Tag: Show Missing Values

Can you filter a small multiples chart?

Donna ColesLeave a comment

Erica set the challenge this week, and I’m not gonna lie, I found this tough. On the face of it, it looks like something I felt I should be ok at, but nuances cropped up as I was building that meant I often had to change tact and try something different.

My intention was to build each version – Beginner, Intermediate then Advanced, adding to my solution each time, but decisions I made early on, then caused me grief later. For example, I did choose to utilise a lot of table calcs, but that meant when it came to applying the sorting mechanism that I wanted, I couldn’t reference the sort field I needed, as it contained a table calc. So I had to unpick the logic and build with LODs instead which took me a while to get right. Getting single lines to display in each ‘state’ cell also proved tricky at times, and that was even before I’d got to the requirement to pad out the ‘missing values’ with 0s. I also seemed to find that some things only seemed to work if I added pills and applied settings in a particular order. All in all, quite a challenge, and while I did get there in the end, I did have to peek at the solution at times to figure out if I was going nuts, but I found trying to scale back Erica’s solution to the beginner/intermediate version also suffered the same issues I was experiencing. I built with Desktop v2024.1 and there were times I was wondering if something had “broken” in that version, although having finally reached the end, I’ve yet to test that theory.

So, I’m blogging this guide with several caveats – Going from beginner to intermediate is ‘okay’, but when it gets to advanced I had to start again(ish). Some of the calcs I provide will just be ‘as is’. I will do my best to explain what’s going on, but there are times that I just don’t get it, and it’s just been trial and error that got me the results I needed – sorry!

So with all that in mind, let’s get building.

Initial steps

After connecting to the provided hyper file, I found I did have to create the modified sales value

Sales Modified

IF SUM([Sales])<5000 THEN SUM([Sales])*10 ELSE SUM([Sales]) END

I also decided to add a data source filter (right click data source > edit data source filters) to restrict the data to just Country/Region = USA.

The later versions of superstore have Canadian Provinces included too, and I don’t think these were listed in Erica’s solution. It just felt easier all round to exclude these records from source.

Beginner challenge

When building a trellis chart, we need to determine which Row and which Column our specific dimensions (in this case State/Province) will sit in. As the requirements already stated it was to be a 3 column grid, our calculations for this didn’t need to be so complex.

Cols

(INDEX()-1)%3

INDEX() returns an incremental number starting at 1 for whatever dimension or set of dimensions we’re counting over. In this case we’re counting the number of State/Provinces. %3 returns the remainder when the index is divided by 3, so we get values of 0, 1 and 2.

Change this field to be discrete (right click -> convert to discrete)

Add State/Province to Rows then add Cols to Rows. Edit the table calculation so the field is computing by State/Province. You can see that the first 3 rows will be positioned in columns 0, 1,2 respectively and so on.

Create a new field

Rows

INT((INDEX()-1) / 3)

This takes the index value (minus 1), divides by 3 and ’rounds’ to a whole number. Make this discrete too and add to Rows, setting the table calculation as described above. Now we can see the first 3 rows will all actually be in the same row (row 0), then next 3 rows in row 1 and so on.

Shift the pills around so Cols is on Columns, Rows is on Rows and State/Province is on Detail. Add Sales Modified to Rows.

Create a new field

Quarter Date

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

and add this to Columns setting it as a continuous exact date (green pill). We’ve got a bit of unexpected ‘spaghetti’ going on…

To fix it, do the following ..

Add Quarter Date to Detail as a discrete exact date (blue pill). Change Quarter Date on Columns to be a continuous attribute (green pill – first change to attribute, then change to continuous). Edit the table calculation settings for both the Rows and the Cols fields to be computing by both State/Province and Quarter Date at the level of State/Province.

I had to reference previous challenges and blog posts I’d written to manage this… maybe there is something simpler, as this is pretty taxing for the ‘beginner’ part of the challenge.

Add another instance of ATTR(Quarter Date) to Columns and make dual axis and synchronise the axis. This will create an axis at the top of the chart as well as the bottom.

Format the ATTR(Quarter Date) pill so the axis format is custom formatted to “Q”q “‘”yy

Edit all the axis (top/bottom and left) and update the title. Adjust the Tooltip. Hide the Cols and Rows fields (right click and uncheck show header). Change the Colour of the line to grey.

This should be the Beginner solution. I have published this here.

Intermediate challenge

For this part of the challenge, we need to set up lots of new calculations, so let’s do this first. As usual, I’ll manage this in a tabular format. So on a new sheet, add State/Province and Quarter Date as a discrete exact date (blue pill) to Rows. Add Sales Modified to Text.

We need to get the threshold value for each State/Province, which is the average of the numbers all listed above, multiplied by 2. We’ll use LODs for this

Threshold

{FIXED [State/Province]: AVG({FIXED [State/Province], [Quarter Date]: ([Sales Modified])})} * 2

working inside out… get the value of the Sales Modified value for each State/Province and Quarter Date (which is the same as the values you see listed above) and then average this at the State/Province level and multiple the final result by 2. Add this to the table. This is the field we’ll be using for the horizontal reference line.

Next we need to identify the rows where the Sales Modified value exceeds the threshold, and then return the Sales Modified values for only these rows. I’ll do this in 2 stages

Is Above Threshold?

INT([Sales Modified] > SUM([Threshold]))

This returns a 1 or 0 depending on whether the statement is True or False. Using actual numeric values rather than boolean helps later on. Set this field to be discrete and add to the table.

Above Threshold Sales

IF [Is Above Threshold?]=1 THEN [Sales Modified] END

Add this to the table too. For the rows where we have 1’s, a value is displayed. This is the field we’ll be using for the red circles.

Finally we need to determine some fields to help us define a reference band. These need to be dates as they’ll be applied to the date axis, but the band doesn’t stretch to the previous/next quarter, and is only present if the last value is over the threshold.

Again using LODs let’s get the final date in the quarter

Max Quarter Per State

{FIXED [State/Province]: MAX([Quarter Date])}

Add this to the table as a discrete exact date (blue pill).

Now we need to know if the value associated with the final quarter is above the threshold or not

Final Quarter Above Threshold

INT(MIN([Quarter Date]) = MIN([Max Quarter per State]) AND [Is Above Threshold?]=1)

Again this will return a 1 or 0. Change to discrete and pop that into the table too. We can see Colorado is the first state listed where this is true.

Now we want to ‘spread’ that value across every row associated to the state

State Has Final Quarter Above Threshold

{FIXED [State/Province]: MAX(
{FIXED [State/Province], [Quarter Date]: ([Final Quarter Above Threshold])})
}

For each State/Province and Quarter Date, get the Final Quarter Above Threshold value and then get the maximum value of this for each State/Province. This is where having the values as 1’s and 0s helps.

Make discrete and add this to the table. Every row for Colorado has this set to 1

Now we can work out some dates

Ref Band Min

DATE(IF [State Has Final Quarter Above Threshold] = 1 THEN
DATEADD(‘month’, -1, [Max Quarter per State])
END)

If the State/Province is over the threshold for it’s final quarter, then get a date and set it to be 1 month less than the final quarter for that state.

Similarly

Ref Band Max

DATE(IF [State Has Final Quarter Above Threshold] = 1 THEN
DATEADD(‘month’, 1, [Max Quarter per State])
END)

If the State/Province is over the threshold for it’s final quarter, then get a date and set it to be 1 month more than the final quarter for that state.

Add both of these of the table as discrete exact dates (blue pills).

Now we have all the building blocks to build the next bit of the challenge.

Start by duplicating the Beginner viz.

Add Above Threshold Sales to Rows and make Dual axis and synchronise the axis.. Remove the 2nd instance of the Quarter Date from Columns, so we now have marks cards relating to the 2 measures rather than the 2 dates. Remove Measure Names from the All marks card.

Change the mark type on the Above Threshold Sales marks card to circle and change the colour to red. Adjust size to suit.

Add Threshold to the Detail shelf of the All marks card. Right click on the Sales axis and add reference line. Set it to be per pane and use the Threshold field. Display the value as the Label. Don’t show a Tooltip. Display a dotted black line.

Update the Tooltip to now have a reference to the threshold value too.

Add Ref Band Max and Ref Band Min to the Detail shelf of the All marks card. Set them both to be continuous attributes (green pills).

Right click on the Quarter Date axis and add reference line. Set it to be a band per pane that goes from the Ref Band Min to the Ref Band Max. Don’t display labels or tooltips or a line. Fill with a pale shade ot red/pink.

Add back in the additional Quarter Date dual axis as described in the Beginner section to get the dates listed the top again.

Hide the right hand axis (uncheck show header) and hide the NULL indicator.

This completes the Intermediate challenge. My version is published here.

Advanced challenge

Go back to the tabular sheet we were using to check the calculations needed for the Intermediate challenge, as we’ll build on this.

Firstly the sorting. We need to sort the states based on whether the final quarter was above the threshold or not, and then by the number of times the state was above the threshold. Let’s get the count to start with

Above Threshold Count Per State

{FIXED [State/Province]: SUM(
{FIXED [State/Province], [Quarter Date]: ([Is Above Threshold?])})
}

For each State/Province and Quarter Date, get the Is Above Threshold? value and then sum these up for each State/Province. This is where again having the values as 1’s and 0s helps.

Make this discrete and add to the table

then create a field we’ll use for the sort. This is going to be a numeric field

Sort

IF [State Has Final Quarter Above Threshold] = 1 THEN
100000 + [Above Threshold Count Per State]
ELSE
[Above Threshold Count Per State]
END

We’re just using a very large arbitrary number to force those states where the final quarter is over the threshold to be higher in the list. Make this discrete and add to the table too.

We can now apply a Sort to the State/Province field to sort by the Sort field descending

This results in Colorado moving to the top of the list followed by Minnesota, which also has 3 quarters above the threshold, including the last quarter, but alphabetically falls after Colorado so is listed 2nd.

To filter the data, I created another field, just for ease

Filter

IIF([State Has Final Quarter Above Threshold]=1,’Urgent’,’Non-Urgent’)

Add this to the Filter shelf and set to Urgent. The states should now be restricted to just those where the final quarter is above threshold.

For the final requirement of this challenge, we’ll build out another table on another sheet to demonstrate, as we need to work with a different instance of the quarter date.

On a new sheet, add State/Province to Rows and add Order Date at the Quarter (month year) level as a discrete field (blue pill) to Rows. Add Sales Modified to Text

For Alabama, we don’t have a 2020 Q3 or a 2023 Q3. Click on the Quarter(Order Date) pill and select Show Missing Values. These quarters appear but with no Sales Modified value.

We’ve had to use this different way to define the date quarter as if we tried to ‘show missing values’ against the Quarter Date field that is set to ‘exact date’, we send up getting every day that is missing, not just the dates relating to the quarter. Also, the ATTR(Quarter Date) field we’ve used on the previous vizzes, doesn’t allow the Show Missing Dates option.

Anyway, we need to get 0s in to these dates.

Show Modified with 0

ZN(LOOKUP([Sales Modified],0))

Apart from the Rows/Cols calcs needed for the trellis, this is the only table calculation I ended up using. It’s basically looking up it’s own row (LOOKUP([field],0)) and if it can’t find a value (as it’s missing) it’s returning 0 (the ZN() function). Add that to the table.

Ok so now we have the components needed, let’s build the viz. We can use the Intermediate version as a starting point, but will need to reapply some of the features.

Duplicate the Intermediate viz.

Remove the 2nd instance of the ATTR(Quarter Date) pill on Columns. Drag the Sales Modified with 0 pill and drop it directly over the Sales Modified pill so it replaces it. Hopefully the chart should still look the same.

Right click the Order Date field from the left hand data pane, and drag it directly onto the ATTR(Quarter Date) pill. Release the mouse and select the continuous quarter/year option from the dialog that displays.

Things will start to look a bit odd… you’ve lost your lines… Remove the Quarter Date pill from the Detail shelf on the All marks card. Fix the Rows and Cols table calc fields by just updating them to compute by State/Province only. Adjust the table calc of the Sales Modified With 0 field to compute by Quarter of Order Date and State/Province in that order.

Things still look crazy…. but just one more step… Show Missing Values on the Quarter(Order Date) pill.

Now every cell should be associated to a single State/Province with no broken lines, and Wyoming, right at the bottom, should show more than a single dot. This was A LOT of trial and error to fathom all this out.

Add back in the reference band following the instructions above (you should find the reference line for the threshold value will just then appear) and re-update the Tooltip.

Add another instance of Order Date at the quarter/year continuous level (green pill) to Columns and make dual axis and synchronise the axis. Edit the axis titles, and format them to the “Q”q “‘”yy custom format.

Apply the sort to the State/Province field on the Detail shelf so it is sorting by Sort Descending. Add Filter to the Filter shelf and select Urgent.

Add this to a dashboard, and that should be the completed Advanced challenge which I’ve published here.

There really was some black magic going on here at times. Tough one this week!

Happy vizzin’!

Donna

Can you build a heat map with bathymetry lines?

Donna Coles2 Comments

What??? That was the first thought that went through my mind when Luke set this challenge. Bathy..huh… ??? What’s that all about. Well read the challenge to find out more 🙂

The what?? was quickly followed by errr…..? The indicator on the challenge overview page said ‘hard’ and this was a Luke challenge after all, so certainly not for the faint hearted! I wasn’t sure how this was going to go, so just started with a basic tabular view and went from there. (hint – it might be worth reading the blog to the end before you start building.. it could save some time 😉 )

I quickly built a basic heat map. I added Order Date at the discrete (blue) month level to Columns and Sub-Category to Rows. I added Sales to Colour and changed the mark type to square then added Sales to Label.

We ultimately need the cumulative Percent of Total Sales per Sub-Category, to display as the label. Click on the Sales pill on the Label shelf and Add Table Calculation. From the dialog window, choose Running Total and verify the calculation is computing Table (across) (or amend and select Specific Dimensions and ensure Month Order Date is selected). Then check Add secondary calculation and in the secondary calc dialog, select Percent of Total, again ensuring Table (across).

If applied correctly, the values in the December column should all be 100%.

I wanted to ensure this calculation was stored so I could reuse, so while pressing shift key, I dragged the Sales pill from the label shelf into the data pane, and renamed the calculation

Cumulative % of Total

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

Format the field to be % with 0 dp

Editing the field should show the details above. Of course, you can just create the calculated field manually and type in the syntax. If you do that, then replace the Sales field on the label field, with this one. Centre align the text.

With this field, we can create the calculation Luke provides for the colouring

Colour

ROUND([Cumulative % of Total]*50, -1)

Replace the Sales field on the Colour shelf with this field, and adjust the colour to use the Blue sequential colour palette. You should now have the basic structure and colouring of the heat map.

Adjust the font style and alignment of the Sub-Category and Order Date Month label headings, and change the month labels to be abbreviated. Hide the Order Date column label and the Sub-Category title (right click hide field labels for columns/rows). Remove all gridlines, row/column dividers etc.

Looking good.. but what next.. how to get those divider lines…. I wasn’t too sure at this point, but I knew I had to identify the cells when a ‘change in colour’ happened both horizontally and vertically.

So the first thing I did was to duplicate the above sheet into a basic crosstab (right click sheet > duplicate as crosstab), and I removed Cumulative % of Total from the display, so I just had the values used for the colour.

I decided I wanted to flag each cell with a 1 or 0 depending on whether the next cell was different or not. I started horizontally. So for each row, and starting with January, I wanted to compare the colour value for Jan with the colour value for Feb. If they were the same, I wanted to record 0 against Jan. If they were different I wanted to record 1 against Jan. I used the following calculation

Horizontal – Next Value Diff

IF ([Colour] = LOOKUP([Colour],1) OR LAST()=0) THEN 0 ELSE 0.99 END

If the Colour value for the current cell (eg Jan) matches the Colour value of the next cell (eg Feb) OR, the current cell is the last month (ie Dec), then return 0 otherwise there is a mismatch so return 0.99. Originally I used 1, but later found I had to adjust the calc to make the line show as I wanted.

Add this field to the tabular display and verify the table calculations used within the field are running Table (across).

You can see that for Accessories, the Colour value for Feb is not equal to the Colour value for Mar, and so the Horizontal – Next Value Diff value for Feb is 0.99. Whereas as the Colour value for Apr matches May, the Horizontal – Next Value Diff for Apr is 0.

I created a similar calculation to test the vertical settings

Vertical – Next Value Diff

IF ([Colour] = LOOKUP([Colour],1) OR LAST()=0) THEN 0 ELSE 1 END

This is essentially exactly the same calculation, but when added to the tabular view, the table calculation for the Vertical – Next Value Diff calc should be set to Table (down) instead

You can see that in Feb, the Colour value for Paper is equal to the Colour value for Phones, so the Vertical – Next Value Diff calc for Paper is 0. But in Mar, the Colour value for Storage is different from the Colour value for Supplies, and so the Vertical – Next Value Diff calc for Storage is 1.

Using these markers, I now want to ‘plot’ them on a viz.

So back to the heat map sheet we built above, we need some axis.

Double click into the Columns shelf and type MIN(1.0) and change the mark type to bar.

You can see a hole has appeared. To fix this, on the Analysis menu, select Infer Properties from Missing Values. The cell will populate.

Confession – I didn’t get this bit initially. I had the chart built with the lines in the correct places, but with a hole. I’d tried all sorts of combinations of ZN, and LOOKUP(expression,0) in calculations to try to make the number appear, but couldn’t get anything to work. I showed my colleague Sam Parsons, who mentioned the above setting. I have honestly never ever used it and was completely unaware of it’s existence. But it solved the problem, so massive hi-five to Sam 🙂

Double click into the Rows shelf and again type MIN(1.0). Having an axis on both rows and columns, means we can now fix the Size of the bar. Click on the Size shelf and select Fixed, width in axis units to 1 and alignment right.

Now we have both an x and y axis, we can add additional detail to get the white bar dividers displaying.

First, adjust the label so it is aligned middle centre.

Add Horizontal – Next Value Diff to Columns. Ensure the table calc settings are Table (across).

Remove both the Colour and the Cumulative % of Total fields from the marks card, and then add Horizontal – Next Value Diff as a discrete (blue) pill to Colour. Remove all gridlines, zero lines, axis ticks and row/column dividers. Change the Size to be Manual and reduce size. Make the chart dual axis and synchronise the axis.

You should have something similar to the above, assuming the colours for the Horizontal – Next Value Diff are distinguishable enough.

I adjusted the colours to set 0 to be a transparent colour (refer to this blog to learn how to add a transparent colour hex code into your custom colour palette, and then 0.99 to be white. Edit the x-axis and fix to be from 0 to 1. The white dividers between the relevant months should now be noticeable.

To set the dividers between the Sub-Category, I decided I just needed to use a constant 0 reference line. For this I needed

Vertical Ref Line

IF [Vertical – Next Value Diff] = 1 THEN 0 END

Add this to the Detail shelf on the All marks card, and verify the table calc setting for the Vertical – Next Value Diff calc is set to Table (down).

Right click on the y-axis and Add Reference Line. Set it per cell using the Vertical Ref Line field, with no label or tooltip displaying. Set the Line properties to be white, 100% opacity and a thick width.

Then edit the y-axis to also be fixed between 0 and 1. The lines separating the Sub-Category should now be prominent.

Then it’s just a case of tidying up – hide the axis, stop tooltips from displaying, and then add to the dashboard, setting as fit to entire view.

If need be you may want to tweak either the size of the bar on the Horizontal – Next Value Diff marks card, or change the thickness of the reference line to get similar sizes.

I have no idea when I’d ever need to use this type of display, but I enjoyed the puzzle and discovered something new which is what I love about using Tableau!

This version of my published viz is here.

BUT….

after writing all this up, and stepping away for a bit, I suddenly realised I’d over-complicated things! I didn’t need a dual axis after all. I could just use a reference line to show the dividers between the months, exactly like I did for the 0 constant reference line – doh! So I made some adjustments..

Amend

Horizontal – Next Value Diff

IF ([Colour] = LOOKUP([Colour],1) OR LAST()=0) THEN 0 ELSE 1 END

Then create

Horizontal Ref Line

IF [Horizontal – Next Value Diff] = 1 THEN 1 END

Then remove the Horizontal – Next Value Diff field from the Rows shelf, so there is no longer a dual axis. Add Horizontal Ref Line to Detail , and display the x-axis MIN(1.0) axis, and add a reference line per cell which references Horizontal Ref Line. Apply the same settings to the reference line as detailed above.

And this resulted in a much simpler looking viz

I know I could reduce the number of calcs used, but I like to have ‘building blocks’ to follow my thought process. I have published the simpler version within the same workbook on a separate tab, here.

Happy vizzin’!

Donna

Thanksgiving Day NFL Games

Donna ColesLeave a comment

Sean Miller posted this week’s challenge based on the results of the annual NFL games hosted on Thanksgiving Day. It immediately reminded me of a previous #WOW challenge that Lorna posted in 2019 when she visualised Rugby League wins (see my viz here).

This is a table calculations based challenge. I did start using FIXED LoDs to help calculate the summary measures (Total Games and Win %) displayed at the front, but found that as there are 2 years (1975 and 1977) when the Dallas Cowboys did not host a game, I ended up with some pesky NULL values displaying which affected how the running sum area chart displayed.

Defining the calculations

As its a table calc challenge, I’ll build out what I can into a table to start with, to sense check I’m getting the correct numbers.

First up add Home Team, Game Date and Visiting Team to Rows and display Home Score and Visiting Score.

We start by determining the result of the fixture, based on whether it’s a home or away win or a tie. In the lollipop chart home wins are plotted at 1 and away wins at -1, so we’re going to store the result as a numeric value rather than text.

Result

FLOAT(IF [Home Score]>[Visiting Score] THEN 1
ELSEIF [Home Score]<[Visiting Score] THEN -1
ELSE 0 END)

The output is wrapped within a FLOAT, as this will help how the axis displays. Without it, by default Tableau will define the field to be a whole number, and the axis will extend to +/-2 which is too much room. We can’t adjust (fix) the axis to a decimal if the field itself is an integer, and adjusting to +/-1 chops off the displayed marks.

If you add this to the display, it will show 1, 0 -1 as you expect. You’ll notice though that the Axis on the lollipop chart is labelled as Win/Loss. This is achieved by applying a custom format to the field – “Win”;”Loss”;”Tie”

This is a sneaky but effective trick. The information stated before the first semi-colon applies to positive numbers, the info after the first semi-colon applied to negative numbers, and the information after the optional second semi-colon applies to zero.

Unfortunately though, it would appear that, at the point of writing, Tableau Public, isn’t honoring the zero formatting, and is displaying Win rather than Tie. The display works on Desktop though.

The win/loss/tie text is just a formatting feature and affects what is displayed, but the underlying value is still a number.

The Result field will be used to plot the lollipop chart. We now want a field to plot the area chart against. This is a running total of the Result values (ie win =1, win, win = 1+1, win, win, loss = 1+1 -1) and we need a table calculation.

However, as stated above due to a couple of missing years, I had to make an adjustment to ensure the running total displayed as Sean had in his challenge. I created another field

Result Adjusted

IIFNULL(SUM([Result]),0)

If the Result field doesn’t exist, as there is no data, then use 0 instead.

To see what’s going on, we’re going to need a different view of the data where the date field is continuous (green) rather than discrete (blue).

Build the below, and filter just for the first 10 years – you’ll see the gaps where the are no marks in 1975 and 1977 for Dallas

Use the context menu of the green YEAR(Game Date) pill and select the option to Show Missing Values. Marks will now display

Add Result to Label. Each mark is labelled Win or Loss, except the ones for Dallas for 1975 & 1977 as there is no data

Now add Result Adjusted to Label. A 0 value is now displayed against those two marks.

We can now build a running total off of this measure instead

Running Total Wins

RUNNING_SUM(([Result Adjusted]))

Add this to the Label too and verify the table calculation is computing by the Game Date field only. The running total for the 2 ‘missing’ dates is displaying a value which is the same as the previous value (since we’ve added 0 onto the running total). This will give us the flat line in the area chart when we come to build it.

Now back to our table of data, we can focus on the other calculated fields we need….

Total Games

WINDOW_COUNT(COUNTD([Game Date]))

This is a table calculation and is simply counting the number of distinct dates displayed. Add this to the table display we were building to start with, and adjust the table calculation to compute by all fields except Home Team. The total should display the same value for all the rows against each Home Team.

Next we want a field to indicate if the row is a win.

Is Win?

INT([Home Score]>[Visiting Score])

This is taking a boolean of true or false and converting to an INT (1 or 0).

From this we can work out the Win rate

Win %

WINDOW_SUM(SUM([Is Win?]))/[Total Games]

Add up all the Is Win? values associated to the Home Team as a proportion of the Total Games played. Format this field to a percentage with 0 dp. Again, add to the table and adjust the table calc to compute by all fields except Home Team, and verify the same settings applied to both the calculations nested in this calculation

For the All-Time Record, we need to know the number of wins and number of losses. We have a field to help us with the wins, but need an equivalent for the losses

Is Loss?

INT([Home Score]<[Visiting Score])

And from this we can work out

All-Time Record

STR({FIXED [Home Team]: SUM([Is Win?])}) + ‘-‘ +
STR({FIXED [Home Team]: SUM([Is Loss?])})

This is the one field I kept from my LoD based attempt.

The circles on the lollipop chart are coloured based on the difference in the score, so lets’s create that

Score Difference

[Home Score]-[Visiting Score]

And finally we need some fields to help display the tooltips properly. The tooltip indicates whether the result was ‘won’ or ‘lost’ which is different text to the axis labels.

TOOLTIP-Result

IF [Result]=1 THEN ‘won’
ELSEIF [Result]=-1 THEN ‘lost’
ELSE ‘tied’
END

The tooltip also displays the scores, but the scores are always presented as highest score – lowest score and not home score – visiting score. So we need fields to store the right values

TOOLTIP–Higher Score

IF [Is Win?]=1 THEN [Home Score] ELSE [Visiting Score] END

TOOLTIP – Lower Score

IF [Is Loss?]=1 THEN [Home Score] ELSE [Visiting Score] END

Pop all these fields out onto the table, so you can validate you’ve got all your calcs right before building the viz.

Building the area chart

Add Home Team to Rows, Game Date (continuous, show missing values) to Columns and Running Total Wins to Rows (ensure table calculation set as required). Change to mark type of Area. You should have 2 horizontal lines from 1974-1975 and 1976-1977 against the Dallas Cowboys row.

Adjust the tooltip, edit the label of the Running Total Wins axis , and remove the label of the Game Date axis.

Building the lollipop chart

Now add Result to Rows directly after the Home Team pill. Change the mark type to circle.

Add Score Difference to the Colour shelf of the circle mark, and adjust the starting colour range to a dark grey. Readjust the colour of the area chart to blue too. Add a border to the area chart too (via the colour shelf).

Add another instance of Result to the Rows shelf, next to the existing one. Set the mark type of this to bar. Reduce the size to the smallest possible, set the colour to grey and remove the border.

Now set this to be dual axis, synchronise the axis, and set the marks of the 2nd Result axis displayed on the right hand side to move marks to back. Uncheck Show Header to remove this axis from displaying.

Add Visiting Team, TOOLTIP-Result, TOOLTIP-Higher Score and TOOLTIP-Lower Score to the Tooltip shelf of both the Result marks cards, and adjust the tooltip on both to

Remove the Column dividers.

Now drag Total Games to Rows and drop next to the Home Team field. Change to be discrete (blue). Verify the number is what you expect and adjust the table calc if need be.

Add All-Time Record and Win % (set to discrete) to the view too. Then format these 4 fields so the text is larger and aligned centrally.

All that’s left now is to add the sheet to a dashboard. My published viz is here.

Happy vizzin’! Stay Safe!

Donna