Edward Tufte's The Visual Display of Quantitative Information is sheer genius - he lays out the principles of how information should be portrayed graphically, with rules like "the number of information-carrying (variable) dimensions should not exceed the number of dimensions in the data." It's like reading The Art of War, except for data analysis.

I eagerly anticipated reading this book. I frequently design data visualizations for my job as a software engineer, and I have a deep love for effective graphs. I love to read about different strategies for representing information visually, and I know that Tufte's work in this area is very highly regarded.

I was completely astounded at how poorly argued this book is, how bizarre its recommendations can be, and how disdainful the author feels about any attempt to make graphs attractive. I know these are bold allegations against such a highly regarded work, so let me be specific.

Tufte argues in favor of graphic minimalism. He doesn't use the word "minimalism", but his principles include "erase non-data-ink, within reason" and "erase redundant data-ink, within reason." This seems reasonable on face -- who would argue in favor of redundancy? -- but he applies this in absurd ways. For example, the graph he uses to explain the idea of "redundant data-ink" is a bar chart with a single vertical bar on it, and a number on top of the bar. He writes:

"[this chart] unambiguously locates the altitude in six separate ways (any five of the six can be erased and the sixth will still indicate the height): as the (1) height of the left line, (2) height of the shading, (3) height of the right line, (4) position of the top horizontal line, (5) position (not content) of the number at the bar's top, and (6) the number itself. That is more ways than are needed."

I stopped for a second when I read this; surely Dr. Tufte is not arguing that a bar chart is inherently ambiguous because the bars are both outlined *and* filled, is he? But in case there was any question, he reinforces this concept a few pages later, when he takes a different bar chart and removes all of those "redundant" lines, and ends up with something truly unintelligible. Of this peculiar result he writes "The data graphical arithmetic looks like this--the original design equals the erased part plus the good part." I wish I could include the illustration in this review, because with words alone I simply cannot communicate how much worse Tufte's revision of this graphic is.

There are so many examples of this, but I will give just one more. At the beginning of Chapter 6, Tufte revisits the traditional box plot and again finds that it "can be mostly erased without loss of information." After offering several iterations of his minimalistic approach, he settles on a version which is just astoundingly bad. To represent the five data points (quartiles) Tufte draws a single line that is offset by a *miniscule* amount between the 25th and 75th percentiles, and has a *miniscule* break at the median. It is not hyperbole to say that when my eyes are 18 inches away from this graphic, the quartiles can barely be seen at all; it looks like he just drew a straight line. About this Tufte says "This design is the preferred form of the quartile plot. It uses the ink effectively and looks good."

These are examples of a larger trend throughout the book, which is to state general principles without much support, and then to judge graphs (and people's intelligence) by how well they adhere to those principles. Here is an example. In Chapter 3, Tufte argues that "relational" graphs -- graphs that show the relationship between two or more variables -- are more sophisticated than time-series or map-based graphs. I will include Tufte's entire analysis in support of this principle, because it will readily fit into this box:

"In order to make comparisons among a variety of newspapers, magazines, scientific journals, and books, I have compiled a rough measure of graphical sophistication--the share of a publication's graphics that are *relational*. Such a design links two or more variables but is not a time-series or a map. Relational graphics are essential to competent statistical analysis since they confront statements about cause and effect with evidence, showing how one variable affects another."

My first reaction (and I hope yours) to this was to note that relational graphs show how one variable is *correlated* with another, and cannot by themselves show cause and effect (we can thank statistics for an endless supply of "information" about what supposedly causes cancer). But besides that is just the overwhelming lack of support for the idea that we can judge the sophistication of a publication on what percentage of its graphs are relational. But that's exactly what Tufte proceeds to do; he trots out a table of publications from different countries and their "sophistication percentages", and uses it to achieve some conclusion that the Japanese are much smarter than anybody else, and the Americans stupider.

Another example of an unsupported principle: that more information is better. Throughout the book Tufte is consistently impressed when someone has discovered a way to cram more bits of information into the same graphic. For example, from page 20: "The most extensive data maps, such as the cancer atlas and the count of the galaxies, place millions of bits of information on a single page before our eyes. No other method for the display of statistical information is so powerful." This attitude inspires the reader to include as much information as they possibly can in their graphs. But Tufte never stops to ask the question: is there a point when more information just becomes noise? To quote Google documentation about their charts API: "Take care not to overestimate the number of data points required for a chart. For example, to show how popular chocolate ice cream was over the last ten years, aggregating search queries for each day would result in more than 3600 values. It would not make any sense to plot a graph at this granularity."

The major credit to Tufte's book is that he includes many examples of creatively designed graphs, many of them historical. He is particularly taken with a diagram of Napoleon's ill-fated attack on Moscow, which is undoubtedly a very engaging and effective graphic. But this makes Tufte's minimalistic recommendations all the more puzzling. He seems to completely miss that almost none of the historical work he admires follows the principles he spends the rest of the book advancing. Most of them use grid lines (which he hates; they are non-data-ink) and they invest effort into being attractive (which he sees as a dumbing down of graphs; he calls any visual flare "chartjunk.").

Tufte's principles totally ignore the primary purpose of graphs, which is to show a data set's *patterns* (or lack thereof) to humans. This is confounding, because many of the examples he cites do this brilliantly. His very first example, Anscombe's quartet (you can Google for it) is a fantastic example of how graphs show patterns even when basic statistical summaries do not. His Napoleon example shows the pattern of how the size of Napoleon's army was so severely diminished over time and space, and the points at which it suffered its greatest casualties. But Tufte seems to completely miss the point. Though his examples repeatedly show patterns, Tufte never talks about patterns at all. About the Napoleon example, Tufte writes "Minard's graphic tells a rich, coherent story with its multivariate data, for more enlightening than just a single number bouncing along over time. *Six* variables are plotted: the six of the army, its location on a two-dimensional surface, direction of the army's movement, and temperature on various dates during the retreat from Moscow." Tufte again is primarily impressed with the amount of data and the number of dimensions.

Principles like "remove non-data ink" and "forgo chartjunk" treat graphs as though they are a form of compression, and treat "ink" as a scarce resource. The truth is that the primary goal of a graph is to communicate data to a human, and humans respond to design and polish (if they did not, there would not be so many colors, icons, boxes, visual effects, etc. on the page you are viewing right now). Design can communicate structure. Visual weight can help draw the eye to the part of the graph that is most significant. Polish can make a graph visually appealing enough to look at in the first place. Tufte has no appreciation for these ideas: "Chartjunk does not achieve the goals of its propagators. The overwhelming fact of data graphics is that they stand or fall on their content, gracefully displayed. Graphics do not become attractive and interesting through the addition of ornamental hatching and false perspective to a few bars." This attitude puts Tufte in the company of usability expert Jakob Nielsen, who probably has good points to make, but when you visit his bland and text-heavy website [...] are you really inspired to spend time there reading?

This review is getting too long, so I can only just briefly state some more of my numerous problems with this book: he makes unsupported indictments against moire (patterns of lines or dots used to fill in regions), he spends almost no time talking about color, COLOR! (most of what he does say is negative -- he prefers grayscale), he rails against the idea of making graphs attractive or readily-understandable (he says that if the graph looks boring it's because you chose the wrong numbers), many of the graphs he cites are confusing or under-explained.

I don't know how to explain the high regard for this book. There are lots of beautiful graphs, to be sure, but most of them are not Tufte's and don't follow his principles. I am disappointed in what I expected to be a great book.

Edward Tufte prides himself on making very complex information accessible. What he doesn't understand is that the average person can not make sense of convoluted charts and graphs. Not everyone can read 5 pt type and overlapping hairline strokes, making his examples successfully unsuccessful.

Tufte's choice of words clearly demonstrates his lack of interest in the "'average' consumer." His writing is overly complicated, much too proud and irrelevant. Intimidating is the antithesis of accessible. "Excessive" immediately comes to mind.

If you are looking for a book from which to copy a few sentences to impress your boss, this book is great. If you are looking for insight into explaining very complex information to a very wide group of people, then steer clear.

Thoroughly disappointed.

PS - Don't attend his workshops. You may as well go on a "team-building retreat."

Perhaps the single most accessible book on data visualizations. You are given a tour of the history of visualizations, the seminal contributions of people such as Playfair, Tukey, and others, a rogues' gallery of sorts of awful visualizations, a peek into small-multiples visualizations, and an exposition of the principles of good graphic design and visualizations. A must-have book for anyone interested in good data visualizations.

Tufte's contention is that a lack of adequate knowledge and expertise and a mistaken notion about numbers are to blame for bad visualizations. The principles of good visualizations, on the other hand, are few and simple. The book is all about exposing bad examples and enunciating these good principles, beautifully illustrated with examples, and printed on excellent quality paper.

Suggested Reading:
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Supplement this excellent book with at least the following, if you are interested in digging deeper into the area of data visualizations:
- Information Visualization, Second Edition: Perception for Design (Interactive Technologies)
- Information Dashboard Design: The Effective Visual Communication of Data


The rest of the review can be best told, in my opinion, through quotes from the book:
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"The theory of the visual display of quantitative information consists of principles that generate design options... The principles should not be applied rigidly or in a peevish spirit... and it is better to violate any principle than to place graceless or inelegant marks on paper. Most principles of design should be greeted with some skepticism." [page 191]

While seemingly a trivial matter, the issue of the size of charts, whether they should be tall or horizontal, Tufte states that "Graphics should tend toward the horizontal, greater in length than height..." and "Many graphics plot, in essence (cause and effect) and a longer horizontal helps to elaborate the workings of the causal variable in more detail." [pages 186, 187]

Time-series displays are at their best for big data sets with real variability. [page 30]

Chapter 2, "Graphical Identity" Is a stunning collection of graphs that distort, lie, deceive, and exhibit all manners of skills other than those required for data visualizations.
"Much of twentieth-century thinking about statistical graphics has been preoccupied with the question of how some amateurish chart might fool the naive viewer. ... At the core of the preoccupation with deceptive graphics was the assumption that data graphics were mainly devices for showing the obvious to the ignorant. ... The assumption led down two fruitless paths in the graphically barren years from 1930 to 1970: First, that graphics had to be "alive", "communicatively dynamic," overdecorated and exaggerated.. Second, that the main task of graphical analysis was to detect and denounce deception." [page 53]

"A graphic does not distort if the visual representation of the data is consistent with the numerical representation." [page 55]
Which leads to his definition of the term, "Lie Factor", which he defines as the "size of the effect shown in graphic" divided by "size of effect in chart".

"Another way to confuse data variation with design variation is to use areas to show one-dimensional data" [page 69]
An example cited is the depiction of "the rate of inflation", for which, "graphs show currency shrinking on two dimensions, even though the value of money is one-dimensional." [page 70]

A very important observation quoted in Chapter 3 comes from Howard Weiner - "Perhaps the reason is an increase in the perceived need for graphs ... without a concomitant increase in training in their construction." [page 79]
Tufte elaborates: "Nearly all those who produce graphics for mass publication are trained exclusively in the fine arts and have had little experience with the analysis of data. ..." "... many graphic artists believe that statistics are boring and tedious. It then follows that decorated graphics must pep up, animate, and all too often exaggerate what evidence there is in the data." [page 79]
And "The doctrine of boring data serves political ends, helping to advance certain interests over others in bureaucratic struggles for control of a publication's resources. ... as the art bureaucracy grows, style replaces content. And the word people, having lost space in the publication to data decorators, console themselves... " [page 80]

Tufte defines "data-ink" in Ch 4 ("Theory of Data Graphics") as "the non-erasable core of a graphic, the non-redundant ink arranged in response to variations in the numbers represented
Data-ink ration = data-ink / total ink used to print the graphic" [page 93]
So, it should not come as a surprise, when Tufte takes a single bar with a value label at the top of the bar, and states that "the labeled, shaded bar of the bar chart, for example, unambiguously locates the altitude in size separate ways." [page 96].

Chapter 5 - "Charkjunk: Vibrations, Grids, and Ducks" is perhaps the most humorous chapter, as the title itself suggests. A quote from Johnathan Swift, indicting 17th-century cartographers, says it all - "With save pictures fill their gaps, And o'er unhabitable downs, Place elephants for want of towns." [page ] ouch!

"This may well be the worst graphic ever to find its way into print:" [page 118] refers to a "series of weird three-dimensional displays appearing in the magazine American Education in the 1970s (that) delighted connoisseurs of the graphically preposterous. Here five colors report, almost by happenstance, only five pieces of data..." [page 118]

You may not, and I certainly did not agree with Tufte's suggestions for maximizing the data-ink efficiency of the box-plot, in the chapter on "Data-ink Maximization", but they are worth examining nonetheless. However, his redesign of the bar chart, with a border and other accouterments, on pages 126-128, are excellent.

Many examples of bad visualizations cited in the book are from the "New York Times", so it is sort of reassuring when you see that the quality of visualizations on the NYT has improved a lot, and are frequently the objects of animated discussions. There may be hope, after all.

The review title, explained, at least part thereof:
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And what about that slightly inappropriate word in the title of the review?
Tufte writes that an art director with overall responsibility for the design of over 3,000 graphics annually had this to say - "graphics are intended to more to lure the reader's attention away from the advertising than to explain the news in any detail. 'Unlike the advertisements,' he said, 'at least we don't put naked women in our graphics.' " [page 80] We must be all thankful for small mercies, I suppose.

The book was in the exact condition the seller described. Fast shipment excellent seller!!!

See the world through the eyes of someone who has seen it before... and discover how much time you can save!

Very good book about how to display statistics in charts and graphs. I wish there had been more examples of what makes a good graph, but overall it's a great reference for anyone who's looking to make a chart or graph.

I am a working scientist. As such, I make my living conveying information to others. Tufte's books are all great, but this one is the most important and is a must read for ANYONE whose business involves the use of numerical data.

Tufte does a great job of stressing making graphics that tell the story efficiently and clearly. Display of quantitative data is all about making data accessible to the audience. Graphs are used because they make the data come alive in ways that tables simply cannot. When we are successful, our audience relates to plotted data and is drawn to the conclusions we have drawn. Creativity in reaching the audience is possible with both quill pen and computer.

Those critics who criticize the book as lacking state-of-the-art computer graphics have really missed the point. Tufte is agnostic to the tools used to craft the message. What he shows is that effective graphics resonate with an audience, they don't confuse it. That message transcends any particular technology. This isn't a book on how to use Excel to make plots, it is about the thought process required to make the plots better whether using Excel or graph paper.

His explanations of "small multiples", the "data-ink ratio", and the proper aspect ratio for graphs have made my academic/professional presentations more effective.

Tufte's volumes is an iconic volume for graphic design that unites legibility with efficiency and beauty in a cogent and stimulating manner. While it's reputation and overwhelming authority may hurt it a bit, it is actually a worth read with a well develop and constructed analysis - with a breakdown of some "best and worst" practices" - and an intriguing attempt to develop a theory for data graphics, which for the most part is worth carrying around and promoting.

Among some of the most obvious defects is a repetition of some trends and examples, a patronizing sense that permeated the narrative here and there, and with that, touches that may seem that the critique is trying to be too final, and offers little room for debate. But all in all these touches are minor and the volume withstands as a pivotal critical point to develop legible and useful graphic information. Something that I would recommend to anyone involved with, or interested in these aspects.

Because of the reviews, I was really excited to read this book. I am a scientist with a graphic arts background that I am told I use to great effect. I was hoping that this book would provide new ideas for presenting my own work and would help me learn to effectively communicate with my graduate students about their graphics. Unfortunately, this book did neither and instead, left me frustrated with the outdated information, overly dramatic characterizations of scientific graphics, and overly reductionist approach.

I could find few graphs that were published after 1980 and not many more than that published after 1960. There are repeated references to drawing plots with a ruler and pen which few, if any, scientists use to produce graphs today. As a result, the information is not of much use. Even the examples used to illustrate the problems with graphics produced electronically look to have been produced with a first generation Mac and bear no resemblence to the scientific graphics of today. While I agree with some of the points made about the graphics used in the text, they are so out of date that it makes it difficult to relate these points to my students.

Another reviewer commented quite clearly about the derogatory tone - with statistics and graphics called "lies" in more places than I can count so I'll leave that point alone.

The biggest flaw for me was the overly reductionist approach used throughout. For example, Tufte presents several alternatives to the venerable box plot. While I agree in principle that reducing useless ink is a good idea, many of these proposed graphs miss the point - conveying information clearly and honestly to the reader. The traditional box plot does a few things very well - it presents the mean of the data as a strong line with the majority of the data presented in an open box, providing visual weight somewhat proportional to the number of data points represented while showing the full range (or some statistical description of the data range) as whiskers which are visually reduced in weight relative to the box, again, relatively proportional to the number of data points they represent. Tufte's proposed alternatives may convey the same amount of data but they are difficult to interpret and do not provide the same visual weight to data but rather provide equal weight to all values represented in the best cases or in the worst, make the viewer focus on the ends of the data distribution instead of the mean value and majority of the data surrounding it. I think this reductionist approach misses how the human brain perceives information in its quest for simplicity and reduced ink. By the time one finishes this book, you'll believe that Tufte pays for graphic ink by the drop. However, text ink is apparently free as the text is often redundant and ovely verbose.

I had hoped to find a book that would be a great resource for myself and my students. I'm still looking.

It's all about charts. Pie chart, Bar chart and other charts. Nothing revolutionary.

It begs to be re-written with the modern needs. After the computer revolution, everyone knows how to use charts. It now needs to focus on what we can do with the today's tools like Adobe Illustrator or Photoshop. No, not the tutorial of using them, but a simplified way to convey exact information or impression, as that was the focus of the book.

Unfortunately, it focused too much on different types of charts. It's not what I expected from the reviewers from Amazon.com.

Statistician Edward R. Tufte makes a case for data graphics as respectable tools for representing and understanding data, not dumbed-down pictures for unsophisticated audiences in "The Visual Display of Quantitative Data". Tufte lays out examples of good and bad graphics and presents a "practical theory of data graphics" which the author believes will produce clearer, more informative, and more pleasing graphics than are often seen in publication. Tufte advocates "the simultaneous presentation of words, numbers, and graphics", not just as way of presenting information, but as facilitating other ways of understanding data. This second edition of the book adds color to some of the hundreds of graphics that Tufte uses to illustrate his ideals.

The subject is presented in two parts: The first addresses Graphical Practice and the second Theory of Data Graphics. Graphical Practice begins with a chapter that presents and discusses examples of excellent data maps, time-series, and spatial time-series over the past few centuries. Many examples from the work of 18th century political scientist William Playfair are featured, as they were pioneering and quite beautiful. Next is a chapter presenting examples of bad graphics, graphics that deceive, and conclusions on how to avoid these pitfalls. That is followed by discussion of the reasons we have so many misleading and dumbed-down graphics.

The Theory of Data Graphics addresses different aspects of design, as the author prescribes the maximization of the "data-ink ratio", meaning that a high proportion of your ink should be dedicated to the data itself, and proscribes "chartjunk", or extraneous decoration, such as moiré effects, that tend to consume and confuse the data. Tufte also talks about multi-functioning graphical elements, data density, and proportion. My own view is that replacing the frame of a scatterplot with a range-frame, which Tufte advocates, leaves the viewer without a point of reference and inhibits comprehension. Like all ideologies, Tufte's can be taken too far. But "The Visual Display of Quantitative Information" will help graphic artists, students, and professionals make the most of their charts, graphs, or maps. And it showcases a lot of creative and lovely graphics.

The title might lead you to think that this is a dry book, of interest only to stuffy academics in statistics-heavy fields. It isn't. Yes, people in those fields should read the book, and the world would be a better place if they'd do so before foisting their graphs on the rest of us. But this book should be enjoyed by everyone with an interest in graphic design, including artists and web designers.

I would recommend reading Tufte's entire "tetralogy" in order, starting with this one, followed by Envisioning Information, Visual Explanations and Beautiful Evidence. I'd say that this one is the second-best, after Visual Explanations.

Highly recommended! This book has been extremely important for understanding the way quantitative information should be displayed.
One of the best books I have ever read.

This gorgeous, entertaining, and fantastically helpful book needs to be required reading for all students and practitioners of science and engineering. Read it! Never again will you dare concoct an illegible chart or a nonsensical table, and you will learn about many other techniques for usefully displaying information.

I have attended one of the author's talks (easy to find on the web), and have all four books. One criticism of Tufte is that it is not obvious how to go about doing many of the graphics in his books. They are carefully crafted by individuals with great skill and expensive software. The fourth book, Beautiful Evidence, might leaving you scratching you head as to how to use the information in preparation for your next business presentation. He deserves his reputation, however. The books are beautiful, and his ideas have great merit. If you want an introduction to Tufte that gives you a chance of putting the advice into practice at work, you must read this one first. To go for the most recent, would be a mistake for most readers. If you become a convert, the other three are also excellent, but offer less practical application for the everyday business person. (For instance, I am a statistician and data miner, not a graphic designer).

The second book is Envisioning Information, and the third is The Visual Display of Quantitative Information, 2nd edition. Beware the inexpensive paperbacks - they are excepts from the hardcovers. Good content, but potentially redundant.

Although it is not a book for everyone, there is a very interesting discussion (albeit short) of Minard's Napoleon's march chart (made famous by Tufte) in The Grammar of Graphics (Statistics and Computing).

Stimulates the visualisation of information with illustrations on every page and easy to read text. Provides many helpful ideas, as well as some `do and don't's. Some overlap with the other book (The Visual Display of Quantitative Information / Envisioning Information).

This book is great. It has a lot of useful insights. However I was expecting something more practical... Maybe it's not a guide but a book with some nice historical data and references. Superb graphs and pictures.

Yes I would recommend you to buy it .

It is rare that a supposedly technical book really changes a reader's life. I can say, though, that after reading Tufte's books, my life is not the same. The complaints of the detracting reviewers are baseless if you understand the nature of this book. This book is the groundworks of a theory of seeing, of communicating through images. It is by no means a new theory. Throughout human history man has communicated through history. But Tufte shows with unparalleled visual eloquence what makes one image successfully communicate while another fails.

After reading this book, I have never looked at printed matter in the same way again. Not only that, through his breadth of examples and the depth of his analysis, the reader is made to realize that visual information/visual communication are at the heart of our human identity. Tufte's definition of successful display and its inherent subtlety are so deeply human that they can be carried over to general rhetoric and aesthetics if not farther.

No, he won't do your homework for you. He won't supply you with handy templates for making projects look snappier. Expecting that is like expecting a philosophy book to think for you. This work (I refer to all of his books--they really are one unit together) is certainly one of the great accomplishments of the last twenty years.

Tufte's book is a very fine book on data graphics.

Although this book gives a lot of simple advice on how to effectively communicate quantitative information, it is not just a recipe-like book, as it also makes you think about a data graphic as something that is telling a story with numbers.

Beware that not all advice given is easily applied using common office suites. This is by no means a problem with the book, it is just that the text is not at all software-oriented. In fact, you may start to see the limitations in the office suites themselves. So, for those who just want some fast rules to use in their favorite software, this book may not be enough, or even the most recommended one. For all other readers, I highly recommend it.

I returned to Tufte's first classic book of graphic design principles over 20 years after first discovering it. At the time, I was the corporate librarian for a major electric utility, and the explosion in the organization and creation of information by individuals with new personal-computer hardware and software was just beginning (I had an IBM PC-XT with 640Kb of RAM and two 360k floppies--no hard drive).

Now, I wondered, aside from the masterpiece of graphic design that "Visual Display" of course still represents, did Tufte's theories of graphics design still apply in a world where those computers at our fingertips pack the power and sophistication of the best publishing equipment? The answer is yes: Tufte's guidelines are timeless and universal, and most of his examples predate the computer era and even the 20th century.

The guidelines boil down to the single principle of making design choices that result in the simplest possible display of complex data. While that may not sound profound, Tufte provides simple and practical rules for implementing sound design choices, and the resulting improvements in your documents and web designs will be noticeable.

I was able to read this fairly quickly. (stealing a few hours here and there at work).

Although I did not find any direct solutions to my current problems - it definitely opened my imagination to consider new possibilities.

It definitely was interesting and educational to read and see Tufte's presentation on Visual Dispaly of Quantitative Information. He illustrates the good, the bad, and the ugly of graphic displays over the centuries. However, I was hoping to see more examples of current computer graphics that should be emulated in this edition instead of terse comments and skeletal constructs in this area.

A picture is worth a thousand words, but Tufte would rather right it all down. It would be funny if it wasn't so sad.

This is a somewhat interesting book for the catalogue of historical visual presentations, but has little to offer someone working today. The most amazing thing about this book is its incessant use of verbiage instead of visual display.

If Tufte intended his book as irony, then bravo.

If you're looking for actual help in visual display using the tools most of us have at our disposal (not the extremely expensive software that Tufte suggests) then look elsewhere for help. I recommend:

Presentation Zen: Simple Ideas on Presentation Design and Delivery by Garr Reynolds
or
The Back of the Napkin: Solving Problems and Selling Ideas with Pictures by Dan Roam

Indexed by Jessica Hagy

If you want to see great (and fun) visual displays on the web, then hit graphjam.com, zfacts.com and indexed.blogspot.com.

I would also suggest a trip to the dentist over paying for one of Tufte's seminars. Getting your teeth drilled is more pleasant than a slide show of Tufte's sculpture garden accompanied by his pedantic narcissism.

Nutshell review - This is an excellent book on chart design and the effective presentation of information. Beautifully illustrated with in-depth insight and research.

Mr. Tufte's book is like nothing I ever read before. At first I was put off by his uber self-confidence, but as I read the book further, I realized that the self-confidence was not out of place.
In an entertaining way, with splendid examples and splendid anti-examples, this book gets to the core of presenting honest and dense data and eliminating all pretense. Wait 'til you grasp the concept of "Small Multiples" and just as importantly, when not to use a graph.
Before I was finished the book, I revamped a couple of my charts and upgraded one to showing multiple variables across multiple years using "Small Multiples".

I own all of Edward Tufte's books, and regularly order his booklets for my MBA students. The reason is simple: to make good decisions, and to help others make good decisions, one must convey data as information and not simply as numbers, words, or even pictures. Business periodicals regularly violate the admonitions we learned in our introductory statistics courses, including failing to use zero as the bottom of any scale (these periodicals don't use zero in order to exaggerate changes). The reason that intelligent people convey data inappropriately is either to deliberately distort it, or because they've failed to read Tufte's books.

Once you've purchased this first book by Tufte, you will never look at charts or other graphical displays without a jaundiced eye. You will also will begin to be more honest in how you convey information to others. You will make better decisions, and you will raise the standard for other communicators and decision makers. Life and death decisions do get made on the basis of data, and not just in the sciences and medicine. Buy this book and you will have a very tough time putting it down.

Aneil Mishra
[...]

This is Tufte's best book in my opinion, maybe because this was his first book I bought. I use this book weekly. I learned many good lessons from Tufte.

Everybody should read a book like "The Visual Display of Quantitative Information" and I do not mean the professionals in the field but really everybody. Tufte really opens your mind and makes you aware of the possibly malevolent or just misleading representations of data we are faced with every day on magazines, newspapers, TV and the web.

This was the first of three books written by Tufte on graphical displays. This book has been heralded by famous statisticians and average readers as an eloquent description of the how to and how not to make graphs. Now in its sixteenth printing, this is still a classic and the pictures tell the story along with the prose.

The book came in wrapped as it was described. Highly recommend for excellent amazon seller.

This was the first of three books written by Tufte on graphical displays. This book has been heralded by famous statisticians and average readers as an eloquent description of the how to and how not to make graphs. Now in its sixteenth printing, this is still a classic and the pictures tell the story along with the prose.

The book came in wrapped as it was described. Highly recommend for excellent amazon seller.

To put it simply, this book is one of the very best I have ever had in my hands. The subject is of utmost importance to everyone having to convey quantitative information to non-specialist audiences. The book is both very thorough in the treatment of the subject and extremely pleasant to read. You read it for fun and you learn enormously in the process. In addition, the typography and layout of the book are in perfect sync with its message. A stunning piece of work.

In this book Edward R. Tufte show us how we tend to over complicate things and how visual effects tend to distort the story that the numbers have to tell us. He introduces the concept of information to ink ratio is introduced, which is a fancy way of saying that each pixel on a chart should add information or help to it's comprehention.

The book is also a beautiful collection of historical charts, whose authors intuitively knew the importance of un-cluttered information but to which Edward Tufte adds his personal touch to make them modern works of art. My personal favorites are the "Carte figurative", which shows the progress of the Napoleonic war and the one shown on the book cover, which represents a train schedule.

Tufte points out common general flaws in presentation of data. He then goes on to examine specific conventional ways of displaying information (boxplots, scatter plots, etc.) and proposes improvements to them.

This is an approachable and informative book which will, as the title says, get you thinking about effective and clear ways to display data.

This book has been talked up by about every design professional I've seen speak at conferences across the country. I bought it to hop on the band wagon -- and it was a great purchase.

It starts as a bit of a dry read, but has some of the greatest content and insight into the theory and profession of information design. Check it out.

Buy this book, buy more copies for your bathroom and garage, take it with you to work and on vacation, petition your state to legally recognize your entering into a civil union with this book. The combination of elegance, brevity, and depth in this book has to be experienced to be believed - and beyond all this, it serves as a utterly practical manual that shares the shelf with Strunk & White. If you don't buy and read this book you will be reincarnated as an unenlightened human until you do so.

I have a lot of mixed feelings about this book.

As a graphic designer and a minimalist: I love the way this book looks and I love the graphics Tufte's team has created.

Yet: the minimalist in me also dislikes Tufte's prose, which is surprisingly un-minimalist. The text is repetitive, and although Tufte does use this effectively at times to reiterate or summarize concepts, there are far more instances where I feel the repetition is simply irritating (Tufte's poems and block-quote summaries are, to me, good examples of this).

The minimalist in me is also not fond of the nature in which Tufte presents his opinions. Tufte makes frequent use of words like "lies" and "tricks," and while I am not fond of the targets of Tufte's derision, I feel that use of these words unnecessarily and unfairly assumes that poor graphs are always the result of malicious intent. Tufte's presentation as a whole, I feel, is often unnecessarily condescending (see e.g., p 120); indeed, Tufte seems to feel that unenlightened minds somehow deserve our ridicule and contempt.

As an academically-oriented statistician: I also have mixed feelings. I give Tufte an immense amount of credit for opening a dialog about statistical graphics. And, I am grateful to him for pointing out the flaws and "wrongs" in the ways in which statistics are so often presented and suggesting ways in which these approaches can be changed. Moreover: I happen to agree tremendously with a large amount of what Tufte has to say, and often passionately so.

That said: I am puzzled by the amount of relevant concepts which are omitted from this text (or merely brushed over). Good examples include: samples versus populations, confounding, continuous versus categorical data, and exploratory graphics versus graphics presented for presentation.

For that reason: the academic and statistician in me is watchful of Tufte's role as an instructor of statistical ideas. Much of what Tufte has to say is not in fact unique or necessarily "right," and it is also not nearly close to being all there is to be said about statistical graphics (even at an introductory level). If students allow this text to be the sole contribution to their statistical education, I fear that -- without statistical intuition or knowledge to draw from -- they will not be critical statistical thinkers but blind followers. (Of course, none of this is intended to be a criticism of Tufte or Tufte's book per se...)

Those seeking a good overview of statistical graphics: keep in mind that this not strictly an instructional book. And while I wouldn't discourage you from reading or buying this text, I also wouldn't discourage you from seeking additional resources, either as an alternative or a supplement to Tufte's works. Much of the ideas supplied by Tufte here -- plus a great deal more -- can fundamentally be found in a good introductory statistical course or text, either directly or indirectly. Moreover, I would argue that there is absolutely no substitution for such an education.

The ability to communicate important information concisely, precisely, and with high fidelity is the essence of successful sales and marketing presentations. Tufte's book offers a wonderful set of guidelines and examples in the use of graphics to communicate ideas that also applies directly to creating and delivering presentations in a sales or marketing meeting or demo.

It is wonderful to see him "deconstruct" overly ornate graphics, removing unnecessary elements to render an image in its strongest possible form. Those organizations that suffer from too much "fluff" in their marketing and sales materials should contemplate applying his principles to their collateral and presentations!

This book is a real tool that should be read thoughtfully by anyone in sales, presales, or marketing, and then remain in easy access on your business bookshelf. The graphic of Napoleon's advance upon Moscow and his subsequent retreat is worth the price alone.

This book established Tufte as the authority on the subject of graphs, charts, tables, indeed the display of data by any means. The book is readable by most anyone and will add to your library and your ability to make your way intelligently and critically through the flood of statistical and graphical arguments and pitches placed before us every day.

Simply and confidently Tufte lays out the basics of the right and the wrong, the good and the bad (and occasionally ugly) regarding graphical depictions of data and information.

This book (The Visual Display of Quantitative Information, 2nd edition )is the first and the foundation of four books by Tufte (I. The Visual Display of Quantitative Information, 2nd edition. II. Envisioning Information. III. Visual Explanations: Images and Quantities, Evidence and Narrative. IV. Beautiful Evidence.) that should be read in the order of publication. You will be a wiser person for the effort.

His short book, "The Cognitive Style of PowerPoint: Pitching Out Corrupts Within", while not part of the "four volume set" is a withering attack on the ubiquitous software program, an attack based on the fact that it encourages the user to break nearly every principle that Tufte has spent the last 20 years elucidating in his books regarding the reading and the writing and presentation of well thought out and presented arguments and reports. I've read it and was convinced; PP constrains complex thought, argument, and statistical (indeed any form of) reasoning with its "bullet points", and is a very inefficient means of depicting information as well, cluttering the display space with useless clip art, huge fonts, and often misleading cookie-cutter graphs. (His satirical PP presentation of the Gettysburg Address humorously makes his points, while his analysis of a very real NASA PowerPoint slide from the decision-making meetings regarding the danger to the Space Shuttle Columbia before its destruction on re-entry makes his points in a very sobering manner.)

All this being said, The Visual Display of Quantitative Information is a Great Book. In the internet age we all spend many hours per week looking at visual depictions of information. Tufte's book will make you a more critical user of nearly everything, from the newspaper, to websites, to work presentations, the sports pages, and even your car's speedometer and other gauges. It is the foundation to all of his published work from the last two decades.

Buy this book!

This book fuses mathematical information with art to tell the underlying story and get your message across to the viewer. I would reccommend it to anyone responsible for conveying objective information to others.

This book was very nicely laid out, and the ideas for presenting were good. Sometimes it was a little hard to follow because it rambled a little. But I did get some good pointers that I can use to visualize my data.

The book strikes a good balance between major concepts and academic nitty-gritty.

Tufte presents an examination of a frankly under-esteemed method of data analysis that can be accurately described as passionate. As a Behavioural Scientist trained in sophisticated methods of statistical analysis, I previously was arrogantly inclined to regard charts and graphs as simplistic and naive approaches to data interpretation. However, I now apprehend the undeniable utility of graphical representation, and have acquired a fascination with the field through Tufte's contagious enthusiasm.

If you work with data of any form, it is IMPERATIVE that you read this book.

An interesting and well presented book, but very specialized.

An interesting and well presented book, but very specialized.

The Visual Diplay of Quantitative Information is not exactly a how-to book, in that it won't give you step by step instructions on how to create charts. Rather Tufte shows us principles of good design, principles of bad design (i.e. how people lie with graphics) all accompanied by many inspirational examples.

His examples strike us with their beauty and economy and show us how picturing data makes a huge difference in how effectively and quickly we understand it. Looking at Mivart's chart of Napoleon's march on Moscow, or the Salyut 6 hand drawn mission schedule, or a Japanese train schedule can only make a geek like me gush out "Way cool!".

I find it gratifying that Tufte takes so many examples from Japan, where I live. The Japanese are often accused of simply working with other people's ideas. This is naive and the Visual Diplay of Quantitative Information provides an excellent counterexample of the Japanese being sophisticated leaders in a creative endeavor.

Vincent Poirier, Tokyo

I was one of those chart-makers who used color just because I could, even when it was unnecessary or even inappropriate. This book changed the way I looked at graph-making. His concepts of data per unit of ink (which should be maximized), and trying to make each droplet of ink convey something useful were extremely helpful, as were his suggestions to minimize distractions and phony 3-d effects.

This, and his second book, "Envisioning Information" are must-reads for anyone designing computer statistical tools (like I was) or simply trying to convert raw data into meaningful graphs, maps, etc.