This is the Sample Data what i want to do is for each document (field "REQUIREMENT_DESCRIPTION") calculate time difference by subtracting the time in "ACTION_DATE" n row from n+1 row.
And then calculate the mean and standard deviation of each document validation time.
So after searching online i found this formula which calculates the difference in time row by row.
First i split the column ACTION_DATE by "space" delimeter to separate time from date and than named the time field "ACTION_TIME".
Diff in Seconds = DATEDIFF(
Table[ACTION_TIME],
CALCULATE(
MIN([ACTION_TIME]),
FILTER(ALL(Table), Table[ACTION_TIME] > EARLIER(Table[ACTION_TIME]))
),
SECOND
)
Related
I'm having a hard time to calculate the running / cumulative total of average values...
My idea is to emulate a sales campaign for a product that never had one, using the average by day of all the products from an specific brand; problem is the code I made is only repeating the numbers from the average, it's not summing them up:
This is how it's now:
This is how it should be:
I managed to filter the values I want to calculate the average for, and that's for an specific brand (this is not going to be replicated to all products, and in the end I want to merge this in another calculated column which will calculate the goal for all the products (including the exception, which are the ones that never had a sales campaign before).
here's the code for the average:
AllPlutoProductsAverage = MAXX(FILTER('f_Leads(teste2)', [percentage] = EARLIER(d_CT_Leads_RT[percentage]) && 'f_Leads(teste2)'[group_name]="Pluto"), 'f_Leads(teste2)'[registers_per_day] )
And here's the code for the cumulative/running total column:
VAR _NoCampaign_RT =
CALCULATE(
MAX( 'd_CT_Leads_RT'[AllPlutoProductsAverage ] ) ,
FILTER( 'f_Leads(teste2)' ,
AND( 'f_Leads(teste2)'[group_name] = d_CT_Leads_RT[group_name] ,
'f_Leads(teste2)'[course] = d_CT_Leads_RT[course]
) &&'f_Leads(teste2)'[course_closed_percentage] = d_CT_Leads_RT[percentage]
)
)
Any ideas on how I fix that...?
Thanks in advance!! :))
I tried:
quick measure for running totals, didn't work
custom code for running totals, still repeated the values
creating a separate measure for average and then mentioned it on the column's running total code, same result
tried building up a running total code by adding the average calculation into it as a variable, didn't work either
tried exporting the calculation to a measure, didn't work either
And by 'didn't work' I mean the column No_PreviousCampaign still shows the repeated values from AllPlutoProductsAverage
I have a dataset of patients visiting several categories(SPECIALISM) of a hospital. A visit lasts a couple of hours each day. Each row in my dataset represents an hour that they are present for a certain hospital specialism.
Input
I want to calculate for each hour of the day, the number of patients that are present on average, per specialism, I used the following code (measure):
daggem = AVERAGEX(values('Date'[Date]),[distinctpat])
with distinctpat being a distinct count of patient IDs
This gives me almost the desired result, but the tales of the graph are too heavy (it shows an average of 1 patient during the night, but this 1 patient was there only on 1 specific day, normally it is zero. But the average, as I calculated, it does not include all other nights when there were zero patients. So I would like to obtain an average that is much lower (and more correct)
Output
You probably need an extra table with all the days and times. Based on the reports, you will be able to find the hours without visits
Here is an example of how to create a Date table with hours; Add relationship and use in calculation.
DatesWithHours =
var Dates = CALENDAR("2021-01-01 00:00:00", "2021-01-03 00:00:00")
var DatesHour =
GENERATE(Dates, (ADDCOLUMNS(GENERATESERIES(1,12,1),"Hours", [Date] + TIME([Value],0,0))))
return
DatesHour
That's the problem with AVERAGEX, it ignores blanks. Try a simple division instead.
daggem =
DIVIDE (
COUNTROWS ( TargetTable ),
COUNTROWS ( Dates )
)
I was attempting to employ the formulas here to calculate a running total of a column in PowerBI. However, my data is time-independent. In addition, every other running total calculation I've seen for PowerBI has been in reference to a date field. The target column is a "Frequency" column, and represents the estimated frequency of the event represented by each record. How do I generate a cumulative total of these frequencies, from lowest frequency to greatest? This is used to generate an exceedence curve for the consequences of events based on the running frequency total, called an F-N curve.
Per this site: https://www.daxpatterns.com/cumulative-total/, I was able to generate the following measure:
Measure_cumF =
CALCULATE (
sum([content.F]),
FILTER (
ALLSELECTED( Sheet1),
Sheet1[Content.N] >= MIN ( Sheet1[Content.N] )
)
)
"MIN" allows the cumulative sum of "Content.F" to start at the row containing the highest value of the desired sorting list, in this case "Content.N". "MAX" will start the cumulative sum at the row containing the lowest value of "Content.N".
"ALLSELECTED" applies the current filters to the measure. Replace with "ALL" to have a static value that always returns the cumulative sum of the entire column.
I am trying to aggregate the following values (NHS, Social Care and Both B) by the reasons for delays column so i can find the reason with the highest value (from the 3 combined values named above).
I have tried using summarize to create a table with just the reasons for delays ,NHS, Social Care and Both B columns. By doing this i hoped i could create a column named totals which adds the NHS, Social Care and Both B Columns together in this summarized table thus giving me the total values for each reason for delay.
Though when i tried to run a maxx function around my totals column it seems to give me the wrong values.
I have tried wrapping my table with the distinct function so it aggregates all the columns in my summarize together, but this did not help either.
Max Delays =
MAXX (
SUMMARIZE (
csv,
csv[Reason For Delay],
csv[NHS],
csv[Social Care],
csv[Both B],
"totals", CALCULATE ( SUM ( csv[NHS] ) + SUM ( csv[Both B] ) + SUM ( csv[Social Care] ) )
),
[totals]
)
The smaller table (which should represent the summarized table) in the above picture with the total column shows the values i expect to carry my max calculation over, where i expect the max value to be 277.
The max value i am getting instead is 182. This is the max value in the unsummarized table below where i have multiple duplicates of my reasons for delay column and 182 is the highest value.
I have uploaded a sample of the pbix file i am working on if it may be of help;https://www.zeta-uploader.com/en/1184250523
First, create a measure for total reasons:
Total Reasons = SUM(csv[NHS]) + SUM(csv[Both B]) + SUM(csv[Social Care])
Second, create a measure for the max reason:
Max Reason = MAXX( VALUES(csv[Reason For Delay]), [Total Reasons])
Result:
How it works:
The first measure is for convenience. You can re-use it in other formulas, making code cleaner;
In the second measure, we create a list of distinct reasons using VALUES. Then MAXX iterates this list, calculates total for each reason, and then finds the largest of them.
Short version of question: how can I create a rank based on a calculated measure?
Question background:
I have a table/query that yields many rows for each employee, with each row having a time taken value.
I'd like to calculate the average time taken for each employee, and then present a table with a row for each employee, showing their name, average time taken, and rank (based on time taken).
To do the first part, I created a measure called AverageTimeLength and set it equal to:
AverageTimeLength = Average(Table_name[Column_name])
Then I coded the following:
AverageTimeLength_employee = CALCULATE([AverageTimeLength], GROUPBY(Table_name, Table_name[EmployeeName]))
These two are measures; I was able to insert the second into the new table chart I'm creating, but unfortunately, I can't use RANKX() on it because the measure values don't come from a column. If I try to create a column derived from the measure (i.e., column_name = [AverageTimeLength_employee]) I just get an error accusing column_name of circular reasoning.
What I want to do seems like it should be simple; does anyone know how I can create a simple rank parameter, to rank the measure values?
You can create the Average measure and use it in the Rank measure as follows:
Average = AVERAGE([Time taken])
Rank = IF (
HASONEVALUE ( Table_Name[Name] ),
RANKX ( ALL ( Table_Name[Name] ), [Average])
)
Hope it helps.