Posts in Workout Wednesday

2019 Week 8: What percentage of products make up 80% of sales?

For this week’s workout, we look at one of my favorite chart types, the pareto. I love the pareto chart as a data exploration resource, and also as a powerful analytic resource. If you aren’t familiar with the pareto, the purpose is to see what % of x, makes up what % of y, with the common assumption that 20% of the x makes up 80% of the y. This week’s workout takes this chart a couple steps further by identifying the point where the % of x crosses 80% of the y. We will also give our users the power to drill into the actual values of any subset of the x. A key piece of this challenge is using Tableau’s built in functionality to your advantage, try and build this viz with two or less written calculated fields!

Have fun!

Requirements

  • Dashboard size is 1200×500 – 2 sheets
  • Place a circle on the mark where the % of Total Products crosses the 80% of Total Sales threshold
  • Place a reference line at 80% of Total Sales and 20% of Total Products
  • Use Tableau’s out of the box features – only two written calculated fields allowed
  • Dynamically show/hide selected products from the pareto chart
  • Make sure there is 15px of inner padding on all sides of your worksheets, and the left and right sides of your title and line separator
  • Match colors, tooltips, fonts, and formatting

Dataset

This week uses the superstore dataset for Tableau 2018.3.  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 #WorkoutWednesday2019 and tag @AnnUJackson@LukeStanke@lorna_eden, and @curtisharris_!

Track Your Progress

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

2019: Week 6: Weekly Orders & Sales by Segment

Those of you who know me well know that I like to create visualizations that include both detail and aggregate in the same view.  I have a particular interest in showing how the smaller components contribute to the overall.  When there’s one major chart on a dashboard I think it works out particularly well – keeping high level attention focused on the macro data shapes, but providing exploratory capabilities in the micro.

This week’s workout is also a little more on the arty side.  The original inspiration for this comes from something I built at work, but once I retooled it using Superstore I was struck by how the result looked like trees.  To add to the whimsy, I’ve included tree trunks which contribute to the overall look/feel and provide the macro details.

But don’t be fooled, although this viz looks pretty, it’s packed with some real takeaways that I’m confident you’ll be able to take back and implement at work.  You’ll want to pay close attention to the viz in tooltip.

Click to view on Tableau Public

Requirements

  • Dashboard size: 1300 x 800, 2 sheets – one for the main viz and one for the VIT
  • Create a tree plot that shows individual orders by week
    • Size of order = sales
    • Circles sorted by sales
    • Make trunk that is the # of orders for the week/segment
  • Create a highlight table VIT with a order summary
    • Sales and quantity by subcategory
    • Sales should have more orange = more sales
    • No color for quantity
  • Include a Region filter (to see the beautiful forests change)
  • Match any additional formatting and tooltip language

Dataset

This week uses the superstore dataset for Tableau 2018.3.  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 #WorkoutWednesday2019 and tag @AnnUJackson@LukeStanke@lorna_eden, and @curtisharris_!

Track Your Progress

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

2019 Week 5: Where are the biggest discounts?

I recently put together this chart for work. I spent more time making it amazing than I am willing to admit, this is mostly due to the amount of formatting I did. I thought I’d make a formatting challenge this week!

Challenge


Click to view on Tableau Public

Requirements

  • Format: 540px by 800px
  • Create a heat map of average discount by sub-category and region.
  • Labels for region should be below the heat map tiles.
  • Use Tableau Light, Size 7 for the tile labels.
  • Use Tableau Light, Size 8, Color #555555 for the column and row labels.
  • Sort sub-categories within each category by average discount.
  • Use Tableau Medium, Size 9, Color #898989 for the category header label.
  • Add bars above and to the right of the heat map indicating the average discount for sub-category and region.
  • The bars should be approximately 2px away from the heat map tiles.
  • Make sure the bar sizes are identical.
  • Add labels to the right of the bars for the bar chart to the right of the heat map.
  • Add labels above the bars to the bar chart above the heat map.
  • Use Tableau Light, Size 9, Color #555555 for the bar labels.
  • Set the color range for all objects to be between 0% and 50%.
  • Create a custom sequential color palette. Use #4A4E68.
  • Add just a tiny amount of white space between each heat map tile (~1px).
  • Add a divider between categories for the entire visualization set. Use #D4D4D4.
  • Add padding of 80px to the left of the visualizations and 50px to the right.
  • Dataset

    This week uses the superstore dataset for Tableau 2018.3.  You can get it here at data.world

    Share

    After you finish your workout, share on Twitter using the hashtag #WorkoutWednesday2019 and tag @AnnUJackson, @LukeStanke, @lorna_eden, and @curtisharris_!

    Track your progress

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

    Attribute

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


2019 Week 4: Headcount Tracking

Hello and welcome to week 4 of Workout Wednesday 2019, and my first contribution as an official team member! This week’s challenge should be on the easier side, and forces us to think a little bit about data prep, before we get to producing our Workout Wednesday visualization.

I was recently challenged at work to product additional rows of data between two dates, all while staying within the confines of Tableau. Assuming you don’t have Alteryx, SQL skills/tools, or other data prep tools… how would you use Tableau and every day applications (Excel, Google Docs, etc) to enhance your data set? For this week’s challenge, I want you to use Tableau Desktop’s data source page to enhance your base data set. Keep an eye on the number of records, it is a key requirement this week!

Click image to view on Tableau Public

Requirements

  • Data prep requirements
    • I’ve provided a scaffold of dates in the file that should be used to extend the employee level data
      • Using the data source page, combine the employees data and the dates data into a single data source
      • Important… bring in only dates that fall between an employee’s hire date and termination date. If an employee has no termination date, use today’s date. Example: employee 2 should have 141 records before extracting (every date between 3/1/2018 and 7/19/2018)
      • Your final extract should have exactly 5,947 records
  • Dashboard requirements
    • Dashboard size: 1000 x 600, and should contain no more than 3 sheets
    • Create a summary number that represents how many active employees we have on the latest date left in the data after data prep is complete
    • Create a line and dot combo chart with a mark for every day. When there are gains in employees, highlight that date with a gray circle. When there are losses in employees, highlight that date with a red circle. Size the circles by the absolute volume of the gain/loss.
    • Create a volume chart below the line chart that shows employee gain/loss by day
    • Match formatting, colors, and tooltips as closely as possible
      • Note the positive, neutral, and negative number format in the tooltips. Gains should be displayed as +n, 0 gain/loss days should be displayed as 0, and losses should be displayed as -n. Do not create three fields to accomplish this behavior.

Dataset

This week uses fake headcount data stored in Google Drive.  Connect to the data in Tableau by using the Google Sheets connection, and this link: https://docs.google.com/spreadsheets/d/1DO9bKM4dFVc4q_cID3VACoxVn3mQ5ipbd8owNXXprrY/edit?usp=sharing

Attribute

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

2019 Week 3: Rugby League 2018 Home v Away

I am super happy that I have joined the team for Workout Wednesday and I am ready to set you some challenges. Sometimes people struggle using text only files. This week’s challenge will, hopefully, give you some ideas on how to use text only files.

Some of you may know that I am a big Rugby League fan, so I thought this would be the perfect opportunity to use my Rugby data. This weeks challenge is looking at Home v Away wins. I wanted to see which teams Win at home or Win away, or even both. With this chart I can easily see the number of Home and Away Wins, plus the losses and draws, and also with a running total of wins, draws and losses.

Click image to view on Tableau Public

Requirements

  • Dashboard size: 1000 x 900. Only TWO sheets!
  • Each point is a Round.
  • Home games are UP and Away games are DOWN.
  • Scores: Win = 3, Lose = 1 and Draw = 2
  • Colour based on Win, Lose and Draw.
  • Lines are a running total of Win, Lose and Draws per team.
  • Teams are sorted by Total Wins.
  • Labels show Percentages related to Wins and Losses only. For Total, Home and Away.
  • Create a Legend so show how to read.
  • Match Colours, Formatting and Tooltips.

Dataset

This week uses Rugby League Data. 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 #WorkoutWednesday2019 and tag @AnnUJackson@LukeStanke@lorna_eden, and @curtisharris_!

Track your progress

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

HINTS

  • The legend is based upon my Favourite Rugby League Team

2019 Week 2: Order Sales Spread by Region

Happy New Year!  It’s time for my first Workout Wednesday of 2019 and I hope you’re ready for a challenge.  This week I’ve decided to take inspiration from a trick or two from past workouts and combine them with some recent work I’ve been doing.  To be more specific, one thing about Tableau that I like is that you can set independent axes for continuous measures if you’ve got headers on the same shelf (rows or columns).  But what if you wanted to have independent axes and headers aren’t on the same shelf?  The workout this week explores that idea and puts it to the test – I’ll be honest, the jury is still out for me on if this works well with the Superstore data set, but I can absolutely see value in this if we were to have a similar metric with extremely varied ranges.

In addition to exploring how to get over that obstacle, I also wanted to play around with date filtering.  This week you’ll be exposed to a user-friendly calendar that doubles as a filter OR highlighter.  I’ve found that it represents a great way for end users to freely pick a single date, multiple dates, date ranges, random individual dates – pretty much any combination that they would like.  Calendars are also familiar visualizations of dates, so I think it’s quite comforting – and additionally it serves as another layer of information – when there isn’t any data, there isn’t a square for the date.

 

click to view on Tableau Public

Requirements

  • Dashboard size: 1200 x 800, jitterplots must be one sheet, everything else is up to you
  • Create a jitterplot that shows sales by order ID (no need to worry if your jitter isn’t exactly the same as mine)
    • Ensure that each plot behaves as if it has an “independent axis” and spans the extent of data within each region
  • Create a calendar view that can be used as a filter or a highlighter
    • When used as a filter, chosen dates will filter the jitterplot
    • When used as a highlighter, chosen dates will change to a darker color in jitterplot
  • Create a footnote that is responsive to the date selection
  • Create average line & callout that are responsive to date selection
  • Match colors & tooltips please 🙂

Dataset

This week uses the superstore dataset for Tableau 2018.3.  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.

2019 Week 1: Sales Drill Down

We’re back for 2019. We’re using the hashtag #WorkoutWednesday2019. The challenge this week involves building a dynamic drill-down table. This one is slightly more difficult than average so be sure to check the spoilers at the very bottom if need be.

Challenge

 


 

Click to view on Tableau Public

Requirements

  • Dashboard size is 500px wide by 600px tall.
  • Create a table that shows sales for category and year. When you click on a category show the sales by sub-category below it.
  • Use the right arrow “►” and the down arrow “▼” to indicate when details are showing. This makes it look like an accordion.
  • Match row borders and row shading to highlight these values.

Dataset

This week uses the superstore dataset for Tableau 2018.3.  You can get it here at data.world

Share

After you finish your workout, share on Twitter using the hashtag #WorkoutWednesday2019 and tag @AnnUJackson, @LukeStanke, @lorna_eden, @curtisharris_, and @VizWizBI!

Track your progress

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

Spoilers

  • Union the data to itself one time.
  • One part of the union will create the summary for category and the other will create the summary for sub-category.

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 49: Where Do Sub-Categories Succeed?

Last week I had the honor of attending Tapestry Conference in Miami.  While I was there Jon Schwabish gave a quick 6 minute talk that connected every chart to every other chart.  This along with some of Elijah Meek’s keynote mentioning that data viz is getting more custom and funky got me curious about some neglected chart types.  Combine this with a recent interest in how clustering works in Tableau and you’ve arrived at the genesis for this week’s challenge.  Your goal is to create a Parallel Coordinates chart (click the link if you’re not sure what it is).

This chart is perfect for multivariate analysis and seeing relationships among more than 2 measures (in this case 3).  It can also be useful for finding commonalities among things.  Traditionally I think most people may shy away from implementing this in Tableau because quite often different measures have different scales, so as part of the challenge, you’ll have to figure out how to overcome that obstacle to present a parallel coordinate chart with 3 measures of different magnitudes.

Also to help reinforce some recent challenges using table calculations – you are not allowed to use LODs and must only use table calculations and regular calcs.

Click to view on Tableau Public

Requirements

  • Dashboard size: 1200 x 850; you choose # of sheets
  • Create a parallel coordinate chart that shows Sales, Profit Ratio, and # Customers (CountD Customer Name) per sub-category
  • Do not use LODs, use table calculations (and normal calculated fields)
  • Each sub-category should be positioned based on its value, but all measures should be on one sheet
  • Ensure there is a dark gray vertical line for each measure
  • Label the top and bottom of each vertical line with the measure name and respective minimum or maximum
  • Color the lines based on which measure the sub-categories have the highest value in
  • Colors are based off of the Viridis color palette, which I encourage you to paste into your .TPS file
  • Create a color legend that has a hover action based on the newly defined colors (high sales, high profit ratio, high customers)
  • Match formatting & tooltips

Dataset

This week uses the superstore dataset for Tableau 2018.3.  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 48: Profitability Bridge

This week we’re building a chart I was asked to create at work. A stakeholder drew this exact chart type and said, “make the chart look exactly like this!” At first glance I wasn’t sure I would be able to do it. After a little playing around I was able to re-create it!

Challenge

Click to view on Tableau Public

Requirements

  • Dashboard size is 500px wide by 800px tall.
  • Create a waterfall chart showing the top 5 sub-categories by sales. Include an other category for all other categories.
  • Show a bar on the far-left of the waterfall that shows all sub-categories. Label it all.
  • Add dashed lines that “connect” each bar.
  • Add a dashed line that connects the All bar with the Other bar.
  • Make sure each line looks as a single continuous dashed line. Watch your padding and axis label width!
  • Label each sub-category above the bottom line of each bar.
  • Label each bar with the profit ratio below the bottom line of each bar.
  • Add a filter by region. Make sure the filter is centered on the dashboard above the chart.
  • Color the bar gray if it above zero (#ACBAC3) or pink if it is below zero (#E48070).
  • Match tooltips.

Dataset

This week uses the superstore dataset for Tableau 2018.3.  You can get it here at data.world

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.