Tableau Weighted Average of Last Value in Date Group over Running Sum Across Extra Level of Detail not in Report - tableau-api

I am an absolute Tableau beginner, so forgive my lack of proper terminology.
Context
To give some context to the problem, think of the dataset as the balances and current interest rates of two different loans for which we are trying to calculate a weighted average cost of funds at any point in time, while retaining the ability to filter on Program (specific loan).
I have a single dataset that looks like:
The Balance field is used as a running sum, i.e. to get the actual balance as of 4/30/2022, you would sum the column across all Date values on or before 4/30/2022.
The Rate field is the opposite: it represents the discrete interest rate as of the Date. Thus, it cannot be summed.
Each data point is specific to a specific loan, or Program.
So to get the interest rate of Program A as of 4/30/2022, you would simply grab the Rate value of the row where Date = 4/30/2022 and Program = A, or 5.30%. Sums are fine here, since the value of Rate is never repeated for a single Program and Date combo, but we cannot use a running sum.
On the other hand, to get the balance of Program A as of 4/30/2022, you would need to add (running sum) the Balance values for all rows where Date <= 4/30/2022 and Program = A, or 10,000 + -2500 + -2500 + -2500 = 2500.
Problem / Need
I need a report (or whatever it's called in Tableau) with the following:
Date as a column
Measures as rows
This report would NOT include Program as a row or column, but would include it as a filter.
In this report, I need a Weighted Average Cost of Funds measure.
This is effectively the weighted average Rate over/weighted by the running sum of Balance across Programs included in the filter, of course for any given Date in the columns.
In other words, by Date, latest Ratefor eachProgramtimes thePrograms running sum of Balance, divided by running sum of all Balancesfor allProgram`s included in filter.
Here's an example in Excel:
Here's an example if we were to exclude Program A:
And here's an example if we were to exclude Program B:
Finally, here's the formulas underneath everything in the Excel example:

Related

Want to SUM all values for a specific date within column NOT sum all values in that column

I want to create a graph which shows the total capacity for each week relative to remaining availability across a series of specific dates. Just now when I attempt this in Power Bi it calculates this correctly for one of the values (remaining availability) but generates a value much higher than expected by manual calculation for the total capacity - instead showing the total for the entire column rather than for each specific date.
Why is Power Bi doing this and how can I solve it?
So far, I have tried generating the graph like this:
(https://i.stack.imgur.com/GV3vk.png)
and as you can see the capacity values are incredibly high they should be 25 days.
The total availability values are correct (ranging from 0 to 5.5 days).
When I create matrices to see the sum breakdown they are correct but it only appears to be that when combined together one of the values changes to the value for the whole column.
If anyone could help me with this issue that would be great! Thanks!

Why are my values multiplying when I apply Month/Year to my values?

When I apply Month/Year to Cases or Deaths from my data, the values explode. For Cases it goes from approximately 48 million to over 1 billion, and for Deaths it goes from about 700 thousand to over 22 million. However, when I try the same thing with Initial Claims or the Stringency Index, my values remain correct. I'm trying to find the month over month percentage change by the way. And I'm using the Date column. I only select 2020 and 2021 in the filter for Year.
What I'm asking about is Sheet 21.
Link to workbook: https://public.tableau.com/app/profile/nilajah.rivers/viz/CoronaVirusProject_16323687296770/Sheet21
Your problem is that the data points are daily cumulative deaths. If you change the date aggregation to anything other than days, Tableau will default to summing the numbers for all the days in the month. This will give the wrong result, obviously.
If you want to show the correct total deaths or cases regardless of the time aggregation (months, days, weeks etc.) then you could use the New Case or New Death numbers plus a running sum table calculation. This will always give the correct total for the time period.
Table calculations will also allow automatic calculation of the period to period % change from the same data fields.
This is a common problem when working with datasets that offer pre-calculated aggregations. Tableau doesn't need that as it can dynamically calculate the aggregation of a field over any given time period but it is easy to forget which field has pre-aggregated data and which has raw data. Pre-aggregated fields assume a particular time period and can't be used for different time periods without disentangling that assumption (which is unnecessary if you also have the raw data (in this case daily new deaths/cases).

Tableau Summing up aggregated data with FIXED

Data granularity is per customer, per invoice date, per product type.
Generally the idea is simple:
We have a moving average calculation of the volume per week. MA based on last 12 weeks (MA Volume):
window_sum(sum([Volume]),-11,0)/window_count(count([Volume]), -11,0)
We need to see the deviation of the current week vs the MA for that week (Vol DIFF):
SUM([Volume])-[MA Calc]
We need to sum up the deviations for a fixed period of time (Year/Month)
Basically this should show us whether on average, for a given period of time, we deviate positively or negatively vs the base.
enter image description here
Unfortunately I get errors like:
"Argument to SUM (an aggregate function) is already an aggregation, and cannot be further aggregated."
Or
"Level of detail expressions cannot contain table calculations or the ATTR function"
Any ideas how I can go around this one?
Managed to solve this one. Needed to add months to the view and then just WINDOW_SUM(Vol_DIFF).
Simple as that!

Sum of calculated averages PowerBI

I'm fairly new to PowerBI, I want to calculate sum of averages as measure.
So average is perfectly fine but I couldn't manage to sum them.
average = AVERAGEX(SUMMARIZE(ProductionVolumeData,
ProductionVolumeData[ProductionOrderID],
MDCProductionVolumeData[MachineID],
"sum_volume",
SUM(ProductionVolumeData[Volume])),[sum_volume])
this formula calculates aggregates volume group by production order id and machine id and find mean.
I checked in table, it works for one ProductionOrderID but whenever I add another ProductionOrderID to table it also calculates average. What I want is to sum up averages.
How can I do that?
Thanks in advance

Power BI: Finding average of averages and STDEV.P of averages

All,
My overall objective is to find outliers within an aggregated data set vs the underlying detail for different date ranges. The issue I am having is that Power BI is averaging the SalesPerDay and finding the STDEV.P at the daily level which is the grain of the raw data. I need to first find the average Sales, then find the average of those averages for that "rolled up" data set. Same with STDEV.P. Need to find the STDEV of the "rolled up" averages. Screenshot below depicting how I need the tool to aggregate.
I have brought the Sales column into my dashboard, dimentionalized by user, and set to AVERAGE to get average SalesPerDay.
Then I created the new measure
newavg = CALCULATE(AVERAGE(SalesPerDay[Sales]),ALLSELECTED())
Which is finding the overall average, but at the daily level vs the aggregated level.
I also tried
newSTDV = CALCULATE(STDEV.P(AVERAGE(SalesPerDay[Sales])),ALLSELECTED())
But you cannot find the STDEV.P of a calculation.
Thank you.
What you are looking for is the iterator functions, which take a table or column of data as a grouping, and then applies a calculation on that group.
Example of one would be SUMX. In the example below, it would do a grouping based on Product. Within each product it would get the total of qty and multiply it by the sum of x. It would then sum the results of that calculation into a total.
SUMX( VALUES( table1 [ Product ] ), [Qty] * [x] )
There also being averagex, minx, maxx, plus for the statistical functions there is STDEVX.P and STDEVX.S