I have a table in power bi in which I have the hours of entry to work. The case is that I can make a table that collects for each hour of work the number of people who have entered at that time with the count function.
See an example:
entry time
09:30
09:30
09:22
In other words, in the table values field I drag entry time and entry time count, which gives me for each entry time the number of people that entered.
The case here is that I would like to create a measure that allows me to obtain the percentage of people who have entered at 9:00 and 9:30 with respect to the total.
[(Number of people that have entered at 9:00)+(Number of people that have entered at 9:30)]/ count of people that have entered
I've unsuccessfully tried to create a measure.
So your table just contains the times when people entered on separate rows. You can count the Timestamps directly with the following measure:
% Count =
VAR selected =
CALCULATE(
Count('Table'[Time]),
'Table'[Time] = TIMEVALUE("9:00")
|| 'Table'[Time] = TIMEVALUE("9:30")
)
VAR allpeople =
CALCULATE(
Count('Table'[Time]),
ALL('Table')
)
RETURN
DIVIDE(selected, allpeople)
Related
I have a table that lists quarter-end account balances by account and business group and I'd like to create a measure or column that shows the quarter-over-quarter balance change for each company/account combo (e.g., Group A, Account 10000 quarter-over-quarter change is $500).
I've tried various formulas using the calculate function, but these don't work if I don't apply aggregation (SUM and SUMX are what I've tried) to the AMOUNT column. The aggregations seem to mess up the results. I either get blank values or duplicate amount values. I think it's because the amounts don't need to be aggregated. They're already aggregated values.
How can I do a simple subtraction based on quarterly dates without having to aggregate my amount column?
The formula(and similar variations) I've tried:
QtrChange =
VAR CurrentAmt = TABLE1[AMOUNT]
VAR PrevAmt = CALCULATE(SUM(TABLE1[AMOUNT]), PREVIOUSQUARTER(TABLE1[DATE].[DATE])
RETURN = CurrentAmt - PrevAmt
Table example:
Business Group
Account
Quarter end balance
Quarter
A
100000
$2000
3/31/22
A
200000
$3000
3/31/22
B
100000
$4000
3/31/22
B
200000
$5000
3/31/22
Edit:
Edited DAX formula with labels tying to example table, for better clarity:
QtrChange =
VAR CurrentAmt = TABLE1[Quarter end balance]
VAR PrevAmt = CALCULATE(SUM(TABLE1[Quarter end balance]), PREVIOUSQUARTER(TABLE1[Quarter].[DATE])
RETURN = CurrentAmt - PrevAmt
I want to show an hourly score for today that refreshes every hour. I built it and it works, but now I want it to compare the hourly average for the last week and if it was higher it shows a red arrow up if lower it shows a green arrow down. I don't have a problem adding the arrows as it's very easy, but I've previously added a column to the query that shows if day = today and then used it as a filter inside the visual to show today's data, so when I try to compare the results the filter also affects the calculation I created:
Measure = calculate(average(rawdata[contacts]),rawdata[Week to Average = 1)
week to average is the column that tells if the week was the previous week is simply if(weekcolumn=weeknum(today())-1,1,0)
Do you know any way i can compare last week average to todays data?
Also visual that i used is a matrix
This is just an idea. So if it is enough to solve the case then ok. If it's not it, then, please, add more info about your data table - a screenshot or sample data. how you calculate your average and what do you mean by average? At least what kind of data you are dealing with is it a sum of some values per day, do you have a different number of values for each day? etc.
measure 1:
averContacts = AVERAGE(rawdata[contacts]) -- no CALCULATE()
measure 2:
avrToday =
CALCULATE(
[averContacts]
,TreatAS({TODAY()}, yourTable[DatesColumn])
)
measure 3:
aveLastWeek =
VAR prevWeekEnd = TODAY() - WEEKDAY(Today(),2) -- 2 -> Mon-Sun week format
VAR prevWeekStart = prevWeekEnd - 7
VAR DatesLastWeek = CALENDAR(prevWeekStart ,prevWeekEnd)
RETURN
CALCULATE(
[averContacts]
,TreatAS(DatesLastWeek, yourTable[DatesColumn])
)
measure for your visual
lastWeek_vs_Today = DIVIDE(avrToday ,aveLastWeek)
I need a DAX measure that gives me the sum of durations for multiple categories restricted by a date slicer.
In this simplified example there are 2 categories with 3 subcategories each. A DateTime Slicer on the dashboard is set to the timespan of 2nd of January 2021 noon to 6th of January midnight. I need the summed up duration of all categories in this timespan.
Input data:
A table containing multiple rows for each category with a start date and an end date.
The complicated part is that there are pauses between the timestamps.
Desired output:
A table on the dashboard containing the category and a calculated measure for the summed up duration during the sliced timespan.
When changing the slicer the meaure shall change as well.
My current solution for this problem is an M formulato create a list of all days in each timespan and to unpivot all lists. In the dashboard the count of rows gives you the number of days in the selected timespan. This solution though reqires a much larger input table and soes not work if you want to be exact on the second, only on days.
I tried so solve this via a measure but didn't make any progress worth showing here.
all datetime values are in the format dd.mm.yyyy hh:mm:ss (24h system)
I found a way to do it by using 2 measures.
First measure calculates the time during the timespan for each element:
I use one Date Table only consisting of all dates available which is the input for the slicer and the data Table called "Data".
duration_in_timespan_single =
VAR MinTs = MIN ('Date'[Date])
VAR MaxTs = MAX ('Date'[Date])
VAR MinUtcMin = MIN ('Data'[Date_Start])
VAR MaxUtcMax = MAX ('Data'[Date_End])
RETURN
IF(
AND(MinUtcMin >= MinTs, MinUtcMin <= MaxTs),
IF(
MaxUtcMax <= MaxTs,
CONVERT((MaxUtcMax-MinUtcMin),DOUBLE),
CONVERT((MaxTs-MinUtcMin),DOUBLE)),
IF(
MinUtcMin < MinTs,
IF(
MaxUtcMax > MinTs,
IF(
MaxUtcMax <= MaxTs,
CONVERT((MaxUtcMax-MinTs),DOUBLE),
CONVERT((MaxTs-MinTs),DOUBLE)
),
0
),
0
)
)
The second measure just sums up the first for each category:
duration_in_timespan = SUMX('Data',[duration_in_timespan_single])
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'm trying to calculate a monthly average number of cases for each investigator. It might be over a quarter, year, or multiple years so it needs to respond to the visual or table context I drop it into. The base table has Case (individual case#), Investigator (person name), Date assigned (not shown), and from that date,month and year columns extracted and a YearMonth categorical column.
I create a caseCount measure as
caseCount = COUNT('Table'[Case])
I've tried several different ways to calculate the average over all months (in this case 4). Because Mary has cases in each month, her average is correct (1.75) but Sam's uses a denominator = 3, thus doesn't calculate correctly. (returns 1.3 instead of 1). How can I force the calculation to use the full number of months.
Additional notes:
There may be cases in the table that fall outside the date range I want so I've tried using a
Avg = CALCULATE(AVERAGE(caseCount), Table[Date] > #10/31/2019#)
I've also tried several variations using CALCULATE(DIVIDE(), [Date] > 10/31/2019. Everything seems to exclude those months when an investigator had no investigations assigned. I also tried connecting to a Date table and using the Distinct YearMonth value created there.
This is because the evaluation context.
I would define the measure as follow:
VAR _casecount = //count number of cases in the selected period, applied on the fact table
VAR _months = COUNTROWS(CALCULATETABLE(VALUES('Calendar'[Month]), ALLSELECTED('Calendar'))) //count number of months in the selected period
RETURN
_casecount/months
Update
I did not consider the scenario of multi-year periods involving May-2019 and May-2020. Then, let's reframe the solution using DATEDIFF:
VAR _casecount = //count number of cases in the selected period, applied on the fact table
VAR _firstCalendarDate = CALCULATE(MIN('Calendar'[Date], ALLSELECTED('Calendar'))
VAR _lastCalendarDate = CALCULATE(MAX('Calendar'[Date], ALLSELECTED('Calendar'))
VAR _months = DATEDIFF(_firstCalendarDate, _lastCalendarDate, MONTH)
RETURN
_casecount/months