Reddit Reddit reviews The Visual Display of Quantitative Information

We found 60 Reddit comments about The Visual Display of Quantitative Information. Here are the top ones, ranked by their Reddit score.

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The Visual Display of Quantitative Information
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60 Reddit comments about The Visual Display of Quantitative Information:

u/dangerscarf · 106 pointsr/dataisbeautiful

Welcome to dangerscarf's school of data visualization!


Although you could just wing it, knowing some of the why's and why not's of data visualization will help put your creations an inch or two above the rest.

I highly highly recommend picking up Edward Tufte's The Visual Display of Quantitative Information. After you read it you'll be able to make jokes about inside jokes about pie charts and be everyone's best friend. On a first read-through it might not make too much sense, but once you start working on projects light bulbs will start going off.


These days the major thing to learn in the world of data visualization is D3. It's a big hunk of JavaScript code that can help with everything from drawing maps to making graphs.

If you want to learn D3 (which you now should), the best place to start is Mike Bostock's Let's Make A Map. The end result is a pretty boring map of the UK, but it steps you through the hows and the whys of every single piece of code. When I first started with D3 I could have saved myself a lot of headaches by reading it closely.

Once you get your feet wet, [](How Selections Work) is great for clarifying some of the concepts behind how D3 deals with data display.

There's also a tutorials page on github, but the shortest and most efficient path to making cool visualizations is just plain copying. How to make great visualizations, in 3 steps:

  1. Visit
  2. Scroll around until you find a couple examples of the kind of visualization you want to make
  3. Copy the code, then hack away at it until it does want you want

    Since you've already got some coding background you might be all set. JavaScript can be an insane beast at times, but if you start simple and from existing code you should get the hang of it without too much work.

    A Brief Introduction To Coding For The Web

    OK, so maybe you do need to learn a little HTML/CSS/JavaScript first. But let me stress the little - it's easy to get bogged down in the details, and the skills you need to edit a visualization to do what you want aren't exactly the same as when learning JS from scratch.

    Fundamentals: HTML, CSS and Javascript. HTML is the information on a page, CSS is what makes it look nice. JavaScript it what makes it move around or be interactive. JS is the toughest, while HTML and CSS are easy (the basics, at least).

    Go ahead and learn HTML and CSS from Codacademy first. I disagree with the way that every single place on the Internet teaches this stuff, but so it goes.

    Check out these recommendations or these recommendations for JavaScript. If you don't feel like reading through them I'll just blindly point you toward Codecademy - JavaScript track, jQuery track.

    Sidenote: jQuery is a big hunk of JavaScript that makes common web programming tasks easier.

    But really, honestly, truly, you should read the links that aren't Codacademy.

    What do I make visualizations about?

    Any time you hear something interesting or read an interesting article or just think, "could I make a visualization out of this?"

    Other resources

    Pretend you're a developer for a news organization. Read up on Source, Data for Radicals, and a million other things I'm neglecting. If you want to get real crazy subscribe to the NICAR email list to see how people who do "computer-assisted reporting" think.

    But honestly, just do it! That singles map was the very very first visualization I ever made, and 5 years later it's still getting plenty of traffic. Throw a bunch of nonsense up on a site, submit it to reddit, and eventually you're bound to have something work out.

    Good luck!
u/seabass · 18 pointsr/datascience

The "bible" is "The Grammar of Graphics" by Leland Wilkinson. (link to amazon). The "gg" of ggplot2 stands for grammar of graphics.

Then we go into other books, resources that help with actually showing visualizations:

u/Jaguarkmd · 17 pointsr/nba

Pretty much everything about this graphic is terrible. The idea (comparing Bynum, Shaq and D12 by age) is great, but the execution makes it next to worthless.

Go check out Edward Tufte's The Visual Display of Quantitative Information if you want to know more about creating truly useful graphics.

For starters, this one contains a ton of useless information that only serves to confuse the viewer. Most distracting are the lightly shaded circles that don't refer to one of the three titled players, but the words "Lin" and the box of players NOT included in the graph are bad as well.

Second, it is nearly impossible to glance at a given circle and tell who that circle refers to. In fact, even after parsing it for awhile I can't tell who some of the circles refer to. It would have been better to make each player a different shape. The lines connecting the player-seasons together should be eliminated as well, as they do nothing to aid understanding of the graphic.

There is probably more in there that a more experienced graphic designer or statistician could point out, but suffice to say that this is a really bad graphic.

Edit: It also uses PER, which is a pretty pedestrian statistic for measuring basketball players' contributions. There is a lot you can read out there about why it is bad, but Wikipedia is always a good starting place.

u/Montaingebro · 10 pointsr/consulting
u/dc_woods · 9 pointsr/web_design

As a person with no education beyond high school, take all that I say with a grain of salt. I'm a pretty successful web designer and front-end developer, having working with four startups and done a year of freelancing.

It is not uncommon to hear industry peers criticize the education system as it pertains to web design because often the practices you learn are no longer the standard or relevant. I've heard of many stories where designers exit college (with no working experience, obviously) and have an incredibly difficult time finding work for the reasons I listed above.

Education has never been brought up at any of the companies I've worked or those that I've consulted with. I believe the reason for this is that I have a body of work to show along with whatever reputation I've garnered on Dribbble, say.

All this being said, it is entirely possible for you to develop your skills on your own, such as I did, and find work. I'm happy to list all the reading materials that I own that helped me get where I am now. I'll list what I remember but I'll have to go check when I can get a second:

Hardboiled Web Design
HTML5 for Web Designers
CSS3 for Web Designers
The Elements of Content Strategy
Responsive Web Design
Designing for Emotion
Design is a Job
Mobile First
The Visual Display of Quantitative Information
The Elements of Typographic Style
Thinking with Type
The Icon Handbook
Don't Make Me Think

If you invest your money in those and actually read them, you will be well on your way. Feel free to ping me. Good luck!

u/[deleted] · 8 pointsr/Design

This is just a sampling of my Amazon list, but:

u/humble_braggart · 6 pointsr/Database

I am currently working in a data warehousing and business intelligence role at a bank. Aside from the basics of ETL, SQL and OLAP, I would recommend having at least a basic understanding of financial accounting. I have also found it useful to read The Data Warehousing Toolkit as well as some other Kimball books.

For entry-level work, there are two recommendations of related skill that have served me quite well to get my foot in the door and show added value: Excel and reporting.

Every institution needs reports developed and it amazes me how rare it is to find well-built reports that clearly communicate their intended information. Being able to follow a few simple guidelines for effective layout and design go a long way. Edward Tufte wrote the definitive work regarding this, but I use Stephen Few's work for more up-to-date examples.

Excel has proven itself very useful for quick ad-hoc analysis and manipulations. Also, it is a mainstay application for most financial services companies and being fluent in functions, pivot charts and VBA is quite useful.

u/Sannish · 6 pointsr/GradSchool

The Visual Display of Quantitative Information by Edward Tufte is very good for anyone making figures at some point.

u/iamktothed · 6 pointsr/Design

An Essential Reading List For Designers


All books have been linked to Amazon for review and possible purchase. Remember to support the authors by purchasing their books. If there are any issues with this listing let me know via comments or pm.


u/ImaginarySpider · 5 pointsr/dataisbeautiful

I took a class in college based on The Visual Display of Quantatative Information that gave me such an appreciation for data and how it is displayed. This sub helped reignite that when I found it. Not all the post live up to it though.

u/rhinegold · 5 pointsr/LadiesofScience

I really like The Visual Display of Quantitative Information. One of Tufte's principles is that you always want to maximize the data-ink ratio to keep your figures clean, informative, and easy to read.

Personally I use MATLAB for figure generation and Adobe Illustrator to put panels together, annotate, and add transparency.

Another pro tip is that you always, always, always want to work with vector graphics. If a journal requires raster graphics make sure that conversion is literally the last thing you do to your figures.

u/johny5w · 5 pointsr/datascience

This might be what you are looking for, The Visual Display of Quantitative Information By Edward Tufte. The book is a little older, but the principles still stand, and it is considered a pretty seminal work for data visualization.

u/spacecadet689 · 5 pointsr/brasil

Aproveitando o assunto, todo mundo deveria ler um livro chamado The Visual Display of Quantitative Information quando o assunto é gráficos e estatísticas.

u/notboring · 4 pointsr/AskReddit

This book: The Visual Display of Quantitative Information by Edward Tufte.

A book about charts and graphs? Buddy, Tufte's made millions and millions of dollars with his books and lectures on this topic. This is an amazing book.

u/chrisvacc · 4 pointsr/datascience

Essential for Data Visualization: The Visual Display of Quantitative Information by Edward R. Tufte.

u/Trumpetjock · 4 pointsr/saintpaul

These charts are complete garbage.

The Y axis for the rental costs is half the scale of the one for ownership. The further obfuscate this by having a yearly income on the left and a monthly costs on the right. This is classic misrepresentation of data.

If you read what it actually shows, it has owner monthly income at $6.7k, with monthly costs at $1,500 (22.4% of income), compared to renter income of $2.5k and rents of $850 (35% of income).

The question then becomes whether we are comfortable with that 13% difference in income towards housing for owners vs renters. I would argue that not only should we be comfortable with it, we should be protecting that gap. The smaller that that gap becomes, the less attractive home ownership becomes. If we closed that gap entirely, there would be no economic incentive to buy a home other than pure preference, while renting brings significant additional freedoms of movement.

-edit: Anyone interested in this topic of data manipulation should pick up The Visual Display of Quantitative Data. I promise it is not nearly as dry as it sounds. It's an entertaining, highly informative, and beautifully illustrated book, and is a sacred text to data scientists.

u/schrodinger26 · 4 pointsr/Clemson

I'd recommend reading:



The graphs don't follow best practices and could use some work to more clearly communicate your goal.

Bar charts should not be center aligned like that, unless 0 on the x axis cuts directly through them (ie if they show positive and negative values simultaneously)

u/RadioRoscoe · 4 pointsr/Android

If you have never referenced the book, then I think that The Visual Display Of Quantitative Information would be right up your alley. Aside from the amazing content, the book is crafted with excellent material and makes a nice coffee table item.

u/the_number_2 · 3 pointsr/Design
u/Waiting_for_Merlot · 3 pointsr/gis

Cool. "Know your audience" is important to any map design, and you'll obviously know more about that than me. Like I said, these were just my first impressions.

I don't think the font size for the title is a huge problem.

This has the makings of a slick-looking map. I think the fact that your title text and legend/notes text is the same color as the warehouses is a bad idea. Try this: Close your eyes, then open them. In that first fraction of a second, where do your eyes go? For me, it certainly isn't the data. My eyes immediately drop the the lower left, where the legend and the (hugely over-sized) notes are. Then they jump up to the title. Then down to the compass rose. Only after that do they want to notice the data.

This is off topic, but I suggest you read Edward Tufte's books. This one is my favorite:

His books aren't really about map-making, but how to display and communicate with data. They really got me thinking, and I hope have made me better at making maps. I'm cheap, so I just got them from my local library.

u/WhackAMoleE · 3 pointsr/cscareerquestions

You don't need to specialize right now. Try to learn as much as you can about everything. Go wide and deep.

If you like automating things, tool development is good. QA automation, continuous integration tools, network configuration tools, etc. Lots of demand for that kind of work.

Data visualization is more cutting edge. Huge piles of data out there but humans can only absorb so much. Involves datamining, UI design.

Have you read this?

It's the classic in the field.

Tools development is kind of corporate and very nuts-and-bolts. Data visualization is cutting edge and will be huge in the future, as we try to grapple with all this data we're collecting.

Between the two I'd definitely go with data visualization. Cross-discipline between datamining and UI design. Interesting work.

u/black-tie · 3 pointsr/Design

On typography:

u/ThatOneWebGuy · 2 pointsr/design_critiques
u/tolos · 2 pointsr/IWantToLearn

Lots of great recommendations in this thread; I've added a few to my reading list. Here are my suggestions (copied from a previous thread):

u/matts2 · 2 pointsr/AskReddit

Lincoln at Gettysburg: The Words that Remade America, but Gary Wills. He completely changed my understanding of Lincoln, the Civil War, and America. If nothing else this short book shows you what it means to really read a text.

Visual Display of Quantitative Information by Edward Tufte. A dull title, an exciting book on how to use pictures to help you understand.

edit: fixed link

GGS might be on my list as well. But Selfish Gene gives you a distorted view of evolution. Dawkins is a hyperselectionists, he really can't seem to grasp that selection is only one of several forces involved in evolution.

u/fullup72 · 2 pointsr/Amd

> Personal opinion:
> If you haven't read this book:
> Then you probably shouldn't comment on this topic.

Classic elitist jerk "personal opinion". I will send you my address and you will get the privilege of shipping me a free copy of the book, so maybe one day I can be worthy of a discussion with you. Deal? No? Then please avoid these toxic comments, or save them for a face-to-face conversation so that the other person can punch you in the nose to bring you back to reality.

u/jessek · 2 pointsr/Frontend

Well, the most important books that I read when learning design were:

u/4thekill · 2 pointsr/BusinessIntelligence

Pretty much anything by Stephen Few. His 2nd edition of Information Dashboard Design is a great start. He's also done some great whitepaper type stuff as well. Google can help you find it.

Edward Tufte is pretty famous in the area as well. The Visual Display of Quantitative Information is a classic and an amazing book on representing data.

To me, telling a story with data is essential to calling something BI. Otherwise, it's just presenting a bunch of data in a different format than it started. You need to guide users to be able to diagnose issues and make decisions. Wireframing out a dashboard that starts big picture and have different paths users can follow to additional focused dashboards is key.

I just did a presentation on dashboard and visualization best practices at my company's conference for the 2nd time, and both times a lot of people told me how it changed their view of how they view analytics, or that they needed their team or boss to see the presentation because they are thinking about things the wrong way. Most of what I know and practice/preach today is a result of the above two gentlemen, plus things learned on the job along the way.

Visualize the data with the best chart type for the data. Not because they are pretty. Not because users want to see it a certain way. Pie charts suck, don't ever use them. I use this tweet in my presentation. Along with an example chart of when to use pie charts. Your dashboard might be KPIs and bar charts, and that's ok.

I could go on forever...

TLDR; Check out a couple of guys who are good at what they do. Tell a story with your data! Pie charts suck. Use the right visual. Feel free to PM me questions.

u/kkastner · 2 pointsr/MachineLearning

Edward Tufte as mentioned by micro_cam ( is a very well regarded source for visual display/information presentation.

My simple tips are:

Don't use straight red, blue green, etc. Play with more subdued colors. In Matplotlib this is color="steelblue" or color="darkred", and there are others as well.

If you look in the webdev community there are lots of charts of colors and the corresponding hex code. Playing a lot with blues, purples, and oranges at the moment but I have no real background other than I like the way they look.

Don't ever use the jet colormap (if you know enough to know when it is ok to violate this rule, you also understand why not to use jet in general ;) )

u/sillyrants · 2 pointsr/IWantToLearn

Get this (very old but very good) book: Visual Display of Quantitative Information by Tufte.


and maybe for inspiration.

Consider the coursera course: (it's very basic but a good overview)

Learn basic design concepts like visual hierarchy, white space, type, visual flow, colors, grid layouts, etc.

u/This-is-Peppermint · 2 pointsr/suggestmeabook

that's a lot of book money! Like other posters suggested, I'd want something that you're going to enjoy passing the time just looking at.

The Visual Display of Qualitative Information might sound dry and terrible but it's beautiful and so very interesting.

u/HoldingUpTheBar · 2 pointsr/pics

+1 for the first person to realize it's not about drinking. :)

If you're serious about infographics there's loads of good resources available. The Visual Display of Quantitative Information, 2nd edition is a very good read - rock solid theory and an essential for every designer. Once you've read that check out the follow up Envisioning Information for some excellent inspiration.

u/toastspork · 2 pointsr/talesfromtechsupport

Gonna leave this here.

u/hishtafel · 2 pointsr/Random_Acts_Of_Amazon

Looks like July 9, 2005. So close!

u/Nautilus_myth · 2 pointsr/videos

If anyone is interested in more great examples of The Visual Display of Quantitative Information, this is a classic book.
And here's a related webcomic

u/ford_chicago · 2 pointsr/BusinessIntelligence

I will second Kimball's books on data warehouse design in general.

My favorite book on data visualization, Visual Display of Quantitative Information, won't show you in three minutes how to build a great dashboard, but will certainly help you recognize good and bad options and think about the topic.

u/bill_cleveland_fan · 2 pointsr/statistics

It's an interesting book.

R's powerful
ggplot2 graphics system has a default output
style which follows many of these principles, and it looks good.

But it's not my favourite book in this area.
My favourite would be (both)
Bill Cleveland's books

  • The Elements of Graphing Data (1ed 1985, 2ed 1994)

  • Visualizing Data (1993)

    After seeing references to Cleveland in the
    R documentation
    (for example, the
    I read both the Cleveland books, and found them extremely interesting.

    There's a classic paper by Cleveland and McGill,
    "Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods"
    (you can download a PDF)
    which is also interesting. (And if you find that interesting, you would
    most likely enjoy the books mentioned above.)

    The Cleveland books are not widely famous like
    The Visual Display of Quantitative Information,
    but I found them more appealing in a way that's kind of
    hard to describe. But, very roughly

  • Cleveland feels more like a statistician trying to create
    visualisations which are efficiently and accurately perceived.

  • Tufte feels a little like a designer trying to create beautiful
    visualisations based on a kind of minimalist aesthetic. Or
    maybe like a philosopher trying to find the essence of a

    The conclusions of the two approaches are not necessarily
    incompatible. They would certainly agree on the
    undesirability of most of the ridiculous

    in the MS Excel plot menu. (So if Tufte stops people doing that, then the more people who read him, the better).

    But when there's tension between the two approaches then I'd
    choose the first (Cleveland).

    For example, the
    Tufte (minimalist) boxplots
    manage to represent the same information as a box plot, but with less ink.
    But they feel like they might not be as easy to read.
    (See also "W. A. Stock and J. T. Behrens. Box, line, and midgap plots: Effects of display characteristics on the accuracy and bias of estimates of whisker length. Journal of Educational Statistics, 16(1): 1–20, 1991"
    (abstract) )

u/mhink · 1 pointr/webdev

To be perfectly honest, the one book that's "gotten through" to me is The Visual Display of Quantitative Information by Edward Tufte. The book has a lot of examples of information design, both good and bad- and plenty of examples of taking a bad design and "refactoring" it so that it does a better job of conveying the information it contains.

u/FadedGenes · 1 pointr/dataisbeautiful

There is no single formula to creating a beautiful, persuasive data presentation. It's not a question of choosing the right tool; it's a question of choosing the right means of communicating. With innumerable options at your disposal, your most valuable tool is your brain and your experience presenting to audiences that are critical, skeptical or easily confused.

Here's where I would start:

u/hardleaningwork · 1 pointr/learnprogramming

It's design... It's art just like any other form, just on a different medium and mixed with technical limitations. You can read a lot of blogs ( is pretty great) but there is no "book" on web design. The Visual Display of Quantitative Information is a classic, but has nothing to do with actual web design.

u/sfurbo · 1 pointr/AskScienceDiscussion

As an off-beat addition to all the excellent suggestions already give, I will recommend The visual display of quantitative information by Edward R. Tufte. One of my pet peeves is that figures and graphs in science are often done really badly. The information could be presented clearer, and more information could be included without sacrificing clearness, if people just knew how to and took the time. This would make their publications much more accessible.

u/shmatt · 1 pointr/programming

yeah. a good gift- the books are beautifully printed. I would get the first one so to get the best understanding of his philiosophies. Anyone who created the term "chart junk" is OK in my book.

u/mobastar · 1 pointr/visualization

I've read and some bad reviews of Tufte, basically that his style isn't for everyone. I currently report a lot in Excel, thus two of the choices lean towards Excel use. For Tufte, do you recommend The Visual Display of Quantitative Information as the ideal beginner book? Not thrilled about the $40 price tag, but if it's worth it I'll happily pull the trigger.

u/datadreamer · 1 pointr/dataisbeautiful

Or you can just read his PhD thesis, Computational Information Design, which covers pretty much all of the same conceptual topics but doesn't go into the technical aspects of project development as much. Other essential reading would be Semiology of Graphics by Jacques Bertin, The Visual Display of Quantitative Information by Edward Tufte, and Visual Complexity by Manuel Lima.

u/yasth · 1 pointr/jobs

For one thing in a lot of places database administration is 75% reporting and analysis, 20% ETL/Integration and 5% Server admin. So no one will be too surprised should a database admin want to become a pure play data analyst.

That said I would A) get a GED (mostly because it will help in B) B) look at wgu or something like it for a degree in databases. You really can't beat hard credentials, and they aren't that expensive.

I'd also consider reading:

  • Visual Display of Quantitative Information ... highly recommended for anyone who has to present information

  • The first few chapters and the last of The Flaw of averages which is over long, but has some good stuff, and great analogies which you'll need to explain things later

  • A deep cover book on your chosen DB's sql

  • A NOSQL database book

    That should get you started.
u/ImInterested · 1 pointr/Entrepreneur

I have always heard good things about any of Tufte's books

You can also search books by data visualization for more options

u/bliker · 1 pointr/Python

I am just going to pick out on some points.

> This should be left up to the user. What looks good is subjective to begin with

This is not true. There are many acclaimed books about topic of information design (The Visual Display of Quantitative Information by Edward Tufte for example) that set up many rules about quality information design that matplotlib does not follow. Majority of users tend to not fiddle with setting, as they do not have time for it. Sane defaults go a long way.

> I’d rather you didn't fork!!! The project as it is could use more help. Have you talked to any of the current developers about this.

I totally agree with you, my plan is to develop in parallel and push changes back into iPython. I think significant change like this needs more breathing space.

u/miggyb · 1 pointr/dataisbeautiful

Sorry, but that image really hits a nerve. Don't take it personally, it might very well be a great idea, but the execution is jarring for us data-as-art people.

  1. You should almost never use circles to represent data unless you have a very, very good reason to. It's harder to visually compare angles in a circle as opposed to height in a bar chart. And if you put the percentage points next to the area, you might as well just show the data in table format.

  2. Neither the Z or the... theta(?) axes make any sense. Is time going outward from the center of the cup? Is it going inward to the end of the day? Is it over the course of a 3 month period? Do all the different categories share the same Z axis? Is the "Time spent on Spacebook" in minutes, hours, or fortnights?

  3. You should almost never use 3D effects unless you have to. Don't feel too bad for this one since it's commonly ignored, but in this case it's very relevant. You could put a series of circles parallel to the coffee cup saying "time" and it would help clear up whether time was increasing outward or inward, but there's no way to fix the Z axis. If you had a series of circles going upwards in a cylinder, it would still be impossible to match any line with any amount.

    The picture you have behind the data is a really nice picture, and I could see how you wanted to use it to tell a story about your day. However, the way you're forcing the data into the picture is completely visually destroying that it.

    Further reading: The Visual Display of Quantitative Information by Edward Tufte. It's a thick book but it's mostly pictures :)

    Again, don't take it too personally, but I figured a harsh answer was better than no answer.
u/hagemajr · 1 pointr/AskReddit

Awesome! I kind of fell into the job. I was initially hired as a web developer, and didn't even know what BI was, and then got recruited by one of the BI managers and fell in love. To me, it is one of the few places in IT where what you create will directly impact the choices a business will make.

Most of what I do is ETL work (taking data from multiple systems, and loading them into a single warehouse), with a few cubes (multidimensional data analaysis) and SSRS report models (logical data model built on top of a relational data store used for ad hoc report creation). I also do a bit of report design, and lots of InfoPath 2010 + SharePoint 2010 custom development.

We use the entire Microsoft BI stack here, so SQL Server Integration (SSIS), Analysis (SSAS), and Reporting Services (SSRS). Microsoft is definitely up and coming in the BI world, but you might want to try to familiarize yourself with Oracle BI, Business Objects, or Cognos. Unfortunately, most of these tools are very expensive and not easy to get up and running. I would suggest you familiarize yourself with the concepts, and then you will be able to use any tool to apply them.

For data warehousing, check out the Kimball books:

Here and here and here

For reporting, get good with data visualizations, anything by Few or Tufte, like:

Here and here

For integration, check these out:

Here and here

Also, if you're interested in Microsoft BI (SSIS, SSAS, SSRS) check out this site. It has some awesome videos around SSAS that are easy to follow along with.

Also, check out the MSDN BI Blog:

Currently at work, but if you have more questions, feel free to shoot me a message!

u/oh-dear-me · 1 pointr/programming


Like a
3-d pyramid bar chart
(only have Libreoffice so, sorry, no 3-point perspective etc),
it might look cool, but it's not a particularly effective
way of understanding the data. (Tufte, etc)

The unzoomed view gives an idea of the top ten (or maybe 20) queries.
That would be clearer in a bar chart or dot plot with the categories
in descending order of frequency.

There is only one quantitative variable here - "counts" and the
categories seem to be ordered according to that variable, which is

This single quantitative variable seems to be mapped (roughly) onto a
spiral. Which means it is mapped onto 2 separate spatial variables -
angular and radial. The angular variable corresponds to the count
variable, so 2 categories that are next to each other in the angular
direction are closest in the number of counts. But which circles are
next to each other in the radial direction is kind of arbitrary - an
artifact of the spiral layout algorithm. So the "second dimension"
(radial) is not really meaningful. Zooming in shows an arbitrary
bunch of chunks of what is essentially one dimensional data.

As an exercise in using the various tools, it's fine.

But as a visualization it's more eye candy (it DOES look pretty - nice
layout and colour palette) but not so much a useful exploratory tool.

u/neel2004 · 1 pointr/AskReddit

The Visual Display of Quantitative Information by Edward Tufte is a beautiful textbook I used in an economics course in undergrad. It was also rated one of the 100 best books of the 20th century on

u/GERMAQ · 1 pointr/Eve

Grouping would have taken 2 more minutes. You could have just combined "before 5/15" into a single data group and the impact would have been made. I appreciate your work, it's interesting information but if you handed this to me at work, I'd never trust you doing any data analytics ever again.

I highly recommend this book for data presentation in theory and practice.

u/idiotswork · 0 pointsr/WTF

A funny, but confusing graphic. Before you make another: The Visual Display of Quantitative Information

u/admiralwaffles · 0 pointsr/funny

Okay, so you've clearly misunderstood what I said. Firstly, your article is thin, at best. If you want some good examples, go to the master. Secondly, my point was that these graphs are cropped to make them more dramatic for visual appeal by business users all the time because they convey what they're trying to get across, but do it in a more dramatic way. If you'd like to believe that it's just Fox News that does this because they're evil, then you need to watch more news. They all do it--MSNBC, CNN, hell, even the BBC. Shit, even Google.

Christ almighty, it's getting very summer in here.

u/BFBooger · 0 pointsr/Amd

which is why you would show the -/+ percentages on a graph instead of absolute values.

You could have two graphs:

one that has zero on the axis and raw values.

one that is a chart of +/- percentage relative to a baseline.

Otherwise its intentionally misleading.

Personal opinion:

If you haven't read this book:

Then you probably shouldn't comment on this topic.

u/aftersox · -1 pointsr/CrappyDesign

It's a poor representation of data. In pie charts you compare angles. Humans are poor at comparing the magnitudes of angles. Without the table, labels with the actual numbers, etc. it would be very difficult to compare the information.

For instance, it is difficult based just on the visualization if Instinct or Valor has more players. A bar, column, or dot plot will show things much better. Humans are far better at perceiving differences in length or position. That table on the right is necessary - that means the pie chart is useless.

If you are serious about designing visualizations of data, I suggest you read some books by Willilam Cleveland or Edward Tufte.

EDIT: Here is article I often share with people on this topic.