2019: Week 19

Chin & Beard Suds Co. is growing from strength to strength and this has led us to think big - sponsorship!

As a keen road cyclist, I use a lot of soap to stay clean from wet, muddy and sweaty rides so the sport choice was obvious. The event to sponsor was even more so... the Tour de France! It starts in a couple of months so the only remaining question is which team? 

What we are looking for in the team to sponsor is a team that works really hard (ie are sweaty!) but are all consistently doing well as we don't want riders sponsoring our soap at the back of the pack or worst "slipping" off the back of the peloton. 

Requirements


Using the results from letour.fr of last year's race we want you to find the team for us to sponsor. The team must:
  • Use the 2018 Tour de France results as your input
  • Make all time fields seconds before doing any of the calculations (we like precision at C&B Suds Co.)
  • Have seven or more riders complete the tour
  • Must average 100 minutes or less behind the leader as a team

Output



  • List of the teams that meet the requirements
  • A file that contains the number of riders and avg. minutes behind the leader
  • 3 columns
  • 2 rows (3 including the header)
Here's our output for comparison. As always, feel free to share your results and methods on Twitter using the #PreppinData hashtag and please don't forget to fill out the progress tracker!

Popular posts from this blog

2024: Week 1 - Prep Air's Flow Card

Image
Created by: Carl Allchin Welcome to a New Year of Preppin' Data challenges. For anyone new to the challenges then let us give you an overview how the weekly challenge works.  Each Wednesday the Preppin' crew (Jenny, myself or a guest contributor) drop a data set(s) that requires some reshaping and/or cleaning to get it ready for analysis.  You can use any tool or language you want to do the reshaping (we build the challenges in Tableau Prep but love seeing different tools being learnt / tried). Share your solution on LinkedIn, Twitter/X, GitHub or the Tableau Forums Fill out our tracker so you can monitor your progress and involvement The following Tuesday we will post a written solution in Tableau Prep (thanks Tom) and a video walkthrough too (thanks Jenny) As with each January for the last few years, we'll set a number of challenges aimed at beginners. This is a great way to learn a number of fundamental data preparation skills or a chance to learn a new tool — New Year...
Read more

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 u...
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