2019: Week 2

So you survived week one (note: if you haven’t completed week one - go back and give it a go as we will be layering the techniques over time)... well done and let’s kick this up a notch. 

This week’s challenge uses a few of Jonathan’s and my favourite Tableau Prep features. Prep has a load of great features built in to the menus so let’s see which of them you can use to save you lots of fiddly calculations. 

So what’s the data? We need you decide where you are going to in the UK; London or Edinburgh, purely based on the weather (every Brit’s favourite subject).

*edit* - you need to update to at least version 2019.1 or there are some serious work-arounds to be done!

Requirements for this week:
  • Import the file
  • Get rid of those nicely formatted titles - no-one is viewing this in Excel! (sorry Excel fans)
  • Make sure you get all the data in the Excel sheet loaded in to Prep
  • Clean up the City names to create two cities in one column (London and Edinburgh)
  • Pivot the data to give a measure per column for the four metrics in the data set
  • Output the data to csv
Your output file should:
  • have 6 columns
  • have 14 rows of data and a row of headers
  • Have no cells without a value
  • Just load beautifully into Tableau

For comparison, here's our output file. Don't to forget to fill in our participation tracker!


  1. Hiya - minor point, having just stared at the screen trying to figure out why I couldn't do something.. might be worth noting the version of Prep required to complete the challenge.. I hadn't upgraded :-) and I guess there's a chance some might not be able to easily if there are work policies in place preventing them...

    1. Hi Donna, completely agree. We hadn't thought of that issue before this week's challenge but will make sure it's in future versions of the challenge (if we can work it out as Prep changes so darn quickly!). Really appreciate the feedback.

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  3. As far as renaming the data fields, it is unclear if this can only be done manually (selecting the data field name and typing in the desired name) and then dropping the measure data field. I spent a few minutes googling this, but I didn't see any other way to change the data field headers, except maybe a Python/R script which doesn't seem better than manually changing it. I suspect the more recent challenges with videos may resolve these kind of questions.


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