berinato ✍️

Good Charts Workbook gives ideas and exercises to help you practice DataViz. Each chapter has an overview of a topic, some examples, practice questions, and an “answer key” that shows his thought process but offers an open mind to alternatives.
The Good Charts Workbook provides tools, exercises, and practical insights that help you gain your skills.
How is the workbook organized? Two core sections make up the book.
Part 1. Build Skills

Build Skills part includes: Controlling Color, Crafting for Clarity, Choosing Chart Types, Practicing Persuasion, Capturing Concepts
Part 2: Make Good Charts

Make Good Charts include: Talk, Sketch, Prototype, The Monthly Report, and The Plastic Problem Presentation.
I would recommend this book 📕 for beginner to intermediate-level data visualization practitioners.
Still, there are many excellent books available for Data Visualization. Also, recommend your favorite data visualization book in the comment.
For more insights on data visualization and data science, follow me on LinkedIn.
https://www.linkedin.com/in/amsavalli-datascientist/
Thanks & Regards
Amsavalli