Tag: Scatter Plot

Let’s Build a Map!

Donna ColesLeave a comment

Inspired by a viz from Klaus Schulte, Sean Miller set this week’s challenge to recreate a hex map with state shapes using Superstore.

Building the data model

I referenced this Tableau blog post and downloaded the HexmapPlots excel file included. I then used a relationship to ‘join’ the Sample – Superstore excel file I was using with the HexmapPlots file, joining on State/Province = State

Since I had the other blog post already open, I then followed the steps included to start building the map.

Building the hex map

Add Column to Columns and aggregate to AVG, and add Row to Rows and also aggregate to AVG. Add State/Province to Detail. Edit the Rows axis and set to be Reversed.

Note – it’s possible you may have extra States showing. As I’m writing I’ve realised I’m rebuilding against an extracted data source that has a filter I originally applied as a global filter, which has now been included in the extract. So you may need to add State/Province to the Filter shelf, and set to exclude NULL and District of Colombia. This filter will need to be applied to all sheets you build.

Change the mark type to Shape and select a Hex shape. I already have a palette full of Hex shapes, but the blog post provides a shape to use and add as a custom shape if you haven’t got one. Increase the size of the marks.

Create a new field

Profit Ratio

SUM([Profit]) / Sum([Sales])

format this to % with 1 dp, and then add to the Colour shelf.

Now add a second instance of Row to the Rows shelf and set to AVG again. Set the mark type of this marks card to Map. Remove the Profit Ratio field from Colour on this card too. Assuming your Map location is set to USA, you should have State outlines depicted (Map -> Edit Location).

Set the chart to be dual axis and synchronise the axis. The State shape axis should now be inverted. Independently adjust the sizes of the Hex shape and the state shapes, so the states sit inside the hexagons.

Right click on the right axis and move marks to back. The adjust the Colour of the hex shapes so its around 85% transparent.

Now adjust the Tooltip on the hex marks to match the requirement.

To fill-out the available area, I also chose to fix both the axis (right click axis -> edit axis). The Column x-axis I set to range from 1 – 12, and the Row y-axis, I set to range from -0.9 – 9. Then hide all axis, and remove all row/column gridlines, divider lines, axis lines and zero lines. Hide the 10 unknown indicator, and set the background colour of the whole worksheet to a pale grey.

Building the Line Chart

This is super simple, Tableau 101 🙂

Add Order Date to Columns and set to be a continuous month (green pill showing month-year). Add Sales to Rows. Change the colour of the line to grey. Hide the x-axis and remove all gridlines, dividers, axis lines and zero lines. Set the background colour of the worksheet to None (ie transparent). Update the tooltip.

Building the Scatter Plot

Add Sales to Columns, and Profit to Rows. Add State/Province to Detail shelf and add Profit Ratio to Colour. Change the mark type to circle. Remove all gridlines, row column dividers and axis rulers. Only the zero lines should remain. Adjust the tooltip and set the worksheet background to None (transparent).

Putting it all together

Create a dashboard and set the size as stated. Set the background of the dashboard to pale grey (Dashboard – > Format).

Add the Hex map, and hide the title. Click on the Profit Ratio legend object and set to be floating. Then remove the right hand vertical container. Move the Profit Ratio legend to a suitable location.

Then add a text box as a floating object and use it to create the title. Add both the trend line and the scatter plot charts as floating objects without titles. Just position them as required. You can always use gridlines (Dashboard -> Show Grid) to help you line things up.

Finally add the interactivity.

Add a highlight dashboard action which highlights the hex map and the scatter plot when either of the other is selected ‘on hover’, and just targets the State/Province field.

Then add a Filter action which on hover of the Trend chart, targets the remaining charts.

And hopefully that’s it. My published viz is here.

Happy vizzin’!

Donna

Can you use Tableau to estimate Aaron Judge’s home run trajectories?

Donna ColesLeave a comment

It’s community month still for #WOW2022, and this week saw Samuel Epley set this challenge to visualise the home run trajectories of Aaron Judge.

I had a little mini-break to Rome this week, so was hoping I was going to be able to get this week’s challenge done and dusted on the Tuesday evening if it landed early enough, as I wasn’t going to be around.

It did land on the Tuesday for me, but wow! it was not going to be easy! I managed to build the KPIs & the scatter plots on the Tuesday evening, and knowing I didn’t have much time, just chose to use the Home Runs stats data set only. I knew these charts weren’t going to need any data densification, so found this approach simpler.

I’m afraid I’m still constrained by time at the moment, so this post isn’t going to be the detailed walkthrough you might usually expect – sorry! I’m just going to try to pull out key points from each chart.

KPIs

I built this on a single sheet, using Measure Names and Measure Values.

I used aliases on the Measure Names (right click -> Aliases) to change the label you can see displayed ie the Distance pill is aliased to ‘Average Distance’

I also custom formatted the various numbers and applied suffixes to display the unit of measure

Note – to To get the degree symbol, I typed Alt+ 0176

Scatter Plots

I built the Exit Velocity by Distance scatter plot first, and completed all the formatting & tooltips. Then I duplicated the sheet to form the basis of the other scatter plots, and just swapped the relevant pills as needed.

For the ball shape, I loaded the provided images as custom shapes into my shapes repository. I then just created the following calculated field to use as a discrete dimension I could add to the Shape shelf

Ball Shape

[HR Number]%9

It’s not as completely randomised as perhaps it should be, but it looks random enough on the display.

The Pitcher in the data is in the format <Surname>, <Forename>, but on the tooltip it needs to display as <Forename> <Surname>, so I just used a transformation on the Pitcher field to split the field based on the comma (right click Pitcher -> Transform -> Split). This automatically created 2 fields I could use on the Tooltip.

I also noticed a very subtle wording change in the tooltip based on whether the match was Home or Away. If Home, the tooltip read ‘New York Yankees vs. <Opposition>’ otherwise it read ‘New York Yankees at <Opposition>’. I used a calculated field for this logic

TOOLTIP: vs or at

IIF([Location]=’Home’,’vs.’, ‘at’)

The Trajectory Plot

OK, so this was the hardest part of this challenge, and mainly due to getting your head round the physics involved, as so many of the calculations are dependent on each other.

I’m generally pretty confident with my maths, but this was complex, especially with the force calculations for the y-axis. Samuel stated that both gravity and drag impacted the Y-axis calcs, but it wasn’t clear to me how both these forces should be applied (a bit of trial and error and I ended up adding them within the formula).

By the time I came to tackle this challenge, Samuel had already posted a video walkthrough, which can be viewed here and is another reason why I’m not going down to the nth degree in this post.

My suggestion is to watch Samuel’s video and/or feel free to download my workbook. I built my workbook independent of Samuel’s video, so there may be steps/calculations that differ.

However, I have tried to number my calculations in the order in which I created them, so you can hopefully follow the thought process. I have also left a CHK:Data sheet in the workbook, which I used to sense check what I was doing.

All the table calculations in the CHK:Data sheet are just set to the default ‘table down’ as I have filtered the sheet to a specific Home Run (HR Number = 1) only (ie I didn’t change any of the table calc settings as I added the pills to the sheet).

However, when you build the main trajectory chart, you have multiple HR Numbers in the view, so all the table calculations must be set so that calculations are only working for each HR Number. This means that any table calc (and any nested calculations) need to have all the fields except HR Number checked

When using the Pages shelf, which isn’t something I’ve ever really had to do before, you need to Show History and adjust the various settings to get the trail lines to show

To rotate the ball (the bonus option), you need another field to use on the Shape shelf. I had lost the will to live a bit by this point, so used the formula from my friend Rosario Gauna’s solution.

Rotation Shape

STR(IIF([14-Start Position Y m] <= 0, 0,
(MIN([Time Interval]) * 1000 / 25) % 9))

Note – when you add this to the Shape shelf, and select your baseball palette, just then use the Assign Palette button to automatically assign a ball to a number – this will get them into the correct order, without you having to do it one by one.

Finally, when adding the reference average lines, be sure to set the scope to per pane rather than table, otherwise you’ll end up with the wrong figures.

I think I’ve pretty much covered all the ‘little’ points that I came across that may trip you up, aside from all the tricky calcs of course!

My published workbook is here. I hope what I’ve written is enough for you to build it yourself. I think I’d still be here next year if I tried to do anything more fully! I’m off for a lie down now!

Happy vizzin’!

Donna

How often is Sean listening to his favourite songs?

Donna ColesLeave a comment

A “scatter plot with a twist” music based challenge this week was posed by Sean Miller, using data from his last.fm account. On the surface, a simple scatter plot of each song, comparing the number of days between first and last listen against total plays. But click on song, and you get to see a timeline depicting days since first play vs cumulative plays, on the same chart. Hmmm…

The data set provided consists of 1 row per song per date played since 2017. For the scatter plot, we’re looking to summarise the data at a song level. For the timeline related to the selected song, we need to have the data at the song and date level. Ultimately we’re mixing levels of granularity within a single chart.

This certainly took some thinking. Creating the 2 charts independently was pretty straightforward, but trying to put them together took some thought. I knew I was going to want to use a set action to drive the interactivity and apply different logic based on whether a song was selected or not, but it took a bit of trial and error to get a solution.

First up, the data provided contained some timestamp date fields, but these were string data types. I chose to use the Timestamp UTC field to get a ‘proper’ date. I actually did this by duplicating the field, renaming it to Date Played and changing the datatype to a date. This generated a calculation which is below… I’d have never of typed this myself 🙂

Date Played

DATE(IF NOT ISNULL( DATEPARSE ( “MM/dd/yyyy HH:mm”, [TimeStamp UTC] ) ) THEN DATEPARSE ( “MM/dd/yyyy HH:mm”, [TimeStamp UTC] ) ELSEIF NOT ISNULL ( DATEPARSE ( “MM/dd/yyyy hh:mm:ss a”, [TimeStamp UTC] ) ) THEN DATEPARSE ( “MM/dd/yyyy hh:mm:ss a”, [TimeStamp UTC] ) END)

Now we have that, we can work out the first date a song was played

Min Date Per Song

{FIXED [Song ID]:MIN([Date Played])}

and the latest dates

Max Date Per Song

{FIXED [Song ID]:MAX([Date Played])}

and then we can derive the days between

Days since first listen

DATEDIFF(‘day’, [Min Date per Song], [Max Date per Song])

We can also get the total plays per song using

Total Plays per Song

{FIXED [Song ID]: [Total Plays]}

and with these calculated fields, we can build the basic scatter, using Total Plays per Song as a range filter, and setting both the axes not to start at zero.

So far so good. Now let’s think about the timeline. We need to identify a ‘selected song’ to help build this, so let’s create a set by right clicking on Song ID > Create > Set, and selecting a single option

We need to capture the number of plays on a date

Total Plays

COUNT([2021_05_26_WW21_My Streaming Activity.csv])

This is the default count field generated (the equivalent of the Number of Records if you’re on older versions of Tableau).

And we also need to capture the number of days from first play date to the current date, as we need to plot on a consistent axis when putting the charts together (ie we can’t plot with date on the axis).

Days to Date

DATEDIFF(‘day’,[Min Date per Song],[Date Played])

Let’s put this out into a table so you can see what’s going on.

Add the Selected Song = True to the filter shelf

There are days when there were multiple plays, so the Days To Date field needs to be set to AVG rather than SUM, to get the correct figure.

For Total Plays we need to plot the cumulative value, so we can set a quick table calculation against the Total Plays field of Running Sum (right click on Total Plays field). We’re going to explicitly set the table calculation to compute by Date Played as when depicted on a viz, the default of table down, might not give the correct values.

So with these fields, we can build the timeline viz (duplicate the table sheet and move the fields around). Set the mark type to line, and change the setting on the Path to make a stepped chart.

Ok, so now we have the 2 charts and hopefully understand what we’re aiming for. But how do we now go about getting everything onto a single chart?

We’re going to need a dual axis chart, since we have different mark types in play. And we’re going to want to plot different measures depending on whether we’re working with the selected song or not.

We’re going to build the data up in a table to get the logic for the fields we need. To just test the concept, we’ll filter to just a few songs, including the one in the Selected Song set. Add Song ID to the filter shelf and filter to a few songs.

Then build out a table as below:

What we’re aiming for, is for the records where In/Out of the set is Out, we want to plot the information we’re getting from the 1st two columns, but for the records where In/Out the set is In, we want the information from the other columns.

So let’s build this out.

Days to Plot

IF ATTR([Selected Song]) THEN AVG([Days To Date]) ELSE SUM([Days since first listen]) END

Plays to Plot

IF ATTR([Selected Song]) THEN RUNNING_SUM([Total Plays]) ELSE SUM([Total Plays per Song]) END

Pop these in the table, making sure any fields which are table calculations are set to compute by Date Played.

If you scroll to find where the data changes from a song out of the set to the one in, you can see how the two new fields are working.

So lets try plotting the chart out using these fields instead.

  • Days to Plot on Columns
  • Total Plays Per Song on Rows
  • Song ID on Detail shelf
  • Plays to Plot on Columns
  • Date Played (set to exact date) on Detail of the All Marks card.
  • Set the table calculation of Plays to Plot to compute by Date Played only.
  • Change mark type of the Plays to Plot to Line and set the Path to stepped line
  • Add Total Plays Per Song to Filter shelf and set to range from 50 to 100 (just to make the chart less busy).

You should end up with the below

You’ll notice we have the line of circles in the top chart, which is plotting a mark per day for the Selected Song. If we remove the Date Played pill from the Detail shelf of the Total Plays Per Song marks card, we lose these marks including the mark for the Selected Song too, which we need.

To resolve this, we need another field.

Is Last?

LAST()=0

Last Plays to Plot

IF [Is Last?] THEN Sum([Total Plays per Song]) END

This is just saying give me the total plays for the last mark in the list. Add these to the table to see what’s going on, making sure to set the table calc to compute by Date Played only

Now if we replace Total Plays per Song with the Last Plays to Plot field, we get
Now make the chart dual axis (don’t forget to synchronise), and we can then sort the formatting.
  • Set the marks type on the Last Plays to Plot to circle
  • Remove Measure Names from the Colour shelf, and set the mark colour to #3dde3c. Reduce the opacity to about 90%. Add a dark grey border.
  • Add Selected Song to the Size shelf, and adjust so the selected song is larger than the others.
  • On the Plays to Plot marks card, again remove Measure Names from the Colour shelf, and set the colour to black.
  • Set the Path to stepped line.
  • Click on the right hand axis and select Move marks to back
  • Reduce the Size of the mark.
  • Add Selected Song to the Colour shelf, and adjust the colours so the line is black and the tiny dots for all the other marks that you can see in the circles, is set to #3dde3c

You’ve now got the core chart, which needs to be further tidied to remove grid lines, axes, add tooltip etc. Once done, you can add to a dashboard, where you can then set the interactivity.

Add a dashboard action to change set values that sets the Selected Song set on Select. Set to work on single-select only.

Finally, you’ll find that if you select a mark, while you’ll get the trend line, the other points will now ‘fade out’

Create a new field True = True, and add this to the Detail shelf of the All Marks card. Then on the dashboard, add a new dashboard highlight action, which is set to Target Highlighting to the True field only.

Now if you click on and off a mark, you should get the trendline show and disappear, and all marks remain at the same transparency throughout.

Hopefully you’ve got enough now to complete this challenge. My published viz is here.

Happy vizzin’! Stay Safe!

Donna

Is Profit Ratio Influenced by Quantity?

Donna ColesLeave a comment

For this week’s challenge, Ann asked we recreated a scatter plot that ‘on click’ became a connected scatter plot and also displayed an ‘insights’ box to the user.

Building out the data

The scatter plot is to show Profit Ratio by Quantity, so first up we need

Profit Ratio

SUM([Profit])/SUM([Sales])

formatted to percentage with 0 dp.

A mark is shown on the scatter plot per Category and Month/Year. When working with dates like this, I often prefer to created a dedicated field to use as an ‘exact date’ which I can then format. So I built

Month Year

DATE(DATETRUNC(‘month’,[Order Date]))

and formatted it to the March 2001 format (ie mmmm yyyy).

We’re also going to need a set based on the Category field, as that is going to drive the interactivity to help us connect the dots ‘on click’. So right click on Category and Create Set and just tick one of the categories displayed for now.

Selected Category

Let’s build these out into a table as follows

  • Order Date to Filter, filtered by years 2018 & 2019
  • Category, Selected Category & Month Year (exact date , discrete) onto Rows
  • Measure Names to Text and Filter to Quantity & Profit Ratio
  • Right click on Selected Category and select Show Set to display a selection control to easily allow the set values to be changed

To help drive the interactivity, we’re going to need to store the value of the Profit Ratio for the Selected Category in the set.

Selected PR

IF ATTR([Selected Category]) THEN [Profit Ratio] END

Format this to percentage 0 dp too, and add this to the table – it will only display the profit ratio against the rows associated to the category in the set

At this point, we’ve got what we need to build out the scatter plot, but I’m going to continue to create the fields needed for the ‘Insights’ piece.

These are looking for the months that contained the Max & Min values for the Profit Ratio and Quantity. I’m going to tackle this with Table Calcs.

Max PR per Category

WINDOW_MAX([Profit Ratio])

Adding this to the table, and setting the table calculation to compute by Month Year only, gives us the Max Profit Ratio for each Category

We need 3 more fields like this :

Max Qty per Category

WINDOW_MAX(SUM([Quantity]))

Min PR per Category

WINDOW_MIN([Profit Ratio])

Min Qty per Category

WINDOW_MIN(SUM([Quantity]))

Add all these to the table, setting the table calc in the same way as described above.

Now we know what the min & max values are, we need to know the month when these occurred.

Max PR Month

WINDOW_MAX(IF ATTR([Selected Category]) AND [Profit Ratio] = [Max PR per Category] THEN MIN([Month Year]) END)

Format this to March 2001 format.

If the category is that selected, and the profit ratio matches the maximum value, then retrieve the Month Year value, and duplicate that value across all the rows (this is what the outer WINDOW_MAX does).

Add this to the table in the Rows, and adjust the table calc settings for both the nested calculations to compute by Month Year only. The month for the selected category which had the highest profit ratio will be displayed against all rows for that category, and null for all other rows.

Again we need similar fields for the other months

Max Qty Month

WINDOW_MAX(IF ATTR([Selected Category]) AND SUM([Quantity]) = [Max Qty per Category] THEN MIN([Month Year]) END)

Min PR Month

WINDOW_MAX(IF ATTR([Selected Category]) AND [Profit Ratio] = [Min PR per Category] THEN MIN([Month Year]) END)

Min Qty Month

WINDOW_MAX(IF ATTR([Selected Category]) AND SUM([Quantity]) = [Min Qty per Category] THEN MIN([Month Year]) END)

Format all these too, and add to the table with the appropriate table calc settings applied.

If you now change the value in the the Selected Category set, you should see the table update.

Building the Scatter Plot

On a new sheet, build out the basic scatter plot by

  • Order Date to Filter, filtered by years 2018 & 2019
  • Profit Ratio to Rows
  • Quantity to Columns
  • Category to Colour and adjust accordingly
  • Month Year exact date, continuous to Detail
  • Change Shape to filled circle
  • Adjust the Tooltip to suit
  • Change the axis titles to be capitalised
  • Change the sheet title
  • Remove all row/column borders & gridlines. Leave the zero lines and set the axis rulers to be a sold grey line

Add Selected PR to Rows, and change the mark type of that card to line, and add Month Year to path. In the image below, I still have Furniture selected in my set.

Add Month Year to the Label shelf too and format so the text is smaller and coloured to match mark colour

Make the chart dual axis, synchronise the axis and remove the Measure Names from the colour shelf of each mark. Hide the Selected PR axis.

If you now change the selected set value, you can see how the other categories ‘join up’.

Building the Insights Box

Take a duplicate of the data table built originally, and add Selected Category to Filter. If you’ve still got an entry in your set, this should reduce the rows to just those records for that Category.

Remove the fields Profit Ratio, Quantity, Selected PR from the Measure Values section, and remove Selected Category from Rows.

Create a new field

Index = Size

INDEX()=SIZE()

and add this to the Filter shelf, setting the value to true.

The INDEX() function will number each row, the SIZE() function will number each row based on the total number of rows displayed (ie all rows will display the same number), so INDEX()=SIZE() will return true for the last row only

Now we’ve only got 1 row displayed, we’ve got the info we need to build the data in the Insights box by

  • Move Month Year to Detail
  • Category to Colour
  • Move Max PR Month, Max Qty Month, Min PR Month, Min Qty Month to Text
  • Move Max PR per Category, Max Qty per Category, Min PR Per Category, Min Qty per Category to Text

This will probably show duplicate instances of the values. This is because we didn’t fix the table calculation setting of the Index=Size field. Edit that to compute by Month Year

and then re-edit the Index=Size filter to just be true again, and expand the display so you can see all the values.

Now you can easily format the Text to the required display

I used this site to get the bullet point image from

Building the dashboard & interactivity

Add the scatter plot to the dashboard, and remove the legends that automatically get added.

Float the Insights sheet and position bottom right, remove the title. fit entire view, and also remove the colour legend which will have been added.

Add a dashboard Set Action to assign values to the Selected Category set and remove all values when the selection is cleared

Additionally, add a highlight action that highlights the Category field only (this keeps the lines highlighted on selection of a single mark).

Now practice clicking on and off marks on the scatter plot and you should see your lines & insights box being added and removed.

Finally add the title and header line by adding a vertical container at the top above the scatter plot.

Add a text box for the title, and underneath add a blank object.

Set the padding of the blank object to 0 and the background to black. Then edit the height to 4, and adjust the height of the container if it’s now too large.

Make adjustments to the position of the floating insights box if need be so it isn’t overlapping any axis.

And that should be it! My published viz is here.

I’ll be taking a break for a couple of weeks, so will be on catch up when I return from some R&R.

Happy vizzin’! Stay Safe!

Donna

Can you create a drill down using set actions?

Donna ColesLeave a comment

For week 30, #WorkoutWednesday alumni Emma Whyte returned re-posting this challenge which was originally set in Week 41 of 2017 (see here). The idea behind this was to see how the challenge could be achieved using features that have been released since that challenge – in this case set actions.

I’ve been doing the #WorkoutWednesday challenges since they were first introduced, so I completed the original challenge, which is posted here.

Despite it being over 2 1/2 years ago, I had a strong recollection as to what was required to achieve this. So the challenge I set myself, was to recreate without looking at my own solution.

Building out the data

This is one of those challenges where we can build the data out into a table to check the functionality before building the actual viz. I always like to do this where possible, as I find it a good reference to make sure I’m getting the logic & the calculated fields I need right.

Start by adding State & City to Rows and add Sales & Profit via Measure Names on Columns .

As the challenge is to use Set Actions, then naturally, we’re going to need a Set. The Set we need is based on State with the idea being that when there is a State(s) in the set, then the City will display instead.

Selected State

Right click on State and Create -> Set. Select an option in the dialog, eg Alabama say

We will need to show the marks based on State or City depending on whether a State has been selected or not. We need a single field that we will use in the viz that displays the dimension we need to show

Display Value

IF [Selected State] THEN [City] ELSE [State] END

Add this onto the Rows and you’ll see how this is working

We can test the functionality of putting values into and out of the set without the need for the dashboard action at this point, by right-clicking on Selected State and selecting Show Set – the list of set values to select will display (a bit like a filter list).

We need a way to figure out what rows to show – how to identify whether there’s anything selected in the set.

Count States Selected

{FIXED : COUNTD(IF [Selected State] THEN [State] END)}

By being an LOD, this will set the count of the items in the set across all the rows in the data. Add to the sheet so you can see how this works

So we want to show information when either there isn’t anything in the set, or for the rows associated to the Selected States only

Records to Show

[Count States Selected] = 0 OR [Selected State]

Add this to Rows and test out… with no State in the set, all the rows are True

but with a State selected, only the rows associated to that State are True

But we seem to have too many marks showing when there’s nothing in the set….?

That’s fine.. just take City out of the view now, and if you deselect all States you should get the 48 rows we’re going to start with listed, and all are Records to Show = True. The Sales & Profit values will also now be aggregated to the appropriate level.

Building the Viz

Ensure your Selected States set is empty, and build out the scatter plot

  • Profit on Columns
  • Sales on Rows
  • Display Value on Detail & Label
  • Records to Show on Filter set to True
  • Mark Type = Shape set to x

Verify the functionality by clicking a State in the list, and the view should change to show the City.

We need to colour the marks based on Profit

-ve Profit?

SUM([Profit])<0

Add this to the Colour shelf and adjust colours accordingly.

Finally we need to look at how the title/subtitle changes based on which level we’re at.

Title

IF [Count States Selected] = 0 THEN ‘Sales vs. Profit by State’
ELSE ‘Sales vs. Profit for ‘ + [State]
END

Subtitle

IF [Count States Selected] = 0 THEN ‘Select a state to drill down to city level’
ELSE ‘Double-click a city to drill up to state level’
END

Add these onto the Detail shelf, then they’ll be available to reference in the Title of the sheet.

And then adjust the Tooltip, and we’re pretty much ready to go.

Adding the Set Action

Create a dashboard and add the scatter plot sheet to it.

Add a dashboard action to Change Set Values which runs on the Select action, and assigns values to the Selected State. On clearing the selection, values are removed from the set.

And that should pretty much be it. My published version is here. I thoroughly enjoyed the ‘throwback’ to previous challenges, and would like to see this theme continue on occasion.

Happy vizzin’! Stay Safe

Donna