Preppin' Data

Challenge by Tom Prowse with collaboration with the Workout Wednesday team! This week is time for our annual get together with Workout Wednesday for a joint challenge so that you can have a full data prep to visualisation solution.  Unfortunately the Olympics was postponed in 2020, so for last year's collaboration we looked at historical winners through the history of the games. However, this year, Japan 2020 is going ahead so we thought it would be the perfect time to create an event calendar to help us keep track of the events that we don't want to miss.  Inputs The data comes from the Olympics website . ( Note; this was taken on Wednesday 14th July so the schedule for some events may have changed since! ). You can download the data here .  1. Event Schedule A list of all the event dates, times and locations throughout the games 2. Venue Details A list of all of the different venue locations Requirements Input the Data   Create a correctly formatted DateTime fiel...

 Challenge by Tom Prowse. '55 years of hurt, Never stopped me dreaming!' It was another night of pain for England fans on Sunday evening when they lost yet another penalty shootout in the European Football Championship final. This seems like it has been a common outcome for a lot of the tournaments that England have taken part in over the years, but what does the data agree?  The challenge this week is to analyse the all of the penalty shootouts in the World Cup and European Championships (Euro's) since 1976. Input Data is from Wikipedia ( World Cup & Euro's ) and is two sheets:  World Cup Euro's Requirements Input Data Determine what competition each penalty was taken in Clean any fields, correctly format the date the penalty was taken, & group the two German countries (eg, West Germany & Germany) Rank the countries on the following:  Shootout win % (exclude teams who have never won a shootout) Penalties scored % What is the most and least successf...

  Challenge by Tom Prowse. This week's challenge comes from the winner of the Prepstar award at this year's Tableau Conference and member of the SportsVizSunday team - Kate Brown .  Kate recently created a viz all about the history of the USGA Women's US Open but before creating in Tableau Desktop she had to prepare the data in Tableau Prep to make this possible.  In the viz Kate has used Polygons to create a square for each round and each year. So for this week's challenge we are going to see what data prep is required to create polygons just like in the viz! Inputs  There are two inputs:  1, US Open Winners 2, Location Prize Money Requirements Input and Join both data tables. Calculate the total par score and round par score  for each year. The par score is the predetermined number of strokes that a golfer should require to complete a round. The tournament is made up of 4 rounds, with the lowest number of shots being the winner.  Next we need to crea...

This week’s challenge is a follow-up from last week ( Week 18 ) as we want to do some further analysis! Last week we found out how many minutes each player had played. Now we want to do some analysis about what positions they were playing in, and how many goals were scored. We are again going to use the lineup data source from last week, then also add some new data sources: 1. Player List. A list of all players at Liverpool, and their preferred position group. The numbers at the start of the string is their squad number, and not the position number from the lineup table. 2. Position List.  This provides us with data about the formations that Liverpool have used, and how these player numbers mapped to positions and position types. Requirements Input the following:  Your Week 18 Workflow Player List  Position List All of these can be downloaded here . We require two outputs this week; they have been broken down here: Output 1 Calculate...

Due to the social distancing and isolation caused by Covid-19, all football games have been postponed across the majority of the world. Therefore to help fill the void, this week’s challenge is all about analysing football team line-ups and in-particular the Premier League games for Liverpool. We start with a nicely formatted spreadsheet that includes the following: Match Details - Including dates, teams, location and formation Match Day Squad - 18 players broken down into Starting XI & Substitutes Starting XI - the 11 players who started the game for Liverpool Substitutes - the 7 players who started as a substitute for Liverpool Substitution Information - Includes the Player On/Off and the Time From this we want to answer some questions about the playing time of each of the players. Requirements Input Data Update the headers for Match Details, Starting XI, Substitutes. Ideally this will be done without just renaming each individual header separately. Note, for su...