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Over 60 New York Times Graphs for Students to Analyze

A collection of graphs, maps and charts organized by topic and graph type from three years of “What’s Going On in This Graph?”

Graphs, Charts and Maps From Three Years of “What’s Going On in This Graph?”

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books magazines charts graphs diagrams

By The Learning Network

Note: Register for our free November 5 webinar about teaching with graphs , or watch a previously recorded on-demand webinar here .

For the last three years, we have collaborated with the American Statistical Association (A.S.A.) to produce “ What’s Going On in This Graph? ” This weekly feature invites students to analyze and interpret graphs previously published in The New York Times, first by noticing and wondering, and then by creating a catchy headline and considering what impact this data might have on them and their communities.

Scroll through the dozens of graphs in the slide show above or explore each graph further in the collection below. This curated list is organized by topic and graph type — ranging from science to sports, and from bar graphs to bubble charts.

If you’re new to the feature, here is how it works:

Each week during the school year we take a graph that has been published elsewhere in The New York Times and ask students to share what they notice and wonder about it. This feature is completely free, and it runs from September to May.

We post these graphs on Thursdays, and include them in our free weekly newsletter , so teachers can plan for the coming week.

Then, on Wednesdays from 9 a.m. to 2 p.m. Eastern time, we host a live-moderated discussion where students from around the world post their observations and analysis while moderators from A.S.A. facilitate the student conversation.

Your class can join the discussion any day of the week, not just Wednesdays, and students can even comment on graphs in our archive.

On Thursday afternoons, a week after we publish each graph, we add a “reveal” to the post which includes additional background about these graphs, shout-outs for great student headlines, and relevant statistical concepts.

Graphs Organized by Topic

Environment, Science and Technology

Houston May Get 50 Inches of Rain. How Long Does it Take Your City to Get That Much?

It’s Not Your Imagination. Summers Are Getting Hotter .

The Places in the U.S. Where Disaster Strikes Again and Again

Where Are America’s Winters Warming the Most?

How Does Your State Make Electricity?

Hang On, Northeast. In Some Parts, Spring Has Already Sprung.

Read a Hurricane Map the Right Way

2018 Continues Warming Trend, As 4th Hottest Since 1880

What’s the Right Number of Taxis?

The Most Detailed Map of Auto Emissions In America

Your Questions About Food and Climate Change, Answered

Privacy Policies Are a Mess

2019 Was the Second-Hottest Year Ever, Closing Out the Warmest Decade

Teach About Climate Change With These 24 New York Times Graphs

Six Myths About Choosing a Major

Old Skills, New Careers: Workers in Fading Jobs Often Already Have What It Takes to Succeed in Growing Ones

Where Education Drives Mobility

How Bad Will the Crisis Get?

Why We Need to Keep the Curve Flat

You Can Break the Chain of Transmission

What If We Open America Too Early?

Seven Ways to Explore the Math of the Coronavirus

How the Virus Transformed How Americans Spend Their Money

How Long Will a Vaccine Really Take?

Is It Safer to Visit a Coffee Shop or a Gym?

The Arts, Sports and Culture

The Words Men and Women Use When They Write About Love

What Music Do Americans Love the Most? 50 Detailed Fan Maps

Pumpkin Pie in Miami: Thanksgiving Flight Patterns

What if a $250 Shoe Actually Made You Race Faster ?

How a New Kind of Pop Star Stormed 2018

Do Summer Songs Sound the Same?

Manny Machado Signed a $300 Million Deal; Bryce Harper’s Could Be for More. Will They Be Worth It?

How Popular Is Baseball, Really?

Inside Footballs’ Campaign to Save the Game

Three Months’ Salary for an Engagement Ring? For Most People, It’s More Like Two Weeks

Health and Wellness

Is Sushi Healthy? What About Granola? Where Americans and Nutritionists Disagree

Obesity Was Rising as Ghana Embraced Fast Food. Then Came KFC

The Age That Women Have Babies: How a Gap Divides America.

A Picture of Social Connectedness in America

How Bad Was Her Commute? This $8,650 Scarf Tells the Tale

F.D.A. to Limit How Stores Sell Vaping Flavors

Bigger, Saltier, Heavier: Fast Food Since 1986 in 3 Simple Charts

Why Euthanasia Rates at Animal Shelters Have Plummeted

The Major Issue of Mental Health

United States Economy, Politics, History and Civics

Unemployment Is So 2009: Labor Shortage Gives Workers an Edge

How the Growth of E-Commerce Is Shifting Retail Jobs

What Explains U.S. Mass Shootings? International Comparisons Suggest an Answer

Apple Is Worth $1,000,000,000,000. Two Decades Ago, It Was Almost Bankrupt.

With Kennedy’s Retirement, the Supreme Court Loses Its Center

A Fast-Food Problem: Where Have All the Teenagers Gone?

The Myth of the Lazy November

Political Bubbles and Hidden Diversity: Highlights From a Very Detailed Map of the 2016 Election

A Typical “Dreamer” Lives in Los Angeles, Is From Mexico and Came to the U.S. at 6.

The Monopolization of America

Is America’s Military Big Enough?

How Much Political Experience Does It Take to Be Elected President?

Undocumented Population and Crime Rate

Data Shows Decline in Number of White Neighborhoods

Why Afghanistan Became an Invisible War: Yearly Front-Page Headlines About War

Mystery of the Missing Bus Riders

How the Virus Transformed How Americans Spent Their Money

Anti-Immigration Shift in U.S. Promoted Rise of a Young Firebrand

Global Economies, History, Politics and Culture

Migrants Are on the Rise Around the World, and Myths About Them Are Shaping Attitudes.

Obesity Was Rising as Ghana Embraced Fast Food. Then Came KFC.

A grid with 20 graphs from the "What's Going On in This Picture?" feature

Graphs Organized by Type

Distribution (values and their frequency)

Six Myths About Choosing a Major (boxplot)

It’s Not Your Imagination. Summers Are Getting Hotter . (histogram)

The Age That Women Have Babies: How a Gap Divides America (histogram)

Data Shows Decline in Number of White Neighborhoods (histogram)

Three Months’ Salary for an Engagement Ring? For Most People, It’s More Like Two Weeks (histogram)

Association (relationship between two or more variables)

Is Sushi Healthy? What About Granola? Where Americans and Nutritionists Disagree (scatter plot)

The Words Men and Women Use When They Write About Love (bubble chart)

What Explains U.S. Mass Shootings? International Comparisons Suggest an Answer (scatter plot)

Obesity Was Rising as Ghana Embraced Fast Food. Then Came KFC. (scatter plot)

Old Skills, New Careers: Workers in Fading Jobs Often Already Have What It Takes to Succeed in Growing Ones (scatter plot)

Manny Machado Signed a $300 Million Deal; Bryce Harper’s Could Be for More. Will They Be Worth It? (scatter plot)

Serena Williams Reaches For Margaret Court (line chart)

What’s the Right Number of Taxis? (scatterplot)

Undocumented Population and Crime Rate ” (scatter plot)

Privacy Policies Are a Mess ” (scatter plot)

How Bad Will the Crisis Get? (scatter plot)

How the Virus Transformed How Americans Spend Their Money (bubble chart)

Is It Safer to Visit a Coffee Shop or a Gym? (bubble chart)

Unemployment Is So 2009: Labor Shortage Gives Workers an Edge (line time series)

How the Growth of E-Commerce Is Shifting Retail Jobs (step time series)

The Places in the U. S. Where Disaster Strikes Again and Again (dot and column time series)

With Kennedy’s Retirement, the Supreme Court Loses Its Center (line time series)

A Fast-Food Problem: Where Have All the Teenagers Gone? (line time series)

Student Loan Rates Are Rising. Here’s What You Need to Know. (area chart)

Where Are America’s Winters Warming the Most? (diverging bar graph time series)

The Monopolization of America (slope time series)

F.D.A. to Limit How Stores Sell Vaping Flavors (line time series)

2018 Continues Warming Trend, As 4th Hottest Since 1880 (time series with baseline)

Why Euthanasia Rates at Animal Shelters Have Plummeted (stacked area time series)

How Popular Is Baseball, Really? (time series)

How Much Political Experience Does It Take to Be Elected President? (timeline)

The Most Detailed Map of Auto Emissions In America (Line time series & stacked area time series)

An Ecological Crisis as 2.9 Billion Birds Vanish (time series)

Why We Need to Keep the Curve Flat (time series)

Mystery of the Missing Bus Riders (time series)

What If We Open America Too Early? (time series)

2019 Was the Second-Hottest Year Ever, Closing Out the Warmest Decade (time series)

Anti-Immigration Shift in U.S. Promoted Rise of a Young Firebrand (time series)

How Long Will a Vaccine Really Take? (critical path diagram)

Comparing Categories

Apple Is Worth $1,000,000,000,000. Two Decades Ago, It Was Almost Bankrupt. (area graph)

The Myth of the Lazy November (pictogram)

What if a $250 Shoe Actually Made You Race Faster ? (dot plot)

A Typical “Dreamer” Lives in Los Angeles, Is From Mexico and Came to the U.S. at 6. (bar graph)

How Bad Was Her Commute? This $8,650 Scarf Tells the Tale (stacked time series graph)

How Does Your State Make Electricity? (ranking area graph)

Do Summer Songs Sound the Same? (radar graph)

Where Education Drives Mobility (data chart)

Bigger, Saltier, Heavier: Fast Food Since 1986 in 3 Simple Charts (back-to-back bar graphs)

Your Questions About Food and Climate Change, Answered (bar graphs)

An Ecological Crisis as 2.9 Billion Birds Vanish (bar graph)

Inside Football’s Campaign to Save the Game (infographic)

Water Crisis May Grip One-Quarter of Humanity (dot plot)

Three Months’ Salary for an Engagement Ring? For Most People, It’s More Like Two Weeks (bar chart)

Out with the Old, In with the Young (bar chart)

Why Afghanistan Became an Invisible War: Yearly Front-Page Headlines About War (bar graph)

How the Virus Transformed How Americans Spent Their Money (bubble chart)

Parts to Whole

How a New Kind of Pop Star Stormed 2018 (segmented bar graph)

Where Education Drives Mobility (segmented bar graph)

The Major Issue of Mental Health (segmented bar graph)

How Long Will a Vaccine Really Take? (probability tree diagram)

Houston May Get 50 Inches of Rain. How Long Does it Take Your City to Get That Much? (heat map)

What Music Do Americans Love the Most? 50 Detailed Fan Maps (heat map)

Migrants Are on the Rise Around the World, and Myths About Them Are Shaping Attitudes. (directed graph)

Political Bubbles and Hidden Diversity: Highlights From a Very Detailed Map of the 2016 Election (heat map)

Pumpkin Pie in Miami: Thanksgiving Flight Patterns ( directed graph)

A Picture of Social Connectedness in America (heat map)

Is America’s Military Big Enough? (bubble map)

Hang On, Northeast. In Some Parts, Spring Has Already Sprung. (time series heat map)

Read a Hurricane Map the Right Way (map)

A ‘Full’ Nation in Dire Need of New Faces (heatmap)

An Ecological Crisis as 2.9 Billion Birds Vanish (heatmap)

Water Crisis May Grip One-Quarter of Humanity (heatmap)

You Can Break the Chain of Transmission (tree diagram)

The Top 20 Data Visualization Books That Should Be On Your Bookshelf

The top 20 data visualization books blog post by datapine

“Most of us need to listen to the music to understand how beautiful it is. But often that’s how we present statistics: we just show the notes, we don’t play the music.” - Hans Rosling, Swedish statistician

datapine is filling your bookshelf thick and fast. Previously, we discussed the top 19 big data books you need to read, followed by our rundown of the world’s top business intelligence books as well as our list of the best SQL books for beginners and intermediates. Now that you’re sold on the power of data analytics in addition to data-driven BI, it’s time to take your journey a step further by exploring how to effectively communicate vital metrics and insights in a concise, inspiring, and accessible format through the power of visualization.

Data visualization, or ‘data viz’ as it’s commonly known, is the graphic presentation of data. These aesthetically striking portrayals are the most effective way to succinctly translate large segments of complex data to a wide audience. Successful visualizations are aesthetically beautiful, providing layers of detail that generate deeper dimensions of insight and whole new layers of understanding. They can be fun and interactive, too.

The field of online data visualization is growing, and whether you’re a data viz expert or just getting started, there is a wide range of books that will help you learn new skills and remain ahead of the pack.

Not sure where to start? A mere Amazon search of this topic returns over 15k items. That’s a colossal number of books on visualization. And while some of them we consider the best books on data visualization, some are really not.

But don’t fret, because we’ve conducted the research and reading on your behalf, refining our findings to create our list of the world’s best 20 data visualization books.

This list is in no particular order, but what we promise you is that these are 20 of the best books on data visualization available today, and you’ll find there’s something for everybody.

Here we’ve included prose based on visualization history, theory, psychology, and practical implementation as well as intricate graphical presentation tips and a visually stunning coffee table book for inspiration.

But before we delve into our list of books on data visualization, here are some facts and figures for your inspiration.

Data visualization: What You Need To Know

  • 90% of the information transmitted to the brain is visual – a testament to the power and potential of data visualization.
  • People are 30 times more likely to absorb high-quality infographics than plain text.
  • Studies suggest that if a scientific claim is presented in only words or numbers, 68% of people will deem the information to be accurate and truthful. But if the same insights or metrics are presented in a simple graph, the number rises to 97% .
  • A BI strategy that leverages data visualization will provide an ROI of $13.01 back on every dollar spent.

Now that we’ve established the importance and potency of visualization in the digital age, let’s take a look at our rundown of the best data visualization books.

1) “The Visual Display of Quantitative Information” by Edward R. Tufte

Data Visualization Book #1: the visual display of quantitative information by Edward Tufte

**click for book source**

You can’t make a list of data visualization books without including Edward Tufte . Tufte is considered to be amongst the foremost pioneers in the field and this really is considered the best book on data visualization out there. “The Visual Display of Quantitative Information” is one of his most famous data visualization books. It covers the theory and design of data graphics and provides 250 illustrations of the best and worst examples. Though printed in 1983, it remains a classic and a bestseller on Amazon. Tufte provides an astute introduction to core visualization theories, building on these concepts throughout the book, and frankly, this should be on every data viz bookshelf.

2) “Storytelling With Data: A Data Visualization Guide for Business Professionals” by Cole Nussbaumer Knaflic

Best data visualization book: Storytelling With Data by Cole Nussbaumer Knaflic

Laszlo Bock, former SVP of People Operations at Google, introduces one of the most beautiful data visualization books in our lineup in a way that nobody else can:

“In ‘Storytelling With Data,’ Cole has created an of-the-moment complement to the work of data visualization pioneers like Edward Tufte. She’s worked at and with some of the most data-driven organizations on the planet as well as some of the most mission-driven, data-free institutions. In both cases, she’s helped sharpen their messages and their thinking.”

You may be able to create complicated, technical, and colorful visualizations and load them with a ton of data. But, if your target audience can’t decipher them, what’s the point? In the end, visualizations are meant to convey or highlight what’s happening with your data – they’re supposed to tell a story. That is why “Storytelling With Data” is on our list.

Cole Knaflic’s mission is to teach readers. “Don’t simply show your data – tell a story with it,” and her offering, which we consider to be one of the world’s best data visualization books, demonstrates how to go beyond conventional tools to reach the root of your data while using a dashboard storytelling process to create an engaging and informative presentation in a way that is accessible to everyone.

The author recently published an “expanded follow-up” to her book called “Storytelling With Data: Let’s Practice!”. In this guide-style publication, Cole Knaflic presents exercises and real-world examples to put all the knowledge you gain from the first piece into practice.

3) “The Big Book Of Dashboards: Visualizing Your Data Using Real-World Business Scenarios” by Steve Waxler, Jeffrey Shaffer, and Andy Cotgreave

Data visualization books: The Big Book of Dashboards by Steve Wexler, Jeffrey Shaffer, Andy Cotgreave

Our next best book to learn data visualization is the “The Big Book Of Dashboards”. Written by professionals in the field, it provides readers with the perfect mix of the theoretical part of using data visualizations and the practical part of actually applying this knowledge to real-life scenarios. 

With dozens of real-world dashboard examples coming from various formats such as print, desktop, or mobile, and different industries such as finance, healthcare, human resources, sports, marketing, and more, this ultimate handbook on business dashboards will give you all the necessary tools and knowledge to build an effective dashboard using data visualizations. In addition to the examples, the book also offers insights into the psychological factors that go into building an engaging and efficient dashboard. 

With more than 30 years of experience combined, these authors put into words the best practices you should follow as well as the challenges you would most likely encounter during your dashboard design process and give you the necessary tools to deal with all of them. It is a definitive reference for anyone who wants to master the art of dashboarding. 

4) “Data Sketches: A Journey Of Imagination, Exploration, And Beautiful Data Visualizations” by Nadieh Bremer and Shirley Wu

Best data visualization books: Data Sketches: A Journey Of Imagination, Exploration, And Beautiful Data Visualizations by Nadieh Bremer and Shirley Wu

This next piece is not a typical data visualization book that shows you the theoretical aspect of using visuals to understand data. Data Sketches is a publication that documents the creative process of authors Nadie Bremer and Shirley Wu in creating 24 data visualization projects. These projects explore different topics which include the Olympics, the Royals, myths, presidents, and more, exploring different technologies, visualization, and design techniques to show that data viz is an equal part of science and art. 

In addition to providing a behind-the-scenes look into the author's processes through sketches and notes, it also offers detailed insights on core data visualization concepts, data gathering and sketching techniques for the web, as well as practical lessons based on the challenges they faced during the creation of these 24 projects. 

Data Sketches is a book covered in full-color images that will lead you through the complete process of creating a data visualization project. You will also find the finalized version of the 24 projects and learn how powerful data storytelling can be. 

Since its publication in 2021, it has been praised by various professionals in the industry. Here is an excerpt from Andy Kirk, another data viz author that you will find later on this list:

“This book brings the perfect blend of ingredients together for a nourishing recipe of inspiration and knowledge beneficial to beginners and experienced practitioners alike. Nadieh and Shirley are generational talents. Through their data visualization work, they relentlessly exhibit a wide spectrum of capabilities across the creative, editorial, analytical, and technical dimensions”.

5) "Data Visualization - A Practical Introduction" by Kieran Healy

Data Visualization – A Practical Introduction by Kieran Healy

If you’re searching for a book that combines theory and practice in a comprehensive and hands-on approach to visualization, you need to have this one on your bookshelf. Written by a professor of sociology at Duke University, this book provides researchers and students instructions on using R and ggplot2 in an innovative and coherent manner.

Whether you are a beginner or an advanced user of data, statistics, and visualizations, this fun, and readable book, authored by Kieran Healy , will show you the unique world of visualizations that can be effectively used for communicating data in a graphical way.

6) “How Charts Lie: Getting Smarter About Visual Information” by Alberto Cairo

How charts lie: Getting smarter about visual information - Alberto Cairo

While displaying data in beautiful charts, graphs, and diagrams is the most successful way to uncover hidden trends and patterns in our data, it doesn’t come without challenges. When not used correctly, charts can lie. The information in them can be misleading or misunderstood in a number of ways, a tactic that has been used for decades by journalists, politicians, and advertisers to manipulate audiences. 

Under that premise, renowned journalist and data visualization expert, Alberto Cairo builds his latest publication: “How Chats Lie: Getting Smarter About Visual Information”. In this book, Cairo uses a wide range of examples to teach readers how to understand graphs and charts and how to spot the misleading visualizations we often see in the media. It is a perfect guide for beginners that need to understand how charts work and the bad practices that need to be avoided when presenting data in a visual way.  

7) “Infographics Designers’ Sketchbooks” by Steven Heller and Rick Landers

Infographics Designers’ Sketchbooks by Steven Heller and Rick Landers

Focusing less on data analytics and more on eye-grabbing presentations, “Infographics Designers’ Sketchbooks” is a data visualization book that will inspire your creative efforts from start to finish.

What's particularly impressive about this data visualization design book is the fact that it offers a rare glimpse into the minds of 50 of the world's most prolific graphic designers through their personal sketchbooks. By examining the creative process of the planet’s best visualists, you’ll be able to spot the link between data and drawings. As a result, you’ll gain the tools and inspiration you need to create a wealth of stunning infographics that will help you present critical information that enlightens and creates value rather than excluding and causing confusion.

8) “Knowledge is Beautiful” by David McCandless

Knowledge is Beautiful by David McCandless

Boasting near flawless reader reviews on Amazon, this graphically-driven book on data visualization makes an excellent companion when it comes to thriving in the digital age.

“Knowledge is Beautiful” is celebrated data journalist David McCandless ' best-selling publication on the subject, and its concept is simple: using sensational visuals to reveal surprising insights into how the world really works and using this knowledge for your own innovations.

If you’re looking to transform head-turning, jaw-dropping aesthetic concepts that connect with others on a meaningful level while yielding real results, this is one of the best data visualization books you will ever own.

9) “The Book of Circles: Visualizing Spheres of Knowledge” by Manuel Lima

The Book of Circles: Visualizing Spheres of Knowledge by Manuel Lima

The follow-up to the critically-acclaimed "The Book of Trees and Visual Complexity", this offbeat and wildly valuable book on data visualization delves deep into millennia of circular information innovation and design.

Coupling a kaleidoscopic array of inspirational visual designs throughout the ages with stunning modern-day examples of visualization in action, author Manuel Lima connects the enduring concept of the human relationship with visuals and its application to data in a way that is exciting, engaging, and practical in equal measure. One of the visualizing data best books available today.

10) “Effective Data Visualization: The Right Chart for the Right Data” by Stephanie Evergreen

Effective data visualization: The right chart for the right data - Stephanie Evergreen

Excel has been the primary tool to generate visuals and manage data for decades. That said, it is still intimidating software that makes the lives of a lot of users very difficult. With that issue in mind, author Stephanie Evergreen put together “Effective Data Visualization: The Right Chart for the Right Data” as a guide for readers that want to learn how to create Excel charts and graphs in an efficient way.

Using approachable and funny language, Evergreen guides readers into learning the fundamentals of data visualization in Excel. The book includes the types of graphs available and on which scenario they are most appropriate to use, as well as a step-to-step checklist to create them on the tool. Originally published in 2016, it has a second edition that was published in 2019 that includes a rewritten chapter on qualitative data as well as 9 new chart types and shortcuts on Excel. A must-read for anyone looking to become an Excel guru.

11) “Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks” by Jonathan Schwabish

Better Data Visualizations: A Guide For Scholars, Researchers, And Wonks by Jonathan Schwabish

As you’ve probably noticed already with our list of books, visuals make the world better. Every piece of information is better received and perceived when it comes in a visual format. Author Jonathan Schwabis put the value of visuals into perspective with his piece “Better Data Visualizations: A Guide For Scholars, Researchers, And Wonks”. 

Through more than 500 examples, the author aims to teach its readers the value of data visualizations and how to create effective ones in different contexts. Anyone reading this piece can expect to learn the do’s and don'ts of visual design, the core visualization types and how each of them should be used, and how to clearly communicate your message using graphics. 

If you don’t trust our word for it, maybe this excerpt from a reader's review will convince you: “This book is quite extraordinary in regards to giving the presentational theory of graphed information. Truly a must to anyone who wants to tell stories through data” .

12) “Data Visualisation: A Handbook for Data Driven Design” by Andy Kirk

“Data Visualization: A Handbook for Data Driven Design” by Andy Kirk

Voted one of the "six best books for data geeks" by The Financial Times, "Data Visualization: A Handbook for Data Driven Design," authored by Andy Kirk , offers a clear, concise, and digestible introduction to the field.

With a host of hand-picked data visualization examples as well as a wealth of real-world tips, methods, approaches, and insights, this really is one of the best books on data visualization for those getting started.

The language is accessible, the advice is practical, and in addition to a physical copy of the book, you will also gain access to comprehensive online data analysis tools and support, which includes a selection of exercises so you can practice your skills. Be aware that there is a second edition to this book published in 2019.

13) “Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures” by Claus O. Wilke

Fundamentals of Data Visualization: A Primer On Making Informative and Compelling Figures by Claus O. Wilke

Being successful when it comes to data visualization is not an easy task. There is a wide range of tools and techniques out there which can make you feel confused and overwhelmed. If this is the case for you, don’t worry, author Claus Wilke data visualization book has you covered. 

In “Fundamentals Of Data Visualization: A Primer On Making Informative And Compelling Figures”, Wilke guides readers through a practical journey to understanding the fundamentals of successful visuals. Covering topics such as the basics of colors, details on chart types, examples of poorly constructed visuals, and tips on how to turn large datasets into a compelling story, this publication is the perfect overview for scientists, engineers, and anyone whose work involves generating data visualizations. No matter the visual analytics tools or programming language you use, after reading this book you should be able to extract the maximum potential out of your visual design process. 

14) “Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics” by Nathan Yau

“Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics” by Nathan Yau

One of the most valuable visualizing data books of recent times, data viz guru Nathan Yau provides another great practical handbook on visualization and how to approach real-world data in his masterpiece, “Visualize This . ” We recommend this book in color to take full advantage of the step-by-step tutorials on how to visualize and tell stories with data.

For developers, there are code examples in R, Python, and JavaScript. Yau’s website flowingdata.com is another great source for all levels of visualization that also showcases fun data viz experiments.

15) “Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations” by Scott Berinato

“Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations” by Scott Berinato

Published in May 2016, this is one of the most relevant visualizing data books on the market. What we like about “Good Charts” is that it’s accessible for the data viz beginner but just as helpful for the more advanced dashboard design user.

Berinato highlights the important point that data viz is no longer being left just to the specialists: data scientists and professional designers. A new generation of data visualization tools, like datapine, and massive amounts of data make it easy for the layperson to create visualizations that communicate ideas far more effectively than spreadsheets and PowerPoint charts. In “Good Charts,” Berinato provides an invaluable guide to how visualization works and how to use data viz to influence and persuade. This is a must-read.

Another gem coming from this author is his second title and the most recent book: Good Charts Workbook: Tips, Tools, and Exercises for Making Better Data Visualizations . The beauty of this publication lies within the practical part; a hands-on guide that will enable you to create your own visualization while teaching you how to develop your own visualization and thinking processes. A must-read for anyone interested in the practical part of data visualization. 

16) “Information Dashboard Design: Displaying Data for At-a-glance Monitoring” by Stephen Few

“Information Dashboard Design: Displaying Data for At-a-glance Monitoring” by Stephen Few

Don’t let the lackluster cover fool you, or as they say: don’t judge a book by its cover, because this visualizing data book has plenty to offer in the way of visualization. Few guides are so helpful in providing a wide range of good and bad dashboard examples . Moreover, author Stephen Few offers a great introduction to the principles of data visualization and design theory. If you wonder which graph displays data in top-to-bottom fashion, then this piece is for you. Oh, and if you become a Stephen Few fan, he has multiple visualization and analytics books to check out.

17) “Information Graphics” by Sandra Rendgen, Julius Wiedemann

Top data visualization book: “Information Graphics” by Sandra Rendgen, Julius Wiedemann

Looking for inspiration? Or just love data viz as an art? One of the most beautiful data visualization books is a great coffee table book or one to keep next to your desk for when you’re in a data viz rut.

It has a little of everything, providing over 400 examples of information graphics from around the world, covering journalism art, government, education, business, and more. The introductory essays on data visualization history and theory as well as data journalism are also a good read, and the accompanying images are worth a long look.

18) “Cartographies of Time: A History of the Timeline” by Daniel Rosenberg

“Cartographies of Time: A History of the Timeline” by Daniel Rosenberg

This book won’t help you get your business intelligence dashboard up and running for next week’s board meeting, but history buffs will be enthralled by the comprehensive history of graphic representations of time in Europe and the United States from 1450 to the present. The accompanying graphics prove that visualization isn’t just a modern-day science. We have been striving to draw time long before the conception of dashboards!

19) “Semiology of Graphics: Diagrams, Networks, Maps” by Jacques Bertin

“Semiology of Graphics: Diagrams, Networks, Maps” by Jacques Berti

We round out this list with another visualization pioneer, Jacques Bertin. Originally published in 1967 in French, Bertin’s Semiology of Graphics holds a significant place in the theory of information design.

Founded on Jacques Bertin’s practical experience as a cartographer, Part One attempts to synthesize principles of graphic communication with the logic of standard rules applied to writing and topography. Part Two brings Bertin’s theory to life, presenting a close study of graphic techniques, including shape, orientation, color, texture, volume, and size in an array of more than 1,000 maps and diagrams.

20) “Beautiful Visualization, Looking at Data Through the Eyes of Experts” by Julie Steele, Noah Iliinsky

Top Data Visualilzation Book #5: “Beautiful Visualization, Looking at Data Through the Eyes of Experts” by Julie Steele, Noah Iliinsky

This piece is part of O’Reilly’s “Beautiful” series, with each book a collection of essays from people who work in the field. “Beautiful Visualization,” authored by Julie Steele and Noah Iliinsky, describes the design and development of some well-known visualizations by examining the methods of 24 visualization experts.

One of the great things about this big data visualization book is that the authors approach their projects from a variety of perspectives: artists, designers, commentators, scientists, analysts, statisticians, and more. The topics include:

  • The importance of storytelling through a simple visualization exercise.
  • Color and how it conveys information that our brains recognize before we are cognizant of it.
  • Uncovering a method to the madness of air travel with a civilian air traffic visualization that is beautifully portrayed.

To summarize, here is our list of the best books on data visualization:

  • “The Visual Display of Quantitative Information” by Edward R. Tufte
  • “Storytelling With Data: A Data Visualization Guide for Business Professionals” by Cole Nussbaumer Knaflic
  • “The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios” by Steve Wexler, Jeffrey Shaffer, Andy Cotgreave
  • “Data Sketches: Journey Of Imagination, Exploration, And Beautiful Visualizations” by Nadieh Bremer, Shirley Wu
  • “Data Visualization – A Practical Introduction” by Kieran Healy
  • “How Charts Lie: Getting Smarter About Visual Information” by Alberto Cairo
  • “Infographics Designers’ Sketchbooks” by Steven Heller and Rick Landers
  • “Knowledge is Beautiful” by David McCandless
  • “The Book of Circles: Visualizing Spheres of Knowledge” by Manuel Lima
  • “Effective Data Visualization: The Right Chart For The Right Data” by Stephanie Evergreen 
  • “Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks” by Jonathan Schwabish
  •  “Data Visualisation: A Handbook for Data Driven Design” by Andy Kirk
  • “Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures” by Claus O. Wilke
  • “Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics” by Nathan Yau
  • “Good Charts: The HBR Guide to Making Smarter, More Persuasive Data Visualizations” by Scott Berinato 
  • “Information Dashboard Design: Displaying Data for At-a-glance Monitoring” by Stephen Few
  • “Information Graphics” by Sandra Rendgen, Julius Wiedemann
  • “Cartographies of Time: A History of the Timeline” by Daniel Rosenberg
  • “Semiology of Graphics: Diagrams, Networks, Maps” by Jacques Bertin
  • “Beautiful Visualization, Looking at Data Through the Eyes of Experts” by Julie Steele, Noah Iliinsky

Now, it’s time to step away from those Excel spreadsheets, forget those static tables, and start telling a real story with your data. As you may have gathered, data visualization is the best way to squeeze every last drop of value from the metrics and insights that are available at your fingertips, and now that you’ve got the tools you need for success, it’s time to get going.

Do you want to get a head start on deciding what data visualizations you should start to build while waiting for your books to arrive? Check out our 14-day trial , completely free!

21 Best Data Visualization Books, According to Experts

books magazines charts graphs diagrams

Want to level up your data visualization knowledge? You may need to head to the library.

With the world more technologically connected, data science and the need for visualizing data have swelled in significance. And though the nature of data and new tools is ever changing, so many core best practices in data visualization remain evergreen. As such, some of the best data visualization books have (pardon the pun) a long shelf life.

“A lot of what changes is just software, [but] a lot of the concepts remain very constant,” said Alli Torban, a Washington, D.C.-based data visualization consultant. “Even a 10-year-old book still has a lot it can teach you.”

We asked four data visualization experts to select and discuss a few of their favorite data visualization books. Our experts include:

  • Cole Nussbaumer Knaflic , CEO of storytelling with data, author of Storytelling with Data: A Data Visualization Guide for Business Professionals and Storytelling with Data: Let’s Practice! and host of the SWD podcast.
  • Alli Torban , an information design consultant and host of the Data Viz Today podcast.
  • Randy Krum , founder of data visualization and infographics design firm InfoNewt, and author of Cool Infographics: Effective Communication with Data Visualization and Design .
  • Tamara Munzner , a computer science professor at the University of British Columbia and author of Visualization Analysis and Design .

According to them, these data visualization books are worth picking up.

21 Best Data Visualization Books

Ranging from casual reads to practical applications and advanced theory deep-dives, here are the must-read data visualization books according to experts.

Best Data Visualization Books

  • Data Sketches  by Nadieh Bremer and Shirley Wu
  • Information Graphics  by Sandra Rendgen
  • Avoiding Data Pitfalls  by Ben Jones
  • Better Data Visualizations  by Jonathan Schwabish
  • Good Charts Workbook  by Scott Berinato
  • How Charts Lie  by Alberto Cairo
  • Info We Trust  by RJ Andrews
  • Data at Work  by Jorge Cam ões
  • The Big Book of Dashboards  by Steve Wexler, Jeffrey Shaffer and Andy Cotgreave
  • Design for Information  by Isabel Meirelles

General Interest Data Visualization Books

1. cartography. by kenneth field.

This book — written by a professional cartographer — isn’t solely about data visualization. Or is it? After all, a map can be thought of as a way to visualize data when the where matters. This is one of the most impressive books I’ve ever encountered. That’s not only due to its sheer heft — there are more than 500 pages packed with content — but also because of the thoughtful way Field structures and organizes so much information in a way that doesn’t overwhelm.

Each two-page spread focuses on a single aspect (for example, a map type or design principle). The text is formatted for easy scanning and paired with a variety of beautiful images. Topics are color-coded and alphabetized, so it’s easy to find items of interest or explore a concept that piques your curiosity. It turns out that much of the design rationale that goes into making a good map can direct efforts visualizing data in graphical form as well. (Knaflic)

Buy: Bookshop , Amazon

2. Data Sketches: A Journey of Imagination, Exploration, and Beautiful Data Visualizations by Nadieh Bremer and Shirley Wu

Data Sketches has a special place in my heart. It’s a tour de force — sort of like a coffee table book meets tech, a great book if you know something about data viz and want to go to the next level. It’s an amazing resource for people who want to level up.

books magazines charts graphs diagrams

More on Data Science 12 Data Science Projects for Beginners and Experts

History of Data Visualization Books

3. information graphics by sandra rendgen.

A great coffee table book. It charts the evolution of visual communication design, with hundreds of graphics. The audience is people who are interested in information design, but it has general interest appeal. Anyone who picks it up will find something interesting.

The chapters are broken up by location, time, category and hierarchy, then every page has giant examples. I like to flip through when I need inspiration, to get a quick sense of how other people have solved similar design problems. So if I’m doing something with, say, time series, I’ll just flip through some dozens of pages of various time based-infographics and end up with a ton of ideas. Also, it’s just a really beautiful book. (Torban)

4. Semiology of Graphics: Diagrams, Networks, Maps by Jacques Bertin

Semiology was written in the 1960s, and Bertin’s insights are even more noteworthy given the technological constraints of the day. He pioneered methods for systematic data analysis that are now done with interactive computation, but he had to try them out as manual operations with paper and scissors and even built some mechanical devices .

The book contains amazing systematic diagrams. On the other hand, the English translation is terrible, and Bertin was admittedly idiosyncratic. A modern English speaking viz person would use very different terms than the ones used in the book. You wouldn’t say “implantation,” you’d say layout. But if you want to go deep and you’re interested in the history of the ideas, there is absolutely nothing like it.

In data viz, there’s visual encoding and there’s interaction. And we have much more deep theory about how to visually encode data than we do about interacting with it. So I think a lot of the ideas here, which are about visual encoding, do hold up. (Munzner)

More on Data and Design What Is Information Architecture?

Practical Applications of Data Visualization Books

5. avoiding data pitfalls: how to steer clear of common blunders when working with data and presenting analysis and visualizations by ben jones.

I recommend Avoiding Data Pitfalls frequently. Conversational in tone and packed with relatable examples, this book details seven pitfalls that Jones has fallen into or seen others stumble over, in an effort to spare readers from making the same mistakes.

Each chapter focuses on a single peril, explaining the specific relevant dangers and illustrating through example, helping you learn how to recognize and avoid them. Though there is but a single chapter focused specifically on data visualization (pitfall No. 6: graphical gaffes), the book demonstrates throughout the types of questions and thought processes that anyone who visualizes data should be pondering when analyzing their data. Great for those early in their data analysis and visualization journey, the lessons outlined serve as an important reminder of issues that can be easily overlooked by more experienced analysts as well. (Knaflic)

6. Better Data Visualizations: A Guide for Scholars, Researchers, and Wonks by Jonathan Schwabish

Published in early 2021 and including a stellar variety of visualizations (more than 500 examples), Better Data Visualizations reads as an enjoyable and educational encyclopedia of graphs.

The book is organized into three sections. It begins with a brief primer on data visualization best practices. Part two is the bulk of the book: chart types. Schwabish dives deep into different types of graphs that go well beyond the standards of lines and bars. He includes insightful discussion about why and when each works — and when they don’t — with many examples. The final section explores design and provides direction for developing and using a data visualization style guide.

While the subtitle suggests a more limited audience, this is an excellent resource for anyone who analyzes and communicates with data. I’m also a big fan of Schwabish’s related One Chart at a Time video series. (Knaflic)

7. Good Charts Workbook: Tips, Tools, and Exercises for Making Better Data Visualizations by Scott Berinato

A great book for a new practitioner, since it offers hands-on practice. It’s written in a style that almost feels like Berinato is a nice mentor or co-worker, and he’s just walking you through. It has quiz-like prompts, asking, for example, why a specific pie chart is hard to read, and what could make it better. Then there’s sketch space to draw what you’d do instead. The data sets he gives aren’t complex, so you can easily sketch them.

And there’s a discussion section where he doesn’t necessarily give answers, but explains how he’d think about it. In data viz, designers can sometimes think the way they do it is the [only] way, so I appreciate his measured approach: This is how I’d probably do it, and these are my considerations. (Torban) 

8. How Charts Lie: Getting Smarter about Visual Information by Alberto Cairo

A must-read guide if you’re designing charts that will be published. Cairo is in data journalism, and he’s dedicated to ensuring data visualizations are done objectively and don’t skew or misrepresent the data .

He’s spoken for years about how some poor visualization choices in the news media have led to misunderstanding of data, whether that’s weather data — hurricane maps — and also election data . It’s a great treatise on how data can be visualized in misleading ways, and for practitioners, what to avoid so that you don’t get strongly criticized by visualizing something in a manner you didn’t intend to do. (Krum)

Cairo’s books are super accessible, very clearly written. His background as a journalist is obvious. He works very hard to get people to think about the use of visuals. For anyone intent on data literacy, on making charts that don’t mislead, he’s your go-to. (Munzner)

9. Info We Trust: How to Inspire the World with Data by RJ Andrews

Info We Trust is a beautiful book. It feels substantial. The colors are vibrant. The language is poetic. The content is inspiring.

Nearly every inch is filled with information: margins are packed with quotes from wide-ranging sources and other relevant tidbits. While I’ve spoken with others who have found this distracting, I thought it gave insight into the extensive research that went into the book and a peek at ancillary paths not taken. The text and margins are interspersed with hand-drawn images and graphs that help reinforce concepts. The chapters are relatively short in length but dense in ideas and abstracts, which provide a good balance.

Info We Trust is definitely not a how-to book, yet it is interlaced with practical advice. At one point, Andrews discusses sparking curiosity in your audience. He says — and I’m paraphrasing — that good stories leave space for the audience to forge connections. The book itself does this beautifully, making astute observations but allowing the reader room to connect and extrapolate to their own work. (Knaflic) 

10. The Wall Street Journal Guide to Information Graphics: The Dos and Don'ts of Presenting Data, Facts, and Figures by Dona M. Wong

It’s written from a journalist’s perspective — with principles to make good charts for the media. But it’s also very helpful for those who don’t necessarily have a data background. Wong’s clear examples address specific, common issues. For instance, there’s a section on good y-axis increments — what an awkward increment looks like, and what to do instead. There’s also a very helpful section on log scales. The book is pretty prescriptive; it’s in the subtitle: the dos and don’ts. So if you’re looking for a foothold, this is a great, example-rich starting point.

Also, she explains math concepts very clearly, such as how to calculate a percent change, which, if you’re creating a chart, those kinds of calculations are things you have to do. But if you don’t necessarily have a math background, it can be confusing and hard to find by Googling. (Torban)  

More on Data Science Human-Looking Data Visualizations Don’t Boost Empathy — Yet

Business-Focused Data Visualization Books

11. cool infographics: effective communication with data visualization and design by randy krum.

I wrote this for people who use infographics, whether for internal communication, such as employee education or as a sales tool, or for public-facing, external marketing. It teaches you how to publish your designs online along with the SEO skills needed — how to set up a landing page and optimize for search. So many companies will design an infographic, throw it on their company blog or Facebook page, and then do nothing with it. You have to prepare before you publish.

Also, a full chapter is dedicated to infographic resumes, to help use the power of data visualization to market yourself. All the power of visualizing corporate data — letting readers quickly digest and retain information — applies to your personal information when applying for jobs as well. The chapter looks at the types of data that people visualize for resumes, plus questions like whether to separate the infographic from your text resume or integrate them together, and how to handle automated submission systems if you have an infographic resume. (Krum)

12. Data at Work: Best Practices for Creating Effective Charts and Information Graphics in Microsoft Excel by Jorge Camões

A great overview of visual perception and information theory, focused on communicating in a business environment. It goes through concepts like preattentive attributes, colors and how to choose the right chart for your data. Camões includes links for all his examples, which were built in Excel — the most common tool out there. So it doesn’t overwhelm people into thinking they need Tableau or Adobe Illustrator to build something beautiful. 

You can download and explore his charts via the links, but the book is not an Excel how-to. It’s all about choosing the best design, communicating effectively and making your visualizations stand out, rather than look like every other Excel chart out there. He also writes about not simply relying on the default chart gallery. (Krum)

13 and 14. Storytelling with Data: A Data Visualization Guide for Business Professionals and Storytelling with Data: Let's Practice! by Cole Nussbaumer Knaflic

My books, Storytelling With Data and the follow-up Let’s Practice! , focus on making graphs that make sense in the business world and weaving them into compelling and action-inspiring stories. They codify and expand upon the lessons that we teach in our workshops, sharing practical tips and strategies that you can use in your next report or presentation .

The first book, Storytelling With Data , is meant to be read. The popularity it’s maintained since publication is likely in a large part due to its simplicity. It’s a relatively quick read that allows you to immediately appreciate the power of the lessons, demonstrated through real-world examples. Once you’ve read it cover to cover, it can serve as a great desktop resource to those making graphs and presentations. 

Let’s Practice! invites you to do exactly that — practice. The same lessons that structure the first book guide this exercise-based book. Three sections of exercises comprise each chapter. In the first section, I pose a scenario for readers to work through on their own, but also detail my solution and the thought process that drove my decisions, sharing a good deal of content and many examples. This is followed by a section of unsolved exercises that are great for those who’d like additional independent practice or who teach others. In the final exercise section of each chapter, I break down strategies and outline how you can apply them to your next project.

Getting good at communicating with data takes practice, and this book will help you flourish. Everyone is invited to explore the interactive online companion resource, SWD community , too. (Knaflic)

15. The Back of the Napkin: Solving Problems and Selling Ideas with Pictures by Dan Roam

A classic. Here, Roam teaches how to communicate visually by focusing on hand drawings. He dives into business communication using diagrams, charts, maps and visual explanations. His visual thinking codex is all about which charts and diagrams go best with which kinds of information.

[The point is:] Don’t be afraid to visualize. Even if you’re a bad artist, like I am, you can still get your point across — and it’ll come across better if you visualize it versus anything else. No matter your drawing or design skills, you will benefit from this book.

I do a lot of our work, whether it’s presentation or infographic design, that involves visual metaphors, using icons and illustrations to communicate concepts, rather than visualizing data. He goes into a lot of that here as well. (Krum)

16. The Big Book of Dashboards: Visualizing Your Data Using Real-World Business Scenarios by Steve Wexler, Jeffrey Shaffer and Andy Cotgreave

This is the perfect book for business analysts , with countless examples of real dashboards, arranged by different scenarios: a sales dashboard for executives, rankings over time, complaint tracking, churn — things that you actually do in business contexts. Each chapter includes an example and explains why that dashboard works, and there are thoughtful discussions throughout each section on various practical and design considerations. Sometimes within a chapter, the co-authors disagree, so it’s really helpful to hear different sides. 

I don’t do dashboards too often, but when I do, it’s convenient to be able to look up exactly what I need based on a given use case. There has been some dashboard backlash, and I agree, they’re not the most exciting thing, but people still need and use them. So you need resources for how to do them well. (Torban)

17. The Big Picture: How to Use Data Visualization to Make Better Decisions—Faster by Steve Wexler

Here, Wexler goes into some data-viz theory, but he really focuses on how to get organizations to adopt a data visualization mentality, how to effectively communicate data internally and how to get executives to start looking at charts that aren’t just bar charts.

I call them the big three: bar charts, line charts and pie charts. There are people who don’t like to go beyond those borders. They don’t want to see a Sankey diagram or a scatter plot. Wexler writes about how to move your organization into those other visual styles that will actually help your people understand the data better. Sometimes that means visualizing the same data in a few different ways to get better understanding.

Companies have so much data, and it keeps growing. They feel an imperative to use it to make better business decisions. Here, Wexler directly connects that to visualizations. If you want to make effective decisions with your data, people need to understand it. (Krum)

More on Data Science 6 Ways to Make Data-Visualization Literacy Part of Company Culture

Advanced Data Visualization Books

18. design for information: an introduction to the histories, theories, and best practices behind effective information visualizations by isabel meirelles.

This book explains how we visually perceive information, plus different ways available to visualize data — charts, but also maps, network diagrams, a lot of flowcharts, trees and other ways to visualize information that may not specifically be a table of data. It’s definitely for [data-viz] practitioners, not for, say, a product manager or someone just dealing with Excel charts. This is more advanced, like if you’re designing timelines of the history of your company.

It’s almost 10 years old now, but the concepts about structure — relational, hierarchical, spatial, temporal or textual structures — don’t change. Whether you use R or Tableau, or draw by hand, the ideas of communicating effectively in a certain structure are consistent and tool-agnostic. (Krum)

[This book is] a carefully curated walk through the world of visualization, specifically from a designerly viewpoint, but one that goes deep. It’s not just a pretty coffee table book; it really does explore the ideas. (Munzner)

Buy: Amazon

19. Interactive Visual Data Analysis by Christian Tominski and Heidrun Schumann

This one is a bit scholarly and technical, focused on visual analytics, which is a particular sub-branch of visualization. It goes thoroughly back and forth between human-in-the-loop analysis and computational methods. This was the first really good visual analytics textbook out there. For those who do want to go deep into the interplay between computational and visual concepts, it’s great. (Munzner)

20. The Elements of Graphing Data by William S. Cleveland

For scientists and engineers who want to make scientific plots or charts for research papers, Elements of Graphing Data is astounding. Cleveland comes out of the statistics tradition. There was a legendary Bell Labs cohort, with John Tukey, who invented the term “ exploratory data analysis .” Cleveland was his associate and very much an intellectual successor. This is where to go deep into, for instance, how exactly to make a statistical plot and all the issues you should think about. Recommended for people who come from very quantitative backgrounds. (Munzner)

21. Visualization Analysis and Design by Tamara Munzner

I wrote Visualization Analysis and Design to scratch my own itch: How do I show people that visualization is a systematic way of thinking, not just a grab bag of this technique and that technique? If you’re interested in diving deep and thinking systematically, it’s a good resource. It’s not just for people with a computer science background. 

Admittedly, it has its dense moments, but I avoid math and jargon. I try to build bridges and present a big picture, but in a way that might make sense for a class textbook. But people definitely read it outside of classrooms — people in neighboring fields who want to know what this visualization thing is all about. (Munzner)

One of my favorite chapters is “No Unjustified 3D.” Usually you’ll just hear, “Well, if you do 3D, then your marks get distorted and you can’t compare values as well.” But she goes further, explaining a number of different issues. And then she talks about cases where 3D actually works and provides examples. It’s a very reasoned consideration of all the decisions you have to make. The examples are more on the academic, scientific side, but it’s a very measured approach to thinking like a data-viz designer. (Torban)

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16 amazing book charts and visualizations.

Most amazing book visualizations

In times of picture-driven internet, where we are hunting for various kinds of infographics, animations, and chart, books prove they are a highly inspiring topic for visual design.

Many of these visualizations are possible thanks to the internet and digitization.

As soon as the book goes digital, its entire content can be analysed like never before. Creators can include much more data in the analysis, what leads to breath-taking visuals.

Let’s just take a tool every internet user can utilize: Google Ngram Viewer . You can track the appearance of selected words in books over time. A simple idea to make infographics like this one: Love DNA of classic novels .

Processing the information is important, but nothing will replace the talent of a designer to present the data in a clear and exciting way.

You’ll see below the greatest examples of data visualization applied to books, but not only that. Having unlimited access to images on the internet artists can create collages that represent the content of a single book or entire book genres. In the list below you’ll see such examples as well.

Please share in the comments the projects that should be highlighted. I’ll add them in the next update of the list.

[ef-reco id=”100684″ title=”Read also” info=”Top article”]

1. A guide to fiction genres

A guide to fiction genre

“A Plotting of Fiction Genres” chart is epic. It investigates the genres of most famous books and puts them together in a catching visual.

Whether you’re partial to Epic Fantasies (“The Lord of The Rings), Romance (“Bridget Jones’s Diary”), Cozy Mysteries (“The Convivial Codfish”), or Literature Qua Literature (“Moby Dick”), this celebration of creative writing’s delineations is sure to please readers of all brows—whether high-, low-, or in-between.

The book covers you’ll find in the design are fictional. The team from Pop Chart Lab designed them for the main fiction genres, like science-fiction, mystery, or horror.

From there you’ll be able to follow sub-genres – each one represented by the most famous title.

⇢ Credits and more info

2. Character interactions in Shakespeare’s tragedies

Book visualizations: Shakespeare tragedies as network graphs

A series of fascinating network graphs created by a Swiss data research analyst and designer Martin Grandjean explores the structure and character interactions of eleven classic tragedies by William Shakespeare.

Each chart presents all characters from a specific tragedy. Each character is represented as a circle. The more important the character the bigger the circle.

The lines connect characters to other characters with whom they interact in the same scene. Network density measures how close the graph is to complete.

The result speaks for itself: the longest tragedy ( Hamlet ) is not the most structurally complex and is less dense than King Lear , Titus Andronicus or Othello .

When you analyze the graphs, you’ll see that in some tragedies characters belong to clear groups. It’s obvious with Romeo and Juliet , where we have Montague and Capulet families.

3. YA reading calendar

2015 YA reading calendar from Epic Reads

This calendar with YA book recommendations is epic. It’s not only a useful tool that lets discover new books, but also an extremely detailed and well designed visual.

The 2015 YA reading calendar brakes down YA books into seasonal, monthly, weekly and daily recommendations. Separate charts for seasonal reads were also prepared by Epic Reads team.

This infographic marks the beginning of the new breed of discovery tools – the ones that put recommended titles into an advanced, visually catchy form that is much more enjoyable to explore than a mere collage of book covers.

It’s not the first creative design from Epic Reads, and I’m sure we can expect a lot more from this YA-focused book community.

4. Opening lines of famous novels

Openining lines of famous #novels

This is one of the most stunning designs from Pop Chart Lab . The chart brings the most exciting analysis of what many book lovers consider the most exciting part of the book: opening line.

Diagrammatical Dissertation on Opening Lines of Notable Novels breaks down grammatical construction of opening sentences of 25 famous novels.

Each sentence is diagrammed into a partitioned, color-coded pictogram, according to the dictates of the classic Reed-Kellogg system.

Whether you’re a book buff, an English teacher, or a hard-line grammarian, this diagrammatical dissertation has something for the aesthete in all of us.

5. Plot Lines

Plot lines - the recipe for writing a bestseller

This is one of the most beautiful examples of literary visualizations I’ve ever seen – and it actually gives a very useful advice for every aspiring author.

What’s the best recipe to make your novel a bestseller? Kill off your characters.

The infographic was developed by Joanna Kamradt and Christian Tate for the literary magazine “Delayed Gratification”. It analyses the plot of 13 novels that won the prestigious Man Booker Prize in 2011.

Every single title includes death – the black part of the chart is overwhelmingly large.

6. Narrative structure of books

Narrative structure of Kafka on the Shore

What you see above is just a teaser – a screenshot of an interactive visualization of narrative flow of  Kafka on the Shore by Haruki Murakami.

The visualization was developed by Natalia Bilenko and Asako Miyakawa, neuroscience PhD students at UC Berkeley. 

A dynamically changing graph studies connections between characters throughout the book. Emotional strength and valence of each sentence are shown in a color-coded sentiment plot.

When you hover over the sentence bars, you’ll see the text of the original sentences.

7. Color signatures

Colour Signatures - Alice Adventures in Wonderland

Artist and designer Jaz Parkinson created a wonderful art project called “Colour Signatures”.

Famous novels are presented in a form of posters/book covers, where colour spectrums are a reference to colours used in novels’ content.

Jaz explains more how the colours are found:

For example when it might say ‘yellow brick road,’ ‘yellow’ gets a tally, or when for example in The Road it says ‘dark ash covered everything’ (not an actual quote), that image evokes dark grey instantly in the mind, so dark grey gets a tally.

8. Romeo and Juliet poster

Romeo and Juliet poster

Created by Saloniki-based design studio Beetroot, the poster links with red ink all instances of words “Romeo” and “Juliet”.

The word “Romeo” appears 308 times in William Shakespeare’s most famous tragedy, “Juliet” – 180 times. That makes 55,440 connections.

Designers from Beetroot included all these connections in the poster, creating an attention-drawing visual, evoking feelings of love and blood.

9. Connections between characters in Infinite Jest

All characters in Infinite Jest

Infinite Jest is a lengthy and complex 1996 novel by David Foster Wallace, full of cultural references, and exploiting deep multilevel relations between characters.

Designer Sam Potts took an attempt to visualize  complex connections between characters from the book in a single chart.

The diagram doesn’t explain the story or show the advance of the plot. It’s just a sheer representation of how intense the narration in a single book can be, as seen through the plethora of connections between characters.

10. Top 10 bestsellers from 2000-2011

USA Today weekly bestsellers 2000-2011

This awesome image includes every book from USA Today Top 10 weekly bestseller lists from 2000-2011. More than 6,000 book covers are shown, from 1,300 individual books.

The visualization was created by James R.A. Davenport, astronomer and social data analyst. He wrote a special script that was grabbing book covers every week.

If the book cover stands for the mood of the book, this chart is a fantastic way to see how our reading preferences evolved over time.

You can see the “decay time” of books as they drift off the bestseller list. Color choices seem to have become more saturated since 2000, and Twilight (big black band) is the undisputed champ.

11. Thematic flow of a book

Thematic flow of a book

In an image above you’ see the visual representation of A Year and a Day , a romance based in medieval Scotland, written by the New York Times bestseller author Virginia Henley.

The visualization is the outcome of a very interesting initiative by BookLamp and the Book Genome Project. A special algorithm was developed to analyze the topic and writing style of a book.

Such visualizations become a new, and very valuable, addition to book’s blurb, ratings and reviews. They fantastically describe (“display” would be a better word) what you can expect from a book, and how the plot evolves.

12. Color distribution of YA covers

YA book covers 1

YA writer Kate Hart wrote a great post uncovering YA covers. The post is accompanied by a series of images (one of them you see above, but there are other interesting ones to explore).

Kate gathered more than 900 books released in 2011 in United States. Then she researched the color distribution and demographic of these books.

13. Penguin sci-fi book covers over time

Penguin sci-fi covers over time

Arthur Buxton put together the most common colors of Penguin Publishing sci-fi books and arranged them over time. It’s interesting to see how iconic Penguin book cover art was evolving over time.

Each timeline represents all the iterations of a cover in chronological order.

Within each bar chart, length corresponds to the time in print and the dive most prominent colors are shown proportionally.

14. Connected words of 1984

books magazines charts graphs diagrams

“Connected” is a work of art by Greg Orrom Swan. The Bristol-based artist and designer connected the letters in the first two paragraphs of George Orwell’s 1984 .

The image is a part of the larger art project called “Five Ways to Read 1984”.

15. Literary Organism

Literary Organism by Stefanie Posavec - a part of Writing Without Words project

Stefanie Posavec created an astonishing Writing Without Words project that analyzes writing styles of famous authors between authors.

The visual you see above is “Literary Organism”. It analyses in detail Jack Kerouac’s On the Road . It’s a simple organic structure that breaks down Part One of the book.

The chart  breaks into chapters, chapters into paragraphs, paragraphs into sentences, and sentences into words. Everything has its own color according to key themes in On the Road .

16. The Great Gatsby chapter by chapter

The Great Gatsby chart by Pop Chart Lab

Here is another visual from Pop Chart Lab. This time you can analyze, chapter by chapter, the plot in The Great Gatsby .

The graph traces the comings and goings of characters, but also movement by trains, cars, and feet – for Daisy, Nick, Tom, Gatsby, and every other character in the novel.

A map at the top of the chart also shows the 20s New York locations of scenes in the book.

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Once upon a time, there was a man named Jack Gilbert, who was not related to me – unfortunately for me. 

Jack Gilbert was a great poet, but if you’ve never heard of him, don’t worry about it. It’s not your fault. He never much cared about being known. But I knew about him, and I loved him dearly from a respectful distance, so let me tell you about him.

Jack Gilbert was born in Pittsburgh in 1925 and grew up in the midst of that city’s smoke, noise, and industry. He worked in factories and steel mills as a young man, but was called from an early age to write poetry. He answered the call without hesitation. He became a poet the way other men become monks: as a devotional practice, as an act of love, and as a lifelong commitment to the search for grace and transcendence. I think this is probably a very good way to become a poet. Or to become anything, really, that calls to your heart and brings you to life.

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The Power of Charts, Graphs, and Timelines: Can They Really Help Students Understand the Text?

The Power of Charts, Graphs, and Timelines Can They Really Help Students Understand the Text Pin - RI.4.7

Sometimes it seems like most information that adults encounter these days is condensed into a visual format. We just don’t have the attention span to read a whole article, and instead, look for a quick infographic showing the bullet points.  

On the other hand, charts and graphs and diagrams have been around for a long time, so maybe people have always wanted the quick version?

Either way, it’s crucial that students know how to interpret information presented to them in visual formats and see how these visuals enhance the text.

In today’s post, I’ll share the process that I use to get students thinking about the different ways information can be presented visually and how these visuals can deepen our understanding of a text. 

Depending on what else we are doing and at what point in the year we start, this could be spread out over several days, a whole week, or even longer.

This works with any informational text, but it’s an especially great way to get students familiar with the Science or History texts they will be using all year long!

Getting Started:

To get students ready to discuss and analyze visual text features, I want to get their brains thinking!  The best way I’ve found to do this is to ask them to name some of the different ways that they have seen information presented visually. These could be from a magazine, a website in a book, or even something from a TV show. Create a class chart and keep track of all of their ideas. 

Find and Analyze:

After students have created a good-sized list, it’s time for them to find examples! You can ask students to self-select a nonfiction book or have them look in a specific textbook if they want to go that route.

Whichever type of text you choose, have students look for specific examples of visuals that provide information. Graphs, timelines, diagrams, charts…it’s all fair game. You might want to hand out a few sticky notes so they can mark the pages (kids LOVE a good reason to use sticky notes)!

After students have had a chance to find some real-life examples, look at exploring and discussing them as a class. It might be helpful to have a few selected ahead of time to highlight the specific points that you want to discuss.

Have students analyze the visuals: 

  • Which visuals are MOST useful, and why?
  • Is the information presented in an organized way?
  • Is the text readable? Is it interesting to look at, does it draw the reader in?

This will help students start to identify what makes a visual element effective.  

books magazines charts graphs diagrams

Compare and Contrast: 

Another fun thing to do here is to compare two different texts, one that has quite a few charts, graphs, timelines, or other visual aids and one that doesn’t have any. This would be a great way to spark a discussion about what exactly these features add to a text. Which text communicates information more clearly? Which text is more interesting to read? 

If you have time, a great idea to go along with this strategy would be to have students create their own visual representation of information. This could be a timeline, infographic, chart…anything that visually shows information.

You could ask all the students to create the same type of visual (a timeline of their life, for example), or give them a few options and let them choose. They can get really creative!

If you are looking for a resource to help you get started with this, check out this freebie ! Students are asked to do a survey about favorite ice cream flavors and then graph the results. It’s labeled end of the year, but really you could use it anytime!

End of the Year Free Graphing Activity

Are you in need of some informational text practice that won’t take ages to prep? I can help you with that! This Informational Text Using Charts Digital Reading Google Slides 4th Grade Nonfiction resource includes high-interest reading passages and colorful graphics (timelines, diagrams, charts, graphs). Students are asked to answer a variety of questions using the text and the visuals. This paperless resource can be used in PowerPoint or Google Slides and doesn’t require any teacher prep!

Informational Text Using Charts Digital Reading Google Slides™ 4th Grade Nonfiction

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Standards Alignmen t RI.4.7 – Interpret information presented visually, orally, or quantitatively (e.g., in charts, graphs, diagrams, timelines, animations, or interactive elements on Web pages) and explain how the information contributes to an understanding of the text in which it appears.

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What's the difference between diagrams, charts and graphs?

Have you been asked to create a chart, a diagram, or a graph? There is a lot of confusion around these overlapping terms, especially as they are most often used interchangeably. However, there are some minor differences in how they are used.

Here’s a rough guide to the difference between charts, graphs, diagrams, figures, plots, maps, and models.

You could think of diagrams as the super-category: Anything that visualises information in an abstract way is a diagram. For example, an image with labels, a tree diagram categorising items, a floor plan, an infographic, an electrical wiring diagram, a process flow, and so on.

A good rule of thumb for using more specific terms - when the visualisation is driven by a numerical data set, chart, graph or plot will be more accurate.

Graphs usually represent quantitative data on an 2D image with an x-y axis, using lines or bars. Graphs can visualise numerical data or a mathematical function, and are often generated from data in a spreadsheet.

Dependency graph of the draw.io website on GitHub

Plots are not as often encountered. They are generated from a numerical data set and commonly used in mathematics, finance, and engineering. Individual data points are plotted on a 2D or 3D axis, for example, as a scatterplot.

Charts also represent quantitative data. Charts can be graphs (line charts), but some aren’t (pie charts). Many charts put quantitative data on one axis, and categories (qualitative data) on the other axis.

An example BPMN diagram that details the steps involved in processing an order

Figure has so many different meanings that depend on the context in which it is used. The most common usage refers to any image, drawing, graph, diagram, chart or plot in a reference book, scientific paper, or digital resource.

The word ‘figure’ can also be used to mean ‘number’ - e.g. a figure 8, or a table of sales figures.

Maps and models and plans

To complicate matters even more, maps, models and plans are also words used to refer to specific types of diagrams.

  • Story mapping and roadmaps are used in product marketing, and mindmaps are used to explore subject areas when brainstorming.
  • C4 models describe and define IT architectures, application threat models are used to explore infrastructure risks, and wireframe models can represent physical objects or the layout of a digital product.

Example data flow diagram for threat modelling

Templates for all types of diagrams

Hover over a template in draw.io to see a larger preview of it

  • Select Arrange > Insert > Template to open the template manager.
  • Browse the categories on the left and select a template on the right. Click on the magnifying glass to see a larger preview.
  • Click Insert to add it to the drawing canvas.

Shapes for different types of diagrams

Enable the Infographic shape library to create abstract graphs and charts

  • Click on More Shapes at the bottom of the Shapes panel.
  • Enable the checkboxes next to the shape libraries you want to use, and click Apply .

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Infographic Examples. What is an infographic? Examples and templates

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By kai tomboc - august 19, 2020.

What is an infographic? We admit that there’s a lot written out there about this topic , it isn’t hard to find infographic examples out there .

However, we’d like to share our thoughts and tips on infographic creation from the perspective of a team behind an infographic maker tool and as a provider of infographic design services since 2015. Now, let’s get to it!

If you’re an educator or student, you’re probably wondering how infographics fit into the picture for your school curriculum or lesson plans.

Meanwhile, if you’re running a business or heading a marketing team, you’re curious about using infographics to share your brand story.

Are infographics expensive and time-consuming to create? Is it even worth pursuing?

What kind of infographic format is ideal for the data that you want to highlight?

In this guide, you’ll find answers to these questions (and more!) as we dive deeper into infographic creation — from its history to design best practices to downloadable infographic templates that you can use right away.

What is an infographic?

Infographic is a combination of the words “information” and “graphics”.

Merriam-Webster defines infographics as “a chart, diagram, or illustration (as in a book or magazine, or on a website) that uses graphic elements to present information in a visually striking way”.

On the other hand, Oxford Learners’ Dictionary describes infographics as information or data that is shown in a chart, diagram, etc. so that it is easy to understand.

So what do we learn from these definitions?

Authors Ekaterina Walter and Jessica Gioglio said it best in their book The Power of Visual Storytelling — infographics, in a nutshell, bring together the best of data and visuals to craft a story .

Here’s an excellent example of an infographic that combined both data and visuals to make the content more striking, shareable, and easy to understand.

example of an infographic that combined visuals and text

The beauty of infographics is that they’re versatile.

You can share infographics on Instagram , embed them on your website, or print them out as a brochure or poster.

Do you need quantitative data to make infographics?

Not necessarily.

You can make an infographic based on qualitative information like when you want to explain a process, define an idea, or highlight differences and similarities between two or more concepts. The possibilities with infographics are endless!

You will learn more about the different ways to use infographics later in this guide.

Why use infographics

Whether it’s for your social studies class or your rebranding efforts , adding visuals to texts (like infographics) has been shown to improve learning and memory recall.

Case in point — an experiment by the Department of Computer Science at the University of Saskatchewan showed that participants prefer embellished charts over plain (minimalist) charts in terms of aesthetics. Also, there was zero difference in the participants’ accuracy in interpreting both charts’ data.

And for the most significant finding?

Here’s an excerpt from the experiment’s conclusion:

We found that people’s accuracy in describing the embellished charts was no worse than for simple charts and that their recall after a two-to-three week gap was significantly better for the embellished charts.

Watch the 3-minute video below to discover why you should use infographics for persuasive business communication , better learning, and stronger memory recall.

Sure, we might be slightly biased, but we made sure to stick with the facts, latest findings, and most reliable insights that we can find.

History of infographics

If you’ve wondered what the first infographic looked like, historians believe that cave images, rock art, and maps are the early versions of infographics. 

Watch the video below to learn about the evolution of infographics.

The spray-shaped images discovered at the Chauvet-Pont d’Arc Cave in France at around 37,000 BC were thought to depict the nearby volcanoes that erupted and expelled lava into the sky. 

cave engravings

Rock art specialists are proposing that the rock art of Serra Da Capivara in Brazil, dating as far back as 36,000 years ago, are the origins of infographics. 

And then there were maps. 

Discovered in the Czech Republic, the earliest-known map was created around 25000 BC. 

Aside from visualizing the land around them, the ancients also mapped the skies.

One of the oldest graphics, the Dunhuang star atlas, dates back to 649 and 684 AD. This ancient Chinese atlas has more than a thousand stars depicted. 

Dunhuang Star Atlas

It wasn’t until the 18th century that scientists and scholars started to visualize knowledge and information. 

In 1764, British polymath Joseph Priestley produced a “Chart of Biography”, illustrating the lives of roughly 2,000 historical figures on a timeline. 

Two decades later, William Playfair plotted the price of wheat against labor costs in the UK. His chart revealed that wages were rising much more slowly than the cost of wheat. 

The Visual Display of Quantitative Information by Edward Tufte

Playfair, considered the father of modern-day infographics, also published The Commercial and Political Atlas and Statistical Breviary , where he introduced line graphs, bar charts, and pie charts to statistics.

The 1830s saw the birth of data-based social science. 

In France, lawyer André-Michel Guerry illustrated maps showing moral statistics with Venetian geographer, Adriano Balbi. Guerry’s work was controversial because it challenged conventional wisdom at the time. French social critics believed that illiteracy led to crime, but the lawyer’s maps suggested otherwise.

By 1857, English nurse Florence Nightingale used the coxcomb chart to convince Queen Victoria to improve military hospital conditions. Her graphic showed the number and causes of deaths during each month of the Crimean War. 

coxcomb chart by Florence Nightingale

Two years later, French engineer Charles Joseph Minard created a map of Napoleon Bonaparte’s 1812 Russian campaign. 

In 1933, Harry Beck made the first map of the London Tube. It was a milestone in infographic history since it proved that visual diagrams could be used for everyday life.

In 1972, Otl Aicher created a set of pictograms for the Munich Olympics. Aicher’s pictograms inspire today’s public signs and generic stick figures. 

pictograms for the Munich Olympics by Otl Aicher

By 1975, Edward Tufte, considered the father of data visualization, developed a statistical graphics seminar alongside John Tukey. 

As a pioneer in information design , Tufte developed the concept of data-ink ratio. For Tufte, the best graphics present their message and information as simply as possible.

example of a visualization with low data-ink ration

In 1983, Tufte later self-published The Visual Display of Quantitative Information.

Tufte argues that any visual elements that do not communicate specific information should be omitted. He called it chart-junk. 

Meanwhile, British graphic designer Nigel Holmes’ work was gaining popularity in 1979.

infographic by Nigel Holmes

Holmes’ visualizations were the complete opposite of Tufte’s desire for simplicity. He supported the heavy use of graphical decoration to embellish information. 

From the 1990s onwards, the terms infographic and information graphics are used interchangeably.  According to the authors of The Power of Visual Storytelling , there is no threshold at which something “becomes” an infographic. Infographics can range from simple road signs to complex charts about the global economy. 

Types of infographics: Choosing the right format for your message

Before you start making infographics, it’s essential to understand which infographic type will most effectively communicate your idea, information, or data.

The video below highlights the different types of infographics and when to use them.

It’s worth noting that one infographic can have the components of another infographic type. For example, a list infographic can also have elements of a statistical infographic.

Let’s take a closer look at each infographic format below.

Visual infographic

An informational or visual infographic makes a piece of writing more interesting and engaging for the audience. As a result, your readers are more likely to share the infographic on social media and similar platforms.

A list of a veterinary hospital’s services is transformed into an eye-catching infographic in the example below.

an informational infographic template for veterinary clinics

Meanwhile, the infographic template below lets you know if you’re a free thinker, optimist, or an adrenaline junkie based on your film viewing habits.

what type of moviegoer are you infographic

List infographic

A list infographic highlights a series of steps. You can add images, numbers, or icons to illustrate each step or point in your list.

The Internet loves lists (next to cats, of course!), so this infographic format is likely to get shared as they’re usually engaging and fun to read.

uses of coconut tree infographic

Map infographic

A map infographic presents data or information based on location.

This format is perfect for highlighting geographic trends or information like the travel Australia infographic template below.

australia travel guide infographic

Comparison infographic

A comparison infographic compares two or more ideas or objects. Also known as versus infographic, this format highlights differences or similarities.

You can also use a comparison infographic to show how one option is superior or inferior to the other.

an infographic template comparing two players

Flowchart infographics

If you want to explain an answer to a question or   showcase how multiple scenarios will pan out, consider flowchart infographics.

The infographic template below describes the steps it would take to make french-pressed coffee. 

a flowchart infographic template explaining how to make french-pressed coffee

Data visualization or statistical infographics

Data visualization or statistical infographics are used to simplify complex data. Graphs, charts, and pictograms are often used for this infographic format.

Take a look at the templates below and use them to make your data and figures stand out!

annual report infographic

Timeline infographics

Timelines in your infographic are suitable if you want to show how one thing leads to another or highlight how something has changed over time.

You can also use this infographic format to take the reader on a journey, whether it’s your company’s history or your dog’s daily routine as illustrated in the templates below.

an infographic template to share your company history

Infographic resumes

Make yourself hireable with infographic resumes .

An infographic resume transforms text-based CVs into a stunning visual story of your skill sets, educational background, and unique personality.

This infographic type is best used to help you stand out from the rest and get noticed during the recruitment process. This is particularly true in non-traditional industries or positions that are looking for creative and out of the box thinking!

Plus, using infographic resumes on your next job hunt will likely get more employers engaged and intrigued by the value that you have to offer.

infographic resume template with black and blue colors

Watch the short tutorial below for a quick lesson on making infographic resumes using Easelly.

Process infographics

Would you like to share your super moist banana bread recipe with your coworkers? Or are you looking for visuals to help explain the science behind GMOs to your class?

A process infographic is the right infographic format you’re looking for. Use this infographic type to simplify a complex process by breaking down each step with stunning visuals.

recruitment process infographic template

Animated infographics

If you’re looking for something more engaging than a standard infographic, try animated infographics!

Animated infographics add motion to plain infographics so you can capture and hold your readers’ attention when you want it.

Motion and movement also make your infographic come to life. Another added benefit of animated infographics is they’re less expensive to produce than videos.

With Easelly, you can have one of our designers make your animated infographic, or you can add animated objects to your infographic using our Animations feature .

Now that you’re aware of the different infographic types, your next step is to understand the infographic creation process.

How to create an infographic for non-designers

Infographic creation can sometimes be a challenge, particularly if you don’t have a design background.

Fortunately, you’re about to learn how to get started with infographic creation even if you’re new to the craft.

In this section, you’ll learn about:

  • The importance of an infographic brief and how to make one
  • The basic infographic structure
  • How to collect reliable information for your infographic
  • How to pick the right color scheme for your infographics
  • How to write compelling infographic content
  • Why you need a call-to-action in your infographics
  • White space in infographic design
  • The standard infographic sizes for online and offline use

What makes an effective infographic

  • How to improve an infographic in 5 easy steps

How to write an infographic brief

An infographic brief sets the vision, clarifies objectives, and determines your infographic project’s direction. What if you don’t need an infographic after all?

Your infographic brief should include the following:

  • Your objective
  • Your target audience
  • Your big idea
  • Your infographic content
  • Your visual specs

Whether you’re using infographics for lead generation or as visuals for your eLearning class, learn how to make an infographic design brief in the short video below. It’s easier than you think!

What does an infographic include

The best infographics have a structure — a catchy introduction, a meaty middle, and a satisfying end (just like a good story).

Download the infographic on the basic infographic structure below or print it out as a quick reminder before starting your infographic adventures.

infographic about infographic structure

How to nail your infographic research with trustworthy information

Informational honesty is a must to make relevant and useful infographics .

When presenting data, statistics, or information in your infographics, consider the following steps:

  • Check for relevance
  • Check the intent
  • Check for opinion versus fact
  • Check the source links
  • Check for accuracy
  • Go old school by visiting the the library to find vetted, reliable information

The infographic below explains each step in detail.

books magazines charts graphs diagrams

How to choose the right infographic colors

Your infographic color of choice captures your audience’s attention for the first few seconds. It can also impact your infographic’s readability.

Here are seven best practices when choosing the right color combination for your next infographic. The video below also discusses each tip in detail.

  • Match the infographic’s color to the overall mood that you want to convey in the infographic.
  • Get to know the basics of color theory and psychology.
  • Draw inspiration from interior design’s 60-30-10 rule.
  • Use your brand colors.
  • Stick to 2-3 colors.
  • Be mindful of color contrast.
  • Take white space into account.

How to write compelling content for your infographics

Writing infographic content is like packing light.

You don’t have to take every favorite piece of clothing with you. You discover how to nail the right balance between function and aesthetics.

The same principle applies when making infographic content.

You can’t put a whole essay in your infographic, yet you have to make sure that you’re not missing essential information.

The 3-minute video below highlights how you can ensure that every word in your infographic is keeping your reader engaged rather than distracting them from your core message.

Why your infographic needs a call-to-action

When you’re done with your infographic content, your next step is to make your infographic work for you with the right call-to-action statements.

The video below summarizes the different ways to add a call-to-action in your infographics.

White space matters in infographics too

Apart from infographic colors, white space also matters in creating infographics.

White space, also known as negative space, is the space between texts, images, icons, illustrations, and other infographic elements.

Learn more about white space in the short video below.

Get your infographic size right

As you put the finishing touches of your infographic, don’t forget to get your infographic sizes correctly to ensure readability and improve reader engagement.

The standard infographic size varies depending on the platform you’re planning to use in promoting your infographic. Perhaps you’re planning to make an infographic poster and would like to print it out.

Bookmark or download the infographic below to help you pick the right infographic size.

infographic size guide

Before you share and promote your infographics, ask yourself if the infographic brings value to your audience?

Nielsen Norman Group user experience specialist Lexie Kane wrote an  insightful piece  on designing effective infographics.

The video below summarizes her tips and suggested best practices to ensure effective data representations in your infographic. 

How to improve your infographic in 5 easy steps

If you’re secretly hoping that your new infographic will bring tons of new visitors to your website or social media page,  hoping isn’t enough!

You have to execute tactics and strategies to make your infographic stand out. 

Watch the short video below for ways to improve your infographic quickly!

Make your infographic stand out with this complete infographic checklist

As you create your infographic, check off each of the following points along the way in the checklist below. You can also use this PDF version  here . 

the complete infographic checklist

You’re all set

Now that you know how to make infographics, you’re all set in making infographics for your classroom or business! If you’re part of a philantrophic organization, consider making one as successful nonprofits also use infographics !

At Easelly, there’s more than one way to skin a cat with infographics.

One option is to choose a template from our infographic template collection and edit it with your information. Or you can ask one of our infographic design pros to make one for you.

Are you looking for an in-depth guide with more video tutorials about infographic creation?

Head on over to our step-by-step guide in creating infographics from scratch or subscribe to our infographic design channel on YouTube .

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What are Text Features?

Kathryn starke.

  • August 24, 2020

Young boy reading a book at his desk in a classroom with other students.

The term text features is used in an academic setting to describe all of the components or features associated with an article or nonfiction text that are not considered the main text. The most common text features of a book include the table of contents, the index, headings, captions, bold words, illustrations, photographs, the glossary, labels, graphs, charts, and diagrams. Many of these text features can also be found in newspapers, magazines, or individual articles.

Text features are used to help navigate and locate specific information provided in a nonfiction text in an easier and more efficient manner. Often times, authors put information in the text features that are not included in the body of the text, so it is imperative to understand how to use them effectively.

What is the Purpose of Text Features?

Each text feature has a specific purpose in nonfiction material, while the overarching goal of every text feature is to quickly and easily gain access to information. Text features make reading informational text and research materials more efficient. The table of contents and index allow the reader to quickly locate which pages of the book contain specific information; the knowledge can be acquired without having to read the entire book.

Many times, information is depicted or documented in photographs or illustrations throughout the book accompanied by captions below each one. The bolded words in text are usually new vocabulary words that are often defined in the glossary or mini dictionary located in the back of the book.

Lastly, visuals or data that match the information are often placed in graphs, charts, or diagrams. These three text features are very important because more often than not, the data is not actually written in the body of text. Each text feature used in a nonfiction source provides as much value as the actual text. The combination of text and text features presents informational material in an organized and structured format that readers can obtain with ease.

Strategies for Introducing Students to Text Features

Students should have the opportunity to learn about and use text features in every nonfiction material beginning in kindergarten. One simple introductory activity that even five-year-old students can complete is the idea of going on a scavenger hunt in the book for text features. Younger readers can look for bold words and photographs while upper grade readers can complete a checklist for every text feature located in the material. When we provide students with a variety of nonfiction sources, they can compare and contrast how text features are used to give information.

Another strategy to take this scavenger concept to the next level is to have students create an anchor chart of text features. Students can work in pairs or groups using magazines and newspapers to cut out each specific text feature. Then, they should organize them on chart paper or poster board, glue them down, and label each one. Thus, they are using a text feature to complete the assignment. Keep these child-friendly anchor charts on display for students to memorize each one.

In addition to recognizing and understanding the purpose of text features, students need to understand how to apply their knowledge of how to utilize the text features. Therefore, students should be provided with a book or article related to a science or social studies objective they already have background information about. Then, they can apply specific text feature tasks including using the glossary to find out the meaning of an unknown bold-faced word.

Students can also make a prediction of what information they think they will learn based on the titles of the chapters in the table of contents or the headings throughout the text. A higher-level thinking activity is to give students paragraphs and have them create the heading to match the content. Students can also create captions for photographs or illustrations. Each student can be assigned a particular section, chart, or diagram of a text and given the task of being an expert for the information from that visual or text. They are responsible for conveying the information to their classmates.

When students are encouraged to actually use text features in reading nonfiction materials, in content areas, and in research projects , they see first-hand the benefit of how text features make understanding information so much easier. This is when they will automatically seek out text features in nonfiction materials to make the reading comprehension process that much simpler.

  • #TextFeatures

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The Writing Center • University of North Carolina at Chapel Hill

Figures and Charts

What this handout is about.

This handout will describe how to use figures and tables to present complicated information in a way that is accessible and understandable to your reader.

Do I need a figure/table?

When planning your writing, it is important to consider the best way to communicate information to your audience, especially if you plan to use data in the form of numbers, words, or images that will help you construct and support your argument.  Generally speaking, data summaries may take the form of text, tables or figures. Most writers are familiar with textual data summaries and this is often the best way to communicate simple results. A good rule of thumb is to see if you can present your results clearly in a sentence or two. If so, a table or figure is probably unnecessary. If your data are too numerous or complicated to be described adequately in this amount of space, figures and tables can be effective ways of conveying lots of information without cluttering up your text. Additionally, they serve as quick references for your reader and can reveal trends, patterns, or relationships that might otherwise be difficult to grasp.

So what’s the difference between a table and a figure anyway?

Tables present lists of numbers or text in columns and can be used to synthesize existing literature, to explain variables, or to present the wording of survey questions. They are also used to make a paper or article more readable by removing numeric or listed data from the text. Tables are typically used to present raw data, not when you want to show a relationship between variables.

Figures are visual presentations of results. They come in the form of graphs, charts, drawings, photos, or maps.  Figures provide visual impact and can effectively communicate your primary finding. Traditionally, they are used to display trends and patterns of relationship, but they can also be used to communicate processes or display complicated data simply.  Figures should not duplicate the same information found in tables and vice versa.

Using tables

Tables are easily constructed using your word processor’s table function or a spread sheet program such as Excel. Elements of a table include the Legend or Title, Column Titles, and the Table Body (quantitative or qualitative data). They may also include subheadings and footnotes. Remember that it is just as important to think about the organization of tables as it is to think about the organization of paragraphs. A well-organized table allows readers to grasp the meaning of the data presented with ease, while a disorganized one will leave the reader confused about the data itself, or the significance of the data.

Title: Tables are headed by a number followed by a clear, descriptive title or caption. Conventions regarding title length and content vary by discipline. In the hard sciences, a lengthy explanation of table contents may be acceptable. In other disciplines, titles should be descriptive but short, and any explanation or interpretation of data should take place in the text. Be sure to look up examples from published papers within your discipline that you can use as a model. It may also help to think of the title as the “topic sentence” of the table—it tells the reader what the table is about and how it’s organized. Tables are read from the top down, so titles go above the body of the table and are left-justified.

Column titles: The goal of column headings is to simplify and clarify the table, allowing the reader to understand the components of the table quickly. Therefore, column titles should be brief and descriptive and should include units of analysis.

Table body: This is where your data are located, whether they are numerical or textual. Again, organize your table in a way that helps the reader understand the significance of the data. Be sure to think about what you want your readers to compare, and put that information in the column (up and down) rather than in the row (across). In other words, construct your table so that like elements read down, not across. When using numerical data with decimals, make sure that the decimal points line up. Whole numbers should line up on the right.

Other table elements

Tables should be labeled with a number preceding the table title; tables and figures are labeled independently of one another. Tables should also have lines demarcating different parts of the table (title, column headers, data, and footnotes if present). Gridlines or boxes should not be included in printed versions. Tables may or may not include other elements, such as subheadings or footnotes.

Quick reference for tables

Tables should be:

  • Centered on the page.
  • Numbered in the order they appear in the text.
  • Referenced in the order they appear in the text.
  • Labeled with the table number and descriptive title above the table.
  • Labeled with column and/or row labels that describe the data, including units of measurement.
  • Set apart from the text itself; text does not flow around the table.

Table 1. Physical characteristics of the Doctor in the new series of Doctor Who

Table 2. Physical characteristics of the Doctor in the new series of Doctor Who

Using figures

Figures can take many forms. They may be graphs, diagrams, photos, drawings, or maps. Think deliberately about your purpose and use common sense to choose the most effective figure for communicating the main point. If you want your reader to understand spatial relationships, a map or photograph may be the best choice. If you want to illustrate proportions, experiment with a pie chart or bar graph. If you want to illustrate the relationship between two variables, try a line graph or a scatterplot (more on various types of graphs below). Although there are many types of figures, like tables, they share some typical features: captions, the image itself, and any necessary contextual information (which will vary depending on the type of figure you use).

Figure captions

Figures should be labeled with a number followed by a descriptive caption or title. Captions should be concise but comprehensive. They should describe the data shown, draw attention to important features contained within the figure, and may sometimes also include interpretations of the data. Figures are typically read from the bottom up, so captions go below the figure and are left-justified.

The most important consideration for figures is simplicity. Choose images the viewer can grasp and interpret clearly and quickly. Consider size, resolution, color, and prominence of important features. Figures should be large enough and of sufficient resolution for the viewer to make out details without straining their eyes. Also consider the format your paper will ultimately take. Journals typically publish figures in black and white, so any information coded by color will be lost to the reader.  On the other hand, color might be a good choice for papers published to the web or for PowerPoint presentations. In any case, use figure elements like color, line, and pattern for effect, not for flash.

Additional information

Figures should be labeled with a number preceding the table title; tables and figures are numbered independently of one another. Also be sure to include any additional contextual information your viewer needs to understand the figure. For graphs, this may include labels, a legend explaining symbols, and vertical or horizontal tick marks. For maps, you’ll need to include a scale and north arrow. If you’re unsure about contextual information, check out several types of figures that are commonly used in your discipline.

Quick reference for figures

Figures should be:

  • Labeled (under the figure) with the figure number and appropriate descriptive title (“Figure” can be spelled out [“Figure 1.”] or abbreviated [“Fig. 1.”] as long as you are consistent).
  • Referenced in the order they appear in the text (i.e. Figure 1 is referenced in the text before Figure 2 and so forth).
  • Set apart from the text; text should not flow around figures.

Every graph is a figure but not every figure is a graph. Graphs are a particular set of figures that display quantitative relationships between variables. Some of the most common graphs include bar charts, frequency histograms, pie charts, scatter plots, and line graphs, each of which displays trends or relationships within and among datasets in a different way. You’ll need to carefully choose the best graph for your data and the relationship that you want to show. More details about some common graph types are provided below. Some good advice regarding the construction of graphs is to keep it simple. Remember that the main objective of your graph is communication. If your viewer is unable to visually decode your graph, then you have failed to communicate the information contained within it.

Pie charts are used to show relative proportions, specifically the relationship of a number of parts to the whole. Use pie charts only when the parts of the pie are mutually exclusive categories and the sum of parts adds up to a meaningful whole (100% of something). Pie charts are good at showing “big picture” relationships (i.e. some categories make up “a lot” or “a little” of the whole thing). However, if you want your reader to discern fine distinctions within your data, the pie chart is not for you. Humans are not very good at making comparisons based on angles. We are much better at comparing length, so try a bar chart as an alternative way to show relative proportions. Additionally, pie charts with lots of little slices or slices of very different sizes are difficult to read, so limit yours to 5-7 categories.

first bad pie chart

The chart shows the relative proportion of fifteen elements in Martian soil, listed in order from “most” to “least”: oxygen, silicon, iron, magnesium, calcium, sulfur, aluminum, sodium, potassium, chlorine, helium, nitrogen, phosphorus, beryllium, and other. Oxygen makes up about ⅓ of the composition, while silicon and iron together make up about ¼. The remaining slices make up smaller proportions, but the percentages aren’t listed in the key and are difficult to estimate. It is also hard to distinguish fifteen colors when comparing the pie chart to the color coded key.

second bad pie chart

The chart shows the relative proportion of five leisure activities of Venusian teenagers (tanning, trips to Mars, reading, messing with satellites, and stealing Earth cable). Although each of the five slices are about the same size (roughly 20% of the total), the percentage of Venusian teenagers engaging in each activity varies widely (tanning: 80%, trips to Mars: 40%, reading: 12%, messing with satellites: 30%, stealing Earth cable: 77%). Therefore, there is a mismatch between the labels and the actual proportion represented by each activity (in other words, if reading represents 12% of the total, its slice should take up 12% of the pie chart area), which makes the representation inaccurate. In addition, the labels for the five slices add up to 239% (rather than 100%), which makes it impossible to accurately represent this dataset using a pie chart.

Bar graphs are also used to display proportions. In particular, they are useful for showing the relationship between independent and dependent variables, where the independent variables are discrete (often nominal) categories. Some examples are occupation, gender, and species. Bar graphs can be vertical or horizontal. In a vertical bar graph the independent variable is shown on the x axis (left to right) and the dependent variable on the y axis (up and down). In a horizontal one, the dependent variable will be shown on the horizontal (x) axis, the independent on the vertical (y) axis. The scale and origin of the graph should be meaningful. If the dependent (numeric) variable has a natural zero point, it is commonly used as a point of origin for the bar chart. However, zero is not always the best choice. You should experiment with both origin and scale to best show the relevant trends in your data without misleading the viewer in terms of the strength or extent of those trends.

bar graph

The graph shows the number of male and female spaceship crew members for five different popular television series: Star Trek (1965), Battlestar (1978), Star Trek: TNG (1987), Stargate SG-1 (1997), and Firefly (2002). Because the television series are arranged chronologically on the x-axis, the graph can also be used to look for trends in these numbers over time.

Although the number of crew members for each show is similar (ranging from 9 to 11), the proportion of female and male crew members varies. Star Trek has half as many female crew members as male crew members (3 and 6, respectively), Battlestar has fewer than one-fourth as many female crew members as male crew members (2 and 9, respectively), Star Trek: TNG has four female crew members and six male crew members, Stargate SG-1 has less than one-half as many female crew members as male crew members (3 and 7, respectively), and Firefly has four female and five male crew members.

Frequency histograms/distributions

Frequency histograms are a special type of bar graph that show the relationship between independent and dependent variables, where the independent variable is continuous, rather than discrete. This means that each bar represents a range of values, rather than a single observation. The dependent variables in a histogram are always numeric, but may be absolute (counts) or relative (percentages). Frequency histograms are good for describing populations—examples include the distribution of exam scores for students in a class or the age distribution of the people living in Chapel Hill. You can experiment with bar ranges (also known as “bins”) to achieve the best level of detail, but each range or bin should be of uniform width and clearly labeled.

XY scatter plots

Scatter plots are another way to illustrate the relationship between two variables. In this case, data are displayed as points in an x,y coordinate system, where each point represents one observation along two axes of variation. Often, scatter plots are used to illustrate correlation between two variables—as one variable increases, the other increases (positive correlation) or decreases (negative correlation). However, correlation does not necessarily imply that changes in one variable cause changes in the other. For instance, a third, unplotted variable may be causing both. In other words, scatter plots can be used to graph one independent and one dependent variable, or they can be used to plot two independent variables. In cases where one variable is dependent on another (for example, height depends partly on age), plot the independent variable on the horizontal (x) axis, and the dependent variable on the vertical (y) axis. In addition to correlation (a linear relationship), scatter plots can be used to plot non-linear relationships between variables.

scatter plot

The scatter plot shows the relationship between temperature (x-axis, independent variable) and the number of UFO sightings (y-axis, dependent variable) for 53 separate data points. The temperature ranges from about 0°F and 120°F, and the number of UFO sightings ranges from 1 to 10. The plot shows a low number of UFO sightings (ranging from 1 to 4) at temperatures below 80°F and a much wider range of the number of sightings (from 1 to 10) at temperatures above 80°F. It appears that the number of sightings tends to increase as temperature increases, though there are many cases where only a few sightings occur at high temperatures.

XY line graphs

Line graphs are similar to scatter plots in that they display data along two axes of variation. Line graphs, however, plot a series of related values that depict a change in one variable as a function of another, for example, world population (dependent) over time (independent). Individual data points are joined by a line, drawing the viewer’s attention to local change between adjacent points, as well as to larger trends in the data. Line graphs are similar to bar graphs, but are better at showing the rate of change between two points. Line graphs can also be used to compare multiple dependent variables by plotting multiple lines on the same graph.

Example of an XY line graph:

XY line graph

The line graph shows the age (in years) of the actor of each Doctor Who regeneration for the first through the eleventh regeneration. The ages range from a maximum of about 55 in the first regeneration to a minimum of about 25 in the eleventh regeneration. There is a downward trend in the age of the actors over the course of the eleven regenerations.

General tips for graphs

Strive for simplicity. Your data will be complex. Don’t be tempted to convey the complexity of your data in graphical form. Your job (and the job of your graph) is to communicate the most important thing about the data. Think of graphs like you think of paragraphs—if you have several important things to say about your data, make several graphs, each of which highlights one important point you want to make.

Strive for clarity. Make sure that your data are portrayed in a way that is visually clear. Make sure that you have explained the elements of the graph clearly. Consider your audience. Will your reader be familiar with the type of figure you are using (such as a boxplot)? If not, or if you’re not sure, you may need to explain boxplot conventions in the text. Avoid “chartjunk.” Superfluous elements just make graphs visually confusing. Your reader does not want to spend 15 minutes figuring out the point of your graph.

Strive for accuracy. Carefully check your graph for errors. Even a simple graphical error can change the meaning and interpretation of the data. Use graphs responsibly. Don’t manipulate the data so that it looks like it’s saying something it’s not—savvy viewers will see through this ruse, and you will come off as incompetent at best and dishonest at worst.

How should tables and figures interact with text?

Placement of figures and tables within the text is discipline-specific. In manuscripts (such as lab reports and drafts) it is conventional to put tables and figures on separate pages from the text, as near as possible to the place where you first refer to it. You can also put all the figures and tables at the end of the paper to avoid breaking up the text. Figures and tables may also be embedded in the text, as long as the text itself isn’t broken up into small chunks. Complex raw data is conventionally presented in an appendix. Be sure to check on conventions for the placement of figures and tables in your discipline.

You can use text to guide the reader in interpreting the information included in a figure, table, or graph—tell the reader what the figure or table conveys and why it was important to include it.

When referring to tables and graphs from within the text, you can use:

  • Clauses beginning with “as”: “As shown in Table 1, …”
  • Passive voice: “Results are shown in Table 1.”
  • Active voice (if appropriate for your discipline): “Table 1 shows that …”
  • Parentheses: “Each sample tested positive for three nutrients (Table 1).”

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

American Psychological Association. 2010. Publication Manual of the American Psychological Association . 6th ed. Washington, DC: American Psychological Association.

Bates College. 2012. “ Almost everything you wanted to know about making tables and figures.” How to Write a Paper in Scientific Journal Style and Format , January 11, 2012. http://abacus.bates.edu/~ganderso/biology/resources/writing/HTWtablefigs.html.

Cleveland, William S. 1994. The Elements of Graphing Data , 2nd ed. Summit, NJ: Hobart Press..

Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.

University of Chicago Press. 2017. The Chicago Manual of Style , 17th ed. Chicago & London: University of Chicago Press.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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Article • 11 min read

How to Use Charts and Graphs Effectively

Choosing the right visual for your data.

By the Mind Tools Content Team

books magazines charts graphs diagrams

Visual representations help us to understand data quickly. When you show an effective graph or chart, your report or presentation gains clarity and authority, whether you're comparing sales figures or highlighting a trend.

But which kind of chart or graph should you choose? If you click on the chart option in your spreadsheet program, you'll likely be presented with many styles. They all look smart, but which one works best for your data, and for your audience?

To figure that out, you need a good understanding of how graphs and charts work. This article explains how to use four of the most common types: line graphs, bar graphs, pie charts, and Venn diagrams.

How to Tell a Story With Charts and Graphs

The main functions of a chart are to display data and invite further exploration of a topic. Charts are used in situations where a simple table won't adequately demonstrate important relationships or patterns between data points.

When making your chart, think about the specific information that you want your data to support, or the outcome that you want to achieve .

Keep your charts simple – bombarding an audience with data will likely leave them confused and uncertain, so remove any unnecessary elements that could distract them from your central point.

Our brains process graphical data in a different way to text. Your audience will subconsciously seek a visual center that draws their attention. Only use bright colors for areas that you want to emphasize, and avoid tilting or angling your chart, as this can cause confusion.

If the data doesn't support your point of view, avoid manipulating it to do so. This is not only unethical, it's also relatively easy to spot for anyone who is experienced in analyzing data.

How to Create Basic Graphs and Charts

The word "chart" is usually used as a catchall term for the graphical representation of data. "Graph" refers to a chart that specifically plots data along two dimensions, as shown in figure 1.

Figure 1: x- and y -Axes

books magazines charts graphs diagrams

When you plot your data, the known value goes on the x -axis and the measured (or "unknown") value goes on the y -axis. For example, if you were to plot the measured average temperature for a number of months, you'd set up axes as shown in figure 2:

Figure 2: The Known Value Goes on the Horizontal x -Axis and the Measured Value on the Vertical y -Axis

books magazines charts graphs diagrams

The following sections cover the most commonly used types of data visualization.

Line Graphs

One of the graphs you will likely use most often is a line graph.

Line graphs simply use a line to connect the data points that you plot. They are most useful for showing trends and for identifying whether two variables relate to (or "correlate with") one another.

Examples of trend data include how sales figures vary from month to month, and how engine performance changes as the engine temperature rises.

You can use correlation data to answer questions like, "On average, how much sleep do people get, based on their age?" or "Does the distance a child lives from school affect how frequently they are late?"

Data can be continuous or discontinuous (or discrete).

Continuous data is measured , and can represent any value on a continuous scale: height, weight and time are all examples of continuous data.

Discontinuous data is not measured but counted : numbers of employees in a company or cars in a traffic jam are examples of discontinuous data.

Along the x -axis of a line graph, you can only use continuous data. This is because line graphs are used to make a direct link between the data points. If the variables are not continuous, a bar graph is probably more appropriate. (See the section on bar graphs, below.)

Using Line Graphs: An Example

ABC Enterprises' sales vary throughout the year. By plotting sales figures on a line graph (as shown in figure 3), you can see the main fluctuations during the course of a year. Here, sales drop off in June and July, and again towards the end of the year.

Figure 3: Example of a Line Graph

books magazines charts graphs diagrams

While some seasonal variation may be unavoidable for ABC Enterprises, it might still be possible to boost cash flows during the low periods through marketing activity and special offers.

Line graphs can show more than one line or data series, too. It's easy to compare trends when you represent them on the same graph.

For example, you might have different lines for different product categories or store locations, as shown in figure 4, below.

Figure 4: Example of a Line Graph With Multiple Data Series

books magazines charts graphs diagrams

Another type of graph that shows relationships between different data sets is the bar graph.

In a bar graph, the height of the bar represents the measured value: the higher or longer the bar, the greater the value.

Using Bar Graphs: An Example

ABC Enterprises sells three different models of its main product: the Alpha, the Platinum, and the Deluxe. By plotting the sales of each model over a three-year period, you can see trends that might be masked by a simple analysis of the figures themselves.

In figure 5, it's clear that although the Deluxe is the highest-selling, its sales have dropped off over the three-year period, while sales of the other two have continued to grow.

Perhaps the Deluxe is becoming outdated and needs to be replaced with a new model. Or it could be suffering from stiffer competition than the other two models.

Figure 5: Example of a Bar Graph

books magazines charts graphs diagrams

You could also represent this data on a multiple-series line graph, as shown in figure 6.

Figure 6: Data From Figure 5 Shown on a Line Graph

books magazines charts graphs diagrams

Often, the choice of which style to use comes down to how easy the trend is to spot. In this example, the line graph works better than the bar graph, but this might not be the case if the chart had to show data for 20 models, rather than just three.

Generally, if you can use a line graph for your data, a bar graph will often do the job just as well. However, the opposite is not always true: when your x -axis variables represent discontinuous data (such as employee numbers or different types of products), you can only use a bar graph.

Data can also be represented on a horizontal bar graph, as shown in figure 7. This is a better method when you need more space to describe the measured variable. It can be written on the side of the graph rather than squashed underneath the x -axis.

Figure 7: Example of a Horizontal Bar Graph

books magazines charts graphs diagrams

A pie chart compares parts to a whole. As such, it shows a percentage distribution. The pie represents the total data set, and each segment of the pie is a particular category within the whole.

To use a pie chart, the data you are measuring must depict a ratio or percentage relationship. Each segment must be calculated using the same unit of measurement, or the numbers will be meaningless.

Using Pie Charts: An Example

The pie chart in figure 8 shows where ABC Enterprises' sales come from.

Figure 8: Example of a Pie Chart

books magazines charts graphs diagrams

Be careful not to use too many segments in your pie chart. More than six and it gets far too crowded.

If you want to emphasize one of the segments, you can detach it a little from the main pie.

For all their obvious usefulness, pie charts do have limitations. For example, the layout can mask the relative sizes and importance of the percentages. Consider whether a bar graph would better illustrate your intentions.

Venn Diagrams

Venn diagrams show the overlaps between sets of data.

Each set is represented by a circle. The degree of overlap between the sets is depicted by the amount of overlap between the circles.

A Venn diagram is a good choice when you want to convey either the common factors or the differences between distinct groups.

Using Venn Diagrams: An Example

Figure 9 shows sales at Perfect Printing. There are three product lines: stationery printing, newsletter printing, and customized promotional items, such as mugs.

Figure 9: Example of a Venn Diagram

books magazines charts graphs diagrams

By separating out the customers by the type of product that they buy, it becomes clear that the biggest group of customers (55 percent of the total) are those buying stationery printing.

But, most stationery customers are only using Perfect Printing for stationery (40 percent). They may not realize that Perfect Printing could also print their company newsletters and promotional items. Perfect Printing could consider some marketing activity to promote these product lines to its stationery customers.

Newsletter customers, on the other hand, seem to be well aware that the company also offers stationery printing and promotional items – 23 percent of newsletter printing customers also buy other products.

Try creating a few example charts using Excel, Google Sheets or other chart-making software. Get comfortable entering data and creating the charts so that when you need to create one for real, you are well prepared.

Charts and graphs help to express complex data in a simple format. They can add value to your presentations and meetings, improving the clarity and effectiveness of your message.

There are many chart and graph formats to choose from. To select the right type, it's useful to understand how each one is created, and what type of information it is used for. Are you trying to highlight a trend? Do you want to show the overlap of data sets, or display your data as a percentage?

When you're clear about the specific type of data that each chart or graph can be used with, you'll be able to choose the one that best supports your point.

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August 1, 2022

How Florence Nightingale Changed Data Visualization Forever

The celebrated nurse improved public health through her groundbreaking use of graphic storytelling

By RJ Andrews

books magazines charts graphs diagrams

DRAFT DIAGRAM Surviving drafts of Nightingale's diagrams give a rare peek into her team's creative process. Drawn by government clerks, these drafts show how the team refined original ideas to improve information design. They also reveal that the mechanical precision of the final lithographs was not present in the original references. This early sketch gives a preview of one of Nightingale's most famous graphics ( below ), which reveals how army deaths from preventable diseases ( blue ) outnumbered hospital deaths from wounds ( red ).

British Library Imaging Services

I n the summer of 1856 Florence Nightingale sailed home from war furious. As the nursing administrator of a sprawling British Army hospital network, she had witnessed thousands of sick soldiers endure agony in filthy wards. An entire fighting force had been effectively lost to disease and infection. The “horrors of war,” Nightingale realized, were inflicted by more than enemy bullets.

Nightingale had earned the moniker “Lady with the Lamp” by making night rounds on patients, illuminated by a paper lantern. She was serving in the Crimean War, where Britain fought alongside France against the Russian invasion of the Ottoman Empire. The causes of the soldiers' torment were numerous: incompetent officers, meager supplies, inadequate shelters, overcrowded hospitals and cruel medical practices.

Nightingale arrived back in London determined to prevent similar suffering from happening again. It would be an uphill slog. Many government leaders accepted the loss of common soldiers as inevitable. They wrongly believed, for example, that communicable diseases were caused by unavoidable realities—the weather, bad diet and harsh work conditions. And the poor quality of army data made it impossible to know exactly how soldiers died. Patient outcomes varied depending on whether you asked the officer who lost fighters, the ferryman who shuttled the sick, the doctor who treated invalids or the adjutant who buried bodies.

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books magazines charts graphs diagrams

Resolute, Nightingale set out to sway the minds of generals, medical officers and parliamentarians. Their poor data literacy muted statistical arguments that could have oriented them toward the facts. Nightingale, with her quantitative mind, had to persuade people with common understanding but uncommon standing. Her prime target throughout this effort was the head of the British Army, Queen Victoria.

With public attention drifting away from the concluded war, Nightingale knew that the opportunity for reform was fleeting. She worked 20-hour days, mostly behind the scenes, writing letters, wrangling data and publishing anonymously. She did not do it alone—a circle of experts, including statesmen, statisticians and scientists, united with her to break the policy makers' inertia and ineptitude. The team focused its campaign on promoting sanitary reform: fresh air, clean sewers and less crowding.

Nightingale's key persuasion tactic was to convey statistics in exciting ways. I recently conducted the first in-depth study of how Nightingale created and used data visualization, and I share my research in the forthcoming book Florence Nightingale, Mortality and Health Diagrams (Visionary Press). I studied correspondence that details Nightingale's information-design process, hand-drawn draft diagrams never before seen by the public and a complete catalog of her information graphics. We can now appreciate better than ever what an innovator Nightingale was and how her techniques foreshadowed how data graphics would become essential to public understanding and debate today.

Recognizing that few people actually read statistical tables, Nightingale and her team designed graphics to attract attention and engage readers in ways that other media could not. Their diagram designs evolved over two batches of publications, giving them opportunities to react to the efforts of other parties also jockeying for influence. These competitors buried stuffy graphic analysis inside thick books. In contrast, Nightingale packaged her charts in attractive slim folios, integrating diagrams with witty prose. Her charts were accessible and punchy. Instead of building complex arguments that required heavy work from the audience, she focused her narrative lens on specific claims. It was more than data visualization—it was data storytelling.

Nightingale's stories showcased how poor sanitation and overcrowding caused unnecessary death. She constructed her arguments from easy-to-understand comparisons. For instance, Nightingale brilliantly framed army mortality by contrasting it with civilian mortality. She showed how, for example, peacetime soldiers living in army barracks died at higher rates than civilian men of similar ages. Her graphics made it impossible to deny the realities represented by the data: army administration needed dramatic reform.

Nightingale's diagrams received broad coverage in the press. Within months after the first batch was published, the issue of overcrowded barracks was debated in both houses of Parliament, which moved to reform the sanitary conditions of the army. This resolution was backed by four subcommissions focused on sanitary construction, health codes, a military medical school and military statistics. Within a couple of years the quality of British Army data soared under the leadership of a Nightingale ally. The new data-collection operation—eventually lauded as the best in Europe—also proved the success of the sanitary reforms: mortality from preventable disease among soldiers declined to less than that in the comparable civilian population. Nightingale celebrated this milestone with a final Crimean War diagram, published in 1863.

Her campaign's biggest impact on civilian public health took another decade to materialize. The reforms Nightingale fought for were finally codified in the British Public Health Act of 1875. The legislation established requirements for well-built sewers, clean running water and regulated building codes. The law and the precedent it set worldwide would be driving forces—along with the development of vaccines that conferred immunity to diseases and artificial fertilizer that boosted crop yields—in doubling the average human life span during the following century.

CONTEXT Nightingale's firsthand experiences in the Crimean War drove her passion for health reform. Here she leads a group on horseback to view the siege of Sevastopol ( top left ), the Crimean War's culminating conflict. Nightingale's graphics departed from the standard visualizations of the time, such as this black-and-white bar chart of soldier mortality ( top right ). In contrast, her charts ( bottom ) amplified the data story by comparing soldier ( red ) and civilian ( black ) mortality rates using horizontal bars, making the chart's labels easier to read. Nightingale's letters reveal that she was the one who designed the chart form, data and text.

Credit: Wellcome Collection; UCLA Library Special Collections, History & Special Collections for the Sciences; Internet Archive archive.org/details/b21365210 ( clockwise from top )

DATA CRAFTWORK Nightingale collaborated with physician and medical statistician William Farr on her first batch of diagrams. They included bar charts, area charts and circular diagrams. This diagram shows the British Army's monthly mortality rate across the war. The small circle at the center of the composition represents the mortality rate for similar groups in the city of Manchester, England, where living conditions and general health were poor at the time, which helped readers grasp the extreme mortality rate in the army.

Credit: UCLA Library Special Collections, History & Special Collections for the Sciences

HANDS-ON LEADER The civilian data came from Farr's vaults at the General Register Office (GRO). The army data were assembled from half a dozen sources who had recorded deaths during the war. An extant army record indicates the nonstandardized data that Nightingale helped to wrangle. Farr's team of GRO clerks assisted with data analysis; they also drafted the diagrams. Nightingale managed and funded diagram lithography, printing and distribution. Her edits, which survive in correspondence and on diagram drafts, reveal a leader engaged with the project from conception through production. Although these first diagrams attracted attention, the circular diagrams contained a visual encoding flaw that caused large values to appear overexaggerated. Nightingale and her team corrected the mistake in their second batch of graphics.

Credit: Wellcome Collection

DATA STORYTELLING—THE PROBLEM Nightingale's second batch of visualizations was her most stunning graphic achievement. The three-diagram set was originally issued in a confidential report to Queen Victoria. After the sanitation reformers were attacked in an anonymous pamphlet, Nightingale and her team repackaged the diagrams with a final rebuttal for public consumption. These graphics form a narrative that exposed the problem (too many deaths), revealed its cause (preventable disease) and offered lifesaving solutions (sanitary reform). The first diagram, shown here, emphasizes the problem by comparing the monthly rate of army mortality across two years ( radiating wedges ) with the average mortality rate in the city of Manchester ( inner circle ).

Credit: Harvard Library

DATA STORYTELLING—THE CAUSE Nightingale's best-known diagram is this colorful depiction of causes of mortality, illustrated by overlapping wedges. Part of the chart's enduring success is attributable to its strange yet interesting form; others at the time presented similar data in conventional line graphs, to little effect. As the middle story element of her visual argument, it elevated two comparisons. The first shows that deaths from preventable diseases ( blue ) greatly outnumbered hospital deaths from wounds ( red ). The second comparison, repeated from the first diagram, is between the first year ( right ) and second year ( left ) of the war. It shows that mortality declined significantly between the two years, which are linked by a jagged line, and encourages readers to wonder what occurred to make such a difference.

DATA STORYTELLING—THE SOLUTION The third diagram completed the story by focusing attention on the moment when a team of sanitation engineers began fixing Nightingale's hospital. The mortality rate decreased greatly with the “commencement of sanitary improvements.” In her quest to highlight sanitary reform in this graphic, Nightingale left out other factors that probably played a role, including a reduction in hospital overcrowding and the end of a miserably cold winter. Furthermore, the sanitary improvements to the hospital did not magically happen in one day; they were the result of several months of work clearing filth, rebuilding sewers and installing ventilation flues. The radiant diagram is an information-design wonder: its wedge angles vary to accommodate the different record-collection periods for its source data.

Scientific American Magazine Vol 327 Issue 2

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Copyright & Fair Dealing

  • Books & Ebooks
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  • Images, Charts, Figures, etc.

Can I copy images to use in my course presentations and assignments?

Best practices for copying images, what about charts and tables, what about book covers, non-commercial user generated content exceptions in the copyright law a.k.a the mashup exception or youtube exception, educational exceptions in the copyright law, exception for "fair dealing", finding and using images, finding images.

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  • 1. Introduction
  • 2. How Does Copyright Law Apply at My University?
  • 3. When Do I Need to Think About Copyright?
  • 4. What Rights Do Copyright Owners Have?
  • 5. User Rights
  • 6. What Do I Need to Know About Licensing?
  • 7. Openly Licensed Materials

Most images you find in print material or on the Internet are copyright protected.  There are educational exceptions in the Copyright Act that allow you to make some limited use of copyrighted images in your course presentations or papers for educational purposes.In addition, for non-commercial use, there is an exception for non-commercial user generated content.

Please see below for more details.

Images include: figures, tables, graphs, photographs, charts and diagrams.

  • Use caution and check the copyright statements or terms of use for each site. Note: Permission to use images is often located in a website's fine print, such as the 'Terms of Use' or 'Legal Notices'.  Check the terms for restrictions or limitations. Please keep in mind that many sites purchase photography that is licensed and for which they do not own the copyright.
  • View the Finding Images page in the Video, Images & Music Guide for more information on finding this type of image.
  • Always cite your sources:  indicate the title, creator and source for each image. In a PowerPoint presentation or a video clip, your citations can be listed on a separate slide.
  • Use images that contribute to the content of the work and reinforce the educational aspect of the paper or presentation.
  • to the best of your ability, ensure the copy of the image is made from a lawful source.
  • You always have the option of requesting permission from the copyright holder to use an image   This may not always be easy or quick, but is an option if you are unsure, or if required by the terms of use.

 A note about Google Images and Microsoft Office/Bing Images :  Use only if you can cite the original image from the original webpage or if you have permission from the copyright owner.

Charts and tables are protected by copyright like images. Did you know that ideas cannot be copyrighted? Copyright protects the original words or images that express an idea. You can recreate graphs and tables from raw data without infringing on the copyright of the original creators.

Copying the ideas of others without giving credit is plagiarism. Always provide credit for the original source of ideas and data when writing a paper, or creating charts and diagrams!

A book cover or jacket is a creative work and the creator is generally not the author of the book itself. If using the fair dealing exception, please weigh the criteria carefully.  Although the use may be educational and not for profit, the book cover is art or photography and not part of the book, so its use does not fall within the usual 10% excerpt from a book. Obtaining permission would be the favored option but often the publisher is not the copyright holder for the book jacket and only has permission to reproduce with the book.  Obtaining permission from the actual copyright holder could be time consuming and difficult.  If after careful consideration your use of a book cover falls within the fair dealing exception, it is recommended to  use thumbnail, low resolution images if available.

Non-commercial user generated content exceptions in the copyright law  a.k.a the mashup exception or YouTube exception

  • Must be solely for non-commercial purposes.
  • You must cite all sources used.
  • Do not use material acquired through a contract or license that prevents using the item in a mashup (e.g. iTunes, iStock Photo).
  • Do not break a digital lock to use the material (e.g. you can’t rip a DVD that has encoding that prevents copying)
  • It must be original! The mashup cannot be substitute for, or does not have a substantial adverse effect, financial or otherwise, on existing works.

Seneca Libraries (2014 June, 16). Copyright in "Mashups"  [Video file]. Retrieved from https://www.youtube.com/watch?v=vuwsCPfd4dk

​An Example of a mashup: 

Justin Trudeau Singing Work by Rihanna

CBC Music (2016 March, 9).  Justin Trudeau Singing Work by Rihanna  [Video file]. Retrieved from https://www.youtube.com/watch?v=yFTA0qHcswk

Reproduction for instruction

Under Section 29.4 (1)  of the Copyright Act, you are permitted to project an image for the purposes of education or training on the premises of an educational institution. Distance courses via the university's web conferencing software, e.g. Blackboard Collaborate or BBC Ultra, are included under the premises of an educational institution.

Work available through Internet

The Copyright Modernization Act, Section 30.04 , allows educational institutions, for educational purposes, to reproduce, save, download and share publicly available materials that are on the Internet, under certain conditions.

You can reproduce an entire image from the Internet, as long as:

  • the website is not questionable or is not using 3rd party material without the copyright owner's consent.
  • the content is not password protected or otherwise restricted from public access.
  • there is not a clearly visible posting on the website that prohibits educational use (and not merely the copyright symbol).
  • you do not need to break or circumvent a digital lock to obtain a copy of the material.
  • you provide the proper citation for the image(s).

The "Fair Dealing" exception allows for  the use of copyright materials for educational purposes under the following conditions:

  • You must properly attribute:  indicate the title, author and source for each image.
  • You must comply with the amounts and limits as defined in the Fair Dealing Guidelines .  Under Fair Dealing you can use one entire image from a compilation of images (e.g. a gallery of images on the Web; a book with images) or up to 10% of a stand-alone image (an image that is not part of a larger compilation but is on its own).
  • Copying is more likely to be fair if it is done for a limited audience. For example, posting material on a secure system with password protection is more likely to be fair than uploading material to the open Internet

Create Image

Remember to check your rights permissions at all times. Images must be properly cited , like any other source.

Photo credit: gfpeck. (2010, March 29). Create [image]. Retrieved from   https://www.flickr.com/photos/wespeck/4473683746 /

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South Carolina State Standards for Language Arts: Grade 3

Currently Perma-Bound only has suggested titles for grades K-8 in the Science and Social Studies areas. We are working on expanding this.

SC.3-1. Reading - Understanding and Using Literary Texts: The student will read and comprehend a variety of literary texts in print and nonprint formats.

3-1.1. Analyze the details that support the expression of the main idea in a given literary text.

3-1.2. Analyze a given literary text to make, revise, and confirm predictions and draw conclusions.

3-1.3. Analyze the text to determine first-person point of view.

3-1.4. Distinguish among devices of figurative language (including simile, metaphor, personification, and hyperbole) and sound devices (including onomatopoeia and alliteration).

3-1.5. Analyze the relationship among characters, setting, and plot in a given literary text.

3-1.6. Analyze the effect of the author's craft (for example, word choice and sentence structure) on the meaning of a given literary text.

3-1.7. Create responses to literary texts through a variety of methods (for example, writing, creative dramatics, and the visual and performing arts).

3-1.8. Classify works of fiction (including fables, tall tales, and folktales) and works of nonfiction (including biographies) by characteristics.

3-1.9. Recognize the characteristics of poetry (including stanza, rhyme, and repetition).

3-1.10. Analyze cause-and-effect relationships in literary texts.

3-1.11. Read independently for extended periods of time for pleasure.

SC.3-2. Reading - Understanding and Using Informational Texts: The student will read and comprehend a variety of informational texts in print and nonprint formats.

3-2.1. Summarize evidence that supports the central idea of a given informational text.

3-2.2. Analyze informational texts to draw conclusions and make inferences.

3-2.3. Distinguish between facts and opinions in informational texts.

3-2.4. Create responses to informational texts through a variety of methods (for example, drawings, written works, and oral presentations).

3-2.5. Use headings, subheadings, print styles, captions, and chapter headings to gain information.

3-2.6. Use graphic features (including illustrations, graphs, charts, maps, diagrams, and graphic organizers) as sources of information.

3-2.7. Use functional text features (including tables of contents, glossaries, and indexes) as sources of information.

3-2.8. Analyze informational texts to identify cause-and-effect relationships.

3-2.9. Read independently for extended periods of time to gain information.

SC.3-3. Reading - Building Vocabulary: The student will use word analysis and vocabulary strategies to read fluently.

3-3.1. Generate the meaning of unfamiliar and multiple-meaning words by using context clues.

3-3.2. Use base words and affixes to determine the meanings of words.

3-3.3. Interpret the meaning of idioms encountered in texts.

3-3.4. Read high-frequency words in texts.

3-3.5. Use context clues to determine the relationship between two or more words (including synonyms, antonyms, and homonyms).

3-3.6. Spell high-frequency words.

3-3.7. Spell correctly

3-3.7.a. Words that have blends,

3-3.7.b. Contractions,

3-3.7.c. Compound words,

3-3.7.d. Orthographic patterns (for example, qu, consonant doubling, changing the ending of a word from -y to -ies when forming the plural), and

3-3.7.e. Common homonyms.

3-4.1. Generate and organize ideas for writing using prewriting techniques (for example, creating lists, having discussions, and examining literary models).

3-4.2. Use complete sentences (including compound sentences) in writing.

3-4.3. Create paragraphs that include a topic sentence with supporting details and logical transitions.

3-4.4. Use grammatical conventions of written Standard American English, including

3-4.4.a. Comparative and superlative adjectives,

3-4.4.b. Prepositions and prepositional phrases,

3-4.4.c. Conjunctions (because, since, yet, until), and

3-4.4.d. Nominative and objective case pronouns.

SC.3-4. Writing - Developing Written Communications: The student will create written work that has a clear focus, sufficient detail, coherent organization, effective use of voice, and correct use of the conventions of written Standard American English.

3-4.5. Revise the organization and development of content and the quality of voice in written works.

3-4.6. Edit for the correct use of written Standard American English, including

3-4.6.a. Capitalization: geographic names, holidays, and historical and special events;

3-4.6.b. Punctuation: commas in addresses, commas in the greeting and closing of letters, commas in compound sentences, apostrophes in contractions and possessive nouns, periods in abbreviations, and indentation of paragraphs; and

3-4.6.c. Spelling: misused homonyms, high-frequency multisyllabic words, words that have blends, contractions, compound words, and orthographic patterns (for example, qu, consonant doubling, changing the ending of a word from -y to -ies when forming the plural).

3-4.7. Use correct letter formation when using manuscript and cursive writing.

SC.3-5. Writing - Producing Written Communications in a Variety of Form: The student will write for a variety of purposes and audiences.

3-5.1. Create written communications (for example, friendly letters that include a greeting, body, closing, and signature and invitations that include the time, date, and place of the event).

3-5.2. Create narratives that include characters and setting and follow a logical sequence.

3-5.3. Create written descriptions about people, places, or events.

3-5.4. Create written pieces (for example, riddles and jokes) to entertain others.

SC.3-6. Researching - Applying the Skills of Inquiry and Oral Communication: The student will access and use information from a variety of sources.

3-6.1. Generate a topic for inquiry.

3-6.2. Use print sources (for example, books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauri) and nonprint sources (for example, pictures, photographs, video, and television) to access information.

3-6.3. Organize information by classifying or sequencing.

3-6.4. Paraphrase research information accurately and meaningfully.

3-6.5. Use the internet as a source of information.

3-6.6. Use vocabulary (including Standard American English) that is appropriate for the particular audience or purpose.

3-6.7. Use appropriate visual aids (for example, pictures, objects, and charts) to support oral presentations.

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COMMENTS

  1. Over 60 New York Times Graphs for Students to Analyze

    Bigger, Saltier, Heavier: Fast Food Since 1986 in 3 Simple Charts (back-to-back bar graphs) Your Questions About Food and Climate Change, Answered (bar graphs) An Ecological Crisis as 2.9 Billion ...

  2. The 20 Best Data Visualization Books You Should Read

    1) "The Visual Display of Quantitative Information" by Edward R. Tufte **click for book source** You can't make a list of data visualization books without including Edward Tufte. Tufte is considered to be amongst the foremost pioneers in the field and this really is considered the best book on data visualization out there.

  3. 21 Great Data Visualization Books, Chosen by Experts

    Published in early 2021 and including a stellar variety of visualizations (more than 500 examples), Better Data Visualizations reads as an enjoyable and educational encyclopedia of graphs. The book is organized into three sections. It begins with a brief primer on data visualization best practices. Part two is the bulk of the book: chart types.

  4. 16 amazing book charts and visualizations

    16 amazing book charts and visualizations 1. A guide to fiction genres "A Plotting of Fiction Genres" chart is epic. It investigates the genres of most famous books and puts them together in a catching visual.

  5. The Power of Charts, Graphs, and Timelines: Can They Really Help

    These could be from a magazine, a website in a book, or even something from a TV show. ... Standards Alignment RI.4.7 - Interpret information presented visually, orally, or quantitatively (e.g., in charts, graphs, diagrams, timelines, animations, or interactive elements on Web pages) and explain how the information contributes to an ...

  6. Blog

    Graphs usually represent quantitative data on an 2D image with an x-y axis, using lines or bars. Graphs can visualise numerical data or a mathematical function, and are often generated from data in a spreadsheet. The word 'graph' is used outside of this context. For example, infographics explain complex topics in simple abstract ...

  7. Infographic Examples. What is an infographic? Examples and templates

    Merriam-Webster defines infographics as "a chart, diagram, or illustration (as in a book or magazine, or on a website) that uses graphic elements to present information in a visually striking way".

  8. What are Text Features?

    The most common text features of a book include the table of contents, the index, headings, captions, bold words, illustrations, photographs, the glossary, labels, graphs, charts, and diagrams. Many of these text features can also be found in newspapers, magazines, or individual articles. Text features are used to help navigate and locate ...

  9. Figures and Charts

    Graphs are a particular set of figures that display quantitative relationships between variables. Some of the most common graphs include bar charts, frequency histograms, pie charts, scatter plots, and line graphs, each of which displays trends or relationships within and among datasets in a different way.

  10. How to Use Charts and Graphs Effectively

    To figure that out, you need a good understanding of how graphs and charts work. This article explains how to use four of the most common types: line graphs, bar graphs, pie charts, and Venn diagrams. How to Tell a Story With Charts and Graphs. The main functions of a chart are to display data and invite further exploration of a topic. Charts ...

  11. How Florence Nightingale Changed Data Visualization Forever

    In contrast, her charts (bottom) amplified the data story by comparing soldier (red) and civilian (black) mortality rates using horizontal bars, making the chart's labels easier to read ...

  12. Research Terms Honors ELA Flashcards

    This is the category of information including books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauruses. Reference. This is a source used to find information. Relevant. This is an adjective that implies a thing closely relates to or is on the same subject matter; appropriate to the situation.

  13. Images, Charts, Figures, etc.

    A book cover or jacket is a creative work and the creator is generally not the author of the book itself. If using the fair dealing exception, please weigh the criteria carefully. Although the use may be educational and not for profit, the book cover is art or photography and not part of the book, so its use does not fall within the usual 10% ...

  14. Informative Writing Flashcards

    This is the category of information including books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauruses. non print source This is the category of information that include digital, electronic, pictures, photographs, video, and television to access information.

  15. RI.5.7 Draw on information from multiple print or digital sources

    This is the category of information including books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauruses. dictionary. a reference book in which spoken or written words are defined. encyclopedia. a book or set of books giving information on many subjects or on many aspects of one subject and typically ...

  16. Books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias

    04/30/2021 English High School verified answered • expert verified Books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauruses are all examples of_ _ _ _ _ media Advertisement Expert-Verified Answer question No one rated this answer yet — why not be the first? 😎 KirtiVT4

  17. South Carolina State Standards for Language Arts: Grade 3

    Use graphic features (including illustrations, graphs, charts, maps, diagrams, and graphic organizers) as sources of information. 3-2.7. Use functional text features (including tables of contents, glossaries, and indexes) as sources of information. 3-2.8. Analyze informational texts to identify cause-and-effect relationships. 3-2.9.

  18. Research Terms Flashcards

    This is a reference book containing an alphabetical list of words, with information given for each word usually including meaning, pronunciation, and etymology. ... This is the category of information including books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauruses. About us. About Quizlet; How Quizlet ...

  19. Research Terms Flashcards

    Graphic. Adj.-Depicted or represented pictures or images. Noun-A picture, image or visual representation of information or an idea. Graphic Organizer. This is a pictorial way of representing knowledge. It is used to help organize ideas and present information. In-Text Citation.

  20. is the category of information including books

    Books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauruses are all examples of_ _ _ _ _ media star 5 /5 heart 12 this refers to the language of a specialized type, usually dealing with a narrow area of study or knowledge.

  21. This is the category of information including books, magazines, charts

    Books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauruses are all examples of_ _ _ _ _ media. star. 5/5. heart. 12. verified. Verified answer. The criteria retailer must meet to receive a reduced penalty and/or protect the license/permit if an illegal alcohol sale takes place at the establishment is often ...

  22. Research Terms Flashcards

    Graphic. adj- depicted or represented with pictures or images. noun- a picture, image or visual representation of information or an idea. Graphic Organizer. This is a pictorial way of representing knowledge. It is used to help organize ideas and present information. In-text Citation.

  23. Books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias

    04/30/2021 English High School answer answered Books, magazines, charts, graphs, diagrams, dictionaries, encyclopedias, atlases, and thesauruses are all examples of Advertisement deangy211206 is waiting for your help. Add your answer and earn points. Add answer +5 pts AI-generated answer Advertisement Answer 1 person found it helpful Dragon103