Can you use Dashboard Extensions?

For this week’s #WOW2021 challenge, Lorna tasked us with using dashboard extensions, some of which can also be used on Tableau Public (see here). I haven’t had an opportunity to use extensions before, so this was going to be a brand new learning experience for me.

Modelling the Data

In a break from the ‘norm’ Lorna provided us with a new set of data to use, which had to be retrieved from the sources Lorna provided in the challenge

  • Emoji Sentiment – a csv file containing a summary of how often a particular emoji was used within tweets in 2015 and whether the tweets were classified as being positive, neutral, or negative in sentiment.
  • Emoji Database – a link to a site where after registering, you can download a csv file which defines and classifies each emoji

The first part of the challenge requires these data sources to be modelled using relationships in Tableau Desktop. Lorna hinted that a join calculation would be required on the codepoint fields.

I found this a bit odd, as both data sources contained an Emoji field which was automatically set to be the relationship field, and seemed to work.

For the purpose of this blog though, I’m going to attempt to rebuild my solution as I type, and use the suggested fields. The Unicode codepoint field in the Emoji Sentiment data needs to map to the codepoint field in the Emoji Database, but they’re not an exact match. We can prefix ‘0x’ to the codepoint field and ensure the case of the letters match. We can use a relationship calculation for this.

Grouping the Groups

This chart shows the top 20 emojis based on Occurrences and should filter to the appropriate group when a ‘category’ is clicked on the dashboard extension image on the left hand side.

The Emjoi Database data has a Group field, but this doesn’t exactly match the groupings on the image – some groups are ‘grouped’ together. I used Tableau’s in built grouping functionality to group the entries as required (right click field -> create -> group).


I grouped People & Body and Smileys & Emotion together and named them Smileys and People

Filtering by Top 20

The list of Emojis needs to show the Top 20 based on Occurrences, but also filtered by Category. Build out a basic table of

  • Emoji Sentiment : Emoji1, Unicode name on Rows
  • Occurrences on Text
  • Emoji1 on Filter, set to filter by Top 20 of Occurrences
  • Category as a Context Filter – select all values to filter by, then right click -> add to context. This means the data will be filtered based on the Category first before the Top 20 filter is applied. The pill will change to grey to show it is a context filter. Show the filter and you can test it’s working

Building out the Top 20 Chart

Now we have the basics of the filtering functionality, we can build out the rest of the chart.

We need to display percentages, so need fields

% Positive


formatted to 1 decimal place. Create similar fields for % Negative and % Neutral

First start by creating a duplicate of the Occurrences field and call it #. Then add this as a discrete pill to the Rows shelf. Remove Occurrences from the Text shelf. Then add Measure Values to Columns and filter by Measure Names so only % Positive, % Neutral and % Negative measures are displayed. Add Measure Names to Colour.

All this has been done on one axis, so now we can add another to display the Position – add this field to Columns. This will create a 2nd marks card. Remove the Measure Names fields from the card, and change the mark type to circle.

Add an additional field MIN(1) to Columns by ‘typing in’ (double click on the Columns area) . Then click on the pill and select dual axis which will combine this field with the Position measure. Synchronise axis. This unfortunately will probably set all the marks to be circle type

so we need to reset…

  • change the mark type of the Measure Values card to bar
  • remove Measure Names from the Position card
  • remove Measure Names from the MIIN(1) card
  • change mark type of MIN(1) card to bar, and reduce size to as small as possible

This should give you the core chart, which can now be formatted accordingly.

Rounded Bar Chart

I always forget how to build these for some reason, so a quick google gave me a refresher via Andy Kriebel’s tutorial on YouTube

  • Add Category to Rows
  • Occurrences to Columns
  • Type in MIN(0) on Columns
  • Drag the MIN(0) pill and drop it on the Occurrences axis. This will change the view so Measure Values is now on Columns and Measure Names is on Rows
  • Change the mark type to Line and drag the Measure Names pill from the Rows onto the Path shelf
  • Increase the size of the mark

Exclude the Null Category and manually sort the categories to match the order in which the entries are listed on the left hand image.

Set to show mark labels, only displaying them at the end of the line, and aligning middle right

Add Category to the Colour shelf and colour accordingly, then apply the relevant formatting again to remove gridlines, axis and hide the Category pill from displaying.

Adding & Configuring the Dashboard Extension

This challenge makes use of the Image Map Filter extension, which you need to download from this link and save the .trex file somewhere appropriate on you machine. I also chose to make use of the image Lorna used rather than create anything, so saved the image from the challenge page to my laptop.

Create a dashboard and add the 2 charts you’ve already built, then add the Extension object to the dashboard. When prompted select My Extensions and browse to the Image Map Filter .trex file you’ve saved.

You’ll then be prompted to configure the extension as below, selecting the image you’ve saved, which is set to scale to container; choosing the Category dimension which is what the chart is filtered by, and then selecting the Top 20 sheet

You then need to select the rectangle option, which allows you to ‘draw’ on the image

Create a rectangle around one of the options, and when prompted select the appropriate Category which the selection relates to.

Repeat this for all the options in the image.

Average Legend

To build this I simply duplicated the Top 20 chart, removed all the pills from the Rows shelf, removed the Emoji pill from the Filter shelf and then changed the aggregation of the Position pill from SUM to AVG. I had to re-tweak the tooltips too.

And after all that, I hope you have all the components you need to deliver this solution. My published viz is here.

Happy Vizzin’! Stay Safe!


Can you build a Fancy Text Table?

Ann Jackson provided this week’s challenge, to deliver a text table using only Measure Names & Measure Values. I thought with Ann’s introduction that “This challenge should be straightforward for users of all levels” that this would be relatively straightforward, but I have to confess there were moments that I struggled with this. I knew the fundamentals that I’d need to complete this; that all the columns except the first were going to need to be numbers (ie measures), that I’d have to use custom formatting to display the number in the required format (a shape, a date, a word), and that I’d need to use the ‘legends per measure’ functionality to colour each column independently of each other. But determining the best/worst date to display proved to be a bit tricksy! I got there in the end, but there was a fair bit of trial and error.

Custom Formatting

I’m going to step through the build of this, as I think that’s probably the easiest way to describe this challenge. But before I do, one of the core fundamentals to this is knowing about how numbers can be custom formatted. By that I mean when you right-click on a measure -> default properties -> number format -> custom

This box allows you to type in, but you need to know what format/syntax to use. If you set the formatting via one of the other options, then look at the Custom option, it’ll have an entry that will give you a starting point. The above is the format for a number set to 1 decimal place, and shows that negative numbers will be prefixed by a minus sign (-). If we wanted to always show a plus sign in front of a positive number, we can edit this custom formatting to +#,##0.0;-#,##0.0.

The first entry to the left of the semi colon (;) indicates what’s applied to positive numbers. The next entry, to the right of the semi colon, indicates what’s applied to a negative number.

With this knowledge, you can apply more ‘creative’ custom formatting to any numeric measure that contains positive and negative numbers. For example if you want to show a ☑ or a ☒ depending on a ‘yes/no’ or ‘true/false’ concept, then we can create a version of the field as a number along the lines of

Field as Number

If [Field] = ‘XXXX’ THEN 1 ELSE -1 END.

We can than custom format this field by entering ☑;☒ into the text box

The field can still be treated as a measure, since the underlying value is still a number (in this case +/- 1), it’s just displayed differently.

Building the measures

So now we’ve covered how this ‘sneaky formatting’ is working, we’ll get on with the overall build.

The data just needs data from 2019 & 2020, so I chose to set a data source filter to restrict to just these two years.

But, I wanted the rest of the challenge to derive the current year instead of hardcoding, so I created fields

Current Year

YEAR({MAX([Order Date])})

Last Year

[Current Year] – 1

From these, I could then use LoDs to create


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

This is formatted to $ with 0 dp

and then


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

again formatted to $ with 0 dp.

We then need an indicator which is ‘true’ if CY SALES is greater than LY SALES, but as discussed above, we need this to be a ‘measure’, which we can custom format.

CY vs LY


Custom format this as ✅;❌ (just copy these symbols from this page… they’ll look black and white in the dialog) – check out this page, to lift the images/other symbols from.

The actual difference identified by △ (again just copy and paste this symbol into the field name) is simply


formatted to $ with 0 dp. Once you’ve done this using the Currency(Custom) option, then go to the Custom option and add + to the front of the string :


Next up is the percentage difference


again format this first to a Percentage at 1 dp, then edit the Custom format to +0.0%;-0.0%

Now we’re getting to the slightly more complex part of the challenge – to identify the best and worst day in the month. We’ll start with the best day. We’re using FIXED LoDs throughout this, and while it’s probably possible to do in a single calculation, we’ll use multiple calcs to build up the components.

Order Month

DATENAME(‘month’,[Order Date])

This is the one dimension that’s going to be used in the final output, and simply outputs the month name (January, February etc).

In the data set, there can be multiple sales (ie orders) in a single day. We want to identify the total sales in 2020 (ie the current year) for each order date.

Sales Per Day

{FIXED [Order Date] : SUM([CY SALES])}

Now we’ve got the total sales per day, we want to identify the value of the maximum daily sales in each month

Max CY Sales Per Month

{FIXED [Order Month]: MAX([Sales Per Day])}

Now we need to identify the date in the month that the max daily sales ocurred


INT({FIXED [Order Month]: MAX(IF [Sales Per Day] = [Max CY Sales Per Month] THEN ([Order Date]) END)}) + 2

WOAH! WHAT??? Let’s try to break this down…

IF [Sales Per Day] = [Max CY Sales Per Month] THEN ([Order Date]) END

If the daily sales value is the maximum daily sales in the month, then return the associated Order Date. But we need to get a date per month, so we’ve wrapped this in a FIXED LoD, for each Order Month. LoDs require the value to be aggregated, so the IF statement gets wrapped in a MAX statement (note MIN would work just as well).

{FIXED [Order Month]: MAX(IF [Sales Per Day] = [Max CY Sales Per Month] THEN ([Order Date]) END)}

Finally, due to the nature of this challenge, that requires we only work with Measure Names & Measure Values, we will convert this date field to a number using the INT function.

The intention here, is that we can then use the Custom formatting option once again, to set the number as a date format – I chose dd mmm yyyy (ie 01 Jan 2020 format, as I feel its less confusing that working out whether the date is in UK or US format).

However, by a very weird circumstance, converting a date to an INT then formatting as a date, will give you a date 2 days out from the one you converted. I don’t understand why, and it left me scratching my head for some time. I had to sense check with a fellow #WOWer who had the same, and checking Ann’s solution, she also was handling the oddity, which is the reason for the +2 on the calculation.

We just create similar fields for identifying the worst day

Min CY Sales Per Month

{FIXED [Order Month]: MIN([Sales Per Day])}


INT({FIXED [Order Month]: MAX(IF [Sales Per Day] = [Min CY Sales Per Month] THEN ([Order Date]) END)}) + 2

format this to dd mmm yyyy

The final measure we need is based on determining the rank of the CY SALES per month. Ie if we ordered the months based on CY SALES descending, the top 6 would be marked as ‘Top’ and the rest as ‘Bottom’.



We can then custom format this to “Top”;”Bottom”

Formatting the Table

Create a text table by

  • Order Month on Rows
  • Measure Names on Columns
  • Measure Values on Text
  • Measure Names on Filter, filtered to just the relevant measures

Add Measure Values to the Colour shelf, and select the Use Separate Legends option to display multiple diverging colour legend controls.

It’s now a case of going through each measure and editing the colour palette, and other settings. Some of this was again a bit of trial and error for me – I chose options that worked.

For the black text fields (CY SALES, LY SALES, %DIFF), choose a diverging colour palette, then click on the coloured squares at each end and select black from the colour picker. Select Stepped Colour and reduce the steps to 2.

Apply the same concept to the BEST DAY and WORST DAY legends, but select the appropriate green or red colour instead.

For the remaining fields, select a diverging colour palette, select the appropriate red at one end, and green at the other, reduce the steps to 2

And subject to some other formatting tweaks (increase font sizes, centre text), this is enough to complete the challenge. My final published viz is here. Note, the published viz does have slight differences to what I’ve blogged… as with many things, you sometimes realise things can be simpler when you try again.

Happy vizzin’! Stay Safe!


Can you predict the future?

Continuing on from last week’s challenge, Candra Mcrae set this #WOW2021 challenge to introduce another new feature of v2020.4 (so you’re going to need this version as a minimum to complete this challenge). Predictive modelling isn’t something I use at all, so I was quite reliant on the help documentation Candra referenced. I’m also not overly familiar with the various different models, and when they should be used, so this isn’t something I’m likely to use personally, without careful consideration and thought – it’s worth reiterating Candra’s warning :

Viz Responsibly: While predictive analysis in Tableau has never been easier, we encourage you to be intentional in how you use this powerful feature because not doing so (e.g., selecting a model type not appropriate for your data) could lead to inaccurate results.  

The focus of this blog will be

  • Building the main chart
  • Creating the tooltips
  • Determining the data for the title
  • Building the measure selector
  • Adding the measure selector interactivity

Building the main chart

The data provided has some records related to years before 1993, but the requirement is just to use data from 1993 onwards, so the first thing I did was to set a data source filter (right click on data source -> Edit Data Source Filters) to restrict the whole data source to Year 1 >=1993

Next I created the measures we need to display

Total Enrollment

[Total enrollment 2 All students]

simply references the existing measure.

% Black Students

SUM([Total enrollment 2 Black students]) / SUM([Total Enrollment])

% Non-Black Students

1- [% Black Students]

These 3 measures need to be displayed on a single chart where the actual measure displayed is determined by user selection. This selection will be driven by the use of a parameter, that will be set by a parameter action. For now, we just need to establish the parameter.


This is simply a string parameter which will store the value of Total Enrollment by default.

Using this parameter, we can now decide which value we’re going to plot on the chart

Actual Value

CASE [pSelect_Measure]
WHEN ‘Total Enrollment’ THEN SUM([Total Enrollment])
WHEN ‘% Black Students’ THEN [% Black Students]
ELSE [% Non-Black Students]

Add this to a view by placing

  • Year 1 as continuous (green) pill on Columns
  • Actual Value on Rows

and you get the basic shape, although it’s not as ‘peaky’. This is resolved by editing the Actual Value axis (right click axis -> edit) and unchecking the Include zero checkbox.

Now change the text in the pSelect_Measure input parameter that’s displayed to % Black Students, and the chart will change. Verify it changes with the text % Non-Black Students too.

In reading through the Tableau KB documentation about Predictive Modeling Functions in Time Series Visualizations, I came to learn of the feature to Extend Date Range, something I’ve never come across before, and I’m not sure what version it first appeared in. Anyway, for this, you need to be working with a field which is a date datatype. The Year 1 field provided is an int.

I’m not entirely sure what I’ve done next is the optimum method, but it worked for me… some of it involved a bit trial and error when I came to defining and invoking the modelling feature later on. In writing this up, I’m essentially helping you to avoid the ‘back and forth’ steps I took in getting it all to work.

Anyway, I needed a date field to represent the year


MAKEDATE([Year 1],1,1)

This resolves to a field containing 1st Jan YYYY for each Year in the data set.

Replace Year 1 on the chart with this field, and changing it to the ‘continuous’ instance of the date by choosing the second ‘Year’ option from the context menu

This changes the pill to green and then the option to Extend Date Range is visible on the menu. Set this to 5 years using the custom option

After doing this you’ll get a 5 nulls indicator displayed, which is basically saying there’s some years without any data. This what we expect for now.

Now onto the modelling part. We need a new calculated field to contain the predicted value using the Gaussian process regression.

Predicted Value

MODEL_QUANTILE(‘model=gp’, 0.5,[Actual Value],ATTR(DATETRUNC(‘year’,[Year])))

again, this took a bit of trial and error to get the date field in the required format.

Add this to the Rows and again edit the axis to ‘exclude zero’. You should now see the data extending for the predicted value beyond 2018. You can now hide the 5 nulls indicator (right click -> hide indicator)

You can now combine to be a dual axis chart (don’t forget to synchronise axis), and apply the relevant formatting to change the marks, apply relevant colours, hide axis & gridlines etc. Note, I set the area chart to 25% opacity, rather than the 75% stated in the requirement, as this gave me the colour most similar to the solution.

Creating the tooltips

Hovering over the chart, the tooltips display the Actual, Predicted and Residual (Actual-Predicted) value for each point. But depending on the measure selected, the format differs – Total Enrollment is in K and the others are in %.

We can’t use the number formatting feature of a field to resolve this, so we need to be a bit more creative. I confess I started creating individual fields for each measure (Actual, Predicted, Residual) based on the measure type selected (Total Enrollment, % Black Students, % Non-Black Students), but this meant I was creating loads of calculated fields, which just seemed a bit unnecessary.

So after a bit of a think, I realised there was a better way.

First up, let’s get our residual

Prediction Residual

[Actual Value]-[Predicted Value]

Now, if we put the values in a tabular form, you can see what the precision of the values are depending on the measure stated

We need to format appropriately. Both displays required the values to be formatted to 1 decimal place, and both have a suffix, either a K or a %.

To get the value in the required display format

Tooltip – Actual Value

IF [pSelect_Measure]=’Total Enrollment’ THEN [Actual Value]/1000
ELSE [Actual Value] * 100

Format this to 1 dp.

Create a similar field for the predicted value, which should also be formatted to 1 dp.

Tooltip – Predicted Value

IF [pSelect_Measure] = ‘Total Enrollment’ THEN [Predicted Value]/1000
ELSE [Predicted Value] * 100

And finally Tooltip – Residual

[Tooltip – Actual Value] – [Tooltip – Predicted Value]

This needs to be custom formatted to +#,##0.0;-#,##0.0 which ensures a + symbol is always displayed for positive values.

Pop these onto the tabular display we built earlier, and you can see the values are now displaying in the way we need

Finally we need to create a field to store the required suffix

Tooltip – Value Suffix

IF [pSelect_Measure] = ‘Total Enrollment’ THEN ‘K’
ELSE ‘%’

We can now add these 4 fields onto the Tooltip shelf of the ‘All’ marks card, and create the tooltip as required

Determining the data for the title

As we need to only use 2 sheets to build this solution, and 1 sheet will be required for the measure selection, we have to incorporate the summary data displayed at the top of the dashboard as part of the title of the chart viz.

In the title, we need to display the following :

  • The latest year in the provided data set (ie 2018)
  • The latest year including the extended date range (ie 2023 – 5 years later)
  • The actual value from 2018 based on the selected measure
  • The predicted value from 2023 based on the selected measure
  • An indicator to show whether the values were likely to increase or decrease

The requirement was to ensure there was no ‘hardcoding’. And as we’re working on getting information related to a specific row (ie year) in a set of data that consists of multiple rows (years), then we’re going to need to make use of table calculations for this.

Let’s start with the ‘easier’ bits first. We want the Year of the latest in the actual data set, and we want this value to be essentially stored against every row in the data

Latest Year

{FIXED: MAX([Year])}

This returns the value of 2018.

Latest Year + 5

DATE(DATEADD(‘year’,5,[Latest Year]))

This simply adds 5 years to the Latest Year, so returns 2023.

Now when I’m using table calculations, I often prefer to see what the data is doing in the table itself, so I can be sure I’m doing things correctly. With the ‘extended year’ stuff, it’s a bit fiddly creating the table from scratch, so I simply started by duplicating the chart sheet ‘as crosstab’ (right click on the sheet name tab, -> Duplicate as Crosstab). Rearrange the fields so Measure Names is on Columns and Year is on Rows and the ‘Tooltip’ named fields are visible. Add Latest Year and Latest Year+5 to Rows, and you can see how these fields show the same value against every row.

Now, remove these fields, as by adding them, we’ve lost the additional ‘extended dates’ rows (ie the ‘fake’ rows that don’t actually exist in the data). Ok, so now we want to get the Actual Value associated to 2018, but then perpetuate this across every row in the data.

Latest Year – Actual

WINDOW_MAX(IF MIN([Year]) = MIN([Latest Year]) THEN [Tooltip – Actual Value] END)

If the Year is the same as Latest Year, then display the value from the Tooltip – Actual Value field. The WINDOW_MAX table calc, then spreads this same value across all rows displayed. Format to 1dp and add this to the table.

We need to do something similar to get the Predicted Value for 2023

Latest Year +5 – Predicted

WINDOW_MAX(IF LAST()=0 THEN [Tooltip – Predicted Value] END)

If we’re at the last row in the data, then display the value from the Tooltip – Predicted Value field. Again the WINDOW_MAX spreads the value across all the rows. Set this to 1 dp and add to the table.

And now we just need to get the increase/decrease indicator

Increase | Decrease

IF ([Latest Year – Actual])-[Latest Year +5 – Predicted]>0 THEN ‘decrease’ ELSE ‘increase’ END

So now we know we’ve got the correct values we need, we can add these fields to the Detail shelf of the chart sheet, so we can reference them in the Title of the chart.

We also need the Latest Year and Latest Year +5 fields added to the Detail shelf, but when you add these, you’ll notice that you lose the ‘extended years’. You can fix this by wrapping the fields in an ATTR function. Double click on the field, which will allow you to ‘type in’ to the field.

You should now be able to create the text in the chart title

Building the measure selector

Phew! Are you still with me… there’s a fair bit going on already, and now we’ve got to build the chart that will drive the user selection.

On a separate sheet, add

  • Measure Names to Rows
  • Measure Values to Detail
  • Measure Names to Text
  • Measure Names to Filter, and restricted to the 3 original measures – Total Enrollment, % Black Students, %Non-Black Students

Uncheck Show Header on the pill on the Rows, then format

  • Set background colour of the pane to a navy blue
  • Set row & column borders to be white
  • Set the text label to be white text, centred, and increase the font
  • Turn off the tooltip

Adding the measure selector interactivity

Create the dashboard and add both the charts. To add the interactivity so that on click of a row in the Measure Selection sheet, it changes the measure being displayed, we need to add a dashboard action, that changes a parameter (Dashboard menu -> Actions -> Add Action -> Change Parameter). Set the action to run on Select when the Measure Select sheet is clicked. The target parameter is pSelect_Measure and the Measure Names field should be passed into this.

And with all that, you should hopefully now have a working solution. My published viz is here (note, my Measure Selection sheet is slightly different from what I’ve described above). The above is a bit simpler I think.

Happy vizzin’! Stay Safe!


Can you highlight profits with Measure Names?

Luke Stanke provided his last challenge of #WOW2020 for the year with this viz to utilise Measure Names & Measure Values. This plots Cost against Sales per Sub-Category (the circles), which are then bounded by a lozenge. The Sales circle and the lozenge are coloured based on profitability, and the lozenges are labelled by Profit, although the position of the label is also based on profitability.

Obviously as the title of the challenge suggests, using Measure Names & Measure Values is key to this. As usual I’ll try to just pull out the main points I think you might find most tricky.

  • Building the core chart
  • Aligning the Sub-Categories against a horizontal line
  • Colouring the circles & lozenge
  • Positioning the labels
  • Formatting the labels
  • Creating a border around the white Cost circle

Building the core chart

You’ll need to create a calculated field to store the cost


SUM([Sales]) – SUM([Profit])

Once done, then add Sub-Category to Rows and sort by descending by Profit. Add Measure Values to Columns and filter just to Sales and Cost. Change the mark type to circle.

Add a 2nd instance of Measure Values to Columns and change the mark type to Line. Add Measure Names to Path.

Then make this chart dual axis and synchronise the axis. This will give the base chart.

Aligning the Sub-Categories against a horizontal line

Whenever you add a blue discrete pill to the rows or columns, you’ll get a ‘header’ pane, which means the label for the pill is by default positioned in the centre of a row, as demonstrated below if I add row dividers to the chart

The requirement is to show the row label aligned with a horizontal line. To achieve this, we need to add a MIN(0) field the Rows. Adding this green pill, creates an axis which has a 0 horizontal 0 line, which is positioned exactly in alignment with the row label

Removing the row dividers, and uncheck Show Header on the MIN(0) pill, and the right aligning the row label, we get the desired result.

Colouring the circles & lozenge

The circles are either coloured white for Cost or dark red or green for Sales depending on the profitability of the Sub-Category.

So we need a new calculated field

Is Profitable?


This returns true or false.

On the circles Measure Names mark card, add Is Profitable to the Colour shelf. If it’s not already there, then add Measure Names to the Detail shelf, then select the detail icon and choose the colour icon to also add Measure Names to the Colour shelf

This has the effect of giving you 4 colour combinations

which can then be edited to set the 2 combinations relating to Cost to white, Sales & True to dark green and Sales & False to dark red (at this point, you probably want to be setting the background colour of the whole worksheet to light grey (right click on sheet, format, select the Shading icon)

For the lozenge, you just need to add the Is Profitable field the the Colour shelf of the line Measure Names card, and adjust the size of the to make it slightly bigger than the circles (you may need to move marks to back to get the lozenge to sit behind the circles).

Positioning the labels

So the tricky thing about the labels is where they are positioned – they are to the right for the profitable sub-categories, and to the left for the non-profitable sub-categories. When you add a label, you can’t provide that sort of conditional logic to control the positioning. However, we happen to have 2 sets of marks cards (as dual axis), and so can use different fields to apply the labelling.

Label Profit is +ve

IF [Is Profitable] THEN SUM(Profit) END

This will only return a value for profitable sub-categories, otherwise the field will store blank.

Label Profit is -ve

IF NOT([Is Profitable]) THEN SUM(Profit) END

Conversely, this will only return a value for the non-profitable sub-categories.

Add the Label Profit is +ve field to the Label shelf of the Circle marks card. Adjust the positioning to be middle right, and adjust the settings as below (tbh this was just a bit of trial and error to find this worked :-)). You may want to additionally add a few <spaces> to the start of the label text to add a bit of breathing room.

Then on the Line marks card, add the Label Profit is -ve field to the Label shelf, but this time choose to Label Line Ends, and select Label end of line. Note – you can try to apply the same settings as above, but I found for some reason it increased the size of the mark around the line end… weird…

Formatting the labels

Right click on the Label Profit is +ve/-ve fields created and custom format with


Creating a border around the white Cost circle

Finally, a sneaky requirement was to add a border around the white circle that represented Cost only. This implied that using the formatting options on the Colour shelf that allows a border to be added to the mark wasn’t going to work, as this will apply to all marks and not just to the Cost circle.

I handled this by creating a 2nd instance of the Cost field (right click Cost and select duplicate).

I then added this Cost (copy) field to the Measure Values section of the chart on the left hand side. This doesn’t appear to do much, since the mark is directly on top of an existing mark, but you will see the Colour legend associated to the Circle marks card change and add 2 new entries.

I changed the colours of the 2 new entries in the Colour legend to a dark grey, then added Measure Names to the Size shelf of the Circles marks card. I then adjusted the range and size of the circles so that the Cost measure is slightly smaller than the Cost (copy) measure. Ultimately all 3 circles are slightly different sizes, but the range is so narrow, it’s hard to tell.

And that’s it. A lovely looking viz with a fair bit going on under the bonnet, but nothing too complex! My published version is here.

Happy vizzin’! Stay Safe!


Can you build a mobile calendar picker?

It was Natalia Miteva‘s turn to post the #WOW2020 challenge this week. It’s a parameter actions based challenge, inspired by a date range picker viz originally posted by Ludovic Tavernier.

Once again, I found this week tough! I understand the concept of parameter actions, and can use them for the ‘basics’, but the funky stuff people come up with to bend them to their will, is really beyond me.

I started the challenge with good intentions as always, ‘relating’ the Dates data to the Superstore data set matching the Date field to the Order Date field, built out the calendar view, but got stuck trying to figure out how to set the parameter action into an ‘End Date’ parameter, when I was already setting a ‘Start Date’ parameter. After staring at the screen for some time, I figured I’d try to work it all out from Ludovic’s viz instead.

There’s A LOT going on in this challenge, so I’ll do my best to explain.

  • Building the Calendar Picker
  • Building the Next / Previous control
  • Building the Year/Month control
  • Building the KPI & Trend Chart

Building the Calendar Picker

The calendar will only show 1 month, so let’s deal with that to start with.

A parameter will be used to store a date related to the month to show.


This is a date parameter that I chose to default to 01 June 2019.

Month Date


This is truncating every Date in the dataset to the 1st of the relevant month

Month To Show

[pMonthSelected] = [Month Date]

Add this to the Filter shelf and set to True will limit the data to a single month, June 2019 by default.

To display the days of the month in the ‘grid’ layout, we need to know the day of the week each day falls on (so we know what column to position the day in), and we need to know what week in the year the day falls in, as this will dictate which row to position the day in.

Day of Week (Abbrev)

LEFT(DATENAME(‘weekday’, [Date]),3)

The basic calendar layout can then be built by

  • Month To Show = True on Filter
  • Day of Week (Abbrev) on Columns
  • WEEK(Date) on Rows
  • DAY(Date) on Text

The WEEK(Date) field is then hidden.

We’re going to need to represent each day by a ‘square’ block. I achieve this by adding MIN(1) to Columns, changing the mark type to Bar, fixing the axis from 0-1, then hiding the axis.

So now the basic calendar layout is achieved, we need to figure out how to select a start & end, and colour accordingly.

We’re going to use a single string parameter to store both the selected start & end dates, using a | to act as a delimiter allowing us to identify & so separate the 2 dates.


String parameter set to empty string by default

Show the parameter on the viz, and I will attempt to walk through the steps, showing how the values in the parameter influence other fields and what is displayed on the viz.

We need another field, that is going to be used in conjunction with the parameter. I’m going to build up what this field needs to store as we go through, so hoping it will all make sense.

Date Control

IF [pSelectedDates]=”” THEN STR([Date]) END

If the parameter is empty, then set Date Control to be the date.

Let’s add this to the Text so you can see what happens to this field.

So the first action we expect the user to take is to click on a single date displayed. This value stored in the Date Control field will be passed via the parameter action into the pSelectedDates field (I’ll show you how this works later). For now let’s assume the user has clicked on the 5th June, so type 2019-06-05 into the pSelectedDates field.

This is now the start date, and we need the Date Control field to change to reflect this

Date Control

IF [pSelectedDates]=”” THEN STR([Date])
ELSEIF [Date]<=DATE([pSelectedDates]) THEN STR([Date])
ELSE [pSelectedDates]+”|”+STR([Date]) END // else store start & end date

If the Date displayed is before that stored in the parameter, then Date Control will continue just to store the date, otherwise it will append | followed by the date onto the existing parameter value.

So when a date is clicked again, the value of the Date Control will once again be passed to the pSelectedDates parameter.

If the date clicked is earlier than the one already stored, eg let’s say 04 June was clicked, the Date Control value of 04 June is passed to the parameter, and is now the ‘start date’. Type 2019-06-04 into the pSelectedDates field.

But if a later date is selected, say 18th June, the Date Control value of 2019-06-04|2019-06-18 is passed into the pSelectedDates parameter, and we now need another step with our Date Control field :

Date Control

IF [pSelectedDates]=”” THEN STR([Date])
ELSEIF CONTAINS([pSelectedDates],”|”) THEN STR([Date])
ELSEIF [Date]<=DATE([pSelectedDates]) THEN STR([Date])
ELSE [pSelectedDates]+”|”+STR([Date]) END

The 2nd statement is now looking for the | character and if it finds it, we know a start & end dates has been selected, so we need to ‘reset’ this control field to how it was originally – just it’s own date.

Type in 2019-06-04|2019-06-18 into the pSelectedDates field to see this.

Ok, so now we can see how the pSelectedDates field is working with the Date Control field, we now need to define some additional fields to help us identify the start & end of the dates selected, so we can work out what to colour.

Date Selection Start


This is looking for the position of the | field and taking everything from the first character in the pSelectedDates string up to the character before the |.

Note I originally used DATE(SPLIT([pSelectedDates], “|”,1)), but after extracting the data set, this calculation caused errors. I don’t know why, but the above workaround sufficed.

Date Selected End

DATE(MID([pSelectedDates], FIND([pSelectedDates],”|”)+1,10))

Find the position of the | and take all the characters starting at the position after the | and ending at the character 10 characters later (the date format is 10 characters so this can be easily hardcoded)


IF [Date]= [Date Selection Start] OR [Date] = [Date Selection End] THEN ‘Hot Pink’
ELSEIF [Date] > [Date Selection Start] AND [Date] < [Date Selection End] THEN ‘Pink’
ELSE ‘White’

Add this onto the Colour shelf, and adjust accordingly

We can remove the Date Control from Text now, but it needs to remain in the view, so it can be referenced when we build the parameter action. Add it onto Detail shelf instead.

Finally add this viz onto a dashboard, then add the parameter action, setting the Target Parameter to pSelectedDates and the Field to pass as Date Control.

As you play around selecting values on the dashboard, you’ll notice the dates appear ‘greyed out’, as the ‘on click’ action is essentially highlighting what you’ve selected. To stop this from happening create a calculated field called True that just stores the value of True and and a calculated field called False that stores the value False. Add both of these to the Detail shelf of the calendar viz.

Then on the dashboard, add a Filter action that goes from the dashboard to the sheet itself, passing the values Source: True = Target: False

Building the Next / Previous Control

We need to store the value of the next month related to the Date unless we’re already in the last month of the data set, in which case we’ll just keep the same month (ie if the month is 01 Nov 2019, next month will be 01 Dec 2019, but if the month is 01 Dec 2019 which is the last month in the data set, the next month will also be 01 Dec 2019. This stops the next control from moving forward when we reach the end.

Next Month

IF [Month Date] = {MAX([Month Date])} THEN [Month Date] ELSE
DATE(DATEADD(‘month’, 1, [Month Date]))

Change the mark type to Shape and select an appropriate arrow. If need be reduce the transparency of the shape colour (I chose 50% which changed a black arrow to look like a grey arrow).

On a new sheet, Add Month To Show = True to the Filter shelf, and Next Month to the Detail shelf.

If you recall, right at the start, we created a pMonthSelected parameter, and this will be used to change the month displayed.

Add the viz to the dashboard, and add a parameter action that on select, targets the pMonthSelected parameter, passing in the Next Month field

For the Previous Month control, we need apply similar steps, but using the field below instead.

Prev Month

IF [Month Date] = {MIN([Month Date])} THEN [Month Date] ELSE
DATE(DATEADD(‘month’, -1, [Month Date]))

Building the Year/Month control

When building the Year selector, we need to filter the data to just the month name already selected/in view, which is based on the pMonthSelected parameter. Ie if the month selected is 01 June 2019, we want the data related to June 2016, June 2017, June 2018, June 2019

Filter Month


Add this to the Filter shelf, set to true, then build out the view as below, fixing the axes between 0-1 again, and then hiding. You can see the values of the Month(Date)) displayed, and it’s this field that will be passed via a parameter action. It can be moved to Detail.

COLOUR:Selected Year


Add this to the Colour shelf and adjust accordingly.

When added to the dashboard, the associated parameter action required is :

When building the month selector, we need a similar filter to ensure the months shown are all associated to a single year

Filter Year

YEAR([pMonthSelected]) = YEAR([Date])

Add this to the Filter shelf set to True.

The layout of the Months, requires some additional fields to determine which row and column the month should be positioned in.

Month Cols

IF (DATEPART(‘month’,[Date]) %4) =0 THEN 4
ELSE (DATEPART(‘month’,[Date]) %4)

DATEPART returns the integer value of the month, ie a number between 1-12, so this calculation is using the modulo (%) function to position based on the remainder when dividing the month number by 4.

Month Row

IF DATEPART(‘month’,[Date]) <=4 THEN 1
ELSEIF DATEPART(‘month’,[Date]) <= 8 THEN 2

Adding these to the view as follows gives us a grid

Note the blue Month(Date) on the Text shelf is showing just the month name ie ‘January’, and has been formatted to it’s abbreviation. The green Month(Date) on the Detail shelf is storing the full month year ie January 2019.

COLOUR:Selected Month

[pMonthSelected]=[Month Date]

Add to the colour shelf and adjust accordingly.

You can then hide the Month Col & Month Row fields from displaying.

When added to the dashboard, the associated parameter action required is

Note You will need to apply the same ‘true=false’ trick described earlier to both these views using filter actions to prevent them from highlighting on selection.

Hiding the year/month selector

On the dashboard add a vertical container, then place the Year Selector sheet and the Month Selector inside.

Remove the chart titles, set the background of the container to white, then set the container to be floating and select the container option to Add Show/Hide Button.

You’ll need to spend some time adjusting the size and the position of the floating container once you have the layout of all the other objects finalised.

Building the KPI & Trend Chart

I’m going to try to be brief with this section. The above is A LOT to take in and write!

Selected Period

This is simply using the Date Selection Start & Date Selection End fields to display in a text field


We need to be able to filter the data being displayed based on the selection

Dates to Show

[Date]>= [Date Selection Start] AND [Date]<= [Date Selection End]

This is added to the Filter shelf and set to True.

After that we’re just building a simple Text based viz utilising Measure Names & Measure Values as shown below

And finally the trend chart, again needs to be filtered by Dates To Show = True, and is a simple line chart plotting Date against the measures required as below

When added to the dashboard, these 2 sheets should be placed side by side in a horizontal container, both set to fit entire view. The right padding should be set to 0 for the KPI chart and the left padding set to 0 for the trend chart. This will have the effect of the horizontal lines for each chart joining together to make it look like a single chart.

Phew! I’m beat! My published viz is here. Keeping fingers crossed for a challenge that is easier to blog about next week 🙂

Happy vizzin’! Stay Safe!


What happens if? Can you update sales forecast and targets using only parameters?

So after Ann’s gentle workout for week 6, newly crowed Tableau Zen Master Lorna, hit us with this challenge, and I confess, I struggled. The thought of then having to write this blog about it even brought a little tear to my eye 😦

But here I am, and I will do my best, but I can’t promise I understood everything that went on in this. I truly am amazed at times how some people manage to be so creative and bend Tableau to their will. It really is like #TableauBlackMagic at times!

So I read the challenge through multiple times, played around with Lorna’s published viz, stared at the screen blankly for some time…. I found the University Planning Dashboard viz by Ryan Lowers that Lorna had referenced in the challenge as her inspiration (she’d linked to it from her published viz). I played around with that a bit, although that took a while for me to get my head round too.

I also did a google search and came across Jonathan Drummey‘s blog post : Parameter Actions: Using a parameter as a data source. This provided a workbook and some step by step instructions, so I used this as my starting point. I downloaded the workbook, copied across the fields he suggested and tried to apply his instructions to Lorna’s challenge. But after a couple of hours, it felt as if I was making little progress. I couldn’t figure out whether I needed 2 or 4 parameters to store the ‘list’ data source variables (one each to store the list of selected categories for forecast, the list of selected categories for target, the list of selected forecast values, and the list of selected target values, or one each to store the list of selected categories and forecast values combined, and selected categories and target values combined). Suffice to say I tried all combos, using a dashboard to show me what was being populated on click into all the various fields/parameters I’d built. But it just wasn’t giving me exactly what I needed.

I downloaded the University Planning Dashboard and tried to understand what that was doing. And finally I shrugged my shoulders, and admitted defeat and cracked open Lorna’s solution. When I finally get to this point in a challenge, I try just to ‘have a peak’, and not simply follow verbatim what’s in the solution. I gleaned that I did need only 2 parameters, and that what I had been doing with my attempts with Jonathan’s example was pretty close. It made me feel a bit better with myself.

How things then transpired after that I can’t really recall – it was still a lot of trial and error but I finally got something that gave me the Sales Forecast data and associated select & reset functionality (by this time I’d probably spent 4 hours or so on this over a couple of evenings). Once I’d cracked that, the target was relatively straight forward, so by the time I’d finished on the 2nd day, I had a dashboard that allowed the selections/resets and simply presented the data in a table on screen. I chose to keep that version as part of my published solution, just for future reference (see here). I then finished off the next day, building the main viz.

What follows now, is just an account of the fields etc I used to build my solution. So let’s get going….

Building the Sales Forecast Selector

I’m going to start by focusing on building the left hand side of the viz, setting and resetting the Sales Forecast values for each Category.

We need 2 main parameters to start with:

Forecast Param

An integer parameter defaulted to 70,000. This is the parameter that stores the value of the forecast to set.

Forecast List

A string parameter defaulted to empty. This is the parameter which will ‘build up’ on selection of a category, to store a delimited list of category + forecast values – ie the data source parameter.

Oh, and I also used a 3rd parameter, Delimiter, which is just a string parameter storing a :

The delimiter needs to be a distinct character that mustn’t exist in the fields being used. The Category field nor the Forecast Param field will contain a ‘:’, so that’s fine. But any other unused character would work just as well. Having this field as a parameter isn’t ultimately necessary, but it makes it easy to change the delimiter to use, if the chosen value doesn’t end up being suitable. It was also a field used in Jonathan Drummey’s solution I’d based my initial attempts on.

Now we need to build the viz to work as the category selector.

I simply put Category on the Rows shelf, sorting the pill by SUM(Sales) descending and set the Mark Type to circle. Oh – and I set a Data Source Filter to set the Order Date just to the year 2019.

I also needed the following

  • something to colour the circles based on whether the Category was selected or not
  • something to use to help ‘build up’ the List parameter ‘data source’
  • something to return the forecast value that had been selected against the specific Category

Category Exists in Forecast List

CONTAINS([Forecast List], [Category])

If the Category exists within the Forecast List string of text, this field will return true, and indicates the Category has been ‘selected’. This field is added to the Colour shelf, and the colour needs to be adjusted once parameter action has been applied to distinguish between true & false.

Add to Forecast List

if [Forecast Param]<>0 THEN
[Forecast List] +
[Category] + ‘_’ + STR([Forecast Param]) + [Delimiter]

If the entered Forecast value isn’t 0, then append <Category>_<Forecast Value>: to the Forecast List parameter. Eg if the Sales Forecast value is $50,000 and Technology is selected, then Technology_50000: is added to the existing Forecast List parameter, which has started as blank.

If the Sales Forecast value is then changed to $10,000 say, and Office Supplies is selected, then the Forecast List parameter will become

Technology_50000:Office Supplies_10000:

This Append To Forecast List calculated field is used in conjunction with the Forecast List parameter within a Parameter Action on the dashboard to make all the ‘magic’ happen. The Append To Forecast List field must be in the view to be available to the parameter action, so it is added to the Detail shelf.

When a circle is selected the Append To Forecast List field is used to ‘set’ the Forecast List parameter, subsequently building up a string of Category_Value pairs.

Finally, on hover, the Category and the value of the selected sales forecast at the time must be visible on the Tooltip. To get the value at the point of selection, which isn’t necessarily the latest value visible in the Sales Forecast parameter displayed on screen, the following field is required:

Current FC Value

INT(if contains([Forecast List],[Category]) then
REGEXP_EXTRACT([Forecast List],[Category]+”_(-?\d+)”)

This manages to pull out the number associated with the Category, so in the above example, would return 50000 for Technology and 10000 for Office Supplies.

This field has custom formatting applied : ▲”$”#,##0;▼”$”#,##0 and is added to the Tooltip shelf.

RegEx is a concept I have yet to really crack, so there is no way I’d have come up with the above on my own. I think it’s looking for the named Category followed by Underscore (_) followed by either 1 or no negative sign (-) followed by some numbers, and returns just the numeric part.

Finally, the circles shouldn’t be ‘highlighted’ when selected on the dashboard. To stop this from happening a calculated field of True containing the value True, and a field False containing the value False are required. These are both added to the Detail shelf, and a Filter Action is then required on the dashboard setting True = False. This is a technique that is now becoming a familiar one to use, having been used in earlier #WOW2020 challenges.

So my ‘selection’ sheet looks like

and when added to the dashboard, the parameter action looks like :

with the filter action looking like :

At this point, I’d suggest using a ‘test’ dashboard which contains the selection sheet, displays the Forecast List and Forecast Param, and has the dashboard actions described above, applied to get an idea of what’s going on when a circle is selected, and the values of the Forecast Param changed.

The final part to this set up, is the ‘reset’ button, which when clicked on, empties the Forecast List parameter.

Create a new sheet, change the Mark Type to Text, and on the Text shelf add the string ‘↺’. I simply typed this ‘into’ a pill, but you could create a calculated field to store the ‘image’, which isn’t actually an image, but a special string character, that I got off my favourite ‘go to’ unicode characters website.

You then need a calculated field

Forecast List Reset

that just contains an empty string. This is added to the Detail shelf.

Put this sheet on the ‘test’ dashboard, and create another parameter action

This takes the value out of the Forecast List Reset field and sets the Forecast List parameter, subsequently resetting the list to an empty string on click.

Verify this is all working as expected.

Building the Sales Target Selector

Subject to Sales Forecast selector working as expected, then apply exactly the same principles to create the Target selection sheet and associated parameters.

The only slight difference with the fields used in the Target selection is:

Add to Target List

if [Target Param]>0 THEN
[Target List] +
[Category] + ‘_’ + STR([Target Param]) + [Delimiter]

This just applies the addition to the list if the entered target is a +ve number (ie > 0), rather than not 0 as in the forecast selection.

The Target also needs to be displayed on the Tooltip, and this time there is a default target value that should be displayed, even when no selection has been made. For this I created


IF ZN(MAX([Current Target Value])) = 0 THEN
MIN(IF [Category]= ‘Furniture’ THEN 270000
ELSEIF [Category]= ‘Office Supplies’ THEN 260000
ELSEIF [Category]= ‘Technology’ THEN 250000
ELSE MAX([Current Target Value]) END

which was formatted to a currency of 0 decimal places, prefixed by $. This was added to the Tooltip shelf.

At this point, you should now have both the ‘selection sheets’ working on the dashboard, so we can now focus on building the main viz.

Building the Bar Chart

Rather than building the bar chart, I first decided to build a tabular view that simply presented on screen all the bits of data I needed for the bar chart, this being

  • Sales value per Category (simply SUM(Sales))
  • Sales Forecast value per Category (ie Sales + selected Forecast value)
  • Selected Sales Target value per Category (this is the Target field described above)
  • % Difference between Sales & Target
  • % Difference between Sales Forecast & Target

So I created the following additional calculated fields:


SUM([Sales]) + MAX([Current FC Value])

formatted to currency prefixed with $ set to 0 dp.

Forecast vs Target Diff


custom formatted to ▲0%; ▼0%

Sales vs Target Diff


also custom formatted to ▲0%; ▼0%

Adding the table to the ‘test’ dashboard allows you to sense check everything is behaving as expected

Now its just a case of shifting the various pills around to get the desired view. Ensure at least one Sales Forecast Category has been selected, to make it easier to ‘see’ what you’re building.

Lorna stated the target should be displayed as a Gantt mark type, with the sales and the forecast displayed as bars. This means a dual axis chart is required, with sales & forecast on one axis and target on the other.

To get Sales and Forecast onto the same axis, we need to add Category to the Rows (sorted by Sales desc) and Measure Values to the Columns, filtering to only the two measures we need.

Set the Mark Type to bar, and add Measure Names to both the Colour and the Size shelf.

Adjust colours and sizes to suit.

You might have something like

where the measures are ‘stacked’, so the bar is the length of the Sales then the length of the Forecast. We don’t want this, so need to set Stack Marks to Off (Analysis menu -> Stack Marks -> Off).

Add all the necessary fields to the Label shelf and format accordingly (you may need to widen the rows to make the labels show against each row).

Note – in my solution I created some fields to make the opening & closing bracket around the Forecast v Target Diff value only show when a Forecast had been selected, however in writing this blog, I realise it was simpler just to change the formatting of the Forecast v Target Diff to add the brackets around the number. The custom formatting was changed to : (▲0%); (▼0%)

Adjust the Tooltip to suit too.

Now add Target to Columns alongside Measure Values. Set to Dual Axis and Synchronise the axis. Reset the Measure Values mark type back to bar if needed, and set the Target mark type to Gantt.

Remove Measure Names from the Colour and Size shelf of the Target marks card. Untick Show Mark Labels too. Adjust the colour of the mark to suit, and you should pretty much be there now…

Tidy up the final bits of formatting, removing/hiding the various axis, labels, gridlines etc etc.

When this is all put together on the dashboard, you might need to fiddle about a bit with layout containers to get the bar chart lined up with the Selector views.

And with that I’m done! My published version is here, along with the ‘check’ dashboard I used to sense check what was going on, as I’m sure if I ever looked at my solution again, I’d struggle to understand immediately 🙂

Once again, I just want to acknowledge those that manage to create this magic with Tableau. I applaud you!

Happy vizzin’!


Can you combine relative & custom dates?

Week 4 of #WOW2020 saw one of the new contributors, Sean Miller, provide his first challenge, based on providing a technique to improve the user experience when working with date inputs.

The date inputs allow a user to select from 2 ‘static’ options (Last 14 Days or Last 30 Days), a custom Last N Days option, where the user is then prompted to define how many days….

… along with a Custom Dates option, which when selected, prompts the user to define the start & end dates

Both the N Days parameter and the Start & End dates only appear when the appropriate selection is made. This makes the displayed interface much cleaner (as it’s less cluttered), and, more importantly, makes the action the user is then expected to make, much more obvious.

So let’s get started.

Define the parameters

The first step in this challenge is to define all the parameters needed, these being :

Date Selector

A string parameter just set to contain the value Last 14 Days

This parameter will be set via a Parameter Action, so there is no need to define this a list with all the options.

N Days

An integer parameter defaulted to 60

Start Date

A date parameter defaulted to 01 Jan 2019

End Date

Another date parameter defaulted to 31 Dec 2019

Build the Sales over time chart

The Sales over Time trend is simply Order Date as a continuous pill at the Day level, against SUM(Sales). Sales is duplicated as a dual axis, allowing one axis to be set to mark type Area, and the other to Line. The colours of each mark are slightly different, to give the ‘edged’ area look

The requirement stated the ‘Last…’ selections should be anchored to the latest date in the dataset, so we need to determine what this is:

Latest Date

{FIXED:MAX([Order Date])}

To restrict the data displayed, we need something we can filter on:

In Timeframe

CASE [Date Selector]
WHEN ‘Last 14 Days’ THEN [Order Date]>DATEADD(‘day’,-14,[Latest Date])
WHEN ‘Last 30 Days’ THEN [Order Date]>DATEADD(‘day’,-30,[Latest Date])
WHEN ‘Last N Days’ THEN [Order Date]>DATEADD(‘day’,-1*[N Days],[Latest Date])
ELSE [Order Date]>=[Start Date] AND [Order Date]<=[End Date]

In Timeframe can be added to the Filter shelf and set to True.

Based on the defaults selected, at this point, you should be displaying information for the last 14 days.

Expose the parameters onto the display, and test out the rest of the logic by changing the value of the Date Selector (type in one of the other options – eg Last 30 Days, Last N Days, Custom Days).


The 3 numbers displayed are the measures Sales, Profit and Profit Ratio, where Profit Ratio is a calculated field of

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

formatted to be a percentage of 1 decimal place.


  1. Add Measure Names to Columns
  2. Add Measure Names and Measure Values to the Text shelf
  3. Add Measure Names to the Filter shelf and select just the 3 measures we’re interested in.
  4. Reorder the columns to match the requirement
  5. Change the formatting of the Measure Names and Measure Values on the Text shelf to set the colour & size of the font to suit, and align middle, centre
  6. Format the display to remove the row lines
  7. Hide the Measure Names heading (right-click the Measure Names pill on the Columns shelf and unselect Show Header).
  8. Add In Timeframe = True to the Filter shelf to restrict the data.
  9. Format Sales and Profit accordingly.

Measure Selector

I built the measure selection view using the technique I’ve already blogged about related to #WOW2020 Week 1 : Can you sort dimensions with a single click? This is the 3rd week out of 4 so far that I’ve employed this technique, which is great, as it means it’s a concept that I’ve started to remember 🙂 The blog also describes

  1. how to set the parameter action which is needed to alter the Date Selector parameter
  2. how to invoke a filter action using a True and False calculated field to prevent the un-selected measures from ‘fading out’.

By this point, all the sheets should be on the dashboard with everything formatted and positioned where it needs. So now for the final task:

Make the Parameters Hide & Show

This part of the challenge was something totally new to me, so I did what I would usually do, and Googled it.

Hiding Parameters & Filters in Tableau – v2 by Andrew Pick @ The Information Lab

This is the primary post I followed to achieve the result for this challenge, so I’m not going to document it all here, when it’s already written down 🙂 It’s a bit fiddly to get the parameters positioned in exactly the right place. From other posts I found, this technique is also sometimes referred to as ‘parameter popping’.

My published workbook can be found here.

Happy vizzin’ & poppin’


Can you build a beautiful & dynamic bar chart?

Week 2 of #WOW2020 saw Ann post this challenge asking us to create a dynamic bar chart that changed both the measure being reported and the timeframe being reported over, based on user selections.

The measure needed to be displayed as the bar label, which needed to be formatted differently depending on whether it was Sales ($ 0 dp), Profit Ratio (% 1 dp) or Items Per Order (1 dp). Due to this, the label can’t be a single field, as it’s not yet possible in Tableau Desktop to apply number formatting within a calculated field *sigh*.

A couple of calculated fields are needed for the measures

Profit Ratio


and Items Per Order

SUM([Quantity])/COUNTD([Order ID])

The timeframe format displayed also needed to change based on whether the timeframe selected was Last 12 months (MMM’YY eg Apr’19), Last 13 Weeks (Week No) or Last 14 days (mm/dd eg 12/31).

The bar colour needed to reflect the measure selected, and measure selector needed to display a filled or open circle depending on whether the measure was selected or not.

Measure Selector

I realised there were a lot of similarities with the behaviour of the measure selector, and Luke’s challenge from the previous week. I’m not sure if this was intentional or not. As a consequence though, I’m not going to explain how I built the Measure Selector chart, as I utilised exactly the same principles for the Week 1 solution, and I’ve already blogged about it here.

Bar Chart

I built the bar chart on a single sheet, plotting a measure that could change based on selection, against a date field that also changed on selection.

To drive the selection change I needed 2 parameters:

Date Period

A string parameter containing the 3 values available

This parameter was just made available as a drop down for the user to select from on the dashboard.

Selected Measure

This was a string parameter that just stored a piece of text. It was set to the value ‘ Sales ‘ by default, but was changed via a Parameter Action following selection via the Measure Selector chart discussed above.

Note the leading & trailing space in the default value ‘ Sales ‘due to the alias that needs to be set – refer to my previous bog post to understand the relevance

The date field to plot then had to alter based on the Date Period parameter, so the following calculated field was created:

Order Date Truncate

DATE(CASE [Date Period]
WHEN ‘Last 12 Months’ THEN DATETRUNC(‘month’,[Order Date])
WHEN ‘Last 13 Weeks’ THEN DATETRUNC(‘week’, [Order Date])
ELSE DATETRUNC(‘day’, [Order Date])

This field is essentially storing the date as the 1st of the month, 1st day of the week or specific day level, so when plotted on a chart it can be set to ‘exact date’ and all the orders in the same month/week/day, are all grouped together.

The measure field to plot alters based on the Selected Measure parameter, so the following calculated field is required :

Measure to Show

CASE [Selected Measure]
WHEN ‘ Sales ‘ THEN SUM([Sales])
WHEN ‘ Profit Ratio ‘ THEN [Profit Ratio]
WHEN ‘ Items Per Order ‘ THEN [Items Per Order]

Plotting Order Date Truncate on columns as a discrete exact date against Measure to Show on rows with mark type set to Bar, and you can use the parameter to change the number of bars.

But this is showing all the months/weeks/days, so we need to add a filter to restrict to amount of information showing.

Dates to Include

CASE [Date Period]
WHEN ‘Last 12 Months’ THEN [Order Date] >= DATEADD(‘month’,-12,[Today])
WHEN ‘Last 13 Weeks’ THEN [Order Date] >= DATEADD(‘week’,-13,[Today])
ELSE [Order Date] >= DATEADD(‘day’,-14,[Today])

This will true or false, and is added to the Filter shelf set to True

Note – [Today] is another parameter that is defaulted to 01 Jan 2020 as per Ann’s requirement.

The field names for the Order Date Truncate isn’t displaying as required though. To fix this, I created


CASE [Date Period]
WHEN ‘Last 12 Months’ THEN LEFT(DATENAME(‘month’, [Order Date Truncate]),3) + ”” + RIGHT(STR(YEAR([Order Date Truncate])),2)
WHEN ‘Last 13 Weeks’ THEN ‘Week ‘ + STR(DATEPART(‘week’, [Order Date Truncate]))
ELSE STR(DATEPART(‘month’,[Order Date Truncate])) + ‘/’ + STR(DATEPART(‘day’, [Order Date Truncate]))

which is building the required string to display.

Add this to the Columns shelf next to the Order Date Truncate field, then untick Show Header against the Order Date Truncate field

Next up is the labels to display on top of each bar. This also needs to show something different depending on the measure selected. For this I built 3 calculated fields:

Label: Sales

IF [Selected Measure] = ‘ Sales ‘ THEN [Sales] END

which is formatted to $ with 0 decimal places

Label: Profit Ratio

IF [Selected Measure] = ‘ Profit Ratio ‘ THEN [Profit Ratio] END

which is formatted to % with 1 decimal place, and

Label: Items to Order

IF [Selected Measure] = ‘ Items Per Order ‘ THEN [Items Per Order] END

which is formatted to 1 decimal place

These 3 fields are then added to the Label shelf, and the label text is then edited to ensure all the fields are positioned side by side. Due to the fact only 1 of these fields will ever contain data, it looks as though there is only 1 label showing

Next we need to colour the bars, which is based on Selected Measure which is just added to the Colour shelf. When it’s added though, you only get a single measure in the colour legend at a time, so to set the colours you need to set Selected Measure to be each option of Sales, Profit Ratio, Items to Order (based on what the alias has been set though), either by manually typing into the parameter, or selecting a measure on the dashboard via the Measure Selector chart you built initially.

The tooltip is then set as follows

and once again the Label:xxx measures are all positioned alongside each other as, remember, only one will ever contain any data.

Finally it’s just a case of tidying up the chart – remove the rows & columns, the Measure to Show axis, and the Label:Date label.

The zero line of the rows is set to be a thicker grey line to get the desired display

Once done, the bar chart can be added to the dashboard, and if the Parameter Action on the Measure Selector chart has been set up properly, the bar chart display should change as that chart is interacted with.

My published version of the challenge is here.

Happy vizzin!


Can you sort dimensions with a single click?

Luke kicked off the 1st workout of 2020 with this challenge – using a ‘header’ sheet to control the sorting on a tabular view below.

Building the table

A couple of measures need creating initially :

Sales / Order

SUM([Sales])/COUNTD([Order ID])

Profit Ratio


The table consists of 3 measures aligned side by side, of different mark types : bar, text, bar. Sub-Category exists on the Rows.

The Sales measure is displayed first on the Columns, with mark type set to Bar, and the axis is fixed to start at 0 so there is minimal spacing between the Row label and the start of the bar. An additional calculated field [Profit Ratio]< 0 is added to the colour shelf and adjusted to be red/grey as appropriate.

As the requirement for the text Sales/Order measure was to right align it, adding Sales/Order measure to columns won’t work. Instead use MIN(0) setting the mark type to Gantt Bar, and making the mark type as small as possible, and setting the opacity to 0. Sales/Order is then added as a label which is then aligned middle left, and therefore right-aligning the text on the screen.

The final measure, Profit Ratio is added to the Columns shelf, also as mark type of Bar. Once again the [Profit Ratio]< 0 is added to the colour shelf.

All row/column lines, gridlines, zero lines and axis lines were set to nothing, but the Profit Ratio measure required a zero line to display. Using the zero line setting of the formatting would have meant a zero line would also display on the Sales bar chart, which wasn’t required. Instead I used a constant reference line of 0 on the Profit Ratio axis only.

And finally, the requirement stated that sort controls on the table should be switched off. This setting can be found under the Worksheet menu. All the axis were then hidden.

Building the ‘Header’ sheet (basic)

To start off I’m just going to describe how to construct a basic header table so it can then it interact with the table on the dashboard, and apply the sorting. I’ll revisit this all later, as getting the header to meet the specific requirements Luke stated was something I admit I struggled with.

At it’s simplest, you can build the header as follows:

  • Measure Names on rows and filtered to just the 3 measures we need
  • Measure Names on Text and aligned Middle Centre
  • Measure Values on Detail
  • Measure Names manually sorted in the order we want
  • Show Header unchecked for Measure Names on the rows shelf

Invoking the Sort

The sort is intended to work by clicking on a label on the header sheet, which in turn should sort the data in the table sheet.

To start off, a string parameter is required which is defaulted to the value Sales

A calculated field is also needed to define the sort measure, based on the sort parameter

Sort By

IF [Sort] = ‘Sales’ THEN SUM([Sales])
ELSEIF [Sort] = ‘Profit Ratio’ THEN [Profit Ratio]
ELSEIF [Sort] = ‘Sales / Order’ THEN [Sales / Order]

On the Table sheet, the Sub-Category field is then set to sort based on the Sort By field

With the Header sheet and the Table sheet added to a dashboard, a Parameter Action can be created which will set the Sort parameter based on the measure name clicked on :

At this point now, you should have the basics of the challenge – a header sheet causing the data in the table sheet to sort based on the label clicked on.

However, Luke added additional complexity to the Header sheet :

  • add an ▼ to identify the column label clicked on
  • change the font to be darker for the label clicked on
  • ensure the column labels not clicked on, remained ‘visible’ (ie did not appear to fade as per standard behaviour when data is selected in a viz).

Building the Header (Initial attempt)

My initial attempt to meet the stated requirements made use of a dual axis MIN(0) table, where one axis was of mark type square, with the Measure Names & ‘ ▼ ‘ on the label shelf, which was formatted to be a dark font, and set to only show when highlighted. The second axis was a Text mark type, with Measure Names on the text, formatted to a lighter font.

On click on one of the labels, the label associated with the square mark type would be shown, but the other labels ‘faded out’.

Whatever I tried to do to stop them, based on tricks I’ve tried in the past (using a Dummy field and applying a highlight action on the dashboard), didn’t work.

As much as I tried I couldn’t get beyond this, so published this as my solution, and waited for Luke to release his workbook. My version using this method is here.

Building the Header (Luke’s method)

Once Luke made his workbook available, I downloaded it to see what he’d done to keep all the header labels ‘enabled’ on click.

He used a dashboard action filter to set a calculated field ‘True’ to match a calculated field ‘False’. Both these calculated fields had to exist on the Detail shelf of the header sheet. (also note how the dashboard source sheet selects the Header v2 view which targets the Header v2 sheet directly (and not the equivalent view on the dashboard).

This is a technique Luke has blogged about on his own site following a discussion in the Tableau Community :

I have to admit, I had seen this post, and am kicking myself I didn’t remember it to try it out 😦

So…. back to my viz, and I applied Luke’s deselect marks idea to my header sheet, but it didn’t work. As I’d made the arrow show on ‘highlight’, this filter action was undoing the highlight, so preventing my label to show.

So I figured I’d just have to copy what Luke had done… and I started to build out his sheet… 3 columns of Min(0) set to Text with Measure Names on the Text :

All I could display was Min(0)… the only way I could see to get the words Sales, Sales/Orders, Profit Ratio displayed, was to add in Measure Values to the Detail shelf… but then all the words overlapped…

So I messaged Luke, as I just couldn’t understand this black magic… but before I got a response, I had a lightbulb moment….


The MIN(0) in the Measure Names had been aliased, to look like the same name of other measures, but I added a leading and trailing space around them all, as you can’t have duplicated names.

This really is something sneaky! but I was quite chuffed I found it before Luke told me.

To get the display and the formatting right, then required an ‘Arrow’ field for each measure along the lines of :

Arrow for Sales

IF [Sort] = ” Sales “
THEN “▼”
ELSE ” “

(note the leading & trailing spaces). This field is added to the Text shelf on the 1st Min(0) marks card. An equivalent field is then required for the other 2 measures, which are added to their respective marks cards.

Sort – Sales

[Sort] = ” Sales “

This boolean field is then added to the Colour shelf of the 1st Min(0) marks card. Again an equivalent is required for the other 2 measures. Setting the colours correctly will require each label to be clicked on the dashboard to get all the true/false permutations to show.

My revised version to meet the requirement is available here. Be aware if you do download, the field naming might not be identical to that above. This is because I have 1 workbook with both solutions in it, so in some cases needed to have duplicated versions of the calculated fields/parameters, to ensure both versions continued to function.

That was certainly an interesting challenge for Week 1 of the new year, and ultimately I was stumped! Hoping this isn’t going to be a theme for the weeks to come 🙂

Happy vizzin’!


Rounded Bar Charts : What % of Sales is from the East Region?

For Week 37 2019 of #WorkoutWednesday, Luke Stanke challenged us to create a rounded bar chart, displaying the % of sales by sub-category in a selected region as a proportion of the whole.

In the challenge (here), Luke hinted that this could be achieved by unioning the data set together, but I recalled doing something similar before, and so didn’t think I’d need this.

Before tackling the bars though, I needed to set up the data required, which was pretty straightforward. I needed a parameter to store the region, and then a couple of calculated fields

Region Sales

If [Region] = [Region Param] THEN [Sales] END

which stored the value of the sales for the region selected and

Region % of Sales

SUM([Region Sales]) / SUM ([Sales])

which stored the % value required.

Having set that up, I then went to my stored ‘go to’ references as a refresher:

Andy Kriebel‘s Tableau Tip : How to create rounded bars and Ryan Sleeper‘s : How to Make Rounded Bars & Scales in Tableau

I started with Andy’s technique first, which uses MIN(0) plotted on the same axis as Region % of Sales, displayed as a line chart with Measure Names on the Path shelf to force the points to join up. Increasing the size of the line produces rounded bars.

However, I then spent some time puzzling over how to get the 2nd bar, which needed to be on a second (dual) axis, and ideally also needed to be created in a similar technique using MIN(0) to MIN(1) instead. I tried a few things, but couldn’t crack it this way, so used the technique Ryan adopts which overlays bars and circles on a dual axis.

For this, MIN(0), MIN(1) and Region % of Sales are all added to the same axis, so Measure Values is plotted against Sub-Category and Measure Names added to colour

However if you look closely, you’ll see the values go beyond 1, as the marks are all stacked. We don’t want this, so we need to turn stacking off…

.. and then move Region % of Sales to the top of the list in Measure Values, to bring it to the front, and adjust the colours to suit

This gives our bars. Now, for the rounded bit.

Duplicate Measure Values, by clicking on the Measure Values pill in the columns shelf, holding down Ctrl and dragging your mouse to the right. This will create a copy of the Measure Values pill which you can drop next to it

Make the chart dual axis, synchronise the axis and change the mark types to be a bar for one set of Measure Values and a circle for the other. Adjust the sizing so the marks appear as one ‘lozenge’ shape

Labelling the end of the bar with the % values, needed a little bit of creativity. Just adding Region % of Sales to the label of the ‘bar’ marks card showed the label a bit too close to the display, even when right-aligned, as the circle mark was taking up the space

Labelling the circles instead would have meant a bit of trickery to only label the last circle.

So the quickest & easiest thing to do, was to simply create a label field to make the spacing work :

LABEL : % Sales

” ” + STR(ROUND([Region % of Sales] * 100,0)) + “%”

Adding this to the Label shelf on the bar marks gave me the desired result.

I just then needed to tidy up the formatting (fix axis start, hide axis etc) and add to the dashboard.

My version of the challenge is here, but do check out others. There will be multiple ways of achieving the same thing!

Happy vizzin!