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2019 Week 11: Profit: Where? and What?

This weeks Workout Wednesday, has lots of hidden tricks and tips inside. But I want you to mainly focus on a specific part. Sorting in Tableau can be a bit of a pain, it has gotten much better with nested sorting. But this challenge allows you to sort A – Z, Z – A, Profit Asc and Profit Desc, now how do you do that?

I also still love Viz in Tooltips, the novelty certainly hasn’t worn off. So this week I focused on a heavily formatted Viz in Tooltip.

Challenge

Click to view on Tableau Public

Requirements

    • Size 600 x 1000 px, 5 sheets.
    • Create a Map which shows Profit by state and Cities sized and coloured by profit
    • Create a City, Abbreviated State (Calc below) by profit.
    • Create a parameter that allows you to sort City, State by A – Z, Z – A, Profit Asc, Profit Desc.
    • Create a Viz in Tooltip
      • City, State and Profit
      • Sub-Category Profit
      • Match all Formatting
    • Use the map to filter by STATE
    • Match all formatting, titles, text and colours.

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.


Abbreviation Calculation

CASE [State]
WHEN "Alabama" THEN "AL"
WHEN "Alaska" THEN "AK"
WHEN "Arkansas" THEN "AR"
WHEN "Arizona" THEN "AZ"
WHEN "California" THEN "CA"
WHEN "Colorado" THEN "CO"
WHEN "Connecticut" THEN "CT"
WHEN  "Delaware" THEN "DE"
WHEN "District of Columbia" THEN "DC"
WHEN "Florida" THEN "FL"
WHEN "Georgia" THEN "GA"
WHEN "Idaho" THEN "ID"
WHEN "Illinois" THEN "IL"
WHEN "Indiana" THEN "IN"
WHEN "Iowa" THEN "IA"
WHEN "Kansas" THEN "KS"
WHEN "Kentucky" THEN "KY"
WHEN  "Louisiana" THEN "LA"
WHEN "Maine" THEN "ME"
WHEN "Maryland" THEN "MD"
WHEN "Massachusetts" THEN "MA"
WHEN "Michigan" THEN "MI"
WHEN "Minnesota" THEN "MN"
WHEN "Mississippi" THEN "MS"
WHEN "Missouri" THEN "MO"
WHEN "Montana" THEN "MT"
WHEN "Nebraska" THEN "NE"
WHEN "Nevada" THEN "NV"
WHEN "New Hampshire"	THEN "NH"
WHEN "New Jersey" THEN "NJ"
WHEN "New Mexico" THEN "NM"
WHEN "New York" THEN "NY"
WHEN "North Carolina" THEN "NC"	
WHEN "North Dakota" THEN "ND"
WHEN "Ohio" THEN "OH"
WHEN "Oklahoma" THEN "OK"	
WHEN "Oregon" THEN "OR"
WHEN "Pennsylvania" THEN "PA"
WHEN "Rhode Island" THEN "RI"
WHEN "South Carolina" THEN "SC"
WHEN "South Dakota" THEN "SD"
WHEN "Tennessee" THEN "TN"
WHEN "Texas" THEN "TX"
WHEN "Utah" THEN "UT"
WHEN "Vermont" THEN "VT"
WHEN "Virginia" THEN "VA"
WHEN "Washington" THEN "WA"
WHEN "West Virginia" THEN "WV"
WHEN "Wisconsin" THEN "WI"
WHEN "Wyoming" THEN "WY"
END

2019 Week 7: What gifts do people plan on spending money on?

Valentine’s Day is officially tomorrow.

This data set looks at percentage of people buying a particular gift. This week I wanted to focus in on building a few things; using the button functionality, sheet swapping and finally a radar chart (because why not). Many Many people have been waiting for the button functionality and I haven’t had a use case to use them since they came out, and because I can’t use them at work due to being a couple of versions behind. Sheet swapping is a great little trick that I use regularly, it allows you to see the same data in different ways and finally I recently built a radar chart as a personal profile for a business dashboard with 20 segments, but the same calculations apply.

Requirements

  • 2 Dashboards (800×800), 6 sheets.
  • 1st Dashboard
    • I want to see Tableau’s Love Heart Radar Chart. With a parameter to change the text at the bottom
    • This contains the first button to the next dashboard
    • Button image can be found in Your Tableau Repository, Shapes, Arrows
  • 2nd Dashboard
    • A parameter to enable users to change between Radar and Line Chart
    • A custom made legend only showing when Radar is selected
    • Each POLYGON is a Year, and each point is an Item
  • Match Colours, Fonts and Formatting.

Dataset

This week uses 2019 Valentine’s Day Survey from NRF .  You can get it here at data.world. Here is the original article

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

Use this blog post for advice on building Radar Charts

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 51: Container Fun!

Ok, this week is all about working with Containers. Now that we have the ability to control inner/outer padding on Dashboard objects, as well as color, we can really make our dashboards shine without having to float everything. Note on the week, the data/charts don’t really matter, I honestly just threw some on the dashboard. The challenge is about working with the containers, and matching the design given the requirements below. Good luck!

CLICK TO VIEW

 

Requirements

  • Dashboard size is 1250px wide by 750px tall.
  • ONLY USE CONTAINERS, NO FLOATING OBJECTS!
  • Dashboard has a total of 5 containers (no more, no less)
  • The Filter Pane.
    • 10px padding on the right/left side.
    • Each filter has 5px of padding
  • The Charts Pane.
    • All 3 charts must be in one vertical container
    • Background must be light grey
    • Each chart has 20 px of padding between them and other objects
    • Each chart has a grey border, slight darker than the Pane background color.
  • The Pane under the Title has a grey border.

Dataset

You can use any data set for this week’s challenge. but  you can get Superstore 2018.3 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.

Week 50: What is the makeup of sales?

This week is another challenge that comes straight from work. I actually had difficulty creating the chart I wanted. I really wanted to sort the states by the selected Sub-Category percentage but I ran out of time and had to hack together a solution for this week. Either way the more important challenge is in creating the appropriate pie chart.

Challenge

Click to view on Tableau Public

Requirements

  • Dashboard size is 800px wide by 800px tall.
  • Create a pie for each state
  • Use a parameter that describes each sub-category.
  • Highlight the sales of the selected sub-category. Also highlight the remaining sales for the remainder of sub-categories that are share the same category of the selected sub-category. The third category will be all other sub-categories.
  • Color by category. Use the Winter and Seattle Gray color palettes.
  • Jedi-level: no hard-coding category to sub-category.
  • Create the legend using a separate sheet.
  • 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.

Week 45: Cross-Highlight

Continuing in line with Ann, I thought it would be great to do another challenge around Set Actions. I’ve used “Cross-Highlighting” in Tableau before, but it required a lot of Data Modelling, and was extremely slow on the Public Servers. But with Set Actions, what use to be a very complicated task, can now be down very quickly. There are a lot of great analytical powers with Set Actions, but there are some nice UX ones as well.

https://public.tableau.com/views/Cross-Highlight/CROSS-HIGHLIGHT?:embed=y&:display_count=yes&publish=yes

Requirements

  • Dashboard size: 520 x 560; 1 sheet
  • Create 2 Parameters
    • Y Axis: Category and Sub-Category
    • X Axis: Region and Segment
  • Create a Crosstab that shows Sales based on the Parameter Selection
  • ***On Hover*** highlight all values in the same Y/X column as the mark being hovered over.

FYI: Set Actions aren’t quite working on Tableau Public, so I encourage you to download the workbook and view in 2018.3 to explore the full interactivity!

Data from this week comes from the Saved Data Source in Tableau 2018 (Sample – Superstore), download here if needed.

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

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

Week 44: Ready, Set: Let’s Drill Down on Sales!

At time of writing Tableau 2018.3 was just released.  With it comes some brand new features, including the one that’s the focus of this workout: set actions.  Sets have long been a feature in Tableau and are responsible for creating dashboard actions, but set actions are something completely new.  Set actions allow you to interact with your data to determine what data elements are part of the set, essentially sets become more dynamic.

One of the most straightforward uses of set actions is one that was demonstrated during Devs on Stage at TC18 – drilling down on the same sheet.  They showed a video that included drilling down on a treemap from one level of detail to a lower granularity, to a third granularity.

So my challenge for you this week is to learn more about sets and set actions.  You’ll find these to be extremely useful moving forward on drill-filtering on the same sheet – both on maps and when you’re trying to explore more detail.  Not a lot of showy formatting or sophisticated calculations – your only goal is to get comfortable with set actions.

click to view on Tableau Public

Requirements

  • Dashboard size: 1200 x 800; 2 sheets
  • Create a line chart of monthly sales
  • Create way for user to select months and drill/filter the line chart, this should also filter the treemap below
  • Create a treemap of sales by category that has the ability to drill to sub-category and product name upon clicking
  • Create dynamic labels (and tooltip) for the treemap that display based on the level of detail shown (category/sub-category/product name)
  • Match all other formatting, labels, and tooltips
  • Add a region filter for fun

FYI: Set Actions aren’t quite working on Tableau Public, so I encourage you to download the workbook and view in 2018.3 to explore the full interactivity!

Data from this week comes from the Saved Data Source in Tableau 2018 (Sample – Superstore), download here if needed.

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

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

Week 43: Where should we focus our sales effort? #TC18 Edition

Heads up: we are at Tableau Conference and we’ll be delayed on checking Twitter. Also Luke will attempt to live stream via Twitter.

Challenge

This week we take Workout Wednesday live at Tableau Conference.


Click to view on Tableau Public

Requirements

  • Create a map and color the overall top, top 5, bottom, bottom 5 states by sales.
  • Label the top 5 and bottom 5 states.
  • Add a filter for segment.
  • Show the city with the top sales for every state.
  • Place a star on the top 5 cities. Place an x on the bottom 5 cities. Place a circle on all other cities.
  • Size the star to be the largest, then the x, then the circle.
  • Match map formatting.
  • Match tooltips.

Dataset

This week uses the superstore dataset for Tableau 2018.1.  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.

Week 42: Radial Mapping

Getting a little bit tricky this week, mostly because I won’t be at TC this year….. 🙁

This week we are going to do some radial mapping in Tableau. While extensions might replace this trick, I think it’s still useful when analyzing locations within N miles of a target location.

Click Image for Interactive Version
(Click for Interactive Version)

Requirements

  • This is a tricky one, so the first thing you want to do is get all the Lats/Longs for City/State from SuperStore and create a new dataset with it. You need to be able to use the Lats/Longs in calcs, and we can’t use generated lat/longs at the moment.
  • Create a Parameter for City/State
  • Create a Parameter to set the number of miles
  • Create a Map of Sales for City/State sized by Sales
  • Draw a Radial Circle around the selected location that has a radius equal to the Miles Parameter.
  • The Map should be filtered down to only show locations within the Radial Circle
  • This does require some data modelling…if you get stuck, check out my blog post on radial mapping.http://www.datatableauandme.com/2017/12/radial-mapping-in-tableau.html

Dataset

This week uses the superstore dataset for Tableau 2018.1.  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!)

Week 36: Scatter Plot Reference Bands

Hello again everyone! This week we are looking to add Reference Bands to our Scatter Plots in order to “group” together like items. Looking at NBA Players Total Games and Points spread.

Click to view interactive version

Requirements:

  • Dashboard size 920 x 825
  • Players are grouped into 5 bins by Avg Points per Game
    • 10-14, 15-19, 20-24, 25-29 and 30-34+
    • Must create an interactive legend on the top right that can be used in a Dashboard Highlight
  • The “Bands” are based on these bins from the Minimum number of points over X games to the Maximum number of points over X games.
  • The Y Axis (Total Points) is fixed at 17,980 to 39,900 | The X Axis (Games) is fixed at 715 to 1667
  • By default, the Top 10 Players (by points scored) will have Text Labels with their Rank, and name
  • When highlighting players using the Points Bin Legend, only show Text Labels for the players in that bin
  • Players that are marked as “active” should have a circle with an outer ring to separate them from inactive players.

Data from this week comes from Basketball-Reference via Jeff Planter. You can download the aggregated data here

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!)

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