2023: Week 8 - Taking Stock

 Created by: Carl Allchin

For the final week of Intermediate Month, our data set needs so cleaning and grouping to allow us to analyse the top trades from The Data Source Bank's trading floor. 

No Wolf on Wall Street moments have happened but we've had some big trades happen across a wide range of companies so we need to understand these more. Can you help us find the top 5 trades for a series of different ways we look at the companies traded and the prices of the trades?

Input

There are 12 files to input this week. Each number in the file name reflects the month it came from (January's file doesn't have a value)

The data can be found here

Requirements

  • Input each of the 12 monthly files
  • Create a 'file date' using the month found in the file name
    • The Null value should be replaced as 1
  • Clean the Market Cap value to ensure it is the true value as 'Market Capitalisation'
    • Remove any rows with 'n/a'
  • Categorise the Purchase Price into groupings
    • 0 to 24,999.99 as 'Low'
    • 25,000 to 49,999.99 as 'Medium'
    • 50,000 to 74,999.99 as 'High'
    • 75,000 to 100,000 as 'Very High'
  • Categorise the Market Cap into groupings
    • Below $100M as 'Small'
    • Between $100M and below $1B as 'Medium'
    • Between $1B and below $100B as 'Large' 
    • $100B and above as 'Huge'
  • Rank the highest 5 purchases per combination of: file date, Purchase Price Categorisation and Market Capitalisation Categorisation.
  • Output only records with a rank of 1 to 5

Output


One file:

10 data fields:
  • Market Capitalisation Categorisation
  • Purchase Price Categorisation
  • File Date
  • Ticker
  • Sector
  • Market
  • Stock Name
  • Market Capitalisation
  • Purchase Price
  • Rank
831 rows (832 rows incl. headers)

You can download all the outputs from here

After you finish the challenge make sure to fill in the participation tracker, then share your solution on Twitter using #PreppinData and tagging @Datajedininja, @JennyMartinDS14 & @TomProwse1

You can also post your solution on the Tableau Forum where we have a Preppin' Data community page. Post your solutions and ask questions if you need any help! 

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