Count the number of occurrences after associated date of certain value in Power BI - powerbi

I'm conducting an exercise around examining test results after tutoring has occurred. Essentially looking at the rates of "pass" post tutoring within the context of a given student. Where the ultimate outcome would be:
pass rate after tutoring = [count passes]/[count test date] WHERE test date > tutoring date.
For example:
Ideally, the final output of the measure would be = 1 (1/1)
Would anyone be able to point me in the direction of achieving this through a Power BI measure?
I've attempted the following to get the single oc with no luck:
Measure 3 = CALCULATE(COUNT(Table[Test Pass?]),FILTER(Table,Table[Test Date]>CALCULATE(Min(Table[Tutoring Date]),FILTER(Table,Table[Tutor (?)] <> BLANK ))))
Where I would then use the student column in a matrix with the measure to group pass rates post tutoring by student

I have used this simple flat table data model:
You can calculate this with a measure that needs to be evaluated with your Student column:
Pass Rate After Tutoring =
VAR _tutor_date =
CALCULATE (
MAX ( 'Table'[Tutoring Date] ),
ALLEXCEPT ( 'Table', 'Table'[Student] )
)
VAR _tests_post_tutor =
CALCULATE (
COUNTROWS ( 'Table' ),
ALLEXCEPT ( 'Table', 'Table'[Student] ),
'Table'[Test Date] > _tutor_date
)
VAR _successes =
CALCULATE (
COUNTROWS ( 'Table' ),
ALLEXCEPT ( 'Table', 'Table'[Student] ),
'Table'[Test Date] > _tutor_date,
'Table'[Test Pass]
)
RETURN
DIVIDE ( _successes, _tests_post_tutor )
But this assumes that students are only tutored for one specific test, and are tutored once.

Related

DAX Measure (e.g., "Count Rows") based upon filtered measure value (e.g., "[Sales]>100")

I need to write a DAX measure that calculates (e.g., "Count Rows"), but only when another measure value is evaluated (e.g., filtering "[Sales]>100"). So if-- in the context of the selected filters-- Sales is great than 100, then the measure is executed only for those rows.
The measure I have defined works in the context of lower smaller grain. But the totals do not sum correctly.
Any suggestions?
DAX Measure
License Usage =
// Users with active viewership in 3 months
IF (
NOT ( ISBLANK (
CALCULATE (
[Activity Date NEWEST],
KEEPFILTERS ( DATESINPERIOD ( dimCalendar[Date], TODAY (), -90, DAY ) )
)
)), 1
)
Activity Date NEWEST =
MAX('PBI Activity'[Date])
Okay, I figured something out that works.
DAX
License Usage =
// Users with active viewership in 3 months
CALCULATE (
[Count Users],
FILTER ( 'PBI Activity', 'PBI Activity'[Date] >= TODAY () - 90 )
)
Count Users = COUNTROWS('Users')
Also, I later came across this article which looks like it also does what I was hoping to do: Execute calculate expression over filtered rows based upon measure filter.
Reference: Specifying multiple filter conditions in CALCULATE - SQLBI
DAX
DEFINE
MEASURE Sales[Big Sales Amount] =
CALCULATE (
[Sales Amount],
KEEPFILTERS (
FILTER (
ALL ( Sales[Quantity], Sales[Net Price] ),
Sales[Quantity] * Sales[Net Price] > 1000
)
)
)
EVALUATE
SUMMARIZECOLUMNS (
Sales[Quantity],
"Sales Amount", [Sales Amount],
"Big Sales Amount", [Big Sales Amount]
)

Running total with a slicer in Powerbi

I am trying to find the running total by month, it worked using the following measure but only without using a slicer for the category "BLK":
With Date = VAR MaxDate =
MAX ( 'Calendar Table'[Date] ) RETURN
CALCULATE (
SUM ( 'Injuries'[Total] ),
FILTER (
ALL ( 'Injuries'[Classification] ),
'Injuries'[Classification] = "FAC"
),
FILTER ( ALLSELECTED ( 'Calendar Table' ), 'Calendar Table'[Date] <= MaxDate)
)+0
The result was only accurate when I don't apply the Category slicer "BLK", I tried a different measure:
With BLK = CALCULATE( SUM('Oxy Oman Personal Injuries'[Total]),
FILTER (
ALL ( 'Injuries'[Classification] ),
'Injuries'[Classification] = "FAC"
), ALLSELECTED('Blocks'[BLK]) )+0
The above gave me something similar to the actual data, it did not sum up the numbers.. at least it gave me the correct total of a the category selected = 5 while the first measure gave the total wrong = 4.
Here is a screenshot of the results for both measures with and without a slicer:
Without BLK slicer:(With Data gave me what I wanted)
Using one Category in the BLK Slicer:
How can I fix that?

How to calculate average of `whole number` data type column by Category

I am currently facing an issue where I need to calculate Average of no. of approvers for each contract type. But the issue over here is that the Approver data i.e. (contract_approval_order_1) field is nothing but USER IDs ( whole number data type). Thus Power BI is not calculating the averages properly as shown in the image below.
I tried the following formula in the column:
Average Approver Order 1 Assigned =
DIVIDE (
COUNT ( view_contracts[contract_approval_order_1] ),
DISTINCTCOUNT ( view_contracts[contract_id] ),
0
)
I am expecting 0.5 as the average of the sample data given below.
Use the following dax formula to create a measure:
Average Approver Order 1 Assigned =
VAR __numerator =
CALCULATE(
COUNT ( view_contracts[contract_approval_order_1] ),
ALLEXCEPT( view_contracts, view_contracts[contract_approval_order_1] )
)
VAR __denominator =
CALCULATE(
DISTINCTCOUNT ( view_contracts[contract_id] ),
ALLEXCEPT( view_contracts, view_contracts[contract_type] )
)
Return
DIVIDE( __numerator, __denominator, 0 )
The ALLEXCEPT statement in the denominator variable may be slightly different if there are other filters ar slicers affecting your table.
This is the result

Using TREATAS to get Measure from Another Table

I'm back with another issue. I have a sales table with transaction details on the products purchased. I also have a table with warehouse inventory information for each product. I'm trying to get the count of products purchased in a Table visualization with columns from the warehouse inventory table.
I tried both of the measures below, but they both return the total Count for each row rather than sliced by product. Any help would be greatly appreciated!
NumProductsfromSales1 = calculate([Count], treatas(values('Sales'[Product]), 'Inventory'[Product]))
NumProductsfromSales2 =
var lineage = treatas(values('Sales'[Product]), 'Inventory'[Product])
var tbl = calculatetable('Inventory Detail', KEEPFILTERS(lineage))
var result = calculate(sumx(tbl, [Count]))
return result
From this source, we see TREATAS works as follows.
[Filtered Measure] :=
CALCULATE (
<target_measure>,
TREATAS (
VALUES ( <lookup_granularity_column> ),
<target_granularity_column>
)
)
is equivalent to
[Filtered Measure] :=
CALCULATE (
<target_measure>,
INTERSECT (
ALL ( <target_granularity_column> ),
VALUES ( <lookup_granularity_column> )
)
)
The important part is the ALL function. That's why you're losing the filter context from the rows in the visual.
I'm not sure if this is the most efficient solution, but I think if you add Inventory as a filter table to your first attempt, it should maintain the filter context on that table from the row in the visual.
NumProductsfromSales1 =
CALCULATE (
[Count],
'Inventory',
TREATAS ( VALUES ( 'Sales'[Product] ), 'Inventory'[Product] )
)
Edit: Regarding your comment, try the following:
a =
VAR top5prod =
SELECTCOLUMNS (
TOPN (
5,
SUMMARIZE ( Sales, Sales[Product], "Count", [Product Count] ),
[Count]
),
"Product", Sales[Product]
)
RETURN
CALCULATE (
[Product Count],
FILTER ( 'Inventory', 'Inventory'[Product] IN top5prod )
)
Using FILTER isn't as efficient as TREATAS but see if it works.
It's very difficult to answer this sort of question without having anything reproducible to work with.

Using summarize and userelationship to generate a sum based on a condition

Story:
I have two date columns in my fact table, one is for orderdate and the second is for orderdate/refund/cancelled date.
I created two relationships between the date table and the fact table.
Active: Date > OrderDate
Inactive: Date > OtherDate
I would like to sum the # of refunds per day using the inactive relationship.
What I tried:
Returns =
VAR summary =
SUMMARIZE (
FILTER ( Query1, Query1[kind] = "refund" ),
Query1[orderId],
"returns", MAX ( Query1[amount] )
)
RETURN
CALCULATE (
MAX ( Query1[amount] ),
USERELATIONSHIP ( Query1[OtherDate], DateTable[Date] ),
summary
)
For some reason, it's using the active date column. Any suggestion on how to fix the above formula?
I'm not sure I understand how you are intending to use the summary variable here, but note that USERELATIONSHIP doesn't affect it at all since it's already computed.
You might not need that variable at all. Try this:
Returns =
CALCULATE (
MAX ( Query1[amount] ),
USERELATIONSHIP ( Query1[OtherDate], DateTable[Date] ),
Query1[kind] = "refund"
)