2021: Week 3

This week is the third in the Starter Challenges series we are running to kick off 2021.  

This challenge will introduce you to the two main types of reshaping data, pivoting and aggregation. We used aggregation last week so we are building on this technique this week. We will also let you work with Unions where we stack data sets that have similar structures on top of each other. 

As with all of our January 2021 challenges, we will be sharing useful links to helpful videos and articles that will give you more technical support if you need it. 

This week's challenge sees us looking at the Accessory Sales at our Bike Store.

Input

One Excel sheet with 5 tabs of data:
  • London
  • Leeds
  • York
  • Manchester
  • Birmingham

The structure of the data is the same in each worksheet. 

Requirements

  • Input the data source by pulling together all the tables (help)
  • Pivot 'New' columns and 'Existing' columns (help)
  • Split the former column headers to form: (help)
    • Customer Type
    • Product
  • Rename the measure created by the Pivot as 'Products Sold'
  • Create a Store column from the data
  • Remove any unnecessary data fields
  • Turn Date into Quarter (help)
  • Aggregate to form two separate outputs of the number of products sold by: (help)
    1. Product, Quarter
    2. Store, Customer Type, Product
  • Output each data set as a csv file (help)

Output

Product Quarter Output

3 Data Fields:
  • Product
  • Quarter
  • Products Sold
16 rows (17 rows including headers)

Customer Product Quarter Output

4 Data Fields:
  • Store
  • Customer Types
  • Product
  • Products Sold
40 rows (41 rows including headers)

Here's our full output for comparison. Remember we don't care about the order of the columns or rows as Tableau Desktop will import them in whatever order they come in!

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!

Popular posts from this blog

2023: Week 1 The Data Source Bank

Image
 Created by: Carl Allchin Welcome to a New Year of Preppin' Data. These are weekly exercises to help you learn and develop data preparation skills. We publish the challenges on a Wednesday and share a solution the following Tuesday. You can take the challenges whenever you want and we love to see your solutions. With data preparation, there is never just one way to complete the tasks so sharing your solutions will help others learn too. Share on Twitter, LinkedIn, the Tableau Forums or wherever you want to too. Tag Jenny Martin, Tom Prowse or myself or just use the #PreppinData to share your solutions.  The challenges are designed for learning Tableau Prep but we have a broad community who complete the challenges in R, Python, SQL, DBT, EasyMorph and many other tools. We love seeing people learn new tools so feel free to use whatever tools you want to complete the challenges.  A New Year means we start afresh so January's challenges will be focused on beginners. We will use dif
Read more

2023: Week 2 - International Bank Account Numbers

Image
Challenge By: Jenny Martin For week 2 of our beginner month, Data Source Bank has a requirement to construct International Bank Account Numbers (IBANs), even for Transactions taking place in the UK. We have all the information in separate fields, we just need to put it altogether in the following order: Inputs A list of the transactions, with information about the receiving bank account  A lookup table for the SWIFT Bank Codes  Requirements Input the data In the Transactions table, there is a Sort Code field which contains dashes. We need to remove these so just have a 6 digit string ( hint ) Use the SWIFT Bank Code lookup table to bring in additional information about the SWIFT code and Check Digits of the receiving bank account ( hint ) Add a field for the Country Code ( hint ) Hint: all these transactions take place in the UK so the Country Code should be GB Create the IBAN as above ( hint ) Hint: watch out for trying to combine sting fields with numeric fields - check data types Re
Read more

How to...Handle Free Text

Image
Free isn't always a good thing. In data, Free text is the example to state when proving that statements correct. However, lots of benefit can be gained from understanding data that has been entered in Free Text fields. What do we mean by Free Text? Free Text is the string based data that comes from allowing people to type answers in to systems and forms. The resulting data is normally stored within one column, with one answer per cell. As Free Text means the answer could be anything, this is what you get - absolutely anything. From expletives to slang, the words you will find in the data may be a challenge to interpret but the text is the closest way to collect the voice of your customer / employee. The Free Text field is likely to contain long, rambling sentences that can simply be analysed. If you count these fields, you are likely to have one of each entry each. Therefore, simply counting the entries will not provide anything meaningful to your analysis. The value is in
Read more