Tag: Table Calcs

Exploring Table Calcs vs LODs

Donna ColesLeave a comment

Erica set the challenge this week, which involved building the same visualisation in two ways – one using Table Calcs only and one using LODs.

To test the functionality and validate what’s going, I’m going to build the data out in a tabular format first.

The Table Calc Table

On a new sheet add Region and Category to Rows and Sales to Text. Sort by Sales descending. Then add Region and Segment to Filter, selecting all options, and show the filters.

Create a new field

Total Sales

TOTAL(SUM([Sales]))

and add into the table. This won’t be used later, but I’ve created so you can see the filtering behaviour.

This is a table calculation, and, by default when added to the table, it shows the total of all the rows against each row. We want to display the total per Region, so every row for a specific region shows the total of that region only. Adjust the table calc setting so it is computing by Category only.

Create a new field

TC – % of Sales

SUM([Sales]) / TOTAL(SUM([Sales]))

format to be % with 1dp and add into the table. By default it should have inherited the table calc settings we just applied for Total Sales, but if not apply the same settings, so it is computing by Category only.

If you do the maths taking the value in the Sales column and dividing by the value in the Total Sales column, you should be able to validate the result.

And if you test by adjusting the Segment and Region filters, everything should work as expected :

Filter out a Segment and the Sales and Total Sales adjust to exclude the value and the TC – % of Sales for a Region still totals 100%

Filter out a Region and that whole block is removed, but the values for all the other rows remain unchanged.

Now add Category to Filter and show the filter. Filter out a Category, and what we now see is the Total Sales now just reflects the total for the selected categories, and the TC – % of Sales still totals 100%. This isn’t the requirement. The % of Sales needs to calculate over all Categories regardless if it is excluded in the display.

To handle this, we create

TC – Filter Category

LOOKUP(MIN([Category]),0)

This is using a table calculation to basically return the value of the Category associated to the current row, which is basically looking up itself. However, as this is a table calculation, when added to the Filter shelf, it applies the filter after other computations (this is Tableau’s order of operations’), whereas the ‘quick filter’ applied above, is filtering the data first before then computing the total sales.

Remove Category from the Filter shelf, and add TC – Filter Category to the Filter shelf instead, selecting all options and showing the filter on the view. By default the table calc setting is set to table down which is fine – it is computing by both Region and Category. Now if you exclude a Category, the relevant rows disappear, but the Total Sales and therefore TC – % of Sales values remain unchanged.

The Table Calc Viz

The simplest way to build this (IMO) is to duplicate the table sheet then

  • Remove Total Sales and Sales
  • Move TC – % of Sales to Columns
  • Show mark labels
  • Adjust colour of bar
  • Adjust colour of worksheet background
  • Widen each row slightly
  • Make the width of bars slightly smaller
  • Edit title of % of Sales axis
  • Adjust fonts of label headers and bar label and axis labels (I set to 8pt)

The LOD Table

Let;s repeat this now using LODs instead.

On a new sheet, once again add Region and Category to Rows and Sales to Text. Add Region and Segment to Filter and show the filter options.

Create a field

LOD – Sales per Region and Segment

{FIXED [Region], [Segment]:SUM([Sales])}

Add into the table. With all segments selected, we can see the total sales for each Region listed

and filtering out a Segment, the totals adjust as required.

If we now add Category to Filter, show the options and filter one out, the totals now no longer change, as the LOD – Sales per Region and Segment doesn’t include Category in its definition – its FIXED to just account for changes to Region and Segment.

So we can now create

LOD – % of Sales

SUM([Sales]) / SUM([LOD – Sales per Region & Segment])

and format to % with 1dp and add into table to validate.

You can now apply similar steps to those detailed above to recreate the bar chart viz for this data.

And once done, add both charts onto a dashboard with their relevant filters.

My published viz is here.

Happy vizzin’!

Donna

Can you build a ranked heatmap tile?

Donna ColesLeave a comment

Erica had a guest coach, Valerija Kirjackaja setting the challenge this week, asking us to use table calculations to build this heatmap table.

I built an initial version of the heatmap only, which I’ve published here, but I couldn’t get the display to match Valerija’s when I clicked on it. (Note – I wasn’t bothered about Viz in Tooltip part at this point). I used 2 dimensions to display the yellow header section, and you can see below, when clicking, this is noticeable. But Valerija’s solution treats the header as a single entity.

I couldn’t figure out how she’d managed this, so I had to have a look at the solution, and then I built my own instance, which is what I’ll now blog about.

Defining the core fields

Connect to the datasource and add a data source filter to restrict the data by the latest year (as I used Superstore 2025, I filtered to 2025). Doing this meant I didn’t have to worry about adding worksheet level filter fields.

On a new sheet add Category and Sub-Category to Rows and add Sales to Text and then sort descending so you can see the data we need to work with. Format Sales to be $ to 0 dp.

Create a new field

Sales by Cat Rank

RANK(SUM([Sales]))

change it to be discrete and then add to Rows. Adjust the setting of the table calculation so it is computing by Sub-Category only, so the ranking restarts for each Category

We will also need to display the Category in upper case, so create

Category Upper

UPPER([Category])

and add to Rows.

Having this tabular layout just lets us clarify how the table calculation will be working.

Building the Heatmap Table

On a new sheet, add Category to Columns and Sub-Category and Sales to Text and align centrally (Note – I originally put Category Upper on the columns, and then changed later after taking all the screen shots)

Add Sales by Cat Rank to Rows. Change it to a continuous (green) pill and edit the axis to be reversed. Adjust the table calculation so it is computing by Sub-Category only.

Create a new field

One

1

Change the mark type to gantt bar and add One to the Size shelf, setting the aggregation to Avg. Increase the size of the mark via the Size shelf to as large as possible. Add Sales to Colour then add a white border.

We need the axis numbers to be central to the ‘row’, so to fix this, double click into the Sales by Cat Rank pill and change it to subtract 0.5 ( [Sales by Cat Rank] -0.5 )

Re-edit the axis to reverse it again.

So our ‘table’ is now displaying data on a axis from 0.5 up to 9.5. To add the header, we’re going to plot another mark at -0.5, so we can display a section of the same size as the existing ones. For this, double click into Rows and type MIN(-0.5).

This has the effect of creating a second marks card

Remove Sales from Colour and Sub-Category from Label. Add Category Upper to Label. Adjust the label text alignment and formatting and change the Colour to yellow.

Make the chart dual axis and synchronise the axis and we now have the required display.

Tidy up by

  • Remove row & column dividers
  • Remove gridlines, zero lines & axis ticks
  • Hide the right hand axis (right click > uncheck show header)
  • Hide the Category Upper column labels (right click pill > uncheck show header)
  • Remove the left hand axis title
  • Fix the left hand axis from -0.5 to 9.5
  • Format the axis with a custom formatting of #,##0;-#,##0;TOTAL so that 0 is displayed as the word TOTAL (this is very sneaky by the way, and took me a while to work out)
  • Then format the font to be bold
  • Adjust the Tooltip on the Sales by Cat Rank marks card to display the Sub-Category and Sales value.
  • Delete the text from the Tooltip on the MIN(-0.5) marks card
  • Name the sheet Table or similar

Building the Viz in Tooltip

On a new sheet add Order Date to Columns at the discrete month level (blue pill) and add Sales to Rows. Add Sub-Category and Category to Detail. Format the date axis so the dates are just using First Letter.

Create a new parameter

pSubCat

string parameter defaulted to Bookcases

Then create a field

Is Selected SubCat

[Sub-Category] = [pSubCat]

and add to the Colour shelf. Adjust accordingly, then make sure True is listed first in the legend, so the line is ‘on top’

Create a new field

Label Line

IF [Is Selected SubCat] THEN [Sub-Category] END

and add to the Label shelf and update to allow marks to overlap. Hide the Order Date label heading (right click > hide field labels for columns). Title the chart Line or similar

Remove gridlines and row/column dividers

Go back to the Table sheet, and update the Tooltip of the Sales by Cat Rank marks card to reference the Line chart and update the filter to pass as just <Category>

Adding the final interactivity

Create a dashboard and add the Table sheet. Then add a parameter action

Set Sub Cat Param

On hover of the Table sheet, set the pSubCat parameter with the value from the Sub-Category field, setting the value to <empty string> when the selection is cleared.

If all has been applied, then the line chart should just display the lines associated to the Sub-Categories in the same Category

My published viz is here.

Happy vizzin’!

Donna

Let’s make a Tableau Pulse-Inspired Dashboard!

Donna ColesLeave a comment

Yoshi set the challenge this week to build a dashboard which looks like the visual you might get as part of a Pulse metric.

Define the parameters

Create a parameter to define the ‘reporting’ date

pBaseDate

date parameter defaulted to 21 Sept 2025

Create a parameter to capture the number of previous weeks the ‘forecasting’ values should be calculated against

pWeeks

integer parameter defaulted to 8, with a min value of 5 and max of 15, incremented every 1 step

Building the KPI card

This section displays the month to date sales and comparisons to previous month, based on the value in the pBaseDate parameter. We need several calculations

MtD Sales

IF [Order Date] >= DATETRUNC(‘month’, [pBaseDate]) AND [Order Date]<=[pBaseDate] THEN [Sales] END

format to $ with 0 dp.

Prev MtD Sales

IF [Order Date] >= DATEADD(‘month’, -1, DATETRUNC(‘month’, [pBaseDate])) AND
[Order Date]<= DATEADD(‘month’, -1, [pBaseDate]) THEN [Sales] END

MtD Sales Diff

SUM([MtD Sales]) – SUM([Prev MtD Sales])

custom format to +”$”#,##0;-“$”#,##0

MtD Sales % Diff

[MtD Sales Diff] / SUM([Prev MtD Sales])

custom format to +0.0%;-0.0%;0%

On a new sheet add MtD Sales, MtD Sales Diff and MtD Sales % Diff to Text. Change the mark type to shape and set to be a transparent shape (refer to this blog to understand how to set this up). Adjust the layout and style of the text on the Label. Set the sheet to Entire View and align the text to the left. Update the title of the sheet and remove the Tooltip.

Building the Line Chart

Before building the viz, we’ll start by building the calculations and checking them through a tabular display.

On a new sheet, show the pBaseDate and pWeeks parameters. Then add Order Date as a discrete exact date (blue pill) to Rows and add MtD Sales to Text. The MtD Sales values should only display against the dates from 1st to 21st Sept.

For each day, we need to calculate the 25th percentile of the Sales value using the gp model against the same day of the week for the previous data.

25th Percentile

MODEL_QUANTILE(“model=gp”,0.25,SUM([Sales]),ATTR([Order Date]),ATTR(STR(DATEPART(‘weekday’,[Order Date]))))

and we also need the 75th percentile

75th Percentile

MODEL_QUANTILE(“model=gp”,0.75,SUM([Sales]),ATTR([Order Date]),ATTR(STR(DATEPART(‘weekday’,[Order Date]))))

These 2 values give the ‘range’ we want to check the actual MtD Sales value against. Add both values into the table, and update the table calculation setting of each so they are computing explicitly by Order Date

However we only want the calculations to be based on the last x weeks, so we want to filter the display.

Dates to Include

[Order Date]>= DATEADD(‘week’, -1 * [pWeeks], [pBaseDate]) AND [Order Date] <= [pBaseDate]

Add this to the Filter shelf and set to True. This will adjust the 25th & 75th Percentile values as they are only considering data within the display (eg compare the highlighted values for 01 Sept against those in the image above)

But when it comes to ‘plotting this data’ on a chart, we only want to display the data for the current month (based on pBaseDate), so we need to apply a second filter that restricts the dates displayed further, but that does not eliminate the data in such a way that we lose reference to the previous x weeks.

We can do this using a filter based on a table calculation

Filter: Dates for Chart

LOOKUP(MIN([Order Date]),0) >=DATETRUNC(‘month’, [pBaseDate])
AND LOOKUP(Min([Order Date]),0) <= [pBaseDate]

The LOOKUP function is a table calc that is basically returning the same value for Order Date and comparing it against the base date. But because it is a table calc, when applied as a filter, it will only be applied after other computations.

Add this to the Filter shelf and set to True. Then adjust the table calc so it is explicitly computing by Order Date and then re-edit the filter again so it is just considering True values (changing the table calc setting, resets this).

Let’s start to build the viz :

Duplicate the tabular sheet above. Move Order Date to Columns and change to be continuous (green pill), Move MtD Sales to Rows and move Measure Values to Rows. Move the Measure Names field to the Colour shelf of the Measure Values marks card. Unstack the marks ( Analysis menu > stack marks > off) – if you can’t see 2 areas, swap the order of the pills in the Measure Values box so the 25th Percentile is listed first. Adjust the colours of the marks so the 25th percentile is white and the 75th percentile is pale blue (#e6f2fe). Ensure the opacity of these marks are 100%. Set the colour of the Mtd Sales line to bright blue.

Note – by moving the pills around and having already explicitly set the table calculation settings, we know the fields will be computing correctly. If you wish, you can build the viz from scratch, but you will need to explicitly set all the table calc pills to compute by Order Date again.

Make the chart dual axis and synchronise the axis. Right click the right hand axis and move marks to back to make the line display in front.

Create new fields

Ref Line – Start of Month

DATE(DATETRUNC(‘month’, [pBaseDate]))

and

Ref Line – End of Month

DATE(DATEADD(‘day’,-1, DATEADD(‘month’, 1,DATETRUNC(‘month’, [pBaseDate]))))

Custom format both of these to dd/mm and then add both to the Detail shelf of the All marks card. Set to be continuous exact date (green pills).

Add 2 reference lines to the Order Date axis, which reference these pills.

Add pBaseDate to the Detail shelf of the All marks card too, and add an additional reference line to that field. In this instance format the reference line and apply a custom format to the date to be dd/mm

Adjust the Tooltip via the All marks card. Remove all gridlines, zero lines and row/column dividers. Hide the right hand axis and the Order Date axis. Remove the title from the left hand axis.

To show the summary of how the MtD Sales value for the pBaseDate compares to the range, we will use the caption feature of the worksheet, which can reference fields, but we need these fields to essentially be ‘constants’ for every row of data, so we need some new fields.

Sales for Base Date

WINDOW_MAX(SUM(IF [Order Date] = [pBaseDate] THEN [Sales] END))

format this to $ with 0 dp.

25th Percentile for Base Date

WINDOW_MAX(IF MIN([Order Date]) = [pBaseDate] THEN [25th Percentile] END)

75th Percentile for Base Date

WINDOW_MAX(IF MIN([Order Date]) = [pBaseDate] THEN [75th Percentile] END)

Switch back to the tabular view of data and add these 3 fields. As they’re all table calculations, you need to set them to be computing by Order Date only (as we did above).

You should find that the values for the latest row (highlighted below) are displayed against every row in the 3 additional columns

With this, we can now work out the ‘text’ we want to disply in the caption

Expected Range Text

IF [Sales for Base Date] > [75th Percentile for Base Date] THEN ‘above’
ELSEIF [Sales for Base Date] < [25th Percentile for Base Date] THEN ‘below’
ELSE ‘within’
END

Add this to Rows, check the table calc settings, and then adjust the pBaseDate value so you can see the text change.

Now switch back to the line chart, and display the Caption (worksheet menu > show caption). Add Sales for Base Date and Expected range Text to the Detail shelf of the All marks card, adjusting the table calc settings as we’ve done before.

Then edit the caption and remove all text and update, referencing the various fields and parameters.

Building the bar chart

On a new sheet, add Segment to Rows and MtD Sales Diff to Columns. Sort descending. Create a new field

Diff is +ve

[MtD Sales Diff]>=0

Add to Colour and adjust accordingly. Show mark labels and set to match mark colour. Format the display to remove all column/row dividers, gridlines and zero lines. Display the Row Axis Ruler as a thicker grey line.

Then add all the components to a dashboard, using containers and padding to organise the display. Make sure to display the caption for the line chart worksheet.

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

Happy vizzin’!

Donna

Let’s practice Table Calcs!

Donna ColesLeave a comment

For this week’s #WOW2025 challenge, Sean went ‘back to basics’ with a focus on table calculations.

Let’s jump right in.

After connecting to the data, add Team to Rows and Timestamp as a continuous (green) pill at the Day level to Columns. Create a new field

Call Count

COUNT([synthetic_call_center_data.csv])

and then add this to Rows.

Add Timestamp to Filter, and select relative date. Set the options to Last 3 weeks, and then additionally check the anchor relative to check box and enter 23 Dec 2024. This is because the data set only goes up to the end of December 2024. Not setting this field will apply the date filter based on ‘today’ so it’s unlikely anything will appear.

(Note – you may also need to update the date properties of the data set to ensure a week starts on a Sunday to get matching numbers: right click the data source and select the date properties option).

To add a marker to the last point, create a field

Call Count – Most Recent

IF LAST()=0 THEN [Call Count] END

Add this to Rows and adjust the table calc setting so it is computing specifically by Day of Timestamp only. By default it was doing this via the Table (across) option, but I tend to always prefer to always explicitly fix what the calculation is computing over, as it won’t then matter where I then move that field too if I choose to change the layout of the viz.

Set the mark type on the Call Count marks card to line, and then adjust the colour to grey and reduce the size. Set the mark type of the Call Count – Most Recent marks card to circle, set the colour to blue and increase the size. Hide the null indicator (right click > hide).

Set the chart to dual axis, synchronise the axis and then remove the Measure Names field from the All marks card.

remove both the axis titles (right click axis > edit axis), hide the right hand axis (right click, untick show header), and format to remove the column divider from the header section only.

Now we’ve got the core display, we need to create the following fields

No. of Calls

WINDOW_SUM([Call Count])

Highest Call Vol

WINDOW_MAX([Call Count])

Lowest Call Vol

WINDOW_MIN([Call Count])

Avg Call Vol

WINDOW_AVG([Call Count])

format this to a number with 0 dp

Calls this period

WINDOW_MAX([Call Count – Most Recent])

the window_max is required here, as the data set we’re displaying at the day level, has 2 values – the latest value and null. We only want to return 1 value, which is the maximum of these.

Previous Period

WINDOW_MAX(IF LAST()=1 THEN [Call Count] END)

LAST()=1 returns the value of the next to last record, and the window_max is again applied, as the nested IF clause will return null for all others records.

Period Var

[Calls this period] – [Previous Period]

Add each of these fields, one by one, to Rows following the steps below

  • Add to rows (it will automatically display as a green continuous pill).
  • change to discrete (right click on the pill and select discrete – the pill will turn blue and move to before the green pills)
  • Explicitly set the table calc to be computing by Timestamp (as above)

Once, you should have something that looks like this

but I noticed, that the display in the solution is sorted based on the total number of calls and not by Team, so add a Sort to the Team pill to sort by Call Count descending

Update the Tooltip if you wish, and then add the viz to a dashboard, floating the Timestamp filter.

My published viz is here.

Happy vizzin’!

Donna

Can you build a colour-coded filter?

Donna ColesLeave a comment

Erica collaborated with Giulio D’Errico for this week’s #WOW2025 challenge, which contained lots of features, though the main challenge was to display filter on Region, which along with the Region name also displayed a KPI indicator that could change based on selection from other parameters.

Defining the parameters

We need 3 parameters for this challenge

pMeasure

strig parameter that lists the two options Profit and Sales; defaulted to Profit.

pProfitThreshold

integer parameter that lists the specified values, defaulted to 2,000

pSalesThreshold

integer parameter that lists the specified values, defaulted to 30,000

Building the core scatter plot

Add Sales to Columns and Profit to Rows and Sub-Category to Detail. Show the 3 parameters.

When pMeasure = Profit, we need to display horizontal reference lines against the Profit axis, and when Sales is selected we need to display vertical reference lines against the Sales axis. We need the following fields to return the user defined thresholds:

Ref – Profit Threshold

IF [pMeasure] = ‘Profit’ THEN [pProfitThreshold] END

Ref – Sales Threshold

IF [pMeasure] = ‘Sales’ THEN [pSalesThreshold] END

We also need to define the average per measure for each region:

Sales Avg Per Region

{FIXED [Region]: SUM([Sales])} / {FIXED: COUNTD([Sub-Category])}

Profit Avg Per Region

{FIXED [Region]: SUM([Profit])} / {FIXED: COUNTD([Sub-Category])}

and then we can create

Ref – Profit Avg

IF [pMeasure] = ‘Profit’ THEN [Profit Avg Per Region] END

Ref – Sales Avg

IF [pMeasure] = ‘Sales’ THEN [Sales Avg Per Region] END

Add the 4 Ref – XXX fields to the Detail shelf. Then add 2 reference lines to the Sales axis; one referencing Ref – Sales Avg (coloured as a purple dashed line at 100% opacity) and one referencing Ref – Sales Threshold (coloured as a black dashed line at 50% opacity). Display a custom label and then format the label to be aligned vertically and coloured based on the relevant line, and with a 0% shading. Set the pMeasure to Sales to make these display.

Then repeat, adding 2 reference lines to the Profit axis instead. Change pMeasure to Profit for these to appear.

Change the mark type to square. Each mark needs to be coloured whether it is above or below the average for the measure selected.

Colour

IF [pMeasure] = ‘Profit’ THEN
IIF(SUM([Profit]) >= SUM([Profit Avg Per Region]),1,0)
ELSE
IIF(SUM([Sales]) >= SUM([Sales Avg Per Region]),1,0)
END

Set this to be discrete and then add to the Colour shelf and adjust accordingly.

Creating the colour-coded filter

The viz needs to be filtered by Region, but the filter displayed needs to show the region name along with an indicator based on whether the average for the region is above the threshold or not. This took a bit of an effort, but I finally managed it.

We need a field to capture the ‘KPI indicator’ based on which measure was selected. It also needs to be computed per region. We need a FIXED LoD for this, and I made use of coloured unicode characters from this site.: https://unicode-explorer.com/ (large yellow circle and large green circle which you can just ‘copy and paste’ into the calculation)

Region Indicator

{FIXED [Region]: (

IF [pMeasure] = ‘Profit’ THEN
IIF(SUM([Profit Avg Per Region])>=[pProfitThreshold],’🟢’,’🟡’)
ELSE
IIF(SUM([Sales Avg Per Region])>=[pSalesThreshold],’🟢’,’🟡’)
END
)}

I then created

Filter – Region

[Region Indicator] + ‘ ‘ + [Region]

Add this to the Filter shelf, select all values and show the filter. If you change the pProfitMeasure to Profit and pProfitThreshold to 6,000, you’ll see the KPI indicators change.

Format the Tooltip

The tooltip requires several calculated fields to be created. Certain fields only need a value based on the pMeasure and others have conditional formatting (different colours) applied. For the tooltip, I created all these fields:

Tooltip – Measure Value

IIF([pMeasure]=’Profit’,[Profit],[Sales])

Tooltip -Threshold

IIF([pMeasure]=’Profit’, [pProfitThreshold], [pSalesThreshold])

Tooltip – Measure Value Above Avg

IF [Colour] = 1 THEN SUM([Tooltip – Measure Value]) END

Tooltip – Measure Value Below Avg

IF [Colour] = 0 THEN SUM([Tooltip – Measure Value]) END

Tooltip – Above text

IF [Colour] = 1 THEN ‘above’ END

Tooltip – Below text

IF [Colour] = 0 THEN ‘below’ END

Label – Region

IIF(COUNTD([Region])>1, ‘All regions’, MIN([Region]))

Add all these fields to the Tooltip. Update the Tooltip to reference the fields and the pMeasure parameter, colouring the text as required. Some of the fields will only display based on the filters selected, so they get places side by side with no spacing.

Finalise the viz by updating the title to reference the pMeasure and the Label – Region field. Remove all gridlines, axis rulers, zero lines etc. Colour the background of the sheet to pale blue.

Building the Overall Indicator

For the bonus challenge, we need to display an indicator that is green if all the regions are green and yellow if at least 1 region is yellow.

On a new sheet, add Region and Region Indicator to Rows and show the 3 parameters.

We’re going to create a field that will return 1 if the Region Indicator is yellow and 0 otherwise.

Region Indicator – Is Below

IIF( [Region Indicator] = ‘🟡’,1,0)

Set to be discrete and add to Rows. Change the pProfitThreshold to 6000 to see the flag change.

Create

Overall Region Indicator

IIF(WINDOW_MAX(MAX([Region Indicator – Is Below]))=1,’🟡’, ‘🟢’)

This says, if the maximum value of the rows ‘in the window’ is 1, then display a yellow indicator, else green. Add to Rows, and adjust the pProfitThreshold to see the behaviour.

Create a field

Filter – Index = 1

INDEX() = 1

Add to Filter shelf and set to True

Move Region to Detail. Remove Region Indicator and Region Indicator – Is Below. Adjust the table calculation setting of Overall Region Indicator to compute using Region only, and do the same for the tableau calculation on Filter – Index = 1 (re-edit the filter after changing, so only True is selected).

Note – originally I used a transparent shape mark type and displayed the indicator as a label, but after publishing to Tableau Public, the indicator became distorted, so I adjusted how this was built.

Set the mark type to circle and add Overall Region Indicator to Colour. Adjust to be green or yellow, depending on the colour of the KPI indicator (you’ll need to change the pProfitThreshold value to ensure you set the colour for both the yellow and green options).

Finally create

Tooltip – Overall Indicator

IIF([Overall Region Indicator]=’🟢’,’All regions meet the ‘ + [pMeasure] + ‘ target’, ‘At least one region does NOT meet the ‘ + [pMeasure] + ‘ target’)

Add this to Tooltip and then set the background colour to pale blue.

Building the dashboard & adding dynamic zone visibility

Using layout containers, add the viz to a dashboard. Use a horizontal layout container to arrange the parameters, the Region filter and the Overall Indicator sheet. I used a floating text object to display the ‘legend key’ again copying come unicode characters from the website referenced earlier.

Then create 2 new boolean calculated fields

Is Profit

[pMeasure] = ‘Profit’

Is Sales

[pMeasure] = ‘Sales’

Select the Sales Threshold parameter object, then update the visibility so it only displays if Is Sales is true (via the Layout > Control visibility using value option)

Repeat the same for the Profit Threshold object, but reference the Is Profit field instead.

Now as you switch the measure between Sales and Profit, the relevant threshold parameter will display. My published viz is here.

Happy vizzin!

Donna

Can you visualise yearly rank change in Sub-Category sales?

Donna ColesLeave a comment

Yusuke set this interesting challenge : to combine a ‘bump’/’slope’ chart visualising the change in rank whilst also visually displaying the Sales value for the relevant Sub-Category in the ranked position.

Defining the calculations

This challenge will involve table calculations, so I’m going to start by building out the various calculations that will be required and displaying in a tabular view.

Add Category to Filter and select Office Supplies. Then add Sub-Category and Order Date at the Year level as a discrete (blue) pill to Rows. Add Sales to Text.

Create a new field

Sales Rank

RANK(SUM([Sales]))

And add to the table, and verify the table calculation is set to compute by Sub-Category only.

We will need to ‘colour’ the viz based on the rank compared to the previous year. For this create

Is Min Year

{MIN(YEAR([Order Date]))} = YEAR([Order Date])

which will return true for the first year in the data (in this instance 2022) and then create

Colour

IF [Sales Rank] = LOOKUP([Sales Rank],-1) OR ATTR([Is Min Year]) THEN ‘Same as last year’
ELSE ‘Different from last year’
END

If the rank is the same as the previous one, or it’s the first year, then treat as the same, otherwise treat as different.

Add the Colour field to the table, and this time make sure the table calculation for Colour is computing by Year of Order Date only (while the nested calc for Sales Rank should still be computed by Sub-Category only)

The labels on the viz only want to show in certain scenarios – if it’s the first record (ie for 2022) or there has been a change in rank. We need

Label : Rank & Sub Cat

IF ATTR([Is Min Year]) OR [Colour] = ‘Different from last year’ THEN STR([Sales Rank]) + ‘ | ‘ + MIN([Sub-Category]) END

and

Label : Sales

IF ATTR([Is Min Year]) OR [Colour] = ‘Different from last year’ THEN SUM([Sales]) END

format this to $ with 0dp

Add these to the sheet, and double check the nested table calculations on each pill are computing as required (Sales Rank by Sub-Category only, Colour by Year Order Date only)

Now we have all this, we can start building

Creating the Viz

On a new sheet, add Category to Filter and select Office Supplies. The add Order Date to Columns, but set to be continuous (green) pill at the Year level. Add Sub-Category to Detail and add Sales Rank to Rows as a discrete (blue) pill. Verify the table calculation setting against the Sales Rank pill is by Sub-Category only.

Change the mark type to line and then add Order Date to Path. By default it should be at the Year level as a discrete pill.

This is the ‘bump’ chart.

Now add another instance of Order Date to Columns as a continuous pill at the Year level to essentially duplicate the display. On the 2nd marks card, change the mark type to Gantt

This gives us the ‘starting point’ for each ‘bar’. But we need to determine the size for each bar. First we’re going to ‘normalise’ the sales values for all the sales being displayed so we get a value between 0 and 1, where 0 is the smallest sale, and 1 is the largest.

Normalised Sales

((SUM([Sales]) – WINDOW_MIN(SUM([Sales]))) / (WINDOW_MAX(SUM([Sales])) – WINDOW_MIN(SUM([Sales]))))

To see what this is doing, format the field to 2dp, then add the field to the tabular view, and ensure the table calculation is computing by both Sub-Category and Year Order Date.

But the ‘axis’ we want to plot the bar length against is in years, so we need to adjust this size to be a proportion of a year (ie 365 days)

Gantt Size

//proportion of a year
[Normalised Sales] * 365

Add this to the Size shelf on the 2nd marks card on the viz. Adjust the table calc setting so it is computing by all the fields listed.

We now have the core concept so now we can start finalising the display.

Make the chart dual axis and synchronise the axis.

Set the view to fit height.

On the 1st marks card (that represents the line)

  • change the line style to dotted (via the Path shelf)
  • reduce the Size to suit
  • change the colour to pale grey
  • Add Label : Sales and Label : Rank & Sub Cat to the Label shelf.
    • Adjust the table calc settings of each so the nested table calcs in each have Sales Ranks by Sub Category only and Colour by both the Year Order Date fields only.
    • Adjust the layout of the text as required
    • Align the font to be top right
    • Change the font style (bold & black)
    • Ensure the Label is set to ‘allow labels to overlap marks’
  • Remove the Tooltip

On the 2nd marks card, the gantt bar

  • Add Colour to the Colour shelf and adjust the colours accordingly.
    • Verify the table calc settings are as expected
    • I chose to reduce the opacity slightly, so I could see the dotted line underneath (set to 70%)
  • Add Sales to Tooltip (format to $ with 0 dp) and the adjust Tooltip as required

Then we just ned to finalise the formatting/display

  • Set the font of the years and rank numbers to black & bold.
  • hide the Sales Rank label heading (right click > hide field labels for rows)
  • remove row & column dividers
  • Add black column gridlines (I set to the 2nd thickness level), and remove any row gridlines
  • Edit the top axis to have a fixed start (use default option) and end at 31/12/2025 so the 2026 label and line disappears.
  • Remove the title from the top axis.
  • Edit the bottom axis – remove the tile, and then set the tick marks to None, so the bottom axis now looks empty.

And that should be it. Now add the sheet to a dashboard and display the category filter as a single select, customising the remove the ‘all’ option.

My published viz is here

Happy vizzin’!

Donna

Let’s Practice RegEx in Tableau with Generative AI

Donna ColesLeave a comment

Yoshi set this week’s challenge which focused on 2 areas : the use of tools such as CHAT GPT to help us create Tableau RegEx functions (which are always tricksy), and the build of the chart itself.

Creating the REGEX calculated fields

I chose to use CHATGPT and simply entered a prompt as

“give me a regex expression to use in Tableau which extracts a string from another string in a set format. The string to interrogate is”

and then I pasted in the string I’d copied from one of the Session Html fields. I got the following response

along with many more code snippet examples. I used these to create

Session Title

REGEXP_EXTRACT([Session Html], '<div class="title-text">(.*?)</div>')

Description

REGEXP_EXTRACT([Session Html], '<div class="description"[^>]*><div>(.*?)</div>')

Location

REGEXP_EXTRACT([Session Html], '<span class="session-location"[^>]*>(.*?)</span>')

Session Level

REGEXP_EXTRACT([Session Html], 'session-level-([a-zA-Z]+)')

Alias this field to show the values in proper case (ie ‘Advanced’ rather than ‘advanced’) and display Null as ‘All Levels’

Session Date

REGEXP_EXTRACT([Session Html], '<span class="semibold session-date">(.*?)</span>')

Session Time

REGEXP_EXTRACT([Session Html], '<span class="semibold session-time">(.*?)</span>')

Start Time

REGEXP_EXTRACT([Session Html], '<span class="semibold session-time">([0-9: ]+[AP]M)')

End Time

REGEXP_EXTRACT([Session Html], '- ([0-9: ]+[AP]M)')

Creating the additional fields

All of the RegEx functions return string fields. To build the viz, we need actual date fields and additional information

AM|PM

IIF(CONTAINS([Start Time],’AM’), ‘AM’, ‘PM’)

Date

DATE(DATEPARSE(“MMMM d yyyy”, SPLIT([Session Date], “, “, 2) + ” 2023″))

returns the day of the session as a proper date field, all hardcoded to 2023, since this is when the data is from.

Start Date

DATETIME(STR([Date]) + ” ” + [Start Time])

returns the actual day & start time as a proper datetime field.

End Date

DATETIME(STR([Date]) + ” ” + [End Time])

Duration

DATEDIFF(‘second’, [Start Date], [End Date])

Add fields to a table as below

Firstly, when we build the viz, we’ll need to sort it based on the Start Date, the Session Level (where Advanced is listed first, and All Levels last) and the Duration (where longer sessions take higher precedence) . For this we need a new field which is a combination of information related to all these values.

Sort

STR([Start Date]) + ‘ – ‘ + STR(
CASE [Session Level]
WHEN ‘advanced’ THEN 4
WHEN ‘intermediate’ THEN 3
WHEN ‘beginner’ THEN 2
ELSE 1
END
) + STR([Duration]/100000)

(this just took some trial and error)

Add this to the table after the Session ID pill and then apply a Sort to the Session ID pill so it is sorting by the Minimum value of the field Sort Ascending. You should see that when the start time and session level match, the sessions are sorted with the higher duration first.

The viz also lists the AM & PM sessions as separate instances, where the 1st session of the PM session is displayed on the same ‘row’ as the 1st session of the AM session. To handle this we need

Session Index

INDEX()

Make this discrete and add to the table after the AM|PM pill. Change the table calculation so it is computing by all fields except AM|PM and Session Date. The numbering should restart at each am/pm timeslot

Finally, the last field we need to build this viz, is another date field, so we can position the gantt chart bars in the right places. As the viz already segments the chart by Session Date and AM|PM, we can’t reuse the existing Start Date field as this will display the information as if staggered across the 3 days. Instead we want to create a date field, where the day is the same for al the sessions, but just the time differs

Baseline Date

DATETIME(STR(#2023-01-01#) + ” ” + [Start Time])

the date 01 Jan 2023 is arbitrary and could be set to any day. Add this into the table, so you can see what it’s doing. You will probably need to adjust the table calculation on Session Index again to include Baseline Date in the list of checked fields.

Building the viz

On a new sheet, add Session Date to Columns and manually re-order so Tuesday listed first. Then add AM|PM to Columns . Add Baseline Date as a continuous exact date (green pill) to Columns . Add Session Id to Detail then add Session Index to Rows and adjust the table calculation so it is computing by all fields except Session Date and AM|PM.

Create a new field

Size

SUM([Duration])/86400

and add this to the Size shelf. 86400 is the number of seconds in 24hrs, so adjusts the size of the gantt bars to fit the timeframe we’re displaying.

Add Session Level to Colour and adjust accordingly. You will need to readjust the Session Index table calc to include Session Level in the checked fields. Add a border to the bars. Edit the Baseline Date axis so the axis ranges are independent

Add Description and Session Title to Detail and again adjust the Session Index table calc to include these fields too. Apply a Sort to the Session Id field so the data is sorted by the Sort field descending

Add Location, Start Time and End Time to Tooltip, and update accordingly. Then apply formatting to

  • change font of the Session Date and AM|PM header values
  • remove the Session Date/ AM|PM column heading label (right click > hide field labels for columns)
  • Hide the Session Index field
  • Hide the Baseline Date axis
  • Add column banding so the Wednesday pane is coloured differently

Add the ability to highlight the Session Title and Description by selecting Show Highlighter from the context menu of each pill

Then add the sheet to a dashboard, using containers to display the colour legend and the highlighter fields.

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

Happy vizzin’!

Donna

Can you create this seemingly simple line chart?

Donna ColesLeave a comment

Lorna set this week’s #WOW2025 challenge asking us to recreate what looked to be a simple line and area chart combination. I have to admit this was indeed a bit tricksy. I built out the data relatively quickly, but when trying to create the area chart I just wasn’t getting any joy.

After lots of trial and error, attempting various options, I eventually resorted to checking out Lorna’s solution. I found there were two specific areas that were causing the creation of the area chart to fail..why this happens is still a mystery….

Before we get on with the solution, I figured it was worth detailing at the start what I tried that failed, just in case you’ve been banging your head against a brick wall too 🙂

What didn’t work

The solution requires table calculations; for one calculation we need a percent of sales per quarter which means we also need to work out the total sales for the quarter. I originally used a FIXED LOD for this but found I could only get the area chart to work if I used a WINDOW_SUM() table calculation instead.

This challenge also requires all the customers for each quarter to be in the view to identify which are in the top X. I used a sorted INDEX() table calculation to identify the top X, but this too failed to work when it came to actually creating the area chart. Using the RANK() table calculation instead worked.

Like I said before why? I don’t know… but putting down as one of ‘just those things’ and hoping that maybe I’ll remember this post in future if it happens again!

Now back to the solution guide…

Creating the calculations

We’re dealing with table calculations, so I’m going to build out the required data in a tabular format to start with.

Create a parameter

pTop

Integer parameter ranging from 5 to 20 with the step size of 5 defaulted to 20

Show this parameter on the sheet, and then create a calculated field

Order Date (Quarters)

DATE(DATETRUNC(‘quarter’, [Order Date]))

Format to the YYYY QX style.  Add Order Date (Quarters) to Rows as a discrete exact date (blue pill). Add Customer Name to Rows and add Sales to Text.

We need to identify customers who are in the top x for each quarter. Create a new calculated field

Is Top X Customer?

RANK(SUM([Sales]))<=[pTop]

Add to Rows and adjust the table calculation so it is computing by Customer Name only. 

We now want the Sales just for those customers who are in the top x, so create

Top X Sales

IF [Is Top X Customer?] THEN SUM([Sales]) END

Add this field to Rows and we should see that Sales are only displayed for those customers that where Is Top X Customer? = True.

We now need the total of these sales per quarter so create

Total Top X Sales

WINDOW_SUM([Top X Sales])

Add this to the table and adjust the table calculation so both nested calculations are computing by just Customer Name. You should see that the total value is the same for every row for each quarter 

We also need the value of the total sales in the quarter regardless of whether the customer is in the top X or not so create

Total Sales per Quarter 

WINDOW_SUM(SUM([Sales]))

Add this to the table and again adjust the table calculation to compute by Customer Name only.

Now we have these two figures we can calculate the percentage. Create a new calculated field

Sales % per Quarter 

[Total Top X Sales]/[Total Sales per Quarter]

Format this as a % to 1dp. Add to the table.

Duplicate this sheet. I like to do this as I make further changes so I don’t want to lose what I had.

Remove all the surplus field so that only Order Date (Quarters), Customer Name and the Sales % per Quarter fields remain 

Create a new field

Customer Index

INDEX() 

Convert this field to discrete (right click on the field).

Add this field to the Filter shelf and select 1. Adjust the table calculation so that it is computing using Customer Name only and sorted by SUM of Sales 

Re-edit the filter and reselect 1 (making changes to the table calculation resets the filter values). 

If everything has been set properly then you should end up with 1 row per quarter. Move the Customer Name pill from Rows to Detail.

We’ve now got the core fields we need to build the viz.

Building the Viz

Once again start by duplicating this sheet. Move Order Date (Quarters) to Columns and change to be continuous (green pill), then move Sales % per Quarter to Rows.

Add another instance of Order Date (Quarters) to the path shelf and change to be an attribute. You should now have a line chart. Increase the size of the line a little.

Add another instance of Sales % per Quarter to Rows, making sure the table calculation is set exactly as the existing version. Change the mark type of the 2nd marks card to Area.

Make the chart dual axes and synchronise axes .

Finally, tidy up the chart by 

  • Adjusting the Tooltip 
  • Removing gridlines, zero lines and row/column dividers
  • Hide the right hand axis 
  • Fix the left hand axis to end at 1 (so the axis goes to 100%)
  • Edit the left hand axis title
  • Update the sheet title to reference the pTop parameter

Then add the viz to a dashboard. My published viz is here.

Happy vizzin’!

Donna

Can you swap measures?

Donna Coles2 Comments

It’s back to the EFL this week for my #WOW challenge. Once again I’ve tried to provide a multi-level challenge – a version that uses some core skills and features, and a version that just pushes the display a bit further, just for fun. I’ll start with the core build and then use that as the base for the bonus challenge.

Setting up the parameters

The main crux of this challenge is measure swapping, so for this we need a parameter

pMeasure

integer parameter listing values 1 to 4 which are aliased as per the screen shot below. Default value is 1 (Points).

Note – you can use a string parameter with the actual words. I just chose to use this method to demonstrate the aliasing ability. Also when referencing this parameter in a CASE statement (which we’ll do shortly), using integer values for comparisons is slightly more efficient than string comparisons.

We also need the user to have the ability to select the team they want to track

pSelectedTeam

string parameter defaulted to your preferred team (I chose Chelsea). This is a List parameter that is populated from the Team field via the Add values from button

Building the calculations

We need to determine the measure to display based on the parameter selection

Measure to Display

CASE [pMeasure]
WHEN 1 THEN SUM([Cumulative Points])
WHEN 2 THEN SUM([Cumulative Goal Difference])
WHEn 3 THEN SUM([Cumulative Goals For])
WHEN 4 THEN SUM([Cumulative Goals Against])
END

We also will need to colour the bars based on the selected team

Is Selected Team

[Team]=[pSelectedTeam]

and we need to sort the data based on best to worst, but need to consider that for Goals Conceded, the higher the value the worse the team is.

Sort Measure

IF [pMeasure] = 4 THEN [Measure to Display]*-1 ELSE [Measure to Display] END

We only want to show teams once they start participating in a Season. For this, we need to identify the team’s 1st season in the EFL

1st Season per Team

{FIXED [Team]: MIN(IF [Cumulative Points] > 0 THEN [Season End Year] END)}

and then we can create a field we can filter on, based on this

Show Team

[Season End Year]>=[1st Season per Team]

We only want to show a label against the 1st team and the selected team, so create

Label to display

IF MIN([Is Selected Team]) OR FIRST()=0 THEN [Measure to Display] END

and finally, we need to display the value of the current season’s measure on the tooltip, as well as the cumulative value, so we need another case statement

Tootltip Measure

CASE [pMeasure]
WHEN 1 THEN SUM([Points])
WHEN 2 THEN SUM([Goal Difference])
WHEn 3 THEN SUM([Goals For])
WHEN 4 THEN SUM([Goals Against])
END

Building the core bar chart

On a new sheet, add Team to Rows and Measure to Display to Columns. Add Season End Year to Filter and select 1993. Add Show Team to Filter and select True. Apply a sort to the Team field to sort by the field Sort Measure descending.

Add Is Selected Team to Colour and adjust accordingly. Add Label to display to Label. Add Season and Tooltip Measure to Tooltip and update accordingly,

Show the pMeasure and pSelectedTeam parameters and the Season End Year Filter. Adjust the Season End Year filter control so that the All option isn’t available and it displays as a single value slider control.

Move the Season End Year filter control on by one value and notice how the chart transitions. Adjust the Animations settings (Format menu > Animations) to be sequential and slow

Finally tidy up the display by

  • hiding the Measure to Display axis (right click > uncheck show header)
  • hiding the Team row label (right click > hide field labels for rows)
  • widen each row a bit
  • hide gridlines, zero lines, axis rulers and axis ticks
  • add pale grey row dividers
  • set the background colour of the worksheet
  • adjust the font of the row labels – I used Tableau Book 8pt in colour #3e1756 (dark purple)

Name the sheet Core or similar and add to a dashboard setting it to Fit Entire View

Add a title to the dashboard that references the pSelectedTeam parameter.

My core viz is here.

Building the bonus viz

Start by duplicating the core viz sheet.

We’re going to use a gantt bar to simulate a central line for each row. This bar needs to extend to the largest measure in the table for every row, so this is the point we’ll plt

Max Measure

WINDOW_MAX([Measure to Display])

Add this to the Columns shelf, and on the Ma Measure markls card that gets added, remove the Is Selected Team from the Colour shelf, and change the mark type to gantt bar.

The bar needs to extend to the 0 or the minimum value in the window (if its less than 0), so we need a field to show the difference between the max and the minimum of 0 or the ‘window min’, but we need to multiple by -1 so the size extends in the right direction.

Max-Min Diff

([Max Measure] – MIN(WINDOW_MIN([Measure to Display]),0)) * -1

Add this to the Size shelf, and then update the size to be as small as possible. Remove Label to Display from the marks card and add a border the same colour as the background to the Gantt bar (via the Colour shelf) to make the line very narrow.

Add Team to the Label shelf and align centre left. Format the label text to be 8pt and dark purple. Then make the chart dual axis and synchronise the axis.

Right click the top axis and select move marks to back. Then hide both axis (right click, uncheck show header) and hide the Team pill on Rows too (again uncheck show header)

Verify the Tooltip on the gantt bar displays the same as on the main bar. If not add the relevant fields and adjust to match.

Tidy up the formatting by removing the row and column dividers. If need be adjust the colour of the Gantt bar to be a paler grey.

Change the measure value to Goal Difference and adjust the year to 2024 and check the display looks as expected, especially at the bottom – the gap between the label of the team at the bottom and the bar is minimal.

Add the chart to a dashboard – the simplest way is to duplicate the core dashboard and then use the swap sheets feature to quickly swap the main vizzes.

My published viz is here

Happy vizzin’!

Donna

Can you show the top X customers in EACH of the last 3 years and their contributions to Sales?

Donna ColesLeave a comment

For Community Month at #WOW2025 towers, Lorna presented a challenge one of her colleagues had brought to her which they solved together. The need is to identify the top X customers in each year (which may not contain the same set of customers each year), and then present the sales contribution, either as a group or individually compared to the rest. Lorna gave a hint in the challenge that sets would help : “Your job is to figure out the best way to SET this up with the last 3 years dynamically”.

It took me a bit of a while to figure out how to make this work, and at the point of writing, haven’t looked at the solution to know if there was a better way. I ultimately ended up creating 3 sets to fulfil this challenge.

Setting up the parameters

This challenge requires 3 parameters

pTop

This identifies how many ‘top’ customers we want to consider. Defined as an integer from 10 to 100, defaulted to 20, that increments every 10 units

pShowCustomers

Determine whether the top customers’ contributions are displayed individually or as a group. Defined as a boolean, defaulted to False, and aliased to Yes or No

pPercentofTotal

Indicate whether the information is displayed as a % of total sales for that year, or as absolute sales values. Defined as a boolean, defaulted to True, and aliased to Yes or No.

Defining the core calculations

The requirement states to be able to determine the last 3 years ‘dynamically’. For this I created

Max Date

{FIXED: MAX([Order Date])}

to return the maximum Order Date in the whole data set.

We want to be able to restrict the data to the last 3 years, so create

Records to Show

DATEDIFF(‘year’, [Order Date], [Max Date]) <=2

I need to create a set for each of the 3 cohorts – the top customers for the latest year, the top for the previous year and the top for the year before that. For this I first need to determine the Sales for each of those timeframes.

The sales for the current year

Sales – CY

IF YEAR([Order Date]) = YEAR([Max Date]) THEN [Sales] END

The sales for the previous year

Sales – PY

IF YEAR([Order Date]) = YEAR([Max Date])-1 THEN [Sales] END

and the sales for the previous previous year

Sales – PPY

IF YEAR([Order Date]) = YEAR([Max Date])-2 THEN [Sales] END

I can then create the sets of customer I need (right click on Customer ID > Create > Set)

Customer ID Set – CY

get the Top number of records using the pTop parameter, and based on the sum of the Sales – CY field

Repeat the same process to create

Customer ID Set – PY

get the Top number of records using the pTop parameter, and based on the sum of the Sales – PY field

and

Customer ID Set – PPY

get the Top number of records using the pTop parameter, and based on the sum of the Sales – PPY field

To verify/understand what we’ve created, on a new sheet

  • Add Customer ID to Rows
  • Add Order Date to Columns at the Year level as a discrete (blue) pill
  • Add Records to Show to Filter and set to True.
  • Add Sales to Text.
  • Sort by the 2024 Sales value descending.
  • Add Customer ID Set – CY to Rows.

You should see the first 20 rows (assuming you haven’t changed the pTop value, display as In

If you now change the sort to sort by 2023 Sales descending, and swap the Customer ID Set – CY with the Customer ID Set – PY, you’ll get the same

So now that’s understood, we want to tag each of our customers based on the year of the order, whether they’re in the top n or not, and whether we want to display the customers individually or not

Group – Detail

IF (YEAR([Order Date]) = YEAR([Max Date]) AND [Customer ID Set – CY]) THEN
IF [pShowCustomers] THEN [Customer ID]
ELSE ‘Top N’
END
ELSEIF (YEAR([Order Date]) = YEAR([Max Date])-1 AND [Customer ID Set – PY]) THEN
IF [pShowCustomers] THEN [Customer ID]
ELSE ‘Top N’
END
ELSEIF (YEAR([Order Date]) = YEAR([Max Date])-2 AND [Customer ID Set – PPY]) THEN
IF [pShowCustomers] THEN [Customer ID]
ELSE ‘Top N’
END
ELSE
‘Other’
END

We’re also going to want to count customers, so need

Count Customers

COUNTD([Customer ID])

On a new sheet add Order Date at the year level as a discrete (blue) to Rows and add Group Detail to Rows too. Add Records to Display to Filter and set to True. Add Sales and Count Customers into the table. Show the pTop and pShowCustomers parameters

When pShowCustomers is set to No, you should just see 2 groupings per year

When set to Yes, you’ll get the Customer IDs listed

Note – the Sales numbers should reconcile to the solution – the count might not, which I believe is due to the solution counting distinct Customer Names rather than Customer ID.

To finalise the core calculations we need to build the initial viz, we have a different display depending whether we’re displaying the absolute or % Sales values.

Create

Sales % Total

SUM([Sales]) / TOTAL(SUM([Sales]))

format to decimal to 2 dp and add into table, adjusting the table calculation so it is computing by the Group – Detail only, so the percentage per year is being displayed.

Then we need

Measure to Plot

IF [pPercentofTotal] THEN [Sales % Total]
ELSE SUM([Sales])
END

format this to a number to 2 dp (just so you can see it has a value) and add to the table, applying the same table calculation settings. Display the pPercentofTotal parameter and flip between to see the column change.

Building the Viz

On a new sheet, add Records to Show to filter and set to True. Add Order Date at the year level as a discrete (blue) pill to Rows. Add Group – Detail to Detail. Change the mark type to bar. Add Measure to Plot to Columns and adjust the table calculation, so it’s computing just by Group-Detail.

Ste the sheet to fit width and show the 3 parameters.

Create a new field

Group – Top N

IF (YEAR([Order Date]) = YEAR([Max Date]) AND [Customer ID Set – CY]) THEN ‘Top N’
ELSEIF (YEAR([Order Date]) = YEAR([Max Date])-1 AND [Customer ID Set – PY]) THEN ‘Top N’
ELSEIF (YEAR([Order Date]) = YEAR([Max Date])-2 AND [Customer ID Set – PPY]) THEN ‘Top N’
ELSE ‘Other’
END

and add to Colour, adjusting the colours to suit. You’ll then need to update the table calculation of the Measure to Plot field to ensure Group – Top N is also checked.

We need to display labels, but these need to differ based what measure we’re showing, and the format is different, so create

Label – % Total

IF [pPercentofTotal] THEN [Sales % Total] END

format this to % with 1 dp and

Label – Sales

IF NOT([pPercentofTotal]) THEN [Sales] END

format this $ K to 1 dp.

Add both of these to the Label shelf and ensure they are listed directly side by side. Only 1 will ever actually display.

Change the pShowCustomers to Yes, and then add a white border via the Colour shelf. Add a Sort to the Group – Detail pill to sort by Sales ascending.

Add Sales, Sales % Total and Count Customers to the Tooltip shelf. additionally create

Tooltip – Customer

IF [pShowCustomers] AND [Group – Detail] <> ‘Other’ THEN [Customer Name] END

and add this to Tooltip too. Adjust the Tooltip to suit (make sure Sales % Total) is computing by both Group – Top N and Group – Detail so has the correct numbers.

Finally, hide the axis (uncheck show header on the Measure to Plot pill) and hide the Order Date label (right click and hide field label for columns).

Then add the sheet to a dashboard, and arrange the parameters suitably.

My published viz is here.

Happy vizzin’!

Donna