2023: Week 22 - Student Attendance vs Test Scores

Challenge by: Tanbir Jalil

This is our next challenge from one of the members of the 38th cohort of the Data School UK.

You have been hired to create a dataset for the Prep School that will allow them to analyse the correlation between attendance and test scores.

Inputs

  1. Student Test Scores Graphical user interface, application, table, Excel Description automatically generated
  2. Attendance Figures 
Table Description automatically generated

Requirements

  • Input the data
  • First we must join the test score data set and the additional class attendance data set 
  • Clean Data: there’s a few spelling mistakes in the data set, use the data tool of your choice to correct these mistakes before we proceed. These mistakes are in the “Subject”  Column
  • Use a calculated field to clean up the test score column, so each number is a rounded to the nearest whole number
  • Split the student name column so we can see the first name and surname in two separate columns, named appropriately
  • If any student has an attendance percentage less than 70%, flag it as "Low Attendance" in a new column "attendance flag". Conversely, if above 90%, flag as “high attendance”. And anything else as “Medium”.  
  • Output the data

Output

Table Description automatically generated with medium confidence
  • 8 fields
    • Attendance Flag
    • First Name
    • Surname
    • Attendance_Percentage
    • Student_ID
    • Subject
    • Test_score
    • TestScoreInteger
  • 20 rows (21 including headers)
You can download all the output 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 @tanbir_jalil, @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