Posts tagged Dates

Week 52: Nobel Laureates, 1901 to Present

Congratulations for making it to the end of 2018 and the last workout of the year!  This week I’ve spiced things up a bit and decided to use a different data set.  The data you’ll be working with is a list of Nobel Prize Laureates from 1901 to 2018 (‘present’ at time of writing).  And I’ve chosen to use the data set to construct a timeline view.

This data set comes from a real life problem I solved recently – a way to work with multiple date columns to construct timelines.  You’ll be forced to work with the data set as-is, no reshaping the data.  And the goal is to display multiple dates as marks of different colors.  And true to form, you’ll also be constructing some custom labels, and be working on creating a drop-down that sorts both alphabetically and by dates.

I hope you’re intrigued!

Click to view interactive version on Tableau Public

Requirements

  • Dashboard size: 1000 x 1200; you choose # of sheets
  • Create a timeline showing birth date, prize date(s), death date or today
    • Death date will be a circle, today will be a gantt bar
    • Assume that each prize is awarded on December 10th of every year
  • Color the dots of the prize dates according to their category
  • Create a line that goes from birth date to death/today depending on the person
  • Construct a label that is beneath each person’s timeline – make sure it only shows up once
    • Include critical birth/death dates
  • Create reference lines for December 1901, the first year of the prize and today (which should be dynamic)
  • Create a legend that acts as a filter
  • Construct sorting for each of the following
    • Alphabetical
    • Birth date newest/oldest
    • Prize date newest/oldest
    • Death date newest/oldest
  • Match formatting & tooltips
    • I’m using Tableau Medium and Tableau Bold this week
    • Colors are from Superfishel Stone

Dataset

This week uses a special Nobel Laureates data set modified from Kaggle (to include more birthdays, and default birth dates to January 1 of the year if unknown).  You can get it here at data.world

Attribute

When you publish your solution on Tableau Public make sure to take the time and include a link to the original inspiration.

Share

After you finish your workout, share on Twitter using the hashtag #WorkoutWednesday2018 and tag @AnnUJackson@LukeStanke@lorna_eden@curtisharris_@RodyZakovich, and @VizWizBI!

Track your progress

Also, don’t forget to track your progress using this Workout Wednesday form.

Week 18: Customer Retention By Cohort and Quarter

If you’ve ever worked with web Google Analytics then you’ve probably seen the cohort analysis chart. To me its the coolest information provided. This week were back with an intermediate and jedi options. Both look basically the same but the jedi forces your thinking to a higher level!

 

Intermediate

Build a cohort analysis heat map that follows quarterly retention of customers.

click to view on Tableau Public
  • Dashboard size is 750 x 750; tiled; 1 sheet
  • Use the first order date to figure out the cohort of each customer.
  • Quarter 0 is quarter in which the first order occurred.
  • The percent is the percent of customers that had returned from the original total.
  • You DO NOT have to fill quarters with missing data.
  • Match color and formatting.

 

 

Jedi

Let’s enhance the intermediate requirements with a few additional details.

click to view on Tableau Public
  • Dashboard size is 750 x 750; tiled; 1 sheet
  • Use the first order date to figure out the cohort of each customer.
  • Quarter 0 is quarter in which the first order occurred.
  • The percent is the percent of customers that had returned from the original total.
  • Add labels for 0% for quarters where there was no customers retained.
  • Place the overall cohort average in the very top row – make sure the numbers match, too.
  • Match color and formatting.

 

Dataset

This week uses the superstore dataset.  You can get it here at data.world

 

Share

After you finish your workout, share on Twitter using the hashtag #WorkoutWednesday and tag @AnnUJackson, @LukeStanke, and @RodyZakovich.  (Tag @VizWizBI too – he would REALLY love to see your work!)

 

Track your progress

Also, don’t forget to track your progress using this Workout Wednesday form.

 

#WorkoutWednesday 2018 – Week 5

This week Andy is back with a challenge and it’s very straightforward. You need to create two quarters starting with the month selected and show months for everything else.

Requirements

  • No Level-of-Detail calculations.
  • No table calculations.
  • The Q2 value must always appear after Q1.

There are no spoilers this week.

This week utilizes the Superstore dataset. You can get it here at Data.World

As you complete this example, feel free to share on Twitter using the #WorkoutWednesday hashtag. Don’t forget to tag @VizWizBI, @RodyZakovich, and @LukeStanke. We really want to see your work.

Also, if you want your efforts throughout 2018 tracked, feel free to fill out this Google Form.

Good luck!