Top products from r/dataisbeautiful

We found 59 product mentions on r/dataisbeautiful. We ranked the 462 resulting products by number of redditors who mentioned them. Here are the top 20.

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Top comments that mention products on r/dataisbeautiful:

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/SharpSightLabs · 1 pointr/dataisbeautiful

You're welcome. Great to hear that it's useful.

In many ways, I started the blog because I don't like most of the beginner resources. They either:

  1. Start with boring, low level, low ROI things like data types (even though most of the time, you'll be working with data frames anyway), or
  2. Tell you to start with the advanced stuff like machine learning, which is sort of like telling someone to start with calculus before doing algebra

    I definitely recommend starting with data visualization (out of the three "core skills" of data wrangling, data visualization, and machine learning).

    Conceptually, I think that Nathan Yao's Data Points is a solid introduction to data visualization. He covers just enough theory, but also lots of practical points concerning best practices, process, etc.

    Also, I think that two of the best data tools in R, hands down, are ggplot2 and dplyr. These two packages are the tools I wish I had years ago. In so many ways, they are perfect for the actual practice of analytics. (you can find the ggplot2 book here. I love the book, though keep in mind, it sometimes reads more like a textbook.)

    To be clear, I have lots of content (i.e., tutorials) that I'll be publishing over the next several months, so keep checking back for more.

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/davomyster · 3 pointsr/dataisbeautiful

I agree that these data aren't nearly as interesting as the old posts but you're comparing two different blogs. The old one with all of the detailed insight was written by one of the company founders, Christian Rudder, who wrote an entire book on the subject. You seem like you're really into the deep data analytics side of things and if you or anyone else who loved the old style of posts hasn't read it, I highly recommend it:

That blog was called OKTrends. It looks like it was last updated in 2014, the same year bought out OKCupid. Maybe Rudder didn't stick around to write blog posts anymore, I'm not sure, but this new blog we're all commenting about is called "The Deep End" so I suspect Rudder didn't write it.

Also, what makes any of you think that this simpler, less in-depth blog post has anything to do with a weakening of their matching algorithm in favor of more "folk wisdom and religion"? It's just a blog post.

u/CardboardSoyuz · 8 pointsr/dataisbeautiful

I can't offer you squat on job hunting, but I used to be a water lawyer here in California and if you want to read an insanely interesting book, that will always up your interest with anyone in any part of the water business in the US (or probably Canada, too), read Marc Reisner's Cadillac Desert, which all about the history of the aquafication of the West. Looks like you are Europe-based from your job applications, but it is a fascinating story well worth your time.

u/Pelusteriano · 1 pointr/dataisbeautiful

To understand the good practices of dataviz, you have to understand graphical design and statistics. Edward Tufte has some great books, like The Visual Display of Quantitative Information, that are great starters. Another great book is How to Lie with Statistics. Finally, an entry level book for statistics would be a nice addition, but only if you're interested in actually learning about statistics.

u/ReviewMeta · 2 pointsr/dataisbeautiful

> I like this. It matched up very closely to my experience.

Thanks! That's awesome!

> It passed the test.

Technically it didn't pass; it got a "warn". There's 3 levels - pass, warn, fail. 3.2 stars is a pretty low rating, and since the ReviewMeta adjusted score stays at a 3.2 stars, it means that Amazon already did a pretty decent job of weighing the reviews to account for the unnatural reviews.

It's not always black and white, and often times we'll see products that have several fakes, but then a lot of honest reviews, and it doesn't makes sense to "fail" the entire product, especially if the rating is already pretty low.

I've bumped up the priority of the "full report" on this item to see if that changes anything. The reports that are generated on-the-fly in about 60 seconds aren't quite as perfect as the ones that take a few hours, so check that report again in a few hours and we'll see some more details about the reviews.

u/jerb3ar · 1 pointr/dataisbeautiful

My first class in business school (a great school btw) was to read this book - the point was to be critical when looking at data/charts/etc and be mindful of this type of BS. Great book if this type of thing interests you.

u/wolf83 · 1 pointr/dataisbeautiful

I think your daughter might enjoy this book: The Day the Crayons Quit.

It's a favorite in our household.

u/zhamisen · 1 pointr/dataisbeautiful

Thanks for the recommendation :)
I'm reading now some pages of its amazon preview.

u/l0udpip3s · 1 pointr/dataisbeautiful

Try reading this book. I've heard it really helps, surprisingly. Especially if you actually want to quit.

u/newsdude477 · 5 pointsr/dataisbeautiful

To anyone considering quitting please take the time to read the Allen Carr book. As a pack a day smoker it really made me realize what I was doing and quitting was honestly simple.

u/RedditStoleMyTime · 7 pointsr/dataisbeautiful

I use San Fransisco Bay coffee from Amazon. They'd completely recyclable and about half the price or less compared to green mountain, especially if you use the subscribe and save option.

u/ejector_crab · 2 pointsr/dataisbeautiful

That was anything but a free market purchase of water rights. LA used massive amounts of political muscle to get those water rights. Cadillac Desert has a really detailed account of this, but wikipedia has a decent summary

Some pretty shady shit went down to build the LA Aqueduct.

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/ManSkirtDude101 · 2 pointsr/dataisbeautiful

He is most famous for his work on the philosophy of free will. I don't think he is that great of a philosopher but he defiantly is one.

u/Made_in_Murica · 1 pointr/dataisbeautiful

You can buy recyclable ones.

I just bought these for the first time since I'm sick of cleaning the reusable and refillable cups. They're cheap and better for the environment, but I bought the Keurig for convenience. So what I just bought is good. Supposedly only the foil lid isn't compassable.

u/edrmeow · 35 pointsr/dataisbeautiful

Dreamland is a great book that goes really in depth on the topic, but basically the current epidemic is the result of a sort of perfect storm of a bunch of causes. To name a few: the over prescription of narcotic painkillers in the late 90s, the decline of the working class (especially in the rust belt), and the growth of Heroin cartels in central america, particularly Mexico.

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/EldeederSFW · 2 pointsr/dataisbeautiful

If you enjoy those kind of conversations, this might be the best $5.25 you'll ever spend.

u/oyp · 1 pointr/dataisbeautiful

This is all based on an amazing non-fiction book by Steven Pinker, The Better Angels of Our Nature: Why Violence Has Declined. This book will change your mind.

u/scstraus · 1 pointr/dataisbeautiful

I like this. It matched up very closely to my experience. I put in a product from a company that had a lot of problems but that I knew worked very hard to impress me and get me to change my review. I know that they wouldn't put this much energy into trying to get me satisfied based off my negative review if they had fake ones there. It passed the test.

And another product which had tons of great reviews over a short time period but which in my experience broke the first day I had it. Extremely fragile if not used in the right way. I couldn't believe the reviews were so high.. And guess what.. Sure enough...

u/theviscioustruth · 66 pointsr/dataisbeautiful

Something every GIS professional should read, and this is a shining example of techniques used, like the ramp used on the CDC data.

u/miyari · 6 pointsr/dataisbeautiful

> Rice Krispies Treats Cereal

You can order it on Amazon Prime. I just got like 8 boxes of it. Tastes the same as ever, the only problem is that there aren't really clumps like there used to be. It's just like really, really sugary Rice Krispies. Dunno if the Walmart boxes are the same.

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/Calabast · 7 pointsr/dataisbeautiful

(And also Dataclysm, the book this article is based on, and where the graphics came from. I know I know, the article very clearly mentions the book, but for people who don't click your link, I want them to at least see its name.)

u/shorttails · 1 pointr/dataisbeautiful

Hadley (ggplot2 author) also has a book on the package if you want to get a solid foundation: here

u/Prof_Acorn · 1 pointr/dataisbeautiful

I'd guess it's from Dataclysm, which just came out.

u/justanothertut · 24 pointsr/dataisbeautiful

The resin that green mountain uses in their cartridges isn't recyclable or biodegradable.

These are and they're a lot cheaper. If you use a keurig 2.0 you may need a clip to bypass the DRM.

u/fieldpain6969 · 1 pointr/dataisbeautiful

The resin that green mountain uses in their cartridges isn't recyclable or biodegradable.

These are and they're a lot cheaper. If you use a keurig 2.0 you may need a clip to bypass the DRM.

u/therealdrag0 · 13 pointsr/dataisbeautiful

In "The Better Angels of Our Nature: Why Violence Has Declined", Pinker talks a bit about honor culture and how it's persisted in the south and how that effects violence.

If I remember correctly there was one study that showed that southern employers are more forgiving of candidates who murdered someone for retribution than of someone who stole cars, whereas for northern employers it was the opposite. Kinda crazy...

u/dog_in_the_vent · 0 pointsr/dataisbeautiful

Our policy with nuclear weapons has never been to use nukes in response to conventional warfare. If you want to learn about it, I recommend Command and Control by Eric Schlosser. We've had our nation attacked and our sovereignty challenged multiple times and have never resorted to a nuclear first strike.

u/leveretb6969 · 1 pointr/dataisbeautiful

According to Amazon's listing Dr. Grant Duwe, “Mass Murder in the United States: A History.” only goes through 1999, not 2015. It's nice that you're miss representing the data here. Especially when that author went on NPR in 2013 saying mass murders were dropping.

u/Mystik738 · 52 pointsr/dataisbeautiful

According to Amazon's listing Dr. Grant Duwe, “Mass Murder in the United States: A History.” only goes through 1999, not 2015. It's nice that you're miss representing the data here. Especially when that author went on NPR in 2013 saying mass murders were dropping.

u/IlGesu · 4 pointsr/dataisbeautiful

If you look at past years' primary polls from before February of the season, you see complete mess. Here's 2012. The polls are meaningless that far out, and in every past primary, establishment endorsements helped choose an electable candidate. Silver used endorsements as a big factor in his analysis. His site even has a tracker that states "endorsements have been among the best predictors of which candidates will succeed and which will fail" which in every other primary was true. Normally, you couldn't just rely on the polls.

In finance, they say the scariest words are "This time it's different" where previous models that accurately made predictions no longer apply. Well, this time it's different. The large, shifting field of candidates made a lot of powerful Republicans abstain from endorsing anyone, and the hatred toward the Republican establishment made endorsements almost worthless. Anyone who read the polls and saw it coming were lucky unless they could also predict why the normally accurate model no longer applied. If they just relied on the polls, any other year they would've been wrong.

EDIT: One analyst who actually did predict that the old rules no longer applied was Norm Ornstein. He even wrote an article back in August titled "Maybe This Time Really Is Different"

u/MxGRRR · 1 pointr/dataisbeautiful

well without getting too in depth I'd like to first say you should look into and read up on the issue because I will undoubtedly get something wrong here. It's overwhelmingly complicated and I'm not an expert. If you want a quick easy intro you could start with netflix's 13TH. Many of the authors you should be reading if you're interested in the theory of structural racism are quoted or interviewed in that documentary.


The New Jim Crow - Michelle Alexander

Not in my Neighborhood - Antero Pietila (caveat: I read about redlining quite a few years ago now, from someone interviewed in 13th. forget who. would cite them instead but in a rush RN. I think I read a snippet of this book at one point but tbh it's been a long time since I went to school)


are both probably good places to start. I have a collection of academic journals and sources from undergrad I might be able to find at home too (although my life is busy this holiday season so no promises). the basic idea is that after the civil rights movement many things aligned to marginalize minorities in place of the more openly racist system of segregation. After WWII vets were given houses, but black vets were encouraged to move into new houses in black neighborhood, which were "redlined" - essentially the houses in black neighborhoods were deemed less valuable and if you lived in these neighborhoods it became progressively harder to get good loans and build your financial assets. so white vets sent their kids to free using the assets their GI bill houses gave their family, while black vets watched their neighborhoods slowly fall into poverty and marginalization.


Meanwhile a rhetoric of "criminality" was cultivated in politics - Nixon ran on an anti-crime platform and his adimistration allegedly used drugs and crime to split up hippies and black, keeping them from unifying politically. Reagan grew these policies and next thing you know The New Jim Crow emerged - sorry for wiki but incarceration skyrocketed and disproportionately hit minorities and the lower classes. Check the sources at the bottom of the wiki it's a much more complex issue than one sentence and I don't have time to cite you a million sources. Although democrats don't like to talk about it, Bill Clinton actually resided over a very large part of this trend of mass incarceration and even enacted some of the harshest laws - like three strikes and you're out and mandatory minimums. It's possible this hard stance on crime helped win back the presidency for the Democrats - by then crime had become such an integral part of campaigning that the only way to beat the republicans was to join them.


during this time you can actually also find some strong examples of more direct violence against major outspoken black voices - there was the time philadelphia bombed itself - here's an op-ed on that one too and there was the assasination of Fred Hampton while he was asleep next to his wife


complicating matters is the privatization of prisons. With so many people in prison states were slow and overcrowding became an issue so profits started to be had in the private prison sector. it didn't take long for other industries to join the party -Lots of big names in American consumerism use or used labor in prison camps to cut labor costs and stay local. Which just makes it more profitable to be tough on crime and run prisons.


tl;dr: it pays to have cheap labor and infrastructure/governement can be used to maintain the status quo with a new spin

u/coldnever · 0 pointsr/dataisbeautiful

You kids need to learn The myth of "balance" in capitalist societies

Overthrowing governments

"I helped make Mexico, especially Tampico, safe for American oil intersts in 1914. I helped make Haiti and Cuba a decent place for the National City Bank boys to collect revenues in. I helped in the raping of half a dozen Central American republics for the benefits of Wall Street. The record of racketeering is long. I helped purify Nicaragua for the international banking house of Brown Brothers in 1909-1912. I brought light to the Dominican Republic for American sugar interests in 1916. In China I helped to see to it that Standard Oil went its way unmolested." [p. 10]

"War is a racket. ...It is the only one in which the profits are reckoned in dollars and the losses in lives." [p. 23] "The general public shoulders the bill [for war]. This bill renders a horrible accounting. Newly placed gravestones. Mangled bodies. Shattered minds. Broken hearts and homes. Economic instability. Depression and all its attendant miseries. Back-breaking taxation for generations and generations." [p. 24]

The 9 trillion dollar bank bailout

Libor scandal

Rule of law is impossible under capitalism, since the kings of business (he who has the gold makes the rules) get to do whatever they want and the public gets fucked.

Regulating capitalism has failed: