Preppin' Data

Building on from Week 1's challenge, we are going to take your data prep skills on one step further. The next steps we are introducing this week are: Aggregation - changing the level of granularity of your data. The combination of the categorical fields often sets what each row represents so aggregating data changes this. In Tableau Prep this is different from how we aggregate in Tableau Desktop. Calculations - If the value or variable that you need to use isn't in your data set, you will often be able to create it from the other data fields you do have.  As per last week, we've attached some help links that will teach you the techniques if you need a few nudges. One of the main challenges with Data Preparation is to think about not just what you want to do but the order you need to do those steps in. The challenge this week will be a good example of that to avoid repeating steps. Here's a post that might help you with your planning .  Also, thank you to all those who p

Firstly, a big thank you for everyone who has got involved with the challenge this week. The response on social media has been amazing and we have loved seeing all of the different solutions, especially across various tools. For anyone who is new to Preppin' Data, the solutions come in following parts:  Downloadable Workflow - these are Tableau Prep packaged workflows that you can download and unpick our solutions. Written Solution - a step by step blog post on how to solve the challenge. This is linked to the workflow that you can download. Video Solution - a walkthrough guide on how to solve the challenge. The written and video solutions may differ slightly as we want to show potential different ways of solving the problem.  Let's get started with 2021: Week 1's solution! Solution The solution is by Tom Prowse and you can download the workflow here . As a recap this week's challenge has a focus on cleaning data so that it's ready to answer some questions from ou

Hello World... Welcome to 2021 Preppin' Data.  Since Jonathan (@JonathanAllenby) and I chatted by a coffee machine in Feb 2019, we along with Jenny Martin (@JennyMartinDS14) and Tom Prowse (@TomProwse1)  have produced 99 challenges to date, completed by 305 different people, who have solved the challenges 2,424 times (that we know of!).  The overall aim of Preppin' Data is to give people a place to learn the power of being able to prepare your own data sets (rather than relying on others) and the capabilities of Tableau Prep. If you want to know more, check out our first post . For those of you who are new to Preppin' Data, here are some basics: We release a new challenge each Wednesday We post a written and video solution the following Tuesday We build our challenges in Tableau Prep but welcome solutions from any other tool too.  One change this year is Jonathan is taking a step back from the challenges but will come up with a tricky problem every now and then I am sure.

  Solution by Tom Prowse and you can download the full workflow here .  The final challenge of 2020 was based on the introduction of a new star sign, Ophiuchus. We compared how the dates have now changed and if your star sign has changed based on your date of birth. Step 1 - Input Data The first step this week is to ensure that we have input our data correctly. As the initial inputs don't have headers and the data starts on the very first row, we need to ensure that we have selected the 'Generate Field Names Automatically' option within the input settings:  Once we have selected this, our headers are now F1, F2 etc therefore we need to update the names so that it's easier for us to understand going forwards. The naming changes look like this:  Old Star Signs    New Star Signs   Step 2 - Pivot Old Star Signs The first step is to remove any null values that have been picked up from the input, we can just exclude these.  Next, we want to pivot the data so that all of the S

Challenge by: Jenny Martin 2020 - what a year! Much has changed, few things have stayed the same. Even our star signs weren't safe! The introduction of a 13th star sign, Ophiuchus, threw things into disarray. Were you born on a day where your star sign has remained unchanged? Let's make a list of all those affected by the changes. Just a quick thank you for those who have stuck with us in 2020, those who joined us in 2020 and all who learnt something new about Prep!  Inputs Old Star Signs and Date Range  New Star Signs and Date Range  Handy Date Scaffold  Requirements Input the data . Be careful your data isn't mistaken for a header. Reshape and clean up the data so you have a column for the star sign, along with the start and end dates. Create a date range for the new star signs. Scaffold the data so you have a row for every date of the year (2020 is a good year to base this off, since it's even a leap year!) For the output, we're looking for a list of dates that h

  Solution by Tom Prowse and you can download the full workflow here .  This week's challenge was from community member Kate Brown who created this workflow so that she could clean and prepare some data so that it was ready for her to make a viz that included Polygons. Let's take a look at how she solved it! Step 1 - Join Tables Our first task is to clean some of the field names from the US Open Winners table so that we have a better understand of what the fields refer to going forwards. We want to make the following field name changes:  Pos to Position player to Player to par to Total to Par round 1 to Round 1 round 2 to Round 2 round 3 to Round 3 round 4 to Round 4 total to Total  year to Year  Also, from the Location table, we don't need to include the Score or To par fields so these can be removed.  Once we have made these changes to both tables, we are ready to join these together using the following join conditions:  Step 2 - Calculate Par Now we have combined both ta