Jump to ratings and reviews
Rate this book

The Visual Display of Quantitative Information

Rate this book
The classic book on statistical graphics, charts, tables. Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays.
This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

197 pages, Hardcover

First published January 1, 1983

Loading interface...
Loading interface...

About the author

Edward R. Tufte

15 books633 followers
Edward Rolf Tufte (born 1942 in Kansas City, Missouri to Virginia and Edward E. Tufte), a professor emeritus of statistics, graphic design, and political economy at Yale University has been described by The New York Times as "the Leonardo da Vinci of Data". He is an expert in the presentation of informational graphics such as charts and diagrams, and is a fellow of the American Statistical Association. Tufte has held fellowships from the Guggenheim Foundation and the Center for Advanced Studies in Behavioral Sciences.

Tufte currently resides in Cheshire, Connecticut. He periodically travels around the United States to offer one-day workshops on data presentation and information graphics.

Ratings & Reviews

What do you think?
Rate this book

Friends & Following

Create a free account to discover what your friends think of this book!

Community Reviews

5 stars
4,458 (55%)
4 stars
2,548 (31%)
3 stars
857 (10%)
2 stars
154 (1%)
1 star
38 (<1%)
Displaying 1 - 30 of 570 reviews
Profile Image for Zanna.
676 reviews941 followers
January 10, 2019
When I started secondary school I was mildly apprehensive about 'physics', an unfamiliar word that elicited an actual shudder from my mother. Fortunately, my elderly teacher had an infectious affection for his subject. I remember that he noticed me examining the monthly night-sky chart pinned to the classroom door, and thereafter would print off an extra copy specially and wordlessly hand it to me if he saw me in the corridor (never in class, not wishing to embarrass me*) Our first lessons tried to tell us what the subject was all about, and a poetic but confusing article telling me that it was about, among other things, not being able to push a blade of grass into the trunk of an oak tree demonstrated clearly that some things are better learned by seeing and doing than by reading.

*he needn't have worried: evidence of my geekiness was not in short supply.

One of our early experiments was The One With The Pendulum (turns out that in the UK this is an A-level practical! I guess in those days secondary school wasn't all OMG exam in 5 years PANIC), and our homework was to write it up. When I had finished it, I must have shown my Dad, as he asked why there was no graph. "We weren't told to draw a graph" I replied. "But graphs are wonderful," he said. "Let's draw one anyway." and he showed me how. Our graph, which is probably still in my parents' attic somewhere, plotted length of pendulum against swing time, which unfortunately yields an exponential curve that's hard to work with. You can (when you do the experiment at A-level) linearise the graph's equation by plotting the square of the time period, and then the gradient tells us 'little g', the strength of the Earth's gravitational field. Neat, eh?

I have taught science for a few years now and I could not have failed to notice that many kids hate graphs and graph drawing. It is unquestionably hard work and needs an understanding of numbers and design logic. I'm lucky that I got an undeserved merit for drawing an unsolicited graph in my first month of high school, because since that day I've been totally freaky for a nice chart (these two pictures are from my own lab book, not the text). This review is dedicated to my Dad.

Tufte really loves data. This book has an informative, accurate, but kinda DRY title. I would have called it


uhhhh-uhhhh I've made a mistake. Tufte says thinking data is boring leads to bad, lying graphs. If your data is boring, why are you even presenting it? He is crisply derisive of the idea that data needs graphically sexing up to be understood. As Freire tells us


Tufte bemoans that graphs are designed and drawn by folks trained as artists, rather than folks trained in the relevant mathematics. "Graphical competence demands three quite different skills: the substantive, statistical and artistic... 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". Don't decorate the data, REVEAL IT.

Bad graphics also lack integrity. Intead of SHOWING THE DATA, they distort it, usually for some political end. There are LOTS of examples

And here is a modern example I couldn't resist adding XD

However, the concern with graphical integrity has often not helped. It tends to encourage the general dislike of graphs and the tendency for publications to dumb them down. Tufte points out that while graphical sophistication is usually low in news publications, journals and text books, the text sophistication is high, sometimes requiring expert knowledge!

Many data sets are better presented in a well-organised table than in a drawing. Tufte follows this principle in presenting data on graphical sophistication and data density, and in showing his commissioned designs. "One super table is far better than a hundred little bar charts"

Oh and for the love of all that is good, follow da Vinci and put the damn chart next to the text, or better nested cosily inside. None of this 'see fig. 2'

Tufte radically redesigns the histogram and the scatter plot to remove distractions and non-data ink, moving towards clarity, data density and design grace. I won't spoil. As for the pie, keep it in the kitchen and put pumpkin in it: 'pie charts should never be used'

There is plenty of graph-porn for us chart junkies (as opposed to chart-junk, which is definitely out). Tufte's favourite is Charles Joseph Minard's extremely famous infographic of Napoleon's army attempting to invade Russia in 1812-1813. He loves it so much it's reprinted four times...

But there are all sorts of lovely maps and charts for your graphical delectation.

Debunking the junk is what Ed is here for and the pleasure of the text is in the ARID humour he deploys and the way he trusts the reader to be a fellow smarty-pants. In more of a folks-are-smart way, not an elitist you-and-me-are-smart way. I was laughing. When a quoted designer says he's all about 'conveying the essential spirit of the data'. Tufte has got me primed. Fool NO! Show me the DATA , not its 'essence' and not its 'spirit'

If you work with data, if you draw graphics, if you look at graphics, if you're interested in politics, economics, geography or science, if you like maths, art, design, truth, beauty, love…

read this.
Profile Image for Lily.
289 reviews49 followers
August 18, 2015
2.5 stars. I read this book because 1) as a scientist, I care a lot about visualizing information in ways that are both meaningful and attractive, and 2) this book is hailed as a classic and cited by many when discussing what constitutes a good graphic. After eying it on many coffee tables and office bookshelves, I finally decided to pick it up from the library. I'm glad that I didn't buy it.

There are some positives: a few inspiring examples of creative, precise designs that tell a story and reveal insights about the data. Some of the negative examples (graphs that exaggerate or obscure the data, or that are heavy-handed and ugly) are also useful to think about, and are occasionally very funny. I also liked how it touched on the history and evolution of different types of graphs.

However, a major flaw is the lack of thought that was put into the writing. Many of the axioms that Tufte proposes for graphics could equally well apply to writing. For example, don't patronize your audience, and don't waste ink on non-information. Tufte unfortunately goes against both these principles with his disdainful, verbose tone. A great deal of verbiage and jargon could be stripped away to yield a text with much higher information density (to use his own term). The advice presented is reasonable, but much of it is just common sense for anyone who's paid a little attention to elementary math/statistics, or who simply takes the time to look at graphs and think about how they could be improved.

He also contradicts his own advice about providing adequate explanation for plots by offering zero explanation for several plots that are nearly inscrutable, beyond saying "this is great" or "this is silly". His attitude towards artists is especially belittling - I was hoping for a more thoughtful take on the balance between beauty and practicality in graphic design. All in all, I think this the book has some smart points and good images, but not quite enough to warrant its position on a pedestal.
Profile Image for Kelly H. (Maybedog).
2,393 reviews219 followers
April 25, 2009
Edward Tufte is brilliant. His books, including this one, are artwork disguised as a textbook. The purpose of all three is to explain both good and bad ways of explaining information but they are so much more than that. There is a rich history interwoven in the books' pages. The examples are so interesting that I found myself learning more than just how to convey information. For example, one of the best graphics for conveying information ever made is a chart/map tracking Napoleon Bonaparte's army's march across Europe which is so impressive it's difficult to describe. The graph includes information about army size, location and timeline in a very readable, straightforwd and yet still beautiful way.

I was fortunate enough to attend one of his seminars after I was already a fan (my work paid for it and I got to keep the books!) which delves into all of his texts. I highly recommend it because he synthesizes the information beautifully and succinctly and you get all of his books and publications in print. If you can't make the seminar (no, I do not get any kickbacks, promise) the books are rather complex but they are absolutely stunning and make fascinating reading.
Profile Image for Roger.
32 reviews4 followers
August 29, 2010
The book led was one of the most enlightening books that I've every read. I've always had a penchant for using numbers, images, and heuristics to explain, and began taking Edward Tufte's courses when the opportunity arose, starting in 1998. He held them in hotel ballrooms throughout the United States, and his followers attended with cult-like repetition, sometimes registering for the same course 6 times in one year.

Edward Tufte is one of the most elegant designers of information alive today, the book was the beginning of my devotion to his philosophy of the visual articulation of facts, figures, and abstract concepts. This book, as well as professor Tufte's academic publishing, have influenced the world around us in so many ways. From the eloquent graphical explanations in the New York Times, to the vibrant digital displays of political elections on Fox News, and the historical statistics of hurricanes put forth on Weather Channel - all of this traces its heritage back to Edward Tufte and his award winning books.

If you want to escape the two-dimensional hell of explanation that is the improper use of Powerpoint, this books and its two companions, provide safe passage to the promised land of clear, robust, graphical discourses of complex ideas.
Profile Image for Daniel Rekshan.
Author 10 books24 followers
May 26, 2011
People have told me to read this book for years and I've always been impressed by the strength of their recommendations.

However, on reading this book, I was initially underwhelmed. I felt like Tufte was just rehashing common sense about graphs. I read through it and found myself saying, 'yeah yeah, I get it.'

On reflection a week after finishing, I realized this book is genius. Tufte concisely and clearly articulates principles, which should be common sense, so well that they have appearance to be common sense.
Profile Image for Michael Finocchiaro.
Author 3 books5,480 followers
July 9, 2021
This was a wonderful, short book about the best ways to present quantitative information. If it sounds like a boring topic, compared to the Excel manuals it is a gripping read ;-) I thought his suggestions were excellent and it was quite a pleasure to read. I hope that my own powerpoints and Power BI reports will be positively influenced by this reading.
Profile Image for Michael Scott.
724 reviews131 followers
July 10, 2018
TODO full review:
i As it turns out, I've read this book from start to finish three times already. Time to give some time to paying back, with a decent review.
+++ Overall, this is an excellent book. My acts speak for themselves: I return periodically to this extraordinary book, seemingly, every few years, to learn and be amused again by its material. It has everything I am looking for about in the design of information visualizations: the historical perspective, insight into how a designer works for this field, principles that are explained and enforced, a creative element (sparklines! small multiples!!), great book design, and even idiosyncratic writing.
+ Edward R. Tufte's [The Visual Display of Quantitative Information] has not aged a bit in its second edition (nearly two decades after its inception and first print). It remains the gold standard in the field: understand the problem, survey existing instances of the problem, address the problem, discuss where to go next.
+ The wealth of historical sources is nicely calibrated, with a predilection for old English time series (associated with good early practice), and for modern Japanese statistics and train schedules (associated with the highest performance). The former is easy to explain: with the age of mechanization, and its penchant for standardization (new) and tax collection (quite old), Ol'Britain has gone to extremes to perfect the communication of qualitative and especially quantitative information. Although, in the end, it's mostly William Playfair (and Joseph Priestley, and Encyclopedia Britannica), the subtext is that there is a wealth of good graphing in the British Empire's history. The coverage of Japanese material seems odd, past the moment when the reader encounters the explanation of the ubiquitous presence of statistical material in the Japanese daily life, and until Edward R. Tufte's analysis of the statistical (visual) content in tens of newspapers and magazines across the world. As it turns out, in the late-1970s and early 1980s the (now) reputable New York Time, Times, and Washington Post were mere doodlers, waddling in relatively simple graphics and even simpler statistics when the Japanese material was already sophisticated and catering to a mature audience.
++/- The principles of good design are sound, simple, and few. With today's eye, they seem not so much good as associated with good practice for trying them out. The only caveat: there is no room for artsy presentations of data in Edward R. Tufte's world; it's minimalism and that should be it, carry on, thank you.
+ The book is deep, so the text is actually both difficult and required reading. This goes in contrast to the approach of many other books in the field, in particular, the series of introductory material from Stephen Few. (I found a good balance between finding new interesting material, and summarizing the principles and good practice, in Nathan Yau's Visualize This: The Flowingdata Guide to Design, Visualization, and Statistics and especially Data Points: Visualization That Means Something; but these books do not propose new types of information visualizations. I found a much deeper treatment of the historical material, with good taxonomical features and analysis, in Manuel Lima's
The Book of Trees: Visualizing Branches of Knowledge
and somewhat also in The Book of Circles: Visualizing Spheres of Knowledge.)
+ The innovative graphs, sparklines and (perhaps not invented here!) small multiples, are good tools. Sparklines are condensed high-resolution, high-frequency graphs amenable to depicting seemingly random processes over short and long periods of time. Small multiples are repetitions of a main visualization theme in a constrained space, so that the differences between repetitions convey the maximal surprise and thus capture the most the viewer's attention.
- Perhaps the only negative aspect is the presence and frequency of disparaging remarks. To Edward R. Tufte, the world is made of professionals adhering to his rules, or to makers of ugly duck-buildings.
85 reviews24 followers
January 19, 2008
This is a book about graphs.

How, you ask, could anyone write a book about graphs, let alone read one? Surely you've never found the sex appeal of a bar chart, the seductiveness of a scatterplot. Well my friend, you simply have never realized the power of a well-designed graph.

Tufte took on the challenge of making visual information interesting decades ago, and it's still considered one of the top 100 books of the 20th century. He shows examples of what the best displays and worst displays are in the first part of the book. In the second, he breaks down graphs piece by piece as the reader learns how to construct a useful and informative graph, chart, table, or whathaveyou.

The best graphs, etc., aren't flashy. You don't need any fancy computers to make them-in fact, Tufte particularly disdains computer programs for making everything busy and excessive. As is true of most things in life, the idea behind a graph is far more important and interesting than how it looks. A good display conveys that information almost instinctively and makes relationships clear. A poor display hides non-ideas behind graphics and labels. A terrible display actually distorts information; and to Tufte, these are inexcusable lies.

Even though the likelihood of me making a chart in the near future is slim, I was surprised by how much thought it takes to develop a good display. I also think it made me a better display reader-something that comes in handy when reading the paper or watching the Colbet Report. Above all, this book reinforces the primary rule of communication: start with a good idea, and edit it down until only what's necessary remains.
Profile Image for Jamie Smith.
479 reviews69 followers
May 31, 2021
Although originally published in 1983, when professional graphics artists prepared most of the charts and graphs used in presentations and official publications, this book remains useful for anyone who wishes to convey information clearly and concisely.

I can remember a job early in my career when all presentations had to be approved by two levels of management, then submitted to the graphics shop at least a week before they were to be used, and what came back was an inter-office envelope full of transparencies to be shown on an overhead projector. We have come a long way since then, but powerful graphics software has not necessarily improved our ability to get the message across in an understandable and informative way.

Tufte starts with some history of the statistical graph. It took a long time for people to make the conceptual leap from a quantity to an abstract visual representation of that quantity as a line or a bar positioned between several axes. The first charts were derived from maps, but maps had existed for five thousand years before charts and graphs appeared in the 1700s.

By the 20th century newspapers, magazines, and business and government publications all included graphics, but they were often done ineptly, because they were created by artists, not the people who understood the data. “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.” (p. 53) The book has many egregiously bad examples, some of which appeared to be deliberately deceptive (such as hiding a business loss by making the y-axis start below zero), and some just incompetently done, apparently by graphics artists who wanted to make a pretty picture without the least understanding of what the data meant. “Inept graphics also flourish because 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.” (p. 79)

The book’s value comes from the fact that Tufte has a number of specific recommendations for how to present data, and he cites good examples as well as bad. The defining graphic in the book is Charles Joseph Minard’s 1861 graph showing the fate of Napoleon’s army in Russia. It is a powerful image, telling the dramatic story of an army withering away on the march to and from Moscow. It manages to plot multiple variables on a two-dimensional page: the size of the army, its location in Russia, the direction of the army’s movement, dates of specific events, and temperatures along the route of retreat. Once seen, the graph is unforgettable.

There is also another brilliant example, a graph by E.J. Marey showing train schedules from Paris to Lyon in the 1880s. At first it looks like a jumble of broken diagonal lines, but then it resolves itself. The slope of the line indicates the speed of the train, the horizontal breaks show where the train is stopped at a station, the x-axis shows the time of the trip (at start, finish, and points along the way), and the y-axis the towns the train passes through. A great deal of information is packed into a simple, easy to read image. The train schedules put out by Amtrak today are far less intuitive and informative.

Tufte’s recommendations boil down one word: simplify. He coined the word “chartjunk,” and recommends paring everything down to its essentials. His fundamental precepts are:

Five principles in the theory of data graphics produce substantial changes in graphical design. The principles apply to many graphics and yield a series of design options through cycles of graphical revision and editing.

Above all else show the data.
Maximize the data-ink ratio.
Erase non-data-ink.
Erase redundant data-ink.
Revise and edit.
(p. 105)

Somewhere along the way in my career I came to internalize some of Tufte’s ideas without knowing I was doing so. Whenever I saw a presentation filled with clipart, with animated, dancing whatevers, with unnecessary three dimensional charts and distracting bright colors I concluded that the presenter was either an idiot or was actively trying to hide something the viewer wasn’t supposed to notice. Subsequent events usually proved me right.

If there is one thing that Tufte hates above all else it is the pie chart. “the only worse design than a pie chart is several of them, for then the viewer is asked to compare quantities located in spatial disarray both within and between pies.” (p.178) Since they only display a small number of data points anyway, you are better off making a simple number chart.

This book is worth reading, and will make you think about how to best present your information. Some of the examples he provides are old, including a couple that were certainly created on ancient dot-matrix printers, but his advice remains excellent. For those interested in his additional ideas about graphics presentation, he also wrote Envisioning Information (1990) and Visual Explanations: Images and Quantities, Evidence and Narrative (1997).
Profile Image for Bruce.
439 reviews72 followers
April 1, 2009
Well, 3 1/2 stars, really, but GoodReads won't permit that. Don't let the horrifically dull title fool you. Edward Tufte knows a thing or two about chart design, to say the least (he's built a second career on this obsession). Think this is dull stuff? Ha, and again I say ha. It's darn sexy. Don't believe me? Consider this consequence of the era of optimism or this version of Little Red Riding Hood or this nifty day-in-the-life or this graphic design shop which is such a brilliant specialist in the whimsical-cum-nostalgic info-graphic style that They Might Be Giants commissioned them to produce everything from the liner notes to Mink Car to the flash animations embedded on No! to their website TMBG.com.

And Tufte's book has its share of worthwhile "Aha!" moments as well. Take this snippet from p. 20, which follows six maps of the continental US depicting various types of cancer over a 19 year period by age, sex, and county. Tufte points out the clarity and key moments of interest in the various images (such as death "rates in areas where you have lived"), and then critiques: "The maps repay careful study. Notice how quickly and naturally our attention has been directed toward exploring the substantive content of the data rather than toward questions of methodology and technique. Nonetheless the maps do have their flaws. They wrongly equate the visual importance of each county with its geographic area rather than with the number of people living in the county (or the number of cancer deaths). Our visual impression of the data is entangled with the circumstance of geographic boundaries, shapes, and areas -- the chronic problem afflicting shaded-in-area designs of such 'blot maps' or 'patch maps.'" He goes on to further dissect the presentation and the foundational data in a way that I would never have dreamed of. Talk about your perfectionists... these map examples were drawn by him.

At any rate, this book is all about comprehensible, usable design, and Tufte even designed it for maximum impact. Its slim girth (a mere 190 pages) is chock-full of historic graphical errors and successes, but you can read the first 50 alone and get the idea. Given that, I'm a bit taken aback (and yet strangely curious) to have discovered that Tufte has managed to produce at least three more disparate volumes.

However, I've since learned that Tufte has some serious (and seriously earned) followers. Just last week, on the theory of in for a penny, in for a pound, I attended a program on improving data analytics, and was pulled aside at the end by one of the organizers who spotted my copy of The Visual Display.... "An important book," he sagely nodded. "You should have them all. But check out Steven Few's perceptualedge.com," he continued. "That's where the rubber really meets the road."

Okay, fine, leave me alone! I swear that I'll never look at another pie chart again, just don't make me give up my dependence on the color copier?
189 reviews
October 3, 2010
One-sentence summary:
The graphical analogue of Elements of Style: obvious (avoid junk!), useless, contradictory, and wrong.

Don't understand the hype about this book; it's super outdated (refers mainly to hand-drawn-ish charts; and considering most of use standard tools to create our visualizations, not sure how we're supposed to actually implement his suggestions), and a lot of the advice and "good" examples (Marey's train schedule? Come on!) are horrible (and even contradictory -- at one point he bemoans Chernoff faces and later exhibits them in an exemplar).

Ignore Part 1 (the first three chapters) entirely. Skim the rest.

Two principles:
1. Maximize data-ink ratio
2. Avoid chartjunk (e.g., moire, grids, and ducks)

Apply these two principles:
1. Redesign box plot (not sure if I agree, though the redesigned box plot does look more elegant)
2. Scatterplot -> range frame
3. Multifunctioning graphical elements (e.g., stem-and-leaf plot)
4. Graphics should tend to the horizontal
Profile Image for José.
195 reviews
February 13, 2021
I think it is safe to say that two monumental names of data-viz are bound to be recurrently recognised - the eye catching master of data pop-art David McCandless and the creator of beautifully simple and elegant data display Edward Tufte. Both of these data visualisers have some overlap - both are, after all, incredibly capable of transmitting complex data and information in striking displays - but it is Tufte's love of simplicity and worship of data that renders him a phenomenal graphical visualisation composer. In "The Visual Display of Quantitative Information" he sets out to present some of his more famous inventions for the graphical display of information, namely the range-frame and the dot-dash-plot. Before presenting these, he sets out several guidelines which are key when producing graphics for the visualisation of any form of data and that hold truthful to this day. A must-read for anyone looking to make their data visualisations clear, clean and impactful.
Profile Image for Max.
63 reviews10 followers
March 8, 2020
Light read, though sometimes the book judged me for having used histograms to display about 5 datapoints. He would even make me quantify how intensely I should‘ve just used a table by calculating his „waste of ink“ data-ink ratio.

„Above all else show the data.

The principle is the basis for a theory of data graphics“

The book is a nice collection of the good, the bad, and the really bad graphs. Among the bad are artsy graphics, that for example use the height of three-dimensional objects like oil barrels to display the oil price development. But with the height the volume changes disproportionally. Among the really bad are pie charts.

„A table is nearly always better than a dumb pie chart; the only worse design than a pie chart is several of them, for then the viewer is asked to compare quantitites located in spatial disarray both within and between pies. […] Given the low data-density and failure to order numbers along a visual dimension, pie charts should never be used.“

At points his data-ink-maximization philosophy hurt my aesthetics:


For some of his advices he even went through popular journals and magazines and counted how often they sinned. For example in the chapter on chartjunk you would learn that of all journals the New England Journal of Medicine would use „the undisciplined ambiguity“ of moiré vibration, giving rise to an „illusive, eye-straining quality that contaminates the entire graphic“.

Recommended for everyone that wants to be reminded that it‘s a good use of time to design clear graphics. I can very well imagine that there exists more concise online guides, though.
Profile Image for Brahm.
460 reviews50 followers
October 14, 2021
Interesting but I didn't love it.

This is a niche book with a cult following - my academic dad for instance, who studied graph theory at one point and cares deeply about data, loves this book. I see it's one of the top books on Goodreads for "design" in general.

I found it quite dated. First published in the early 80s, there are still tons of references to putting pencil and ruler to paper, and the efficiency of one style over another based on reducing the number of pencil-strokes of lab technicians/scientists. A big focus on moire effects as chart fills that we just don't use any more (because computers and graphics packages have improved a LOT since in 90s - although many Excel/PowerPoint templates still count as "chart junk").

I liked the exploration of some very elegant historical graphs, and an exploration of good chart and graph principles - I will take some lasting knowledge away.

But I was just not that excited/engaged. Since I bought a copy on Thriftbooks for cheap, I will put in the background for video calls where I want to look smart when talking to a graphic designer or academic.
Profile Image for Tiago Pereira.
64 reviews11 followers
August 29, 2018
Controverso em alguns momentos, exagerado às vezes, crítico e provocador, mas sempre muito inspirador. Não é um clássico da área à toa: realmente merece ser lido por quem se interessa por visualização da informação. Além disso, o livro é fisicamente lindo, um dos livros mais bem "designados" que já vi. E, para completar, li o livro como parte do "Data Vis Bookclub" (https://twitter.com/datavisclub), e a experiência de ler o livro e depois "discutir" por escrito, ao vivo, num notepad online com a participação de pessoas do mundo inteiro (o gif nesse tweet resume um pouco a experiência: https://twitter.com/lisacrost/status/...), foi muito legal.
(fui pegar o link e agora que vi que me "quotaram" no post! :) )
Profile Image for Sashko Valyus.
197 reviews9 followers
May 17, 2017
Книга про те як перетворювати цифри в красиві мінімалістичні графіки. Досить занудна не дивлячись не те, що контенту не багато. Основні тезиси:
- розберіться спочатку в тому, що маєте малювати
- не брешіть графіком, і не дайте виглядом неправильного розуміння
- при оцінці цін на часовій шкалі, варто враховувати рівень інфляції
- відсікайте все лишнє і надавате додаткової цінності
Profile Image for Coop.
40 reviews14 followers
September 23, 2018
Entertaining and illustrative. Tufte shows strong examples of both elegant and ghastly designs, taking several opportunities to improve the latter with surgical erasure. These examples form the basis for a set of now-canonized principles.

The only part I really disagreed with was the beginning of chapter 6, wherein the author proposes revising the box plot design by reducing it to a mere point floating between two lines, with only white space to represent the size of the interquartile range. It looks roughly like this:

- . -

The author argues that this is preferable because it eliminates all non-data ink. I would counter that the "box" aspect of the box plot is crucial to understanding the data at a glance, and that the white space makes interpretation harder on the reader. However, I'm pleased to say that this is the only deviation from sound design in the book.
Profile Image for Michael Burnam-Fink.
1,472 reviews220 followers
July 31, 2018
The Visual Display of Quantitative Information is an absolute classic on the creation and use of graphs. Done correctly, a good graph can make complex information instantly comprehensible, reveal relationships and patterns, and both delight and inform. Done poorly, a bad graph causes eyestrain, confusion, and the deliberate obfuscation of the truth. And in a world where graphs are ordinary, Tufte provides a quick history of how they came to be, and the cognitive leaps required.

Tufte rails against the sins of bad graphics: scaling and axes that lie about trends in the data; the use of unnecessary ink to convey redundant information; visual clutter and bad aesthetics. He advocates for a kind of elegant minimalism, conveying the most information with a few well-chosen lines of varying weights, and cleverly using edges and white space to mark boundaries, while supporting information with text. The advice is for a pre-computer graphics era (at least in my signed 1983 edition), but the aesthetics still hold, even if we aren't drawing graphs with a marker and straight-edge.

The problem is that Tufte turned out to be a voice crying in the wilderness. There are the majors flaws, like the use of flashy cluttered "infographics" that combine the worst features of text-heavy articles and data graphics. But then there is the minor things. I have at my fingertips about a half-dozen data visualizations packages, from Excel (boo!) to ggplot and bokeh. And not a single one, by default, does everything that Tufte says. They get close, but the defaults are not quite minimalist enough. And truly great graphs, like Minard's plot of Napoleon's invasion of Russia, with his army vanishing into the snows, still require an artist's touch.
Profile Image for Josh Friedlander.
716 reviews102 followers
March 16, 2019
Most of Tufte's critiques of ugly and dishonest data visualisation have been long internalised, in our age of 538 and "data journalism". But this {art/architecture/graphic design}-informed book is still an engaging read, despite occasional bursts of pomposity.
Profile Image for David Schwan.
1,003 reviews33 followers
March 12, 2022
Bought the five book set a while back. The author provides many examples of both poor and great display of quantitative information. Much of what is presented are concepts that I was previously aware of, but great that this was all presented in one place.
Profile Image for Sasha.
79 reviews1 follower
February 7, 2017
Never was a dude so salty about bad graphs and bad data. Humorous as well as clever.
January 19, 2013
Before going into the review itself, a comment on a slight oddity of the book (which will become important in the review): The copy I read is the 7th printing (March 2011) of the second edition (originally published in 2001; the first edition was published in 1982). The reason I bring this up is a discrepancy not mentioned anywhere in/on the book or on any website I could find. At least one chapter has been rewritten (or added) since the second edition was originally published. Chapter 8 contains examples and data from 2003 and 2004, as well as ending with a data point from 2009! Generally, one would consider the rewriting of a chapter (rather than the correction of typos and other errors) to be, if not a new edition, at least worthy of mentioning in the description of the book, but no such mention has been made. Without a copy of an earlier printing of the same edition, I cannot comment on whether other changes are present or absent; this was the only chapter where I noticed data or examples that post-date the original second edition printing.
This book by Edward Tufte is considered a classic in graphics design and its easy to see why. Filled with examples of both good and bad graphic design, he eloquently argues for rules of design that maximize information and "truth" to avoid misinformation and distraction. Truly a masterwork, it is not without flaws. He has a tendency toward hyperbole, declaring certain graphs to be the "worst ever made" or "best ever made". He accuses many graphical designers of deliberately lying to the consumer, when the reality in many (although certainly not all) cases is likely more a case of incompetence or ignorance. He states rules to follow with a certainty that are sometimes themselves not backed up with data, but rather simply reflect opinion.

And finally, some of his principles lack any real discussion or acknowledgement or context, something which stands out in particular with the recognition that most of the examples are rather dated. For example, he has a large discussion focused on the size of printed graphics, a discussion which completely ignores any context in which a graphic might be presented beyond the printed page. When the second edition was originally printed in 2001, most scientific presentations were still using overheads or physical slides; the widespread use of Powerpoint for presentations did not take off until a few years after the book was published. However, the chapter with this discussion is the one mentioned above that has clearly been updated since 2009! This enhances the dated feeling of some of the discussion, making one wonder if there is a bit of statistical and graphic Luddite influence to the writing.

I should say that he does mention Powerpoint and Excel at one point with clear disgust, and I am the first to agree that using either for designing *printed* graphics is a very poor choice. However, for for visual presentation in a talk or lecture, Powerpoint is better than many of its competitors. Unfortunately, some of his design discussion simply doesn't translate to non-printed publication, including presentations and graphics to be found on the web, which may have very different design considerations, not the least of which is the potential for consumer interactivity. (He has written additional books, some of which I plan on reading, and some of which may get into these issues, although I suspect not).

Despite all of these flaws, I truly believe the book is incredibly well done and its influence since it was originally published cannot be understated. Scattered throughout the book, often (although not always) recapped at the end of chapters, are "rules" of design that are so striking in their statement, I plan on collecting most of them onto a single piece of paper to hang on the wall by my desk as a visual reminder of what to do and think about when designing my own graphics going forward. That, more than anything else, illustrates my feelings toward this book.
Profile Image for Padraig.
37 reviews13 followers
October 3, 2014

It's good, I guess I’m knocking a star off because it focuses on paper-based graphs as opposed to computer ones (not really the fault of the book as it was first published in 1983).

The book is like the graph equivalent of Strunk & White’s The Elements of Style. Where Strunk says ‘Omit needless words.’, Tufte says ‘Omit needless ink.’ (I’m paraphrasing). Despite concerning itself with paper-based graphs, the concepts still apply, and if I took one lesson from the book, it’s to let the data shine through.

The production of the book is beautiful, it’s printed on vellum-like paper, and there are many example graphs, good and bad, going back to the 1700s. For an academic-style book, it’s also very readable.

There’s another message of the book, which is the under-utilisation of graphs. Graphs are capable of conveying a large amount of information very concisely, showing correlations between inputs, but how often do you see graphs in newspapers? Not nearly enough.
Profile Image for Michael Economy.
195 reviews244 followers
July 2, 2010
I'm imaging tufte writing up this rant in a basement with "we're not gonna take it" blaring in the background, every few paragraphs he mumbles something like "this will show them!" to himself.

Section two is pretty much the kind of five paragraph essay I was required to write in school. It's not very often someone makes an argument that hard.

Overall, this book is awesome, the book isn't 100% up to date, but the same complains with visualizations would still apply.

I'm all amped up to create lots of info graphics now.
Profile Image for Lindig.
713 reviews53 followers
November 11, 2011
I discovered Tufte when I was collecting movable books and this showed up in my bookstore with a pop-up pyramid in it. I found out later that he had self-published this title because no printer or publisher he approached wanted to do the pop-up and he was determined to have it.

It's a wonderful explication of the ways in which to analyze data and figure out how to present it in clean, efficient ways that slide the information into waiting minds.


And anybody who enjoys this book will like the site flowingdata.com
2 reviews
April 9, 2015
Interesting subject matter but incredibly pompous author.
Profile Image for Steve.
60 reviews3 followers
July 7, 2017
I went to a Tufte course and four of his publications were given out as part of the course fee. This is the first one he published on this subject, and the first I've read. Overall, if you've never made a statistical graphic, this covers some of the basics but it feels a bit dated as well. Read this book if you're looking for some history on the subject of plotting data, and plenty of opinions from the (well-respected) author.

I'm no stranger to making statistical graphics, it's a task that comes up when writing research publications, at work, and sometimes in my home projects. I was hoping to find some novel ways to think about plotting data, or at least some clean guidelines beyond those I already knew (e.g., use less ink, focus on data-ink, and emphasize unexpected or critical results). Since I had no formal training in the subject just exposure to many examples and some tips from random blog posts over the years I figured I had a lot to learn. With that perspective, the material in this book was a bit of a let down. I have to imagine that when it was written, Tufte dropped some wisdom on chart designers, but it has since percolated out into the mainstream, both embedded in tools and anecdotal advice given to plotters.

Tufte has a justifiably dim view on how computer drawing tools were used at the time to make charts, but I think he unrealistically kept the focus on manual production of plots in the second edition. As a point of reference, I have never published in a venue that allowed hand-drawn graphics to be included in a manuscript, and I think that's pretty much a universal standard these days. He also highlights a few plot designs that were pretty interesting (and unused) in 1980 when this first came out, but have not caught on at all in the fields that I know of in the 35 years since. Time to revisit their utility, maybe? One major omission in this book was the role of bias in chart preparation. Some data visualizations are pretty straight forward and have very little bias injected into the display (think scatterplots, with simple points that let you pull out their patterns using "visual analytics"). Now consider his proposed "rugplot", which is basically a series of 2D scatterplots arranged next to each other such that 1 dimension is shared between adjacent plots (just look at the pic near "Data Ink Minimization 135" in the link). There is a huge hidden bias here: the chart preparer can select any pair of the N dimensions to show next to each other. Different choices will lead to different stories being told, but with no way for the viewer to really consider alternative hypotheses than the one presented by the designer. But what if you wanted to pick other pairs of dimensions to look through? You can't. Since there are so many possible combinations to choose from, you would be right to doubt that the designer chose the "best" or even a "fair" representation of the data. This is one specific example of bias in data visualization, but given that this problem crops up in sufficiently complex multi-dimensional data source such as those championed by Tufte, I would have thought it would have been a topic of discussion in the text.

Well, this review got away from me a bit. The book is a fun thing to flip through, it's easy reading, and just feels great to hold. More non-fiction books should be like this! One of his updated books might be more fulfilling to a student of modern statistical graphics, but this one certainly frames the history and advances through the 1970s quite well, if that's what you're looking for.
Profile Image for Vishal Katariya.
168 reviews15 followers
February 16, 2019
What an experience. You may find it strange that I look upon this book almost reverentially, for it is merely an exposition of what constitutes good graphic design for data visualization. However, this is no ordinary exposition: Edward Tufte is unquestionably one of the masters at the forefront in this task, and he does a thorough job of describing some heuristics and "laws" for what make good graphs, plots, maps and so on. Given his mastery of the subject, I allowed for his sometimes brazen rules, which almost seem like commandments. Make all your charts wider than tall, for example. I don't think that's a rule that can be followed universally. Anyway, I suggest you read it if you can get access to it. There is much to learn in case you need to make graphs for your personal or professional use, and there's also the joy of witnessing someone unquestionably good at what they do expounding on their knowledge and expertise.
Displaying 1 - 30 of 570 reviews

Can't find what you're looking for?

Get help and learn more about the design.