The Visual Display of Quantitative Information

This book is as amazing as it is beautifully illustrated and packed with useful tips. After reading it I've never looked the same way at charts. It's amazing how bad most of the existing charts are. It's like taking a course in professional photography and then realizing the difference between a professional photograph and an amateur snapshot.

Bought based on my boss's recommendation to expand my knowledgebase in creating compelling visuals. Realized Edward Tufte is the Guru I have been looking for! Bought it along with other 2 books to complete the set.

I read this book as a preparation before designing dashboarding tools and systems for an analytics product.

It was astonishing how much thought Edward Tufte has put into his data graphic design theories and how the principles in this book still hold strongly to this day.

Absolutely recommend this book to anyone who wants to be better at visualizing data in a useful way to their users/customers/management.

Best of best. Master Edward lead us through a journey of visualization across centuries. It is the utmost important book to start studying data visualization and the nuts and bolts of its application to meaningful business cases.

Absolutely should be required reading for anyone in science, technology, policy, journalism or any profession demanding clear, concise and informative visual communication. This book changed my life, no joke.

I have heard rave reviews about this book and the accompanied book ... both for Quantitative and Qualitative analyses. I suppose these are ok if you are absolutely at a dead-end on how to visually express your data but most of the time you can just read a manuscript in your field and see what others are doing...

Tufte is an academic. Extremely intellegent. Well studied. Well spoken. The message is good. Very thought provoking. Applicable. His four texts are very repetative. All four of his texts fall short for me in the modern age. The application of these concepts into current graphic communication is missed - websites, info graphics, apps, presentations (do not do a power point!).

My sister requested this book for Christmas. I was thrilled to receive the package very quickly after I ordered the book. It was in excellent condition, better than I had expected. Overall very satisfied with this purchase

My sister requested this book for Christmas. I was thrilled to receive the package very quickly after I ordered the book. It was in excellent condition, better than I had expected. Overall very satisfied with this purchase

The review of good and bad designs is useful. But Tufte's "theory" of good design seems to boil down to one thing only: use less ink. Using this single-minded technique, he "improves" several designs, which look worse to me, not better. Similarly with his new design ideas, most of which didn't look like improvements over existing ideas.

The book itself has useful information in it, somewhat relatable to the work place, dependadnt on what you do. The writing style is hard to follow and reads like a 1980's professorial lecture. Seller shipped accordingly. Item rating: 5/10, shipper rating: 10/10.

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.

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.

Other reviewers have mentioned a few negatives. To me, these mostly boil down to short-on-substance problems. The author is a bit pompous -- which wouldn't matter that much if he had a lot to say. Alas, he does not. The author's major point is: eliminate "chart junk" (e.g. 3-D effect bars, etc). He is manically obsessive-compulsive about this point so that he takes it to extremes -- get this: computing "data ink" to "junk ink" ratios he even eliminates the axis line (to increase the ratio). Giving the book a second chance now over a year later, I found that the "eliminate chartjunk" is not the sole point the author makes -- but 80% of the book is about that one point. During my "2nd chance" read of the book I did find a couple of substantive ideas: the white-grid run-thru of bars on bar charts, and the discussion of aspect ratios. (Plus the tics-at-data to give marginal disbn's of X and Y.) However, I still maintain, if you really want to learn new techniques and real-value PRINCIPLES get William Cleveland's two books "Elements of Graphing Data" and "Visualizing Data." Cleveland's book are enjoyable to read and filled with eminently useful ideas. I've used principles from Clevelend's book to great effect. I'd been graphing for decades, but with Cleveland's book I made a GIGUNDOUS jump in the quality of my graphical communication. Skip the low-on-substance, one-note Tufte and go for the full-of-substance, emminently useful Cleveland.

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.

In my opinion, Tufte is a not worth the excitement. I used to worship him until I took his seminar. He's good at recognizing other people's genius charts, but his philosophy is actually the antithesis of what most modern data visualization experts recommend. He believes in using visualization only when something is complex and is worth time examining and learning the visualization. As an example, he gives maps, which he says everyone understands. Except we've all spent years learning them. I don't want that in my presentations. I want them to get my point instantly.

When he says something is not complex, you should either write it in words or display it in a table. He quotes some famous CEO who has everyone read a 2 page document before each meeting. If your CEO asks for that, then more power to them, but if I went to MY CEO with pages full of words when all I needed was a quick headline and a chart, I'd be looking for a job. Please don't do this to your audiences. I have 15 years of marketing and data analytics experience, focused on data visualization and presentations and teach classes on this stuff. This is just awful advice. When I went to his class he spent 45 minutes talking about the elegant simplicity of ESPN box scores. Ironically, ESPN changed them to be visual less than 2 years later if that tells you anything. Don't waste your time.

Having already read a bit of Tufte’s work already [1], albeit out of order, reading this book is comfortable and pleasant, and it is striking to see how from the beginning of his career as a writer on information design that Tufte both honored the founders of his craft, including his mentor Tukey, and also struck out authoritatively in critiquing the graphical design of our contemporary age. Although this work is not written with the same sense of devastating wit as some of his other works, it is written in such a way that it demonstrates skillful graphical information design as a node between fields requiring a combination of art history and criticism, mathematics (particularly statistics and analytical geometry), and mastery of mechanical or graphic design for the technical art work. As an originally self-published book, a story which Tufte tells in his modest and self-effacing introduction, this work manages to combine many interests and also exemplars of poor and excellent design in an effective manner that integrates text, numbers, and graphics, admirably living up to its own principles discussed within the book. Despite the immense depth and richness of many of the graphics of this book, the book itself is not a graphical puzzle—it is very clear that Tufte is aiming at improved graphics that are data-driven and that convey a large amount of information efficiently and effectively, showing respect for the data and for the viewers of that data. This is an approach that serves well in many areas of communication.

In terms of its organization and structure, the book is divided into two roughly equal sections in terms of overall size with unequal divisions into chapters. The first part of the book, Graphical Practice, takes about 90 pages to examine three interrelated matters: graphical excellence, graphical integrity, and the sources of graphical integrity and sophistication. Here the author examines questions of aesthetic judgment and the fine balance between artistic skill and skill in grasping numbers and their relationships, as well as the moral importance of conveying information accurately and transparently so that it may be understood and acted on. The second part of the book takes about a hundred pages to provide a principle-based theory of data graphics, examining such areas as the reduction of non data-ink in graphics within reason and the redesign process of graphics to make them more effective and more efficient, the avoidance of chartjunk, grids, and ducks (which includes a humorous picture of a building actually shaped like a duck to make its point clear), the maximization of data-ink density within design by several means, using graphical elements that serve multiple functions to increase the information value of graphics within reason, the increasing of data density by smarter graphic design, including the use of small multiples, tables, and shrinking thin graphics to make them more dense, closing with an examination of aesthetics and technique as well as very short and principled discussion designing for the display of information.

As someone with a strong personal and professional interest in the intersecting concerns of this book—art history and criticism, the moral and technical aspects of communication, the creation and understanding of data presentation and graphics—this book is part of a growing collection of works that I view with a great deal of respect and pleasure. As this book seeks to encourage those in my profession to great data presentations that are rich in narrative value, in integrity and humility, and with a strong desire to be well-understood and to communicate effectively, it mirrors my own concerns in a variety of areas both personal and professional. This is a book that has deserved its wide respect and regard, as it can be appreciated on many levels, in the pleasure of its aesthetic beauty and occasional bits of humor (like the aforementioned picture of the duck building or its enjoyment of graphical puns), as an encouragement to morally upright data practices that support integrity and that show respect for one’s reading audience, and as a thoughtful work on art history and art criticism that is richly informative and instructive in sound graphical techniques as well. It is little wonder that these works are considered masterpieces in their fields—the honor is richly deserved.

To me, Tufte's series of books on data visualization seem like the explorations of somebody who is beginning a new branch of science. Tufte can be rather dogmatic in his judgments, ironically not backing up his dicta with sufficient evidence, but this is because there are so few people who understand that data visualization is a subject worthy of its own study. Despite the fact that billions of charts are made every year, few people have the subject matter expertise to produce information rich graphics.

For Tufte, data visualization is not about making charts which look pretty but is about reestablishing graphics as a means of conveying information. This can be done poorly or brilliantly depending on the skill of the maker. Since, as far as I know, Tufte was the first and most successful exponent of the art and science of data visualization these books are indispensable to those working in analytics, data science and academia.

While these books do not provide a dummy's guide to Powerpoint or Tableau they do provide principles and guidelines to follow for those who must work with these programs. If you are willing to look afresh at what makes a chart or graphic insightful rather than merely decorative, Tufte's books are the place to begin.

Easily the best book I have read all year -- certainly the most engrossing non-story work I have read in ages. Almost all of the chosen examples are astoundingly clear, and each chart's merits and failures and their contributions to the author's point are visible instantly. I highly recommend this book to anybody who needs to communicate through graphs, data, or charts.

Other reviews have complained about the attitude or ego with which the author speaks; I cannot deny that there is a "this is stupid" condescension at some points, but typically at those points I can't help but agree with the author that whatever he's pointing out really is poorly done. And the prose carries you very quickly and fluidly through the book, which is really needed lest the reader jump from one graph to the next trying to skip the explanations.

As for the argument that the author is showing the "One True Way," I really didn't get that. It's pretty clear that, while there are attempts to make objective some subjective points (e.g. data density, or data-ink ratio,) the author's opinion is that every rule should be tempered by how the result looks, and what the viewer's reaction to it is. Almost all the hard and fast "rules" end with the two words, "within reason." Tufte is taking the reader 80% of the way to the goal and then launching them forward independently, as though he were saying "... and the rest is art."

I really enjoyed the book, I learned a lot, and I think I have better tools to design presented material with from now on. Worth five stars to me.

Tufte's books are astonishingly wonderful. However, his one-day course is a horrendous waste of time and money. Since there's no apparent place for reviews of the course, I wanted to record my experience here in the hopes that it can keep a few people from wasting their money. I went to the course with high hopes, excited to learn about the power and potential and nuances of data visualization. The morning started off interestingly, a bit disjointed but on topic. And then it fell apart. His discussion of visualization turned into an incoherent rant about proprietary ownership of all content, followed by another long rant about fudging data in medical studies (with no apparent connection to visualization) interspersed with rambling, unrelated medical advice. The afternoon devolved rapidly into incoherence. It was the strangest thing I've ever seen -- I kept wondering if he was drunk, but he wasn't slurring. The organizational theme seemed to be "things I'm outraged about that either have a vague relationship to data or look gee-whiz cool." The Tufte workshop took 500 people's perfectly good afternoons and tossed them in the toilet. The Tufte industry has a good thing going, surfing on his reputation while preventing any collection of attendee reviews -- which would shut this thing down in about two weeks.

Edward Tufte is the god of graphics. He's created a set of world-class volumes showing how to present data, of which The VDQI (famous enough to have its own initials) is the first and probably best. This isn't a quick how-to book. This is a rich work to savor for years. And in fact, if you can I highly recommend going to a Tufte lecture in your area, it's worth every penny. It's a whole day, but he teaches a lot and you get four of his books last I checked.

As a work, I have no criticism of the VDQI, but it would be nice to have a 5 page summary of the design principles in all the books. I can summarize his philosophy by saying this:

1. Maximize the clarity of what you are presenting
2. Minimalism: present the data with as little ink as possible.
3. Display as much data as possible on each page to allow comparison (but not too much to be unclear).
4. Be honest and avoid chart junk and other tools that obscure the true meaning of the data
5. When possible, avoid references but embed the information directly at the point in the document (example, Sparklines which are tiny graphics embedded in the middle of text).

Edward Tufte's "Visual Display of Quantitative Information" is considered a classic. He passionately argues for useful graphing of quantitative information that truthfully portrays complex data. He rails against much of the "chart junk" that print media often uses that are flashy yet do not display the data accurately.
In this beautiful volume, he cites numerous examples to make his points. At times he is repetitive, driving home his main points forcefully. His ideas for good chart design are useful, but limited. Modern day users of Excel software will find general ideas here to use in their efforts. I hungered for more detail.

Good graphs:
' show the data
' induce viewer to think about substance, not method
' avoid distracting data
' Present many numbers in a small space
' Make large data sets coherent
' Encourage the eye to compare different data

"Graphic excellence is the efficient communication of complex quantitative ideas."

Graphical excellence:
' Complex ideas communicated with clarity, precision, efficiency
' Greatest number of ideas in shortest time with least ink, in the smallest space
' Nearly always multivariate
' Tells the truth about the data

Good graphs:
' Above all, show the data- don't waste ink
' Maximize the data to ink ratio
' Erase non-data ink

General ideas:
' Show data variation- not design variation! (Excel isn't capable of it anyway).
' In time series displays of money, deflated and standardized units are usually better than nominal units
' Don't use 3-D for 1-D data, even 2-D is suspect.
' Avoid "chart junk" which is optical illusions, hash lines, dots.
' Avoid grid lines - dark grid lines are chart junk!
' "Graphical excellence is often found in simplicity of design and complexity of data."

Pro:
+ Good, "intuitive" points about exaggerated and flawed graphical designs that lie and deceive
+ Rich with real, cited examples of poor graphics that have been published
+ Cites many other scientific works which adds credibility and advances the science of graphics
+ After reading, this book will help you spot the rampant abuses of data and related graphics... (see chapter 3, table 1)
+ Intriguing observation about Japanese propensity (love of) statistics
+ When provided, well-written end of chapter summaries - strongly consider reading them first
+ For me, concepts such as Lie Factor, Data-Ink Ratio, Chartjunk, Range-Frame, Data Density concepts seen first/only here

Con:
- Overuse of the crutch phrase, "within reason" which allows principles to be vague (why leave so much to "art"?)
- Please describe a principle succinctly first, then provide supporting evidence or follow-on points second
- I would like to see the same data set followed throughout the text instead of repeatedly switching graphics
- Please number every page, figure, and table, e.g. the first figure in chapter 3 could be expressed as "figure 3.1"
- Does not provide summaries for all chapters (they're good, please add them where missing!)
- Often oversized graphics, margins measured in inches, and redundant examples which violate many of Tufte's own rules!
- Some history of who used what first is ok I suppose, but doesn't really advance the science much, does it?
- Please try replacing absolutes (e.g. "almost never" for "never") as it just reads like stammering
- Beginning in chapter 5, principles/design criteria are added but its not immediately evident to me how these elements fit with the others

Neutral:
> Through no fault of the author, I don't believe many recommendations are compatible with popular software packages (e.g. MicroSoft Excel, Minitab)

Bottom line: Recommended, but only as a high-level, introductory text on the display of quantitative information. It might be useful also a companion to one of Tufte's interactive lectures so you don't have to take as many notes. I am, perhaps naively, hoping for follow-on works which explore more detail, exceptions, and items left simply as artistic license (although after 14 printings there are only 2 editions since its debut in 1983).

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.

According to Edward Tufte, the purpose of graphics is, "Not the complication of the simple; rather [...] the revelation of the complex." And his THE VISUAL DISPLAY OF QUANTITATIVE INFORMATION, first self-published nearly 30 years ago, is now a bible -- a sort of THE ELEMENTS OF STYLE applied to information graphics.

Tufte reviews how information can be presented (i.e. a minimal amount via a sentence; a moderate amount via a table; a huge amount via a graphic) and then turns his attention to graphics -- from their beginnings in cartography to how to achieve graphic excellence today.

He urges a multi-disciplinary approach, cautioning that, "Allowing artist-illustrators to control the design and content of statistical graphics is almost like allowing typographers to control the content, style, and editing of prose." He touches on psychology and cognition. He rails against using graphic design to deceive, and pulls numerous examples of misrepresentation from prominent media. He devotes a large part of the book to improving the effectiveness of graphs by urging the elimination of "chart junk" (e.g. moiré-effect cross-hatching) and numerous other sources of "non-data ink." In fact, a chapter wherein he strips away seemingly necessary text, frames, hatch marks, etc. (leaving little more than an ether vapor but in the process simplifying and clarifying the meaning) is revelatory.

So many books I've read recently have referenced Tufte, and I'm glad to have finally read him directly. Highly recommended.

The Visual Display of Quantitative Information is a rather dry title for what turns out to be a supremely interesting and innovative study of how graphics can explain quantitative information.
Tufte is the pre-eminent scholar of graphical representation and this book is a clear example of why. The book outlines Tufte's theories for better displaying data in graphical forms. According to Tufte's well-argued point of view, simpler is often better--good graphics are able to convey multiple levels of information with minimal ink. He rails against unnecessary "chartjunk" which merely takes up space without conveying any information and he is quick to note that "pretty" graphics are often the least informative. Tufte's theories for achieving graphical success are presented in a straightforward manner and are always highlighted by examples. Some of the most interesting sections of the book show how Tufte would transform an otherwise ordinary graphic into a more powerful one--these sections clearly illustrate Tufte's theories and enable the reader to learn from the mistakes of other designers.
Tufte's book is extremely well researched and he consistently uses graphics from various time periods to highlight the points of his argument and to illustrate the good and bad of graphic design. He writes quite passionately about his "favorite" graphic (Charles Minard's time series map of Napoleon's march into Russia) and is equally passionate about exposing the lack of data within bad graphics (he calls one "the worst graphic ever to find its way into print").
Tufte is a clear and compact writer and is very good at explaining complex ideas both in words and in graphical form. While the book sounds very academic, it is certainly accessible to the general reader. This is a must read for graphic designers and those who seek to present quantitative information successfully (e.g. scientists, statisticians, students, businesspeople, etc.). Tufte's ideas are simple and broad enough to translate into a wide range of graphical areas--readers will be able to conceptualize and present data much more effectively after reading this book. Readers will also have a much sharper eye when viewing other's graphics. In a time when computer programs have largely automated graph-making (usually with bad results), Tufte's book is a helpful guide to making graphs and charts as effective and informative as they can be.

Mr. Tufte recently gave a full day seminar on the concepts he expounds in his three books (he is working on a fourth), which I was able to attend. This, his first book, is really the foundation for understanding the principles he puts forth in the next two, and present a clear template on how to do the best possible job when presenting data visually. This book explains how to clearly and elegantly design data for presentation in order to maximize its efficiency. While there are several fields where this is directly applicable, web design, finance and any other area requiring significant quantiative analysis, it is difficult to envision any field which would not benefit from Mr. Tufte's very insightful and educational opinions.
This book is divided into two parts, a history and guide to "Graphical Practice" and a section describing the "Theory of Data Graphics." In the first, the author describes what makes for good visual data and outlines the history of the visual presentation of data. In the second part the author discusses many specific techniques for evaluating the efficiency of graphics and methods for ensuring that graphics are created in an intelligent and thoughtful manner. The whole of the book is full of wonderful historical examples of good and bad graphics. Every page has a graphic, and every graphic has been thoughtfully chosen and tells a wonderful story. If you were to purchase this book and merely look at the charts and figures it would be a worthwhile purchase, if you take the time to read the back up text the book truly is a masterpiece. The author does an exceptional job of clearly presenting his points at the conclusion of the chapters and provides a large number of well selected examples of his points.
Mr. Tufte's theories are clear, (1) charts are not just a way of livening up 'boring' data, (2) no chart can overcome poor content, (3) charts should contain as much relevant data as possible, and (4) charts should not be livenend up with 'chartjunk' just for the sake of displaying nifty graphics capabilities. This is an excellent book, which is well thought out and clearly illustrates the author's point - but given the subject matter, that is exactly what you should expect.

Edward Tufte is a prophet of the Information Age come to warn us that we must repent or be consigned to oblivion.
One of the great advances which has made the Information Age possible has been the development of easy-to-use graphing software to swiftly create charts which used to take skilled draftsmen days to produce.
Unfortunately, the commoditization and automation of this once-dear skill set has resulted in the proliferation of lies, damned lies, and lousy statistics.
Tufte, a Princeton professor and polymath with passionate interest in statistics, information design, and public policy, offers up a thorough diagnosis of what ails our data-rich, information poor society:
- Poor graphical integrity, where the visual proportions are out of synch with the data's proportions
- Chartjunk, unnecessary clutter which reduces the proportion of data-ink in a graphic
- Poor labeling, which robs data of context
- Low-density presentations, where complex and nuanced data are "dumbed down" for the sake of a fleeting aesthetic
Fear not---Dr. Tufte also provides the reader with a course of treatment (called "Graphical Excellence") thoroughly illuminated with real-world examples drawn throughout history.
This is one of those rare works which feeds both your right and left brain. It is a closely-argued work on behalf of clean and clear communications. It is also a wonderful art book depicting the evolution of an often-misunderstood art form.
Whether you're an engineer, a statistician, a businessman, or a teacher, this beautifully-designed book will help you become a more effective communicator.