For this week’s challenge, Kyle looked to solve a problem that he’s seen discussed within another blog – how to solve a highlighting problem when filtering donut charts.
I’ve been away on a little holiday abroad for a family wedding, so am on catch up this week. So I’m going to make this as brief as I can as time is limited.
Building the donut charts
Use the steps described in this blog post I wrote for my company to build a donut chart using the dual axis method.
For the Category donut chart, you will need Category on Colour and Sales on Angle of the outer Pie Chart. For the inner circle, you will need to add Sales to Text. Adjust the text as required. Sales needs to be formatted to $ with 0 dp.
For the Sub-Category donut chart, you will need to add Category to Colour. Then add Sub-Category to Detail and click on the 3 dots to the left of the Sub-Category pill and change to also add to Colour.
To adjust the colours, edit the colour legend, select all the options within the same Category. Select a sequential colour palette that matches the core colour for the category, then select Assign Palette. The colours should change to a range of that colour.
Create a new field
# Products
COUNTD([Product ID])
and add this to the Angle shelf. Add Sales to the Tooltip shelf and adjust the tooltip.
For the inner circle, add #Products to Text. Adjust the text as required
Filtering the donut
Add the two sheets to a dashboard. Add a dashboard filter action
Filter Cat
On select of the Category donut, target the Sub-Category donut chart passing in all fields. Keep filtered values when selection cleared.
Stopping the Category donut from being highlighted
Create new fields
True
TRUE
False
FALSE
and add these to the Detail shelf on the All Marks card of the Category donut sheet.
Then create a dashboard filter action
Unhighlight
On select of the Category donut on the dashboard, target the Category donut sheet itself, passing in the fields Tue = False. Show all values when selection cleared.
Now when the Category donut is clicked on, the other segments won’t fade. However, the selection is still visible – the edges of the pie are displayed.
Stop showing the selected section of the pie
For this we employ a trick mentioned in the blog post referenced in the challenge. Create a new field
Dummy
‘Dummy’
and add this the Detail shelf of a new sheet. Change the mark type to polygon so nothing is visible.
Add this to the dashboard as a floating object – make it small and place somewhere inconspicuous
Whilst the selections will still be visible when testing on Desktop, once published to Tableau Public, the presence of the polygon forces the whole dashboard to be rendered server side rather than client side. This reduces the amount of interactivity, and consequently the pie chart segments don’t display when clicked.
In 2024 the #WOW coaching crew has extended to include Yusuke Nakanishi (@YusukeNakanish3) and Yoshitaka Arakawa (@yoshi_dataviz) from the Japanese #datafam. This week Yusuke set this challenge asking us to build donut charts that represented when percentages were > 100%.
Building out the calculations
In the data set provided the Self-sufficiency ratio for food in calorie base [%] is a number that represents the actual % value ie 90 means 90%, 196 means 196%. To help me remember that, I formatted the field to be a number with 0 decimal places which had a % suffix.
But building the donut charts we need to ‘normalise’ the figures to represent a percentage out of 100. ie, if the value is 90%, we want 90%, but if the value is 196%, we want 96%. So I created
Self Sufficient %
([Self-sufficiency ratio for food in calorie base 【%】] %100) / 100
and then formatted this to a % with 0 dp.
but I can’t build a donut chart with just this value, I need to know the non self sufficient % too
Not Self Sufficient %
1-[Self Sufficient %]
and formatted this to be a % with 0 dp too.
Let’s put these into a tabular view. Add Prefecture to Rows and Measure Names to Columns. Add Measure Values to Text. Add Measure Names to Filter and restrict to the fields Self-sufficiency ratio for food in calorie base [%], Self Sufficient % and Not Self Sufficient %. Add Fiscal Year to Filters and restrict to FY2018. Sort the data by Self-sufficiency ratio for food in calorie base [%] descending.
You can see those rows where the Self-sufficiency ratio for food in calorie base [%], Self Sufficient % and Not Self Sufficient % is over 100% have a different value for the Self Sufficient %.
Showing the Fiscal Year as a filter the user can select, I can change to FY2019 and also see how these fields are behaving; ie when Self-sufficiency ratio for food in calorie base [%] is also over 200%, I’m getting the ‘remainder’ over 200 displayed ie 216% has a Self Sufficient % of 16%, which is what is needed for the ‘bonus’ challenge.
However, due to the way I’m building, I’m going to able to get the display working for the top & bottom 7 records regardless of year (making the build of the bonus challenge a bit easier).
So with this in mind, I now what to categorise the Self-sufficiency ratio for food in calorie base [%] based on what percentage range the values fall into.
% Bracket
FLOOR([Self-sufficiency ratio for food in calorie base 【%】] / 100)
This gives me values of 0, 1 and 2. By default this field will be created within the ‘measures’ section of the data pane (ie below the line). Drag it into the top section to convert it to a discrete dimension. Alias the values (right click -> Aliases) and set as below:
Then add to Rows.
and with the filter still set for FY2019, we can see the rows are categorised into 3 brackets.
Set the filter back to 2018. Now we want to restrict to the top and bottom 7 records only. For this I use Sets.
Create a set against Prefecture (right click the field > create > set).
Top 7
Top 7 records by Sum of Self-sufficiency ratio for food in calorie base [%]
Then create another set, this time for the bottom 7
Bottom 7
Bottom 7 records by Sum of Self-sufficiency ratio for food in calorie base [%]
Then create a Combined set (right click on one of the sets > create Combined set), that includes all values from both sets
Records to Include
Add this to the Filter shelf. By default it will show the records ‘in’ the set. However based on how the order of operations in Tableau works, this will apply the conditions based on the set first before it considers the year being filtered. Ie it will get the top and bottom 7 records based on the total sum of the Self-sufficiency ratio for food in calorie base [%] field for all the data in the data set, then filter to 2018. It means it could show some records that were in the top 7 overall, but not in the top 7 for 2018. To resolve this, and to ensure the data gets filtered by the Fiscal Year first, we need to add the Fiscal Year pill on the Filter shelf to context (right click pill and Add to Context). The pill will go grey.
Next we need a way to ‘categorise’ which rows are the top and which are the bottom. Add Top 7 to Rows which will split the rows into In or Out. Alias these values so In displays as Top 7 and Out displays as Bottom 7 (right click the text > Edit Alias).
Finally, when we build the viz, we need to ensure the 7 entries for each section align with each other. For this create
Top | Bottom Index
INDEX()
and convert the field to Discrete, then add to Rows before the Prefecture pill. Edit the table calculation so that it is computing based on the Prefecture and % Bracket pills only. This gives us an index from 1-7 for each set.
Building the Top & Bottom 7 Donut chart
On a new sheet, add Fiscal Year to Filter and set to 2018. Add the pill to context. Show the filter. Also add Records to Include to Filter.
Add Top 7 to Rows, then double click into rows and manually type MIN(0) to create a ‘fake axis’. Change the mark type to Pie.
Add Prefecture to Detail and Measure Values to Angle. Ensure only Self Sufficient% and Not Self Sufficient % are the only measures displayed (remove any others by dragging them out of the Measure Values box). Add Measure Names to Colour.
Add Top | Bottom Index to Columns and edit the table calculation so it is just computing by Prefecture. This should now give 7 columns of pie charts.
Add a Sort to the Prefecture pill on the Detail shelf, so it is sorting by the Self-sufficiency ratio for food in calorie base [%] field descending.
Add % Bracket to the Detail shelf, then click on the 3 dot icon to the left, and select the colour icon to add this pill to the Colour shelf as well as the Measure Names pill.
Re-edit the table calculation associated to the Top | Bottom Index pill so it is now also computing by the % Bracket field, so you get back to your correct top & bottom 7.
Adjust the order of the pills on the Colour shelf so that the % Bracket pill is listed before the Measure Names pill. Also adjust the order of the pills in the Measure Values box so Self Sufficient % is listed before Not Self Sufficient %.
Then adjust the colours on the colour legend as below and add a dark border to the marks (via the colour shelf).
Change the year filter to FY2019, and you can adjust the colours for the 200% entries too.
To make the ‘hole’ in the donut, double click into the Rows and add another instance of MIN(0). This will create a 2nd MIN(0) marks card.
On that marks card, move Prefecture from Detail to Label. Remove % Bracket, Measure Names and Measure Values. Add Self-sufficiency ratio for food in calorie base [%] to Label. Change the mark type to circle. Set the Colour of the circle to white. Align the label middle centre, and adjust the format/font to suit.
Set the chart to be dual axis and synchronise the axis. Adjust the Size of the pie chart mark independently from the size of the circle mark, so one is slightly larger than the other.
Finally tidy up the display by hiding the axis (uncheck show header), and the Top | Bottom Index field. Remove all gridlines, zero lines, axis lines/ticks and row/column dividers. Hide the In/Out Top 7 field label heading (right click label and hide field labels for rows. Update the title of the sheet so it references the Fiscal Year field. Change the filter back to 2018. Hide all tooltips.
Building the Legend
On a new sheet double click into Columns and type MIN(0.0). Add % Bracket to Rows. Change the mark type to square and add % Bracket to Colour and Label. Adjust colours to suit and add dark border to shape.
From the donut chart sheet, click on the Fiscal Year pill in the Filter shelf and set to apply to worksheets > selected worksheets and select the sheet you’re building the legend on. This will add the pill to this sheet too and changing the value on one sheet will impact the other.
Edit the axis so it is fixed to start at -0.1 and end at 1. This will shift the display to the left.
Hide the axis, and the % Bracket header column; remove all gridlines, zero lines, row/column dividers. Hide the tooltips.
Both the legend and the donut can now be added to a dashboard, and you’ve completed the main challenge. I chose to add the Fiscal Year filter to the display so the user could switch years if they wished.
The bonus challenge – Building the trellis chart
Because of how I’ve built the above, we’ve already done the hard work to handle the 200%+ data. The challenge here now is just to display all the 47 Prefectures for a given year in a 10 x 5 grid – a trellis.
So to build this, I started with the donut chart already built and duplicated the sheet.
When creating trellis charts, we need to create fields that represent which row and which column each Prefecture should sit in. There’s lots of blogs on creating trellis charts. As we know the number of rows and columns we need, I created
Cols
INT((INDEX()-1)%10)
Take the index of each Prefecture, decrement by 1 and find the remainder when divided by 10. This means the Prefecture with the highest % value at at position (rank) 1 will be positioned in column (1-0)%10 = 0. The Prefecture at position 11 will also be positioned in column (11-1)%10 = 0.
We also need
Rows
INT((INDEX()-1)/10)
Take the index of each Prefecture, decrement by 1 and divide by 10.
Convert both fields to be Discrete.
From the duplicated sheet, remove Top | Bottom Index from Columns and In/Out Top 7 from Rows. Remove Records to Include from Filter. Don’t panic if things look odd!
Add Cols to Columns. Adjust the table calculation to compute by both %Bracket and Prefecture. Specify the sort order to be a custom sort on the field Self-sufficiency ratio for food in calorie base [%] descending.
Now add Rows to Rows and apply the same settings on the table calculation. If all is well, you should have all 47 donuts displaying in the correct order.
Hide the Cols and Rows headings, and you can then add this to another dashboard.
In his final challenge for 2022, Luke set this challenge asking us to recreate this pie chart. Although not mentioned in the challenge text, there was a hint on the splash page that map layers would be required.
I’ve only really used map layers in other #WOW challenges, and they actually involve maps. This challenge was obviously a bit different – utilising a functionality built for one purpose in an entirely different way. I remembered when map layers were first released there was a big buzz about the potential possibilities, and had seen some examples, but I’d never gotten round to trying out for myself, so this was the perfect opportunity (and one of the many plus points as to why I love doing #WOW challenges).
So where to start… good question. If you read up on the official Tableau KLs relating to map layers, it’s all about geography, and while the data source does have geographic data (State, City etc), they aren’t relevant in this case. In my ‘googling’ I found the following resources of use
The first 2 blogs helped me understand the need for the use of the MAKEPOINT function, Sam Parson’s Pies & Doughnuts viz helped me understand the calculation I’d need for the MAKEPOINT function, and the final blog post really helped with putting in all together.
Feel free to ignore the rest of this blog and use the above to help you out 🙂
Building the first map layer
The first step is to create the geometry field we need to base this off of.
Zero
MAKEPOINT(0,0)
Double click this field, and it will automatically add the point centrally onto a map with Longitude and Latitude fields automatically generated too.
This is a key step in getting things started and enabling the use of map layers which we’re going to utilise.
Add Segment to Colour and adjust the colours. Change the mark type to pie chart and add Sales to angle. Increase the size to be as large as possible.
However the size isn’t as big as we need. To increase further use Ctrl-Shift-B (windows) or Cmd-Shift-B (mac) to increase the size further (Ctrl-B / Cmd-B) to reduce. This trick I found in the Interworks blog above. All Tableau key shortcuts are listed here.
Add Segment to the Label shelf. This completes our lowest map layer.
Building the second map layer
Drag Zero onto the map canvas, and drop it over the Add a Marks layer section that displays. This will add a second marks card called Zero(2).
On the marks card that is named Zero, rename it to Outer Pie.
On the marks card named Zero (2) rename to White Circle. Change the mark type to Circle, change the Colour to white and increase the size to leave a narrow border of the coloured pie underneath.
Building the third map layer
Drag another instance of Zero onto the canvas and add another marks layer. Rename Zero (3) to Inner Pie. Change the mark type to Pie chart and add Segment to Colour and Sales to angle. Increase the Size so it’s just smaller than the white circle. Change the opacity of the colour to 70% and add a white border (Colour shelf).
Adding the labels in the pie chart
The simplest way to do this is just to label the inner pie chart with the required fields and then manually move the labels from outside the pie to the desired location. However if your data changed in some way, eg the proportion of the slices changed, the labels may not be where you wanted without further tweaks.
So instead I’ve added a 4th map layer.
Add Zero once again to the sheet and add a marks layer. Rename this marks card to Labels-Inner Pie. Change mark type to Pie chart and add Segment to Detail, Sales to Angle and Sales to Label. Create a new calculated field
Pct
SUM([Sales]) / TOTAL(SUM([Sales]))
Format to % with 0 dp and and add to Label. Adjust the fonts of the labels so the Sales value is larger.
Increase the size of the pie chart so the labels are positioned ‘nicely’ within the segments of the Inner pie
Reduce the opacity of the ‘label’ pie chart to 0% and set the mark layer to be disabled
Finishing up
Adjust the tooltips to display as required (you’ll need to add Pct to the Tooltip shelf on both the Outer and Inner Pie mark cards).
Then remove the map background via the Map menu -> Background Maps -> None. Hide all axis and remove all gridlines/zero lines/row/columns dividers. You should now be left with a ‘clean’ pie chart which can be added to a dashboard.
A colourful #WorkoutWednesday challenge this week, courtesy of Ann Jackson incorporating pie charts, top N functionality and interactivity and a highlight table. Pie charts can cause much debate amongst the data viz community and if this one was just representing the multitude of sub-categories, it certainly wouldn’t be ideal. But when the core aim is to simply present 2 key measures (those in the top N against the rest), the pie is a familiar and effective visual. In this instance, the outer ring segmenting all the sub-categories provides additional context without detracting from the main purpose of the viz.
So lets build…
Creating the core calculations
Building the Pie Chart
Building the Highlight Table
Adding the Interactivity
Creating the core calculations
First up, we’re going to need a parameter to define the ‘Top N’. Create an integer parameter with a range from 1 to 17, that steps every 1 interval, and is defaulted to 5.
pTopN
Next we’re going to use a Set to capture the Sub-Categories that are in the Top N Sales. Right click on Sub-Category -> Create ->Set. Use the Top tab to define a set captures the Sum of Sales that is based on the pTopN parameter.
Now, we want to create a grouping of those in and out of the set, which will be used as part of the highlight table
Sub-Cat Group
IF [Sub-Category Set] THEN ‘IN TOP ‘ + STR([pTopN]) ELSE ‘ALL ELSE’ END
Pop all these fields out into a table so you can see what’s going on as you change the pTopN parameter. Sort the Sub-Category by Sales descending.
Now we need to identify the % value of Sales for the Sub-Categories that are in the Top N (this is the label on the darker segment of the central pie chart), so for that we need
Total Sales
{FIXED:SUM([Sales])}
Top N Sales (in hindsight, this should have been named Sales per Group or similar)
{FIXED [Sub-Category Set] : SUM([Sales])}
Top N Sales %
IF ATTR([Sub-Category Set]) THEN SUM([Top N Sales])/SUM([Total Sales]) END
Format this to percentage with 0 dp.
Adding to the table, we can see the values
The final field we need in order to build the pie, is an additional one to store the label text
Label:SubText
IF [Sub-Category Set] THEN ‘TOP ‘ + STR([pTopN]) END
Building the Pie Chart
To achieve this we’re going to build a dual axis pie chart, where one pie is used to define the In/Out of Top N segmentation in the centre, and the other pie is used to create the outer ring.
Create an axis by typing in MIN(0) onto the Rows shelf, and then adding another instance of MIN(0) next to it. This will generate 2 marks cards, which is where the fields to build the pie charts will be placed.
In the first MIN(0) marks card, change the mark type to Pie, then add Top N Sales to the Angle shelf and Sub-Category Set to the Colour shelf. Adjust colours to suit. Then add Top N Sales % and Label:SubText to the Label shelf. Adjust size of the view and the chart to suit. Also remove all text from the Tooltip.
Positioning the text is a bit fiddly. If you click on the text so the cursor changes to a cross symbol, you can then drag it to a better location. However, when you change the Top N parameter, the text will move. You can go through each parameter value and reposition the text each time (which I did.. it wasn’t too onerous for 17 values), however I found when published to Tableau Public, the positioning wasn’t honoured. Ann’s solution was the same, so I didn’t get too hung up on this, although if anyone resolved it, I’d love to know!
Now on the 2nd MIN(0) marks card, again change the mark type to Pie, and this time add Sales to the Angle shelf and Sub-Category to Colour. Sort the Sub-Category field by Sales descending. Additionally add Sub-Category Set to the Detail shelf (this will be needed later on to make the interactivity work). Edit the colour palette to use the Hue Circle options. Adjust the size of the pie chart. Adjust the tooltip too.
Now make the chart dual axis and synchronize the axis. If the colourful chart is displayed ‘on top’, then right click on the right hand axis and select move marks to back. Adjust the sizes of both pies, so the colour wheel is slightly larger than the other one.
Now hide the axis, and remove all borders and gridlines.
Building the Highlight Table
I’ve built the highlight table as a bar chart. Start off by adding Sub-Category Set, Sub-Cat Group and Sub-Category to Rows. Sort Sub-Category by Sales descending. Then type in MIN(1) into the Columns shelf.
Now add subtotals via the Analysis > Totals > Add all Subtotals menu. This adds 2 additional rows to each section
But we don’t want the ‘grand total’, so click on the Sub-Category Set context menu, and uncheck Subtotals
To position the totals at the top, go to Analysis > Totals > Column Totals To Top
Then add Sub-Category to the Colour shelf, and adjust the colour of the Total bar to white
We now need to get some text onto those bars, but we need some additional calculations to help up with this. Firstly, we want to get the rank of the Sub-Category. We’ll use a table calculation for this
Sales Rank
RANK(SUM([Sales]))
We also need a way to identify the Total rows differently from the main Sub-Categories. I referred to this Tableau KB for help here, and subsequently created
Size
SIZE()
To see what this is doing, add Size to the Label shelf, and adjust the table calculation setting to compute by all fields except the Sub-Category Set. The size of the total rows is 1.
Based on this logic, we can then create
LABEL:Bar
IF [SIZE]=1 THEN ‘SUBTOTAL FOR GROUP’ ELSE ‘#’+STR([Sales Rank]) + ‘ ‘ + ATTR([Sub-Category]) END
Add this to the Label shelf instead of the Size field and adjust the table calc settings as above. Align left. Then add Sales to the Label shelf too and adjust so its on the same row. Adjust the tooltip too.
Now hide the Sub-Category Set and the Sub-Category fields. Right click on the ‘IN TOP x’ text and Rotate Label, then click on Sub-Cat Group text and Hide Field Labels for Rows. Format the header text to suit.
Hide the MIN(1) axis, and set columns and gridlines to None. Adjust the Row dividers to be darker
Adding the Interactivity
Add the 2 sheets onto a dashboard, and add a Highlight Dashboard Action, that on Hover of either of the charts, it highlights the other chart based on the Sub-Category Set only.
I think that’s covered everything. My published viz is here.
This week Luke challenged us to create Donut Charts in Tableau, but added additional requirements to make it just a bit spicier. The full details are here.
Taking inspiration from Ann’s challenge the week before, Luke provided an advanced version to incorporate grey circles for each date when there were no orders, but stated this should be achieved without any data duplication or densification. Deep down, I knew Luke really meant ‘only one sheet’, but he didn’t state this, so my initial interpretation was to tackle the challenge in a similar way to Ann’s, and use 2 sheets; a background with all the grey circles displayed, and a foreground with the donuts/green circles, and float one over the other. This week, while still tricky, I managed to get them aligned, so that was the version I published and released.
I documented this floating technique last week, here, so have no plans to repeat, except to state that I got all the dates to display by creating a Baseline Date field of
which is basically setting all the dates in the dataset to the same year. I then used this date to build my background viz, and as there was an order in every region for the day/month combination, I didn’t get any gaps. If the dataset didn’t exhibit this behaviour, this technique would not work, so it isn’t the most robust solution.
Right, now I’ve finished talking about that, let’s get onto building the chart…
Fixing the report date
Luke stated the report should be based on the last 7 days from 6th Nov 2019, so this date had to essentially be ‘hardcoded’ into the report. The easiest way to do this in a way that could be quickly changed if need be, was to create a parameter, Report Date, defaulted to 6th Nov 2019.
Restricting to 7 days
I created a calculated field to limit the data just to the days I was interested in
This required a few calculated fields. First up, we needed to know if the order had shipped before the report date or not
Has Shipped?
[Ship Date]<= [Report Date]
# Shipped
IIF([Has Shipped?],1,0)
This returns 1 or 0 depending on whether the order has shipped before the report date or not. This field when added to the viz, can then be aggregated (summed) to provide a count of the orders that have shipped.
% Shipped
SUM([# Shipped])/SUM([Number of Records])
How many shipped as a proportion of all records. NOTE – in this solution, an order equates to a row in the data set. However technically, an order can contain multiple rows, so when counting orders, you could think you need to COUNTD([OrderID]). This is certainly valid, and IMO more accurate, but things do get a bit more complex this way. Luke had counted rows, so I decided to work with getting the data to match his solution.
Finally we needed to know if the orders had been fully shipped or not, as this is what will determine whether we’re showing a green circle with a tick, or a donut.
Fully Shipped?
[% Shipped]=1
Building the Donuts
I’ve worked with donut charts before, so knew that the trick was in using a dual axis technique to show a pie chart with a smaller circle mark on top.
I also needed ‘axis’ to work with, so incorporated our old friend MIN(0), and added 2 instances as synchronised dual axis like below:
The first instance, I changed to be of mark type Pie chart, adding SUM([Number of Records]) to the Angle shelf, and Has Shipped? to the Colour shelf. The colours were set to green if Has Shipped? was true and grey otherwise. The colours were reordered, so True is listed first, so the green starts at 12 o’clock.
On the second instance, I changed the mark to be a circle, adjusted the size so it was smaller, and added Fully Shipped? to the Colour shelf. This time the colour is set to green if true, but white if false.
For the labels, I created 2 calculated fields :
Label Tick
IF [Fully Shipped?] THEN ‘✓’ END
Label % Shipped
IF NOT([Fully Shipped?]) THEN [% Shipped] END
and added these side by side to the Label shelf of the Circle mark. The font was adjusted to fit, and centre aligned.
Removing the column/row labels, hiding some of the pills and formatting the axis/gridlines etc, and the core of the viz is built. This would achieve the ‘standard’ solution.
Date Format
The order date was set to a custom format of mmm d, ‘yy to get the desired display.
Displaying the grey circles
As stated above, I originally used the 2 sheets & floating technique to show the circles within the gaps.
After publishing, I had a look at Luke’s solution to see how he’d tackled it.
However much I stared at his workbook though, I could not see what he’d done. All I could tell by playing around was that there were no further marks than what I had already got displayed.
Then Rosario Guana posted up her solution, so I checked hers out too…. still couldn’t see it. I went through every menu option I could think of, trying to find what the secret was…..
Eventually I pinged Rosario a message… background image was the response.
Doh! I don’t use these often, well actually I’ve only used it once on another #WorkoutWednesday challenge that Rody Zakovich set sometime ago. Tableau’s help on using Background Images (which you often associate with maps, and hence is under the Maps menu option), is here.
So now I had the clue, what did I need to do….
First up, I needed an image to use. As I’d already downloaded Rosario’s workbook, I used the one in her workbook.
Secondly, I needed ‘proper’ pills to map the co-ordinates of my image to, my ‘typed in’ MIN(0) wouldn’t suffice. So I created
Col
0.0
Row
0.0
I then rebuilt the viz with Col (set to be a dimension), and added Row to the rows shelf (again set to be a dimension). I hid all the headers again
I then added the image via Map > Background Image > <Data source name>, then Add Image, and applied settings below
The sizes just then needed to be adjusted to fit, but this is best done when displayed on the dashboard itself, as what you see in the sheet view might not present the same when on the dashboard.
Both my versions of this challenge can be viewed here.
Donna + DataViz 