Using Show Me without using Show Me

At The Information Lab we are rather lucky to have so many certified Tableau trainers. This means that we get the chance to teach either complete newbies the FUNdamentals of Tableau or how to leverage some of the more advanced features of Tableau very often as there are not that many trainers out there. We also get the chance to teach each other so much that we won’t otherwise come across. Why is this important you rightly ask? Read on…

This week I the chance to teach some very bright analysts how to make the most of their skills with Tableau. Whilst teaching the attendees about the Marks Card through a technique that I call ‘Whiteboard Tableau’ (more on this soon), one attendee Natasha corrected me about the way to create a Stacked Bar chart without using the Show Me panel.

Normally I would say add your discrete field (blue pill) that you want to be your bars on to the Column or Row shelf (depending on whether you want a vertical or horizontal bar chart respectively) and add the measure (green pill to the opposite Shelf you placed the discrete pill. To create a stacked bar chart you can then drop what you are dividing each of those bars by on to the Colour Shelf of the Marks Card. Easy.

But I heard… “Just drag the new discrete field on to the bars and it colours the chart”. I froze, not wanting to say “No Tableau doesn’t work that way” as I have learnt you never say that as someone has always found a way. Despite using Tableau heavily for the last three years, I never had come across this technique before. I got Natasha to talk me through the technique and it worked a treat.

Ever noticed @tableau doing things you didn't expect but is actually better than expected? Blog article coming soon pic.twitter.com/mX6uAjydmj

— Carl Allchin (@Datajedininja) November 13, 2015

I posted it on Twitter and got eight favourites and a retweet. The tweet even got a reply from my favourite English Zen in America:

@Datajedininja @tableau never ever done that before, nice!

— Peter Gilks (@pgilks) November 10, 2015

Most people I have showed didn’t even know of this technique until I showed this guy:

It's almost keynote time! @Datajedininja and I are getting ready to be amazed #data14 pic.twitter.com/4xUlTPqxMf

— Robin Kennedy (@Odbin) September 9, 2014

(note the ‘guy’ in question is that clever one on the right not that other floppy haired fella on the left)

For those who haven’t come across Robin. I’m sorry. The man is a Tableau legend and always knows a trick or two to get you round that surreal blending issue or why that Table Calc won’t add itself to your Filter Shelf.

Robin instinctively knew the solution, “well, Tableau’s using Show Me”. Uhh? No, it’s not? I’m dropping it in to the view. Robin has an amazing teaching patience and didn’t call me the imbecile that I deserved to be regarded as. Watch the gif closely as the mouse reaches the View, it changes to have the Show Me logo pop-up.

What Tableau is doing here is using the Show Me logic that decides what is the best way to visualise the data you have selected. What I would have expected Tableau to do is treat this drag-and-drop in the same way that it would if you would double click this new discrete field (in the gif example ‘Category’). I would expect Category to be added to the right of Region (the discrete value dictating the bars). But no, Show Me is assessing that the best way to visualise this data when dropping this new discrete pill in to the view is to use it on colour.

How else can you make use of this?

Well understanding what Tableau is going to do in certain situations is key so the table below details what else happens when the Show Me logo pops up as you drag something in to the view

Starting Point	Type of new pill	Result
Basic bar – one discrete pill on columns and one continuous pill on rows	Discrete	Stacked bar – new pill used as colour
Basic bar – one discrete pill on columns and one continuous pill on rows	Continuous	Shaded bar chart – new pill used as colour as well but as it is continuous the colour is a scale rather than categorised
Basic Line Chart – Date on Columns, Continuous pill on rows	Discrete	Depends – if there are less than 20 Discrete Values then Table picks colour, if there are more then it just add the new field to Detail and created multiple lines
Basic Line Chart – Date on Columns, Continuous pill on rows	Continuous	Colours the existing line by the new data field
Part to Whole Chart (Treemap, Packed Bubble or Pie Chart)	Discrete	Creates additional rows using the new data field but retains the marks type
Part to Whole Chart (Treemap, Packed Bubble or Pie Chart)	Continuous	Creates additional rows retaining the marks type also but uses Measure Names and Measure Values to form the new rows

So next time you use Tableau, go a little slower and see what Tableau is doing is you might uncover something that you think is normal behaviour but isn’t, it could lead you to other time savings!  

Keynote 4 – Data & Me - Hannah Fry

Maths is clean, data is not Mark J (a Wikipedia game) – you keep clicking on the 1st link on a Wikipedia page. Everything gets you back to ‘philosophy’. 95% of Wikipedia searches will take you through to Philosophy.

Mathematicians see 2 separate worlds – the real world and the mathematical world that can describe what is going on around you. Data provides the link between the two worlds. OK Cupid intentionally build in data collection elements. Men’s rating of women is a nice bell curve. Only 1 in 6 women rate men as above average HF started to focus on data with Google Trends – mistyping Google as Googlw is increasing massively. But why are people Google, Google anyway?

London Cycle Hire – spikes found in usage as people cycle downhill but won’t cycle as much back uphill Visualisation of transport mapping for every transport type in London is fantastic. Analysis done on worst place to have an issue and it was found to be Highbury & Islington. There are very few options of a different route if there is an issue there.

Data isn’t the end of the story it’s only the beginning Team collected gelocated tweets to see the second language in London and where they are located. A French community actually turned out to be one Frenchman tweeting a lot in just French. This led HF to think about the ‘Trough of Disillusionment’ and about what data you leave in or takeaway. Can lead to misleading conclusions.

Austerity issue – economic theory – you don’t grow when you have high debt as a country. New Zealand had only one year (1951) of high debt but didn’t weight the data so the New Zealand result skewed the results hugely. With mathematics you can only have absolute truths where data can be cut in different ways.

‘Street Bump’ app to detect when your car goes over a pot hole so the local government can find road quality issues. But this twisted the results as only the more affluent had smartphones and the inclination to download and use the app (or have a car to ride in). The challenge of encryption is tough but geolocation on your apps show your normal behaviour. Ie when you leave home and posting any gelocational tweets or messages.

The data revolution can give you new insights. A 17 year old boy wearing an Apple Watch showed his heartbeat was very high and remained high after exercise. He went to the doctors only to discover he was having heart and liver failure.

Prediction is the holy grail. Humans have a prediction addiction. “We can predict everything but the future”. HF doesn’t think anyone has made good predictions about the future. Likely is possible but exactly is not possible. Probability is the only way we can really predict what is likely to happen. 

Serial killer, Dr Harold Shipman chart of his patients’ deaths showed a massive increase in deaths in the afternoon in comparison to all other doctors. Police want to be able to search through events and find potential suspects. You are looking for trends that rely on very few assumptions. This can be used on infectious disease or bomb factories.