Can you show the Year-on-Year Trend?

It’s Community Month over at #WOW HQ this month, which means guest posters, and Kyle Yetter kicked it all off with this challenge. Having completed numerous YoY related workbooks both through work and previous #WOW challenges, this looked like it might be relatively straight forward on the surface. But Kyle threw in some curve balls, which I’ll try to explain within this blog. The points I’ll be focussing on

  • YoY % calculation for colouring the map
  • Displaying the circles on the map
  • Restricting the Date parameter to 1st Jan – 14th July only
  • Showing Daily or Weekly dates on the viz in tooltip
  • Restricting to full weeks only (in weekly view)

YoY % calculation

The data provided includes dates from 1st Jan 2019 to 21st July 2020. We need to be able to show Current Year (CY) values alongside Previous Year (PY) values and the YoY% difference. I built up the following calculations for all this



This is just hardcoded based on the requirement. In a business scenario where the data changes, you may use the TODAY() function to get the current date.

Current Year


simply returns 2020, which I could have hardcoded as well, but I prefer to build solutions as if the data were more dynamic.


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

stores the value of the Subscription field but only for records associated to 2020


IF YEAR([Subscription Date]) = [Current Year]-1 THEN [Subscription] END

stores the value of the Subscription field but only for records associated to 2019 (ie 2020-1)


(SUM([CY])- SUM([PY]))/SUM([PY])

format this to a percentage with 0 decimal places. This ultimately is the measure used to colour the map. CY, PY & YoY% are also referenced on the Tooltip.

Displaying circles on the map

This is achieved using a dual axis map (via a second instance of the Latitude pill on Rows). One ‘axis’ is a map mark type coloured by the YoY% and the other is a circle mark type, sized by CY, explicitly coloured black.

The Tooltip for the circle mark type also shows the % of Total subscriptions for the current year, which is a Percent of Total Quick Table Calculation

Restricting the Date parameter to 1st Jan – 14th July only

As mentioned the Subscription Date contains dates from 01 Jan 2019 to 21 July 2020, but we can’t simply add a filter restricting this date to 01 Jan 20 to 14 Jul 20 as that would remove all the rows associated to the 2019 data which we need available to provide the PY and YoY% values.

So to solve this we need a new date field, and we need to baseline / normalise the dates in the data set to all align to the same year.

Baseline Date

//set all dates to be based on current year
MAKEDATE([Current Year], MONTH([Subscription Date]), DAY([Subscription Date]))

So if the Subscription Date is 01 Jan 2019, the equivalent Baseline Date associated will be 01 Jan 2020. The Subscription Date of 01 Jan 2020 will also have a Baseline Date of 01 Jan 2020.

We also want to ensure we don’t have dates beyond ‘today’

Include Dates < Today

[Baseline Date]< [Today]

Add Include Dates < Today to the Filter shelf, and set to True.

Add Baseline Date to the Filter shelf, choose Range of Dates , and by default the dates 01 Jan 2020 to 14 Jul 2020 should be displayed

Select to Show Filter, and when the filter displays, select the drop down arrow (top right) and change to Only Relevant Values

Whilst you can edit the start and end dates in the filter to be before/after the specific dates, this won’t actually use those dates, and the filter control slider can only be moved between the range we want.

The Baseline Date field should then be custom formatted to mmmm dd to display the dates in the January 01 format.

Showing Daily or Weekly dates on the viz in tooltip

The requirements state that if the date range selected is <=30 days, the trend chart shown on the Viz in Tooltip should display daily data, otherwise it should be weekly figures, where the week ‘starts’ on the minimum date selected in the range.

There’s a lot going on to meet this requirement.

First up we need to be able to identify the min & max dates selected by the user via the Baseline Date filter.

This did cause me some trouble. I knew what I wanted, but struggled. A FIXED LOD always gave me the 1st Jan 2020 for the Min Date, regardless of where I moved the slider, whereas a WINDOW_MIN() table calculation function caused issues as it required the data displayed to be at a level of detail that I didn’t want.

A peak at Kyle’s solution and I found he’d added the date filters to context. This means a FIXED LOD would then return the min & max dates I was after.

Min Date

{MIN([Baseline Date])}

Note this is a shortened notation for {FIXED : MIN([Baseline Date])}

Max Date

{MAX([Baseline Date])}

With these, we can work out

Days between Min & Max

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

which in turn we can categorise

Daily | Weekly

IF [Days between Min & Max]<=30 THEN ‘Daily’ ELSE ‘Weekly’ END

We also need to understand the day the weeks will start on.

Day of Week Min Date

DATEPART(‘weekday’,[Min Date])

This returns a number from 1 (Sunday) to 7 (Saturday) based on the Min Date selected.

Using this we can essentially ‘categorise’ and therefore ‘group’ the Baseline Date into the appropriate week.

Baseline Date Week

CASE [Day of Week Min Date]
WHEN 1 THEN DATETRUNC(‘week’,([Baseline Date]),’Sunday’)
WHEN 2 THEN DATETRUNC(‘week’,([Baseline Date]),’Monday’)
WHEN 3 THEN DATETRUNC(‘week’,([Baseline Date]),’Tuesday’)
WHEN 4 THEN DATETRUNC(‘week’,([Baseline Date]),’Wednesday’)
WHEN 5 THEN DATETRUNC(‘week’,([Baseline Date]),’Thursday’)
WHEN 6 THEN DATETRUNC(‘week’,([Baseline Date]),’Friday’)
WHEN 7 THEN DATETRUNC(‘week’,([Baseline Date]),’Saturday’)

Ideally we want to simplify this using something like DATETRUNC(‘week’, [Baseline Date], DATEPART(‘weekday’, [Min Date])), but unfortunately, at this point, Tableau won’t accept a function as the 3rd parameter of the DATETRUNC function.

Let’s just have a look at what we’ve got so far

Rows for California only showing the Subscription Dates from 01 Jan 2019 – 10 Jan 2019 and 01 Jan 2020 to 10 Jan 2020. Min & Max date for all rows are identical and matches the values in the filter. The Baseline Date field for both 01 Jan 2019 and 01 Jan 2020 is January 01. The Baseline Date Week for 01 Jan 2019 – 07 Jan 2019 AND 01 Jan 2020 – 07 Jan 2020 is 01 Jan 2020. The other dates are associated with the week starting 08 Jan 20202.

So now we have all this information, we need yet another date field that will be plotted on the date axis of the Viz in Tooltip.

Date to Plot

IF [Days between Min & Max] <=30 THEN ([Baseline Date]) ELSE [Baseline Date Week] END

If you add this field to the tabular display I built out above, you can see how the value changes as you move the filter dates to be within 30 days of each other and out again.

When added to the actual viz, this field is formatted to dd mmm ie 01 Jan, and then is plotted as a continuous, exact date (green pill) field on the Columns alongside the Daily | Weekly field, with State & Subscription on Rows. The YEAR(Subscription Date) provides the separation of the data into 2 lines.

Restricting to full weeks only (in weekly view)

The requirements state only full weeks (ie 7 days of data) should be included when the data is plotted at a weekly level. For this we need to ascertain the ‘week’ the maximum date falls in

Max Date Week

CASE [Day of Week Min Date]
WHEN 1 THEN DATETRUNC(‘week’,([Max Date]),’Sunday’)
WHEN 2 THEN DATETRUNC(‘week’,([Max Date]),’Monday’)
WHEN 3 THEN DATETRUNC(‘week’,([Max Date]),’Tuesday’)
WHEN 4 THEN DATETRUNC(‘week’,([Max Date]),’Wednesday’)
WHEN 5 THEN DATETRUNC(‘week’,([Max Date]),’Thursday’)
WHEN 6 THEN DATETRUNC(‘week’,([Max Date]),’Friday’)
WHEN 7 THEN DATETRUNC(‘week’,([Max Date]),’Saturday’)

so if the maximum date selected is a Thursday (eg Thurs 11th June 2020) but the minimum date happens to be a Tuesday, then the week starts on a Tuesday, and this field will return the previous Tuesday date (eg Tues 9th June 2020).

And then to restrict to complete weeks only…

Full Weeks Only

IF [Daily | Weekly]=’Weekly’ THEN
[Date To Plot]< [Max Date Week]

If we’re in the ‘weekly’ mode, the Date To Plot field will be storing dates related to the start of the week, so will return true for all records where the field is less than the week of the max date. Otherwise if we’re in ‘daily’ mode we just want all records.

This field is added to the Filter shelf and set to true.

Hopefully that covers off all the complicated bits you need to know to complete this challenge. My published solution is here.

Happy vizzin’! Stay Safe!


Can you excel at bar charts?

When Luke’s #WOW2020 challenge landed this week, I did a little happy dance inside, as I was pretty sure I was going to be able to crack this fairly quickly with minimal head scratching effort. This isn’t because I create these types of charts often, but because this type of side-by-side bar formed the basis of a #WorkoutWednesday challenge way back in 2017, and is a technique I can still recall – I didn’t even have to check my published workbook for a reminder… there’s just some techniques that just ‘stick’.

There may well be other ways to solve this challenge, but the technique I know is based on ‘normalising’ and ‘jittering’ dates, and is one I recall I picked up from Zen Master Jonathan Drummey’s Bars & Lines Blog post and associated workbook which can be downloaded from the blog.

So let’s gets started & hopefully, all will become clear.

Building the chart

In the dataset we’re using we have 4 years worth of orders, and need to plot the value of sales per month, per year in a bar chart which ‘groups’ the yearly bars for the same month together.

We’re going to plot the dates on a continuous axis (green pill), which typically would give a bar chart that looks like this, where Year(Order Date) is also added to the Colour shelf (Note I’ve also adjusted the colours to match the requirements).

We have 1 bar per month per year, but the months are ‘grouped’ in their sequential years.

So the first thing we want to do, is ‘normalise’ the dates as if they all occurred in the same year – any year is fine, I’m going to baseline them all to 2019

Date Normalised

MAKEDATE(2019,MONTH([Order Date]),DAY([Order Date]))

As you can see if plotting Order Date alongside Date Normalised this is simply transposing 03 Jan 2016 to 03 Jan 2019, 03 Jan 2017 would also be transposed to 03 Jan 2019

Replacing Order Date with Date Normalised on our initial chart gives us

But we want the bars side by side.

When using the automatic date hierarchy to plot dates at the month level, what Tableau is doing ‘under the bonnet’, is ‘truncating’ each date to the 1st of the month; so 3rd Jan 2019 and 18th Jan 2019 etc, are both actually plotted at 1st Jan 2019, and so on.

And when a bar chart is used to plot on a date axis, the left hand side of the bar is plotted at the 1st of the month point.

So with all this in mind, what we’re going to is ‘jitter’ the dates for each year to be clustered before the 1st of the month (for 2016 & 2017) and on/after 1st of the month (for 2018 & 2019).

Date Jitter

CASE YEAR([Order Date])
WHEN 2016 THEN DATEADD(‘day’,-9, DATETRUNC(‘month’, [Date Normalised]))
WHEN 2017 THEN DATEADD(‘day’,-4, DATETRUNC(‘month’, [Date Normalised]))
WHEN 2018 THEN DATEADD(‘day’,1, DATETRUNC(‘month’, [Date Normalised]))
WHEN 2019 THEN DATEADD(‘day’,6, DATETRUNC(‘month’, [Date Normalised]))

If the year of the original Order Date is 2016, then truncate the normalised (2019) version of the date to the 1st of the month, but subtract 9 days. So if the Order Date is 03 Jan 2016, then transpose it to 03 Jan 2019, then truncate to 1st of month, 01 Jan 2019, then subtract 9 days to 23 Dec 2018

03 Jan 2016 -> 03 Jan 2019 -> 01 Jan 2019 -> 23 Dec 2018

Depending on the year depends on whether dates are subtracted or added, and they have a suitable spacing between. The table below shows the relationship between the Order Date, the Normalised Date and the Date Jitter

Replacing Date Normalised with Date Jitter like for like, gives us the same view though, since it’s automatically rolled up to ‘month’

Change the Date Jitter to Exact Date

and ta-dah! you have your side-by-side chart. Each bar is being plotted at the exact date. If we just filter to look at May for example, we can see this clearer

The bars are obviously thinner than we want, so adjust the Size to be Fixed with a value of 4

To get the Tooltip to display the correct month and year, you need to add Order Date to the Detail shelf and change it to the discrete Month level (blue pill), then format the pill to display as an abbreviated month.

To get the axis to display an abbreviated month name, format that too and set to custom formatting of mmm.

Finally, to get the bottom axis and axis ticks to be darker, adjust the Columns Axis Ruler and Axis Ticks to be a solid dark line, then edit the axis, and delete the axis title

Your bar chart should be complete

Building the Legend

F0r the legend, I simply created a very simple existence chart using the circle mark type as below

And that’s it (once added to a dashboard of course!). The date jittering is a useful technique to be aware of – I’m pretty sure I’ve used it in other challenges too, but not necessarily for a side by side bar chart.

My published viz is here.

Note, my Date Normalised & Date Jitter fields in my published viz aren’t exactly as detailed above, because I decided to jitter then normalise originally, which meant I had to make an additional adjustment in my normalisation calculation. It’s only when typing this blog out and essentially rebuilding as I go, that I realised it was so much simpler the other way round!

Happy vizzin’! Stay safe!