Please advise if the below case may have a solution in DAX, Power query.
Have a model in Excel to identify reorder points based on Min/Max levels over 52 time periods (year). It works perfectly with 1 item, start having difficulties with 3,000 part #s (array formulas and chain calculations) therefore trying to rebuild that with DAX. Was able to reproduce all columns in DAX except for [Reorder] and [Inbound], spits out circular dependency error. I understand that DAX was not meant to be used for recursive calculations, however, I am sure there must be a workaround.
This is an abstract of an Excel spreadsheet (1 with part #)
where:
Safety, Min & Max - stock levels
LT Weeks - lead time (time between ordering and restocking)
INV_0 - opening inventory = Closing inventory from the previous period
INV_1 - closing inventory
Demand - outbound quantity = separately modeled forecast
Inbound - inbound = Quantity reordered [LT Weeks] periods ago
Reorder - reorder quantity =
IF (
[INV_1] - [DEMAND] + [INBOUND] + [PIPELINE] <= MIN,
[MAX] - ( [INV_0] - [DEMAND] + [INBOUND] + [PIPELINE] ),
0
)
Pipeline - sum of quantities reordered in preceding [LT weeks] interval -1
Total inv = INV_1 + [Pipeline].
Help would be much appreciated.
Related
In my cube, I have several measures at the day grain that I'd like to sum at the day grain but average (or take latest) at the month grain or year grain.
Example:
We have a Fact table with Date and number of active subscribers in that day (aka PMC). This is snapshotted per day.
dt
SubscriberCnt
1/1/22
50
1/2/22
55
This works great at the day level. At the month level, we don't want to sum these two values (count = 105) because it doesn't make sense and not accurate.
when someone is looking at month grain, it should look like this - take the latest for the month. (we may change this to do an average instead, management is still deciding)
option 1 - Take latest
Month-Dt
Subscribers
Jan-2022
55
Feb-2022
-
option 2 - Take aveage
Month-Dt
Subscribers
Jan-2022
52
Feb-2022
-
I've not been able to find the right search terms for this but this seems like a common problem.
I added some sample data at the end of a month for testing:
dt
SubscriberCnt
12/30/21
46
12/31/21
48
This formula uses LASTNONBLANKVALUE, which sorts by the first column and provides the latest value that is not blank:
Monthly Subscriber Count = LASTNONBLANKVALUE( 'Table'[dt], SUM('Table'[SubscriberCnt]) )
If you do an AVERAGE, a simple AVERAGE formula will work. If you want an average just for the current month, then try this:
Current Subscriber Count =
VAR _EOM = CLOSINGBALANCEMONTH( SUM('Table'[SubscriberCnt]), DateDim[Date] )
RETURN IF(_EOM <> 0, _EOM, AVERAGE('Table'[SubscriberCnt]) )
But the total row will be misleading, so I would add this so the total row is the latest number:
Current Subscriber Count =
VAR _EOM = CLOSINGBALANCEMONTH( SUM('Table'[SubscriberCnt]), DateDim[Date] ) //Get the number on the last day of the month
VAR _TOT = NOT HASONEVALUE(DateDim[MonthNo]) // Check if this is a total row (more than one month value)
RETURN IF(_TOT, [Monthly Subscriber Count], // For total rows, use the latest nonblank value
IF(_EOM <> 0, _EOM, AVERAGE('Table'[SubscriberCnt]) ) // For month rows, use final day if available, else use the average
)
I want to calculate total value between two dates in DAX. I have a formula SUM(C5:C16) in excel sheet, which C5 is the sales amount for a specific date (last year + 1month), and C16 is the sales amount for current row date.
I tried this formula in DAX, but it did not return sum value:
var Rolling = CALCULATE(sum('proces'[HOURS]),DATESINPERIOD('Date'[DateField],ENDOFMONTH('proces'[date_start]),-12,MONTH))
Also, I tried this one, but it is not working:
=SumX (
var prev=DATEADD(DATEADD('proces'[date_start] ,-1,YEAR),+1,MONTH)
return
Filter ( 'proces',
'proces'[date_end] <= Earlier ( 'proces'[date_end] ) &&
'proces'[date_start]>=prev,
'proces'[HOURS])
Also, I tried this one but it returns nothing
=CALCULATE(
SUMX('proces','proces'[HOURS]),
DATESBETWEEN(
'Date'[DateField],
STARTOFMONTH(DATEADD(LASTDATE('Date'[DateField]),-1,MONTH)),
ENDOFMONTH(DATEADD('Date'[DateField],-1,MONTH))
)
)
You seem to be confused about variables in DAX and your formulas are not even valid DAX expressions. Learn about variables in the official documentation:
Use variables to improve your DAX formulas
If you need further help with calculating the your total amount, add sample data to your question.
I am trying to create a measure that would count the instances when another measure is between given values.
The first is a measure of forecast accuracy, which is calculated over products and customers with a target value of 1. Then I would like to make a monthly report which shows for how many products the forecast accuracy is less than .85, between 0.85 and 1.15 and over 1.15.
The measure I tried for the middle category, which does not give the desired result:
var tab = SUMMARIZE(data, data[ComponentNumber], "Accuracy", [Forecast accuracy])
return SUMX(tab, IF([Accuracy] > 0.85 && [Accuracy] < 1.15, 1, 0))
The data table has also a customer number, which is why I tried first evaluating the measure [Forecast accuracy] only over components, disregarding the customers.
One source of the problem may lie in the fact that the measure [Forecast accuracy] is calculated as a division of two measures [Ordered Quantity] and [Forecast Quantity], of which the former is in another table. Does this affect the evaluation of my attempted measure?
I have a few things I am struggling with so hopefully I can ask all at once ?
I am using VS 2010 and I think with Vb.net to build reports, I use databases from Sql - I am mainly using matrix tables
I have a report that is multiple tables in one but not sure how to set/define to still show the tables that has no data ? So currently if there is a blank one it messes up the full report look ?
In another scenario how can I use an expression/custom code to filter out items in one row - in a calculation for example if I only want to sum 3 items of 5 etc
How can I work out % of a row or coloumn based on criteria or filters so if total items is 30 and item 1 is 5 the % of will be 17% and all items will total to 100%
How can I work out growth of the row/column so if year 1 is 50 and year 2 is 60 the growth/variance will be 20%
There are some issues with the expressions:
=IIF(Fields!Total_Amount__Excl_VAT_.Value = 0
OR Fields!Total_Amount__Excl_VAT_.Value = "", 0, Sum(Fields!Total_Amount__Excl_VAT_.Value))
The SUM should be around the IIF:
=SUM(IIF(Fields!Total_Amount__Excl_VAT_.Value = 0
OR Fields!Total_Amount__Excl_VAT_.Value = "", 0, Fields!Total_Amount__Excl_VAT_.Value))
The same issue for
=IIF(Fields!Total_Amount__Excl_VAT_.Value = 0
OR Fields!Total_Amount__Excl_VAT_.Value = "",0,Sum(Fields!Total_Amount__Excl_VAT_.Value))
Should Be:
=SUM(IIF(Fields!Total_Amount__Excl_VAT_.Value = 0
OR Fields!Total_Amount__Excl_VAT_.Value = "", 0, Fields!Total_Amount__Excl_VAT_.Value))
The growth formula looks correct - are you getting a different result than expected?
I have a panel data set for multiple waves (13) for roughly 10,000 individuals each year, with people entering and exiting at various time points. I am interested in what happens as people become diagnosed with a disease over time. Therefore I need to recode the time variable so that it becomes t=0 the first wave when diagnosed, then t=1 is the next year and so on, so that all of my individuals are comparable (and I guess -1 for t-1 etc). However I am unsure about how to go about this in stata. Would anyone be able to advise? Many thanks
The case of one diagnosis per person
clear all
set more off
*----- example data -----
set obs 100
set seed 2357
generate id = _n
generate year = floor(10 * runiform()) + 1990
expand 5
bysort id: replace year = year + _n
bysort id (year): generate diag = cond(_n == 3, 1, 0)
list in 1/20, sepby(id)
*----- what you seek -----
bysort id (diag): gen time = year - year[_N]
sort id year
list in 1/20
I assume the same data structure as #RichardHerron and use his example. diag is an indicator variable that takes on the value of 1 at the time of diagnosis and 0 otherwise (only one diagnosis per person is considered).
The sorting done by bysort is critical. The observation holding the time of diagnosis is pushed to the end of the database (by id groups) and then all that's left to do is compare (subtract) all years with that reference year. See help _variables for details on system variables like _N.
The case of multiple diagnoses per person
If several diagnoses are made per person, but we care only for the first occurence (according to year), we could do:
gsort id diag -year
by id: gen time = year - year[_N]
Simple but not optimal solution
Suppose diagnosis is 1 when diagnosed (at most once per person) and 0 otherwise.
Then the time at diagnosis is at its simplest
egen time_diagnosis = total(diagnosis * year), by(id)
but you need to ignore any zeros. To spell that out,
replace time_diagnosis = . if time_diagnosis == 0
Better alternative
A more complicated but preferable alternative can handle multiple diagnoses if they occur:
egen time_diagnosis = min(year / diagnosis), by(id)
as year / diagnosis is year when diagnosis is 1 and missing otherwise. This yields missing values if there is no diagnosis, which is as it should be.
Then you subtract that to get a new time variable.
gen time2 = time - time_diagnosis
In short, I think you can get this done in two statements, handling panel structure too.
Update
#Richard Herron asks why use egen with by(), and not just
gen time_diagnosis = time * diagnosis
A limitation of that is that the "correct" value is contained only in those observations for which diagnosis is 1; that value still has to be "spread" to other values for the same id. But that is precisely what egen does here. In the simplest situation, with one diagnosis the total of time * diagnosis is just time * 1 or time, as any zeros make no difference to the sum.
It is usually helpful to provide test data, but here they are easy enough to generate. The trick is to find the first year for each individual (my fyear), which I'll do with min() from egen. Then I'll subtract this first year fyear from the actual year to find the year relative to diagnosis ryear.
/* generate panel */
clear
set obs 10000
generate id = _n
generate year = floor(10 * runiform()) + 1990
expand 10
bysort id: replace year = year + _n
sort id year
list in 1/20
/* generate relative year */
bysort id: egen fyear = min(year)
generate ryear = year - fyear
list in 1/20
If the first year in the panel is not diagnosis, then just construct fyear based on diagnosis criteria.
Edit: Thinking more on this, maybe it's the last part that you're having a hard time with (i.e., identifying the diagnosis year to subtract from the calendar year). Here's what I would do.
bysort id (year): generate diagnosis = cond(_n == 5, 1, 0)
preserve
tempfile diagnosis
keep if (diagnosis == 1)
rename year dyear
keep id dyear
save `diagnosis'
restore
merge m:1 id using `diagnosis', nogenerate
generate ryear2 = year - dyear