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?
Related
I've got the following DAX Measure that provides me with the ability to filter down to the last XX of activity from an individual.
I can only seem to add the measure to the Filter on Visual so when chosing to filter down on say the last 10 this does not update other visuals in the report.
What can I do so that I am able to view the last 10 activities, but for the other visuals to update?
Rank = RANKX
(ALLEXCEPT(Sheet1,Sheet1[Name]),
CALCULATE(MAX(Sheet1[Date])),,
DESC)
It's likely you are applying that filter to only one visual.
It's better to implement the logic in the DAX calculation.
DAX Calculation
Rank =
VAR _Calc =
RANKX (
ALLEXCEPT ( Sheet1, Sheet1[Name] ),
CALCULATE ( MAX ( Sheet1[Date] ) ),
,
DESC
)
RETURN
IF ( _Calc <= 10, _Calc )
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.
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]
)
I am new to DAX and have 2 questions I would like answered for a project. I am working on figuring out what the first value per customer is so what amount does the customer come in with.
In addition I would like to know what is the time between customer's orders does the customer come back to buy something after a day, week or only after a year. And if a customer comes 5 times what is the time between the orders each time.
Data set
enter image description here
Now I tried the following but then I only get the first date back each time but then each customer gets the very first order date that exists.
First Order = CALCULATE(FIRSTDATE(Text[Datum].[Date]),VALUES(Text[Datum].[Date]))
How can I solve this two question with DAX
You can try the following:
Initial value for customer measure
Initial value =
-- find customers first appearance date
VAR first_date =
CALCULATETABLE (
FIRSTDATE ( 'Table'[Date] ),
-- remove all filters on 'Table'[Date]
REMOVEFILTERS ( 'Table'[Date] )
)
RETURN
CALCULATE (
SUM ( 'Table'[Value] ),
first_date
)
First order date measure
First Order =
CALCULATE (
FIRSTDATE ( 'Table'[Date] ),
REMOVEFILTERS ( 'Table'[Date] )
)
Days passed since last visit measure
Days passed =
VAR last_visit =
CALCULATE (
MAX ( 'Table'[Date] ),
'Table'[Date]
-- from example expecting Customer ID & Date form unique combination,
-- otherwise use MAX() instead
< SELECTEDVALUE ( 'Table'[Date] )
)
RETURN
DATEDIFF (
last_visit,
-- same here as above with SELECTEDVALUE()
SELECTEDVALUE ( 'Table'[Date] ),
DAY
)
The result will then look like this (represented in a table visual):
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