2020: Week 1

Welcome to Preppin' Data 2020! If you are returning from completing some of the challenges in 2019 then welcome back. If you are joining us for the first time then here's a quick overview of how the Preppin' Data challenges work:

  1. The CHALLENGE is set in a post like this, often released on a Wednesday. You'll get:
    1. The Business case / positioning for the challenge
    2. The Requirements clearly laid out including the data input
    3. The Output file and the structure that file should have
    4. A link to fill in the participation tracker so you can see how you are progressing in the viz here.
  2. The SOLUTION post posted the following Tuesday or later depending on what the Dr Preppers have going on in there non-Preppin' lives.
There are loads of places to get started with Tableau Prep. The videos by Tableau here are great and we've produced a load of 'How to...' articles to help guide you through some of the datary basics you need as well as some more of the complex techniques you will come across. 

One final point - no you don't have to use Tableau Prep for the challenges. We love seeing submissions from any tool (Alteryx, R, Python, SQL etc) with blogs / pictures of how you have completed the challenges but the challenges will be focused on being possible in Tableau Prep. 

So on with 2020's challenges...
                       ___________________________________________________
Whilst reading through some great Tableau blogs over the Holidays, the bosses at Chin & Beard Suds Co. (our fake soap company that might have the worst data in history) stumbled across Ryan Sleeper's post on Financial Statements (tip 6) and decided they needed a nice Profit statement for their board meetings from here on. Sadly our data isn't structured like we would ideally like so your challenge this week is to automate the production of the profit statement. 

Requirement


  • Input the data set
  • Find the profit totals for X items
  • Find the profit sub-totals for X.X items
  • Add the relevant values to the relevant items by replacing the nulls
  • Add the leading spaces:
    • 5 spaces for X.X items
    • 10 spaces for X.X.X items
    • NOTE: Do not manually rename these there is a function that will help!
  • Output the data (not csv or you'll lose the spacing)

Output

One file: 
  • Two Columns:
    • Item
    • Profit
  • 31 Rows (32 incl Headers)
The outputs can be found here for comparison. Don’t forget to fill the participation tracker and share your solutions using #PreppinData on Twitter.

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