One of the things Tableau is.....

A few days ago Paul Banoub posted this on Twitter:

and yesterday Dan Murray of Interworks posted this blog entry describing his thoughts on what Tableau is and what Tableau isn't. And I agree with everything Dan wrote (he is a smart man after all!).

However there was one thing missing from Dan's description of what Tableau is and it got me thinking that I need to blog about it.

One of the things Tableau is is the best tool yet created for data exploration

At this point you might be thinking "no shit Sherlock" but I think this is something I need to write about, so first a little history of my journey with Tableau.....

I first came across Tableau in 2010 when working at Barclaycard in the customer insight team. A lot of my job revolved around extracting information about our customers from transactional databases, finding the interesting nuggets in the data and basically turning that data into stories to provide 'insight' for use in product development, strategy and marketing decisions. In practical terms what that meant was writing code in SQL or in SAS, exporting aggregations of data to Excel to produce charts and then converting these to PowerPoints. 

The thing is that this process is not particularly forgiving when there is an error in the data, or when the data story you were looking into turned out to be not very interesting or insightful. Starting the whole process again was a time consuming effort and on the fly analysis, while possible, was sometimes painful.

When I first started using Tableau, thanks to an introduction from my then new colleague Brian O'Connor, I actually had the 'personal' version which did not allow direct connection to databases. And so I was using Tableau only against Excel files. It made my life easier even then, but I was mostly using it as simply a way to make charts a lot prettier than they were coming out of Excel.

And then Brian and I had our Eureka moment. We attended a Tableau meet-up in London for a preview of version 6.0 and saw what the then small but enthusiastic group of users (including one Tom Brown) were doing with it and we realised we had only scratched the surface.

So after that my job and career took a dramatic turn for the better. I was plugging Tableau directly into Teradata, analyising data on the fly, finding outliers, spotting possible data errors, seeing patterns  and relationships and testing out scenarios at 100 times the speed I had before. I started being able to turn around answers to questions in seconds rather than minutes and began doing analysis sat side by side with my colleagues from different business teams, working together to find the stories in the data before shipping off the results to PowerPoint. 

And for a long time that's the only way I used Tableau. I am very happy to admit that I had never even heard of the words Business Intelligence, had no background in IT and had no concept of things like Cognos and Business Objects. I did not produce dashboards, or manage servers, or consider how other people would use Tableau, I was using it for my own needs.

That is what I mean by 'data exploration'. Its the process of plugging directly into some data and experimenting until you find an answer to a question you may have never known existed. I think its the most important part of using Tableau (and its the reason why I still do not plan out a dashboard before I play with and understand the distribution and relationships of the data).

And that's why I'm writing this blog post. Because when I look at everything I've done so far on this blog, its mostly been in the context of using Tableau to produce nice looking and user friendly dashboards for other people to consume. But if you took all that away, if took away Tableau Server, Tableau Public, Tableau Online, took away Story Points and even just the ability to produce dashboards in Tableau desktop - it would still be my favourite piece of software ever produced. 

PS - have a nosey around here for some interesting background on the development of Tableau

Guest Post! A look at the success of the UCONN basketball team over the years

I've  been a bit distracted from blogging recently so new posts haven't exactly been coming thick and fast. BUT you are in luck, because my colleague Chamberlaine Kerr has come up with a cool basketball related viz and she's chosen this as the place to debut it.

Chamberlaine also works for Slalom Consulting and is helping to drive growth of the data visualization practice at our Hartford office. This is Chamberlaine's first foray into the world of Tableau Public and I think its a good one. You can find her on twitter as @ChamberlaineK

Chamberlaine Kerr

Slalom Consulting – Business Intelligence

Hartford, Conn.

In February, 2012 I started my career with Slalom Consulting at our headquarters in Seattle. After roughly one-and-a-half years I relocated to Hartford, Conn., and joined Slalom’s Information Management and Analytics practice.

Prior to Slalom I attended the Foster School of Business at the University of Washington – go Dawgs!   After moving to Connecticut, I quickly realized we aren’t the only Huskies around.  I now refer to my alma mater as the Huskies of the Best (oops! I mean West*) coast.

I’d like to say a huge “thank you” to my Slalom Consulting colleagues Peter Gilks (for allowing me to take over his blog for the day) and Curtis Looney (for helping with the original POC).  Hopefully my own blog will be a part of the not-so-distant future.   In the interim, I want to share the first Tableau viz I created outside of client work – a UCONN Men’s Basketball viz!

The Viz

This past year the UCONN Men’s Basketball team took #Winning to a whole new level as they laughed all the way to the NCAA championship.  The 2013-14 season was UCONN’s 4th NCAA Championship win in the last 16 years … not a bad start for Kevin Ollie’s first year as head coach.
With this year’s college basketball season well underway, it’s a good time to take a deeper look at some of the UCONN Husky’s historical trends.
Please feel free to comment.  All feedback is welcome and much appreciated.  Enjoy!

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Skyscrapers in New York update

A year a go I made this blog post for Tableau Public Design Month, including a viz on the tallest buildings in New York.

Well over the last year a new very tall building has popped up in the city to take the number 2 spot away from the mighty Empire State Building and so I thought it was time for an update.

The new building is 432 Park Avenue, the tallest residential building in the Western Hemisphere. Its penthouse apartment is currently for sale listed at $95m.

432 Park Ave is part of a new craze for super skinny super tall luxury residential buildings in New York, many more of which are in the pipeline. I'm not really a fan of these new buildings, especially since many of the apartments will be bought and left empty. But whatever happens, I'll try to keep this viz up to date.

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A Rough Guide to Tableau Dashboard Actions

As you probably can tell by now, I really enjoying building data visualisations in Tableau. Whether for this blog or for work, I strive to build dashboards that people will be able to use to explore the data at their own pace and discover their own insights.

One way I attempt to do this is by using, what I hope is, engaging visual design. The other is by building in interactive features into the dashboard that people can play with to start changing the views of the data. This is accomplished in three primary ways: Quick Filters, Parameters and Dashboard Actions. Of these three Dashboard Actions have become my favourite as they are probably the most flexible and offer the most immersive experience. So here's my rough guide to Tableau Dashboard Actions. Its not completely exhaustive, and its not particularly technical,  but if you are fairly new to Tableau, or even an experienced user, I hope you will find it a useful guide.

What is a Dashboard Action?

A dashboard action is an interactive element on a Tableau dashboard that is driven from the worksheets within that dashboard. There are three types of dashboard action:
 - Filter
 - Highlight
 - URL

Tableau themselves provide a good run down of how to build in Dashboard Actions here http://onlinehelp.tableausoftware.com/current/pro/online/mac/en-us/actions.html. So rather than repeat what Tableau have already documented, I am going to show a variety of use cases for using Dashboard Actions and how to implement them. Those use cases are:

Use Case 1: Basic Chart to Chart Filtering
Use Case 2: Pre-Filtering a Large Table
Use Case 3: Creating a 'Cross-Blend' Filter
Use Case 4: Showing Images
Use Case 5: Dynamic Text or Titles
Use Case 6: Linking Out to Web Pages
Use Case 7: Highlighting and Labelling
Use Case 8: Switching Dashboards
Use Case 9: Mixing Things Up

2014/15 Zen Master

A couple of weeks before the Tableau Conference I received this rock in the post and it made me very happy!

I feel very honoured to have been selected and to be in the same group as all the wonderful people listed here http://www.tableausoftware.com/ZenMasters

Thank you to anyone who nominated me, I really do appreciate it and I am so happy to be involved in this community.

OK, better start thinking of my next blog post......

Why Does It Always Rain On Me?

We are now only a couple of weeks away from the 2014 Tableau Conference so I thought I would make a viz in honour of Tableau's home and the location of the conference this year, Seattle. Two years in row is a tradition right? Here's what I did last year

I ruled out making a Seattle Supersonics viz as it seemed just too morbid, so I went for one of the other things that Seattle is famous for - rain!

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A few things I spotted in the data:
 - London is nowhere near as rainy as its reputation. When I moved from London to New York I was convinced it was raining here more, and it turns out the data backs me up. Time to lay off the London weather jokes.
- Seattle does deserve its reputation for rain. It doesn't rain the most in terms of volume, but it does rain often.
- The rainy and dry season patterns of some places like Cairo and Mumbai are more extreme than I had previously thought.

I hope you enjoy exploring the viz, and please don't be offended if your city isn't on there, it was a pretty random selection apart from Sheffield where I grew up and it felt like it rained all the time.

Comments welcome, and hope to see you in Seattle! You probably won't need an umbrella in September.

Turbo Tip - solving an issue with Excel not opening due to Tableau add-in

The Tableau Excel add-in in and data reshaper is a fantastic little tool http://kb.tableausoftware.com/articles/knowledgebase/addin-reshaping-data-excel
however with some combinations of versions of the add-in and Office it can cause an issue to occur where it becomes impossible to open Excel files from simply double clicking, from within an email for example.

To fix this, use the following tip courtesy of Chuck Hooper (http://www.bialytics.com/).

In Excel go to File->Options->Advanced, scroll down to general and un-check 'ignore other applications that use the Dynamic Data Exchange (DDE)' and that should fix the issue.

Thanks Chuck!


Peter

Minimum Wage - the Story Points Edition

Tableau version 8.2 recently launched and along with the long awaited Mac release (yay!) one of the main new features is something called 'Story Points'. The idea behind this feature is in Tableau's own words "a way to build a narrative from data".

So I decided to try it out and re-work one of my recent vizes into a story, using my Mac of course. I chose the minimum wage viz because it already fit into a story. The original is here, let me know what you think of the differences between the two.

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A few of my early thoughts on the new Story Points feature:

To be honest, when story points was announced, I was a little skeptical for a few reasons. I’ll address each of these below.

1.       The functionality isn’t that different from having multiple tabs in a published Tableau workbook, and I know from experience that people don’t often click past the first tab in that environment so I wondered if this would be any different.

I am however seeing how story points works pretty well in leading people through the vizes. The simple and clean design change of having the story point headlines clear across the top does I think engage the viewer enough to want to click through to the next page. It also sets in the mind of the author more of an impetus to create that connected story, rather than just a series of seemingly disconnected dashboards.

2.       Its applicability in an enterprise setting seems niche, and there are other developments that perhaps should have taken precedence over this in the release cycle.

My initial reaction to story points was that it will be great for Tableau Public and for data journalists, but will have limited appeal within businesses where timely, accurate reporting is still a high priority and powerpoint rules the roost for sharing stories. I think this will be the case for a while, but I am interested to see how the use of story points develops in a large business setting as Tableau Server becomes more mainstream and business users begin to experiment with the tool.

3.       Creativity is limited compared to the single dashboard approach.

This may seem counter-intuitive, but I believe that the design thinking behind producing a single screen dashboard that allows the user to explore a story at their own pace requires a greater amount of creative thought than the creation of a guided story. I am a big fan of ‘seeing everything in one place’ and so for me story points doesn’t create that same excitement I get from seeing the single stand-out viz. Having said that, there is already some great work going out on Tableau Public so my mind is starting to change (see these examples by Matt Francis and Carl Allchin). And I’m sure that people are really going to start pushing the envelope with it as it becomes more familiar.

On a more tactical note, the current version of story points is quite restrictive in the design options available. As you will have seen from my viz designs, I’m a big fan of using images, shapes and custom fonts to add to the overall look and feel of a dashboard and help unify the theme. This is much less possible with story points as I can’t use an image for the title, and those grey boxes are very restrictive in size, color and font. Also the grey boxes suffer from a mismatch between how the words fit in desktop and how they look once published.

4.       It has been billed in some quarters as ‘the power point killer’.

I don’t see this happening for a long time! Don’t get me wrong, I love the idea of more people using Tableau to present, and when you are presenting a data heavy story I do think that Tableau story points will catch on. The main problem though is Tableau is not really designed for those ‘non-data’ elements, such as images and text. In fact to get my dashboards looking just right I often do a lot of design and creative work in powerpoint before exporting images into Tableau.

Microsoft have I think done a really solid job in improving the design functions of Powerpoint and that’s going to be hard for Tableau to compete with. And actually I don’t think they should compete on that front. In the future I see more of a split in presentation tools, Powerpoint will still exist but Tableau will be used in some more situations, as will other popular tools like Prezi.

Overall I like this addition to the Tableau tool set, but I feel its a work in progress and I expect the community and many great Tableau Public authors will help steer its development.

An idea for a small but useful Tableau improvement

I have a new idea up on the Tableau Forums, you can check it out and vote it up here http://community.tableausoftware.com/ideas/3447

Here's the idea, its one of those small things that can sometimes drive me a bit nuts.

 - You know how sometimes you are doing something on a Tableau dashboard through server, and either you can't remember what you've been clicking on, or un-clicking your filters would just take too long? Well isn't the 'Revert' button helpful? This little beauty below:

Well I would really love to see this button in Tableau Desktop too, particularly in presentation mode. The reason is that sometimes when I am demoing Tableau I do not have either web access or specifically Tableau Server access, and so I can demo dashboards through presentation mode on desktop. But it can get a bit sticky if you need to start over.

There is a 'Revert to Saved' option but this doesn't always do the trick.

100 Blocks - A 'Quantified Self' Random Walk Experiment

When I was studying Statistics at University one of my favourite topics was Markov Chains and how they could be applied to real life situations. I was particularly fascinated by the simple Random Walk which to borrow from Wikipedia is "a mathematical formalisation of a path that consists of a succession of random steps".

What fascinated me was that random walks don't just fluctuate around an average, they usually 'go' somewhere. And there are so many possibilities of where they will go. Take this example:

Starting at point zero on a simple x,y axis for every move along x of 1, move along the y axis with a randomly chosen value of +1 or -1. You might think that all such 'walks' would just end up around the zero line, but they don't. Again borrowing from Wikipedia, here's what a bunch of such Random Walks end up looking like:

Anyway, the reason I mention this is because I've always had the rather geeky desire to do my own random walk, and by this I mean an actual physical walk - going for a stroll but letting chance determine my route. And this month, thanks to Tableau Public's Quantified Self Month, I finally got the kick I needed to actually go and do it. Plus now I live in a city built around a massive grid, where walking anywhere can be done in any number of combinations of streets and avenues, I had no excuse not to. Then of course I had to visualise the results in Tableau:

(click play for an appropriate sound track)

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So how did I actually go about it? Well first off I need to give massive props to my wife Heather for doing this with me, helping come up with the plan and doing all the photo and photoshop work for the viz. Here's what we did:

 - We decided on a few rules
1. We would start the random walk close to home, at the intersection of Avenue B and 11th St.
2. We would roll a di (actually an iphone app called Dice Roller) and take the following actions:
    - Roll 1 or 2: Turn left and walk one block
    - Roll 3 or 4: Go straight ahead and walk one block
    - Roll 5 or 6: Turn right and walk one block
3. We were not allowed to go down the same block twice (to keep us sane)
4. If an intersection has less than 3 options, split the probability equally.
5. Walk for exactly 100 blocks and see where we end up

Here we are at the start:

Then we walked! And along the way we recorded a few of the things that we passed in order to give a flavour of the streets we were going down and how they differ. The, fairly random, list of things we recorded were:
 - Bars (just bars, restaurants with bars didn't count)
 - Laundries and dry cleaners
 - Independent coffee shops
 - Big chain coffee shops
 - Street art (loosely defined)
 - Pizza shops
 - Bodegas and delis

In retrospect I wish we'd recorded the number of psychics, because we definitely passed a lot of them! In order to record everything we passed, the street names and the results of the di throws we used the latest in data collection technology:

Heather also took a photo of every intersection and a photo of something on the block, which you can see in the viz.

Well the whole thing took a whopping six and a half hours, including a few rest stops for bagels, beer and pizza. And we also saw a surprise street market, the Hells Angels club house and a bit of a rain storm. But I was impressed with how far we travelled, we certainly took the long route but we ended up going completely East to West across Manhattan before basically going round and round in circles in the West Village (one part of Manhattan where the grid goes a bit skewy). I'm pretty happy with the results, it was a long day but worth it. Its an interesting way to discover your city and takes you down streets you may never otherwise go down.



Oh, and we took a taxi home.

How I built BALLCODE

My last post, BALLCODE: Scanning the 2013-14 NBA Season has been quite popular, has sparked some debate and has also (very generously I think) made an appearance in Tableau Public's round up of Tableau Tips Month as the 'most beautiful tip'. All of which is lovely. However its dawned on me that my tip portion of the blog post was pretty short so I'm going to expand here to show how I made the viz.

First up I'd like to clarify the origin of the chart type. For a long time I've wanted to do something with small multiples as I really enjoy these visualisations, they give you so much to mull over and you can make lots of comparisons on a single page. Small multiples don't have to be charts, they can be pictures too, like this one we have on our wall at home. Delicious!

I also love the NBA, so I patiently waited until the end of the regular season in order to be able to achieve my goal: Show all the results of the NBA season, by team, in a single small multiple visualization.

My original idea was actually to use line charts, but when I tried this it looked pretty crappy. So I switched around the chart types and fell into bar charts, which I realised was pretty cool as they reminded me of bar codes, AND quite clearly showed the wins against the losses. When I did this I thought it was a pretty original idea, but of course it turns out I was beaten to it some time ago by the king of visualization Edward Tufte (Jonathan Drummey made the spot). Tufte did this chart for baseball teams as sparklines 

So my idea wasn't totally original. But nonetheless I'm pretty happy with how it turned out, and I think the addition of  a colour split between both team and win/loss has worked out pretty nicely.

So...... here's how I made it:

First up I had to get some data. Fortunately NBA data is pretty easy to come by thanks to the good folks at http://www.basketball-reference.com/. Unfortunately, a seasons worth of results data includes one row for each game. Where as I needed to be able to visualize each game twice, once from the perspective of the home team and once from the perspective of the visiting team. In order to do this I copied the data out into Excel twice (two big lists of every game stacked together) and then did a few functions. Here's how the top half of the Excel sheet looked:

Columns A to E are straight from basketball-reference.com. The rest of the columns I created.

F (Team) = The visiting team

G (Place) = Where the game took place for that team (i.e. always 'Away')

H (Win) = 1 if Team won, -1 if Team lost

I (Team Score) = the score of Team

J (Opponent) = the other team

K (Opponent Score) = the other teams score

L (Date) = a string function of column A which ignores the day

M (List) = a simple index of each NBA game in order 1 to 1230

The bottom half of the Excel sheet then looked the same, except this time I switched it around so that 'Team' now refers to the Home team and the results are shown from their perspective:

Bingo! Two rows for every game, one from each teams perspective of home/away and win/loss.

I also wanted to organise the teams by division so I created a little look up table in the same Excel file to join to in Tableau:

So now I had my data for Tableau I made the connection and started doing some vizzing. As stated above, my first idea was to do a series of line charts, but I soon decided this wasn't going to work very well because of all the back and forth between winning and losing:

So I played around and decided on bar charts, which look a bit weird in the worksheet view where they are all really tall, but work well in the dashboard when they are squished vertically. I made the bars as narrow as possible and put in levels of detail to get each game in order of date.

A couple of things to note, here's the tooltip:

And here's how the colours work:

Its been pointed out in the comments to the original post that the colours don't add any additional insight and could constitute 'chart junk'. Which is true, and probably not good practice in a business context, but in the case of things like sports teams I think the visual clues that the colours give create both a positive emotional response to the viz and also provide another quick way to find the team you are looking for (i.e. if you are looking for the Bulls, look for red).

So with one worksheet per division I then put these together in a tiled dashboard, very carefully adjusting the tiles to try and evenly distribute the 6 sheets. I also left room for a title and usual turned to dafont.com for a snazzy title. Something I've started doing to save time if I'm just doing a fancy title is instead of downloading the font, I use the preview in DaFont and take a screen grab. The colour can then be changed later in powerpoint or photoshop or anything else.

Hit Save to Web, done.

PS - a note on spelling. As an Englishman now living in the US my use of spelling and grammar is all messed up as I navigate cross-language spell checkers, auto correct, colleagues, clients and my 32 years of built in habits. So I apologise/apologize for the inconsistency.

BALLCODE: Scanning the 2013-14 NBA Season

The 2013-14 NBA Regular Season finished last night. I'm really excited about the playoffs this year, particularly in the West where there are going to be some epic match ups. But before we get to that I wanted to make a viz which would summarise all the games played into a single view. So here it is:

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As you can see I've tried to represent each teams season as an individual bar code representing their performance over the season. Let me know if you think it works, I'm purposefully trying to make some vizzes which are a bit 'non traditional since this blog is a bit of creative space.

And since its Tableau Tips Month on Tableau Public http://www.tableausoftware.com/public/blog/2014/04/tableau-tips-month-2419 here's a little design tip too.

In order to present each bar code with a single colour for losses, and a team based colour for wins I used the following table calculation:

and then assigned one colour for 'black' and each other team colour separately. (Note each Division is a separate worksheet).

This is a simple version of a technique I use a lot, mixing a colour scheme based on one or more fixed values, and some values that change. This helps with say highlighting an individual item driven by a parameter selection, exactly the same idea.

That's all for now. Enjoy the Playoffs!

Blue Blood

UPDATE: I made it to the final four! http://www.tableausoftware.com/public/blog/2014/03/sports-viz-contest-final-four-2403 if you like the viz please tweet with #Elite8Peter to vote

Well its that time of year again when the Iron Viz entry competitions roll around. This year the first topic is all about sports http://www.tableausoftware.com/public/blog/2014/03/submissions-open-elite-8-2365.

Here's my entry and its a quick history of the Duke vs North Carolina rivalry. To be honest I'm not 100% convinced with this viz, its a bit 'simple', but its a been a busy few weeks including a massive dose of the flu, so its about all I can muster for now. Anyway, hope its topically interesting.

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Taking a look at what the minimum wage means across the USA

Recently my colleagues at Slalom Consulting have launched a great concept called Viz for a Cause - http://www.vizforacause.com/ which is designed to be a place to gather visualization pieces that address both global and local issues. The hope is that in doing so we can more easily share the stories and the evidence around the things we believe are important - and in turn engender debate, discussion and engagement.

The launch of this site caused me to to consider my own viz output and I decided to attempt to address an issue I think is very important - that of the minimum wage, which is low in many places but in my opinion is scandalously low in the place I now live - the very expensive city of New York.

This has been quite a change and a challenge for me as I usually produce work on my blog that could be considered 'fun'. And its ended up being quite text heavy. But I hope you find it interesting and thought provoking. As usual, comments are welcome.

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Tableau Tip - The End of Time.... series based calculations

OK time for another little Tableau tip which might come in useful. This is one I now use all the time. The idea of using an index to hide time based values was first brought to my attention about 18 months ago by Tom Brown of The Information Lab (if I remember correctly - there is a chance it was Craig Bloodworth or Andy Cotgreave but I'm pretty sure it was Tom).

The situation is this: You've got a time series based table calculation going on that you are interested in showing, something like a running total, YTD total or difference from last month, however you don't want to show all the data - instead you only want to show the latest month.

Your starting position might look something like this below, with year, month, sum of sales, monthly difference in sales and running total.

Now lets say you only want to show the latest month, in this case December 2013. Well the first thing that springs to mind might be to filter, but that messes with the calculations PLUS its not going to automatically update to the latest month when the data updates:

Now the next idea you have might be to HIDE the 'non latest month' data, and that will solve the issue of the filters messing up the table calculations, but its still going to leave you with a problem when you get a new months worth of data you want to automatically show. So this is what you can do....

First create an index field:

now make this discrete

then pop the index field into your viz just after the 'month' pill

now comes the clever bit. To show just the latest month you want to hide everything else. To do this you need to make the Index value along side the latest month be equal to something unique and that will stay constant as the data updates, and then hide everything else. One way to do this is to sort year and month descending, and then highlight all the index fields that are not 1 and click hide. This can work fine for calculations of difference along time BUT does not work for running sums as it flips the year around to calculate from December running to January. So the safe bet is to take the following step:

Create another calculated field that looks like this

this creates a Boolean True/False variable that you can now add to your view and hide the Falses:

then unclick 'Show Header' for both 'index' and 'index match'

and you are left with the view you want, which will automatically update to the latest month as your data refreshes:

And then you can do what you want with that view, change the aliases, add it to a dashboard etc....


If anyone has an alternative approach to this I would love to hear what it is, as with so many things in Tableau there are probably multiple ways to achieve the same goal.

Crowdsourcing - The World's Biggest Stadiums

OK so here's a viz I made just because I felt like it :-) No other reason at all.

Its looking at the biggest stadiums (or stadia if you like) in the world, specifically those with a capacity of at least 60,000. You can hover and filter to select different sports and regions, and a picture of each stadium should pop up.

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A few things I noticed from the data:
1. College football stadiums in America are HUGE. They make the NFL stadiums look tiny. Think about this for a second - these are teams run by institutions of higher education with unpaid players and there are some 46 teams with seating for over 60,000 people. The biggest, Michigan Stadium, is the third biggest stadium in the world. The Premier League by comparison has 2 teams that meet this criteria.
2. I was surprised by the lack of baseball stadiums. I guess it has to do with the shape and size of the field. The biggest baseball stadium is Dodger Stadium with a capacity for 56,000.
3. There are big stadiums really all over the world. There are loads in Africa and Asia, and pretty much everywhere. There are definite regional differences between the sports enjoyed, and these become obvious in the map. The UK is probably the country with the greatest diversity of sporting venues at this level.
4. I'd quite like to go to the 'Mass Games' in North Korea, its probably quite a sight!


Peter

NB - I lumped Rugby Union and League together, sorry if that bothers anyone. Also I tried to pick the 'primary' sport for each venue but may have got this slightly wrong, if you spot a mistake, please let me know.

Copy and Paste within Tableau is your friend

Ok here's an admission. Table Calculations sometimes confuse the heck out of me. However I've developed a few little tricks I use to make life easier. Here's one I utilised in my latest Tableau Public viz.

Lets say you've been using the cool new Rank feature in Tableau 8.1 on loads of fields, but then you want to filter your data and NOT have the ranks recalculate. What do you do? There are probably many ways to skin this cat, however here's the one I used. It may not be the 'best' way, but I like it. As usual I'm going to use Superstore Sales data to demonstrate.

First I'm ranking all countries by four fields:

Ok good, and I've sorted by the rank of Discount to make the order clear. Now I tidy things up a bit and add a quick filter on country:

Now you see I've de-selected a few countries, and they have disappeared from the view, but the rank has re-calculated. That's expected behaviour, but in my case I didn't want the ranks to recalculate. So here's what I do to fix the rankings (I think of this like doing a copy and paste values in Excel when you want to stop the formulas from calculating).

First, put everything back in the filter.

Then hit CTRL+C

Open a new worksheet

hit CTRL+V

and bingo I now have a new hard-coded data set from the clipboard!

This data set includes only four fields:
Country
Measure Names - Rank of Discount, Rank of Profit, Rank of Sales, Rank of Shipping Cost
Measure Values - the original 'hard-coded' ranks for each
Number of Records

So now when I filter out countries, the countries disappear from the view but the ranks stay as they were:

and then this can be easily brought into a dashboard along with the main data set by using data blending on country.

And all's well that ends well.

Comparing University League Tables

Today's Viz of the Day http://www.tableausoftware.com/public/gallery/more-net-costs by Jon Boeckenstedt of Higher Ed Data Stories, which shows the relative costs of US university tuition, got me thinking about doing a viz on UK universities. Since they all basically charge the same price I was going to have to look at something other than fees (though there is a rather sad story in the trend for increasing UK tuition fees overall, perhaps a story for another day).

Here's the viz:

The main story is that at the very top end of the tables, both newspapers are in complete agreement with each other - Cambridge, Oxford, LSE and St Andrews making up the top 4 for both. After that, the two begin to differ leading to a maximum ranking difference of some 43 places for Anglia Ruskin University.

Creating the composite rank was fairly straightforward using Tableau's new RANK function in version 8.1. I simply averaged the two ranks, and then ranked that average! A note on ranking styles - The Guardian uses 'competition ranking' (e.g. 1,2,2,4) where as The Sunday Times ranks are unique. For the composite rank I used competition ranking.

PS - do you believe for one second that St Andrews should be above UCL? Treasonous if you ask me.