The Visual Display of Quantitative Information
- Downloads：8126
- Type：Epub+TxT+PDF+Mobi
- Create Date：2021-03-31 11:20:54
- Update Date：2025-09-06
- Status：finish
- Author：Edward R. Tufte
- ISBN：0961392142
- Environment：PC/Android/iPhone/iPad/Kindle
- Download
Summary
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。
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。
Reviews
Igor
，
Beautifully bound and full of inspiring examples。 I enjoyed the author's theory of data graphics and plan to use elements of it in daily life。 I do recommend the book but I felt it dragged on towards the end and became overly oriented towards detail。 Beautifully bound and full of inspiring examples。 I enjoyed the author's theory of data graphics and plan to use elements of it in daily life。 I do recommend the book but I felt it dragged on towards the end and became overly oriented towards detail。 。。。more
Jack O'Hagan
，
Magical， beautiful book！
Ha Pham
，
Some pieces are useful， and some pieces are dated as the book was written for the time when charts are published on printed materials。 Nevertheless， a good starting point for people practicing data visualization。 Highly recommend https://www。goodreads。com/book/show/2。。。。 Some pieces are useful， and some pieces are dated as the book was written for the time when charts are published on printed materials。 Nevertheless， a good starting point for people practicing data visualization。 Highly recommend https://www。goodreads。com/book/show/2。。。。 。。。more
Amy
，
Even though I'm in Data Literacy for my profession， I'm just now getting around to reading this book。 While clearly foundational and incredibly influential， the book feels so dated - particularly since I started with much more recent books。 So many of the things in the book were specific to either the printed medium or functional constraints from the technology of the time。 How long will this book remain relevant？ Should this really be a starting point for people wanting to dip their toes in the Even though I'm in Data Literacy for my profession， I'm just now getting around to reading this book。 While clearly foundational and incredibly influential， the book feels so dated - particularly since I started with much more recent books。 So many of the things in the book were specific to either the printed medium or functional constraints from the technology of the time。 How long will this book remain relevant？ Should this really be a starting point for people wanting to dip their toes in the data visualization pool？ I actually only read it because book club at work picked it， though granted I did recommend it as a choice。 I'm glad that I read it for context， but there were just so many things that I disagreed with in principle throughout。Some points I found valuable and want to implement: - Small multiples for seeing trends and correlations - Reducing chart junk （though my definition of what constitutes junk is pretty different from Tufte's） - Avoiding data distortionSome points I disagreed with: - If you can understand a visual， then your audience can， too。 Nope。 Flies fully in the face of UX principles， and I have seen the opposite in action （with very astute audiences） waaay too many times。 I don't think this is a function of passing time and audiences getting dumber。 I think it was maybe just a lack of being able to put yourself in the audience's shoes effectively。 - Supertables are a good thing。 Gross。 No。 Not in the information overload age。 But maybe on the printed page in 1980。 - His suggestion for replacing bar charts with those hook visuals。 Nope。 Maybe on the printed page， but I find them so hard to read on our current digital screens。 Sometimes more color and pixels really does help improve legibility。Having read Tufte， I can see his influence in so many things today so I'm glad to have read this。 But I would never stop here。 And maybe not even start here。 My next goal is to find a more modern introductory approach to data visualization for the beginner so I can recommend that to people instead。 。。。more
Sumit Anand
，
This book is great for everyone in their career who has to visually show data and especially for management consultants。 I find this book a great source of inspiration， and others like it by the author。 It puts a bad practice tag on much of the conventional graphical templates and offers some more unorthodox alternatives， which on second thought actually seem more convincing。 The standard rules for optimizing the data/ink ratio， graphics， and text integration are all spot on and demonstrate how This book is great for everyone in their career who has to visually show data and especially for management consultants。 I find this book a great source of inspiration， and others like it by the author。 It puts a bad practice tag on much of the conventional graphical templates and offers some more unorthodox alternatives， which on second thought actually seem more convincing。 The standard rules for optimizing the data/ink ratio， graphics， and text integration are all spot on and demonstrate how statistics are far from dull when handled correctly。 There is a rich past woven into the pages of the books。 The explanations are so fascinating， that I found myself learning to communicate knowledge with ease。 For example， one of the best graphics ever made for transmitting information is a chart/map tracking the march of Napoleon Bonaparte's army across Europe， which is so amazing that it's hard to explain。 In a very readable， clear， and yet still beautiful way， the graph provides details about the army size， location， and timeline。 The advantages of improved presentation of details should not be underestimated。 As well as explaining the philosophy behind the techniques， the book is a short read and has great examples。 You won't be disappointed。 。。。more
Mark Evans
，
Tufte is always worth reading more than once。 And the good thing is， he follows his own advice， i。e。 minimising non-data ink applies to text， not just graphics。 This book can be read in just a few hours， I wish authors of other non-fiction books would follow suit and reduce their information down to only what's actually required。 Tufte is always worth reading more than once。 And the good thing is， he follows his own advice， i。e。 minimising non-data ink applies to text， not just graphics。 This book can be read in just a few hours， I wish authors of other non-fiction books would follow suit and reduce their information down to only what's actually required。 。。。more
José
，
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 visua 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。 。。。more
Barrysmyth
，
A classic and well worth a read by anyone with an interest in the data visualisation。 A large book but not a long book， it nonetheless provides an excellent accounting of some of the most important design principles that correlate with good visual design。 Balancing text and discussion with plentiful examples， including many classics of the genre， the pages of this book are filled with vintage charts and graphics， given it an almost coffee-table feel。 It offers as much pleasure as a book to dip i A classic and well worth a read by anyone with an interest in the data visualisation。 A large book but not a long book， it nonetheless provides an excellent accounting of some of the most important design principles that correlate with good visual design。 Balancing text and discussion with plentiful examples， including many classics of the genre， the pages of this book are filled with vintage charts and graphics， given it an almost coffee-table feel。 It offers as much pleasure as a book to dip in and out of as cover-to-cover read by students of its subject matter。 。。。more
M。
，
I attended Tufte's seminar about 10 years back。 It was fascinating。 His coverage of Minard's depiction of the Napoleanic Russian campaign and Tufte's supplement showing how visual displays in business and technological decision making scenarios （specifically， the relevant-knowedge-obstructing effects of PowerPoint） directly contributed to the U。S。's Challenger space shuttle disaster， are classics you should not miss。 No serious visual communicator or consumer should be without Tufte's trilogy。 I attended Tufte's seminar about 10 years back。 It was fascinating。 His coverage of Minard's depiction of the Napoleanic Russian campaign and Tufte's supplement showing how visual displays in business and technological decision making scenarios （specifically， the relevant-knowedge-obstructing effects of PowerPoint） directly contributed to the U。S。's Challenger space shuttle disaster， are classics you should not miss。 No serious visual communicator or consumer should be without Tufte's trilogy。 。。。more
Jordan Zagham
，
Solid general principles although fairly opinionated。
Shan Zhong
，
Definitely my favorite printed book
John Ayers
，
This book is a classic。 It presents many examples of effective and ineffective charts。 I found some but not all tips for making effective charts useful。 I found it to not be suitable as a textbook in the university science honors seminar I teach。 Even though the book was published in 1983 and is widely read， many of its design suggestions have not been universally adopted。 Yet its impact on the fields of statistics and data graphics has been large。
Ron
，
Unbelievably thought provoking & comprehensive presentation of methods & principles behind effective graphs & charts， from both the present & the past。 Highly recommended。
Bold Batdorj
，
lot of data visualization history
Hamish Seamus
，
An academic take on dataviz。 Not as practically helpful as other books， but good for historical background。Tuft devises quantitative measures for data visualisation quality: - data-to-ink ratio- lie factor- data densityTuft presents several tables of average measurements of these quantities for various publications。 I wonder what compelled him to do this。 It must have taken an ungodly amount of time and I can't imagine it being of much interest or utility to anyone。 An academic take on dataviz。 Not as practically helpful as other books， but good for historical background。Tuft devises quantitative measures for data visualisation quality: - data-to-ink ratio- lie factor- data densityTuft presents several tables of average measurements of these quantities for various publications。 I wonder what compelled him to do this。 It must have taken an ungodly amount of time and I can't imagine it being of much interest or utility to anyone。 。。。more
Dr
，
“Visual Display…” has my minimalist self at odds with my usability self。 I find Tufte’s approach quite compelling …though perhaps sometimes it goes a little （eensy weensy） too far。 As in， some of his pinnacle examples left me quite befuddled。 All in all though， another gorgeous production by Tufte with a plethora of rich examples to explore。 I wish I could frame every page and hang on it on the wall。As a series， The Visual Display of Quantitative Information， Envisioning Information and Visual E “Visual Display…” has my minimalist self at odds with my usability self。 I find Tufte’s approach quite compelling …though perhaps sometimes it goes a little （eensy weensy） too far。 As in， some of his pinnacle examples left me quite befuddled。 All in all though， another gorgeous production by Tufte with a plethora of rich examples to explore。 I wish I could frame every page and hang on it on the wall。As a series， The Visual Display of Quantitative Information， Envisioning Information and Visual Explanations largely cover the same material - some illustrations are even discussed in multiple books - and the differences are really a matter of the degree of emphasis。 If they weren't all so enchanting my advice would be to just pick one， but。。。 they're just THAT good。 。。。more
Alex Olteanu
，
Contentious， a bit obsolete， but brilliant！
Maaz Muhammad
，
Many modern data graphics and typography principles derive from Tufte （eg。 the R package ggplot contains many Tufte-style modifications， there are LaTeX packages that emulate the typographical design of Tufte’s books）， which is why I had to check it out。This book， Tufte’s first， is a fascinating compilation of data graphics from across the news media and scientific literature， coupled with Tufte’s commentary on why certain graphics are good and why others are bad。 From this commentary， he develo Many modern data graphics and typography principles derive from Tufte （eg。 the R package ggplot contains many Tufte-style modifications， there are LaTeX packages that emulate the typographical design of Tufte’s books）， which is why I had to check it out。This book， Tufte’s first， is a fascinating compilation of data graphics from across the news media and scientific literature， coupled with Tufte’s commentary on why certain graphics are good and why others are bad。 From this commentary， he develops certain ideals that data graphics should strive for: among them to minimize the non-essential “ink” and to maximize the information density。 I personally found his modifications quite beautiful （for example， his simplified bar chart， his slopegraph plot， sparklines， etc）。 I also thoroughly enjoyed examples he gave of classical graphics; he calls Minard’s graph of Napoleon’s invasion of Russia the best graphic ever made。As someone who often has to make data graphics for scientific papers， this is the type of book I would keep around as a reference。 。。。more
Hannah
，
What a treat。 Rating this highly because of the font of information I read that I felt compelled to share with others。 It reads a little like a history book， too， and I sometimes found myself laughing at the very decisive， opinionated tone that is then walked back again and again。 But overall this was pretty informative for someone who has not considered the topic in depth since I was forced to in math classes。
Ulysse
，
Transforming
Jack
，
There are lots of pictures， so this is a quick read （haha）。 On a serious note， this is not a very long read and I learned a lot from this book about creating charts and tables and such。 This was one of the most important books that I read in terms of preparing me for my early career as a researcher who sometimes displays quantitative information。
Mikko
，
It was good， still relevant in 2020。 The history lesson in the first half was interesting but you can skip it if you want to get straight to the good stuff。
Daniel Maurath
，
It's an interesting read in seeing how Tufte's perspective came to dominate most subsequent data visualization theory writing but shows its age。 While he makes excellent points on the graphics of the time， he makes at least an equal portion of questionable points。 He's a bit of a luddite when discussing the utility of computers and takes a dogmatic approach to minimalism and design that doesn't have room for differing opinions。 His opinions also do not hold in light of recent research into how h It's an interesting read in seeing how Tufte's perspective came to dominate most subsequent data visualization theory writing but shows its age。 While he makes excellent points on the graphics of the time， he makes at least an equal portion of questionable points。 He's a bit of a luddite when discussing the utility of computers and takes a dogmatic approach to minimalism and design that doesn't have room for differing opinions。 His opinions also do not hold in light of recent research into how humans interpret visual information。 For example， he often recommends tables over bar charts when it' now been shown that bar charts are processed faster and easier。 In the end， this is useful for inspiring one to minimize their design and to read the base principles of graph design in their most primal form。 。。。more
Mary
，
A work of art and informative all at once。
Antti Aalto
，
A beautiful work of art and a delight to read。
Danièle
，
I love data visualisation， so this was a joy of a book。 Lots of examples of great （and some not so great） presentations of data， with very thoughtful musings on how visualisations can be optimised。 I enjoyed part 2 of the book more than part 1 as it felt more structured。 Part 1 kind of launches straight into things without first setting the scene of what the book - or even the first chapter - is trying to do。 So at first， while enjoying the ride， I was a little bemused as to where we might be go I love data visualisation， so this was a joy of a book。 Lots of examples of great （and some not so great） presentations of data， with very thoughtful musings on how visualisations can be optimised。 I enjoyed part 2 of the book more than part 1 as it felt more structured。 Part 1 kind of launches straight into things without first setting the scene of what the book - or even the first chapter - is trying to do。 So at first， while enjoying the ride， I was a little bemused as to where we might be going。Part 2 is great though， with excellent chapters on where visualisations have a habit of going wrong and how this can be avoided， and how the information density of a visualisation can be maximised。 I loved Tufte's suggestions for alternatives to things like box plots， using about half the amount of ink to convey the same information。 Some great notes on making better use of graph axes to convey information too。 I'm definitely going to be bearing some of these ideas in mind; if only the engineers behind programs like Excel （I'm not that advanced in producing my own stuff yet！） had cottoned on！ 。。。more
Claudio Noguera
，
This book is a classic and thus very influential。 I found a flaw， though。 Probably because it's old， it talks about not using patterns to fill shapes because of the Moiré effect （agreed） but almost does not speak about color; color is very important these days。 And even though I agree that getting color right is difficult， I would like to see an addition to the book about "getting color right"。Besides that， there are a lot of good tips。 I really liked the data-to-ink ratio， which focuses on remo This book is a classic and thus very influential。 I found a flaw， though。 Probably because it's old， it talks about not using patterns to fill shapes because of the Moiré effect （agreed） but almost does not speak about color; color is very important these days。 And even though I agree that getting color right is difficult， I would like to see an addition to the book about "getting color right"。Besides that， there are a lot of good tips。 I really liked the data-to-ink ratio， which focuses on removing unnecessary decorations to graphics。Pie charts should be avoided， 3d charts as well。 I don't agree however with removing grids， they should be made very thin and almost white， but not removed。 They help to navigate the graphic。Some of the redesigns that he suggests I find non intuitive。Still， good for looking things up some times。 。。。more
Natalie
，
Riffyn rec from Jan
Ian
，
"A table is nearly always better than a dumb pie chart; the only worse design than a pie chart is several of them。。。"Well said。 "A table is nearly always better than a dumb pie chart; the only worse design than a pie chart is several of them。。。"Well said。 。。。more
Petros Cheretakis
，