# Can you compare a 3-day vs 14-day moving average and describe the latest trend?

This week for #WOW2020, Ann provided a table calculation feast of a challenge! This certainly is not for the faint-hearted! As well as cracking all the table calcs, the challenge features multiple views, measure swapping, parameters, BANs, filtering, sorting …. it’s got it all going on!

Ann hinted you’d probably want to start with the table, and even if there hadn’t been a table output in the display, this is what I would have done. If you’ve read enough of my blogs, you’ll know I often like to build up a ‘check data’ sheet, which just contains the data I need in tabular form as a quick reference. When working with table calculations this is an absolute must have!

So let’s build out that Check Data table to start with. I have a feeling this is going to be a lengthy blog ðŸ™‚

Initial Set up

First up, the requirements stated that the latest date would be 7 June, but I found records with a 8 June date. All the associated info for this date was null though, so I set a data source filter to exclude this. This means I wouldn’t get any issues if I needed to store the max date in a FIXED LoD calculation at any point.

I also found it easier to rename a couple of the measures provided to match the output, so rename PEOPLE_POSITIVE_NEW_CASES_COUNT to New Cases and PEOPLE_POSITIVE_CASES_COUNT to Reported Cases. I’ll refer to these renamed fields going forward.

Building all the Calculated Fields

To build out the table, we’re just going to focus on one State & County, as there’s a lot of data. So add Province State Name = Tennessee and County = Davidson to the Filter shelf.

Add Report Date (discrete exact date – blue pill) and New Cases & Reported to Rows. As you scroll down, you’ll see data starting to come in on 8 March.

We want to create our moving average calculations

3 Day Moving Avg

WINDOW_AVG(SUM([New Cases]), -2, 0)

14 Day Moving Avg

WINDOW_AVG(SUM([New Cases]), -13, 0)

Notice the number of rows to average over is 1 less than you might expect, as the current row is included, so the calculation is saying ‘current row’ and 2 | 13 previous rows.

Add these to the table, and adjust the table calculation so it is explicitly calculating by Report Date. This would have happened automatically, as the calculation would have been computing ‘down’ the table, but it’s best to fix the computation, so it doesn’t matter where the pill gets moved to in the view.

We now need to work out whether there is an increase or not between the 3-day and 14-day average.

Is Increase?

IF [3 Day Moving Avg] > [14 Day Moving Avg] THEN 1 ELSE 0 END

Is Decrease?

IF [3 Day Moving Avg] <= [14 Day Moving Avg] THEN 1 ELSE 0 END

I’m using 1s and 0s as it’s going to help with a later calculation.

NOTE – I’m assuming that if there is ‘no change’ it’ll be recorded as a decrease. This is how I interpreted the requirement, “Â …whether it is an increase or a decrease (or no change)” and it wasn’t easy to find any matches anyway.

I also need some text to indicate the increase or decrease

Increase | Decrease

UPPER(IF [Is Increase?]=1 THEN ‘Increase’ ELSE ‘Decrease’ END)

The UPPER is used as that’s part of the tooltip formatting.

Let’s get these onto the view, always making sure the table calculations are set to Report Date.

We need to calculate the number of days that has been reported INCREASE in succession, and the number of days where successive DECREASE has been reported.

So first, let’s identify which rows match the previous row.

Match Prev Value?

LOOKUP([Is Increase?],-1) = [Is Increase?]

If the value of the Is Increase? field in the previous (-1) row is the same as the Is Increase? field in the current row, then this is true, else false.

Add to the view, and verify the table calculation for itself and all nested calculations being referenced, is set to Report Date.

We now have all the information we need to help us work out the number of days in the increase/decrease ‘trend’.

Days in Trend

IF (FIRST()=0) OR(NOT([Match Prev Value?])) THEN 1
ELSEIF [Increase | Decrease] = ‘INCREASE’ THEN ([Is Increase?]+PREVIOUS_VALUE([Is Increase?]))
ELSEIF [Increase | Decrease] = ‘DECREASE’ THEN ([Is Decrease? ]+PREVIOUS_VALUE([Is Decrease? ]))
END

If the row in the table is the very first entry (so there’s nothing previous to compare against), or the row in the table didn’t match it’s predecessor (ie there was a change), then we’re starting a new ‘trend run’, which obviously starts at 1.

Otherwise, if the current row we’re on indicates an increase, then we’ll add the value of the Is Increase? field (which is 1) to the previous value (which is also 1). PREVIOUS_VALUE works recursively though, so it essentially builds up a running sum, which gives our trend.

We ultimately do the same thing using the Is Decrease? column. This is why using 1 & 0s in the earlier calculation help.

Adding into the view, and setting the table calculation correctly, you should get something similar to this…

Finally, there’s one key field we need to add; something to help identify the latest row as we will need it for filtering in the table that’s displayed on the dashboard. Simply applying a standard ‘quick filter’ won’t work, as the table requires we show the 3-day & 14-day moving averages. A ‘quick filter’ to limit the data to the latest date (7th June), will show the wrong values, as the data related to the other days will be filtered out, so the table calc won’t have the information to correctly compute over.

We need to create another table calculation that we can use as a filter, and that due to Tableau’s ‘order of operations’ will apply later in the filtering process than a traditional quick filter.

Max Date

{FIXED : MAX([Report Date])}

The latest date in the whole data set.

Show Data for Latest Date

LOOKUP(MIN([Report Date]),0) = MIN([Max Date])

If the Report Date of the current row is the same as the maximum date in the whole data set, then return true.

We’ve now got all the core data components we need to create the various charts.

In the interest of time (my time in writing this out), I’m going to attempt not to describe the building of all the charts in too much detail, but just call out the useful bits you might need. If you’re attempting this challenge with the table calcs above, I’m assuming you know Tableau enough to not need everything defined to the lowest level.

The whole report is driven off a parameter which the user must enter a State – County combo.

You’ll need a calculated field to store the combo

State – County

[Province State Name] + ‘ – ‘ + [County]

and then create a parameter (State – County Parameter) off of this (right click, Create -> Parameter) which will create a string parameter with all the permutations.

When displaying on the dashboard, set this to be of type Type In

BAN

The BAN is a basic summary of the latest trend for the entered state county.

We need to filter the sheet to the value entered in the parameter

Is Selected State County?

[State – County Parameter] = [State – County]

Add this to the Filter shelf as true, along with the Show Data for Latest Date.

Add the relevant fields to the Text shelf to display the required text. The Report Date needs to be custom formatted to ddd, mmm d to get the Sun, Jun 7 display

Map

For the map, as well as filtering the latest date, we’re also going to need to filter just to the state only (not state & county) as above. So I created

Is Selected State?

LEFT([State – County Parameter], FIND([State – County Parameter],’-‘)-2) = [Province State Name]

This is unpicking the State – County combined string stored in the parameter, to just find the State part and compare to the Province State Name.

Build a filled map based on County and filter to the latest date and the selected state. I set the Map Layers to that below, which seems to match up

You’ll need to set both the Is Selected State County? and Increase|Decrease fields to the Colour shelf.

Bar & Line Chart

You’re going to need a few more calculated fields for this.

Moving Avg Selector

for the user to choose what the line should display. I’ve set it to an intger parameter that displays text

We then need a field to show on the display depending on what’s been selected in the parameter

Moving Avg to Display

If [Moving Avg Selector] = 3 THEN [3 Day Moving Avg] ELSE [14 Day Moving Avg] END

You’ll need a Dual Axis chart plotting New Cases and Moving Avg to Display against Report Date (continuous exact date)

The data only starts from 8th March, so I added Report Date to filter to start from 8th March. 8th March is also added as a constant reference line.

Table

Based on the State / County entered, the table is filtered to show the data for the latest date for all the counties in the state entered. Although not stated in the requirements, the first row is the county selected, with the rest ordered by Reported Cases.

You can get the selected county to the top, by adding Is Selected State County as a hidden field to the Rows, and moving ‘True’ to the top.

And that should be everything you need to build the dashboard, which is pretty much just stacking all the sheets one on top of each other in a single column.

My published viz is here.

Happy vizzin’! Stay Safe!

Donna