I have a dataset where I am trying to calculate the user response time to dealer note using the note date of every action.
Here is my sample data look like, I've calculated this in hive query using lag, lead, and min window functions, but my user wants to see this in Power BI.
This is what I tried so far.
I've created a "user note date" measure to get the first response of the User response
user note date = CALCULATE(MIN(Query1[Note Date]),ALLEXCEPT(Query1,Query1[incident],Query1[Action Type]),
LEFT(Query1[lastuser],1) in {"U"} )
Dealer Note Date =
CALCULATE(
MIN(Query1[pdate]),
FILTER(ALLEXCEPT(Query1,Query1[incident],Query1[action_type]),
Query1[action_type] in {
"DLR_CUST_Update"
))
I am getting this error from Dealer Note Date Measure, I am not understanding what's wrong with the above calculation.
error: A single value for column 'Action Type' in table 'Query1' cannot be determined. This can happen when a measure formula refers to a column that contains many values without specifying an aggregation such as min
Here is my sample data
Your column in calculation for [Dealer Note Date] is query1[action_type] or Query1[Action Type]??
You cant access column Query1[action_type] in [Dealer Note Date], because you are excluding it in ALLEXCEPT
Dealer Note Date =
CALCULATE(
MIN(Query1[pdate]),
FILTER(ALLEXCEPT(Query1,Query1[incident],**Query1[action_type]**),
Query1[action_type] in {
"DLR_CUST_Update"
))
Related
Below is the sample dataset
The data has two slicers ( date and category ) shown below
I am writing a DAX Statement to multiply the sum(values) * 10 only if the date range is in the current year 2023.
The StartYear gives the start of the current year, firstD gives the lowest date from the date slicer.
Formula =
var new = sum(Test[Value]) * 10
var startyear = DATE(YEAR(TODAY()),1,1)
var firstD = CALCULATE( MIN( Test[Date]), ALLSELECTED(Test[Date]) )
return if( ISFILTERED(Test[Categories]) && firstD >= startyear, new, 0 )
Now when I filter dates to 2023, the total value should be 2300 but it shows as 0
However the DAX works when I select A or B
If we remove the ISFILTERED function then, it gives wrong value, the expected value is 0 because the start date is in 2022, but it shows 650
let me know if that is the right syntax
It looks like you are not using a separate calendar table to handle this, which you need!
In your very last example you have set your slicer to some time late 2022, but the minimum value of 'Test'[Date] for your selected category is in year 2023. Hint: set the slicer to e.g. 2022-12-14, this will include a 2022-date for Category A in your data.
Your measure behaves exactly how it is supposed to, in other words!
To fix this, you need to do the following:
Create a calendar table in your model, this should contain contiguous dates, which is necessary for the filtering method you want
Establish a relationship between the calendar table and existing Test table.
Use the date column from your new calendar table in your slicer and as date reference in your measure
Exactly how to create a calendar table is thoroughly documented on Google, I recommend you search and find an article or video you understand for implementing this.
Lastly: Your use of ISFILTERED in this measure seems strange, since you mention nowhere the requirement of only showing a number if the column you are testing filtering on is filtered, if that makes sense.. :-) The way you describe your calculation, you only need to check whether the selected date range starts in current year.
When using endofmonth dax statement with my fact table it works:
EOM =
CALCULATE(
SUM('Table'[sales]),
ENDOFMONTH('Table'[date])
)
However when I use it with my date table it returns blanks does anyone know why?
dax command using my date table:
EOM_DTBLE =
CALCULATE(
SUM('Table'[sales]),
ENDOFMONTH('DATE'[Date])
)
You need to check what end of month returns first:
If we test it with a simple code:
Test = CALCULATE(ENDOFMONTH('Date'[Date]))
So basically, It returns the last date of each month. If you have no data in the end of the month specified, It returns empty.
If you have data (I have 679 on 31/01/2022) then, Code returns:
I think that the following formula summarize pretty well what I want to achieve:
date diff =
ABS (
DATEDIFF (
data_table[login_date],
SELECTEDVALUE ( 'Date'[Date] ),
DAY
)
)
but it returns me the following error
A single value for column 'login_date' in table 'data_table' cannot be determined. This can happen when a measure formula refers to a column that contains many values without specifying an aggregation such as min, max, count, or sum to get a single result.
In other word I want have a column in my data_table with date diff calculated dynamically based on min slicer date selection.
My final goal is to filter out dynamically users that has not been logged for the last 3 months based on the slicer date range.
Here is the dataset
user_id, login_date
111, 01/02/2021
222, 02/15/2021
444, 03/15/2021
555, 01/15/2021
I want user ID to be filtered out when the number of days between the max date of the date range and the day of the last connection is higher than 90 days.
Edit
I'm adding a different formula I'm working on but having few issues to make it work
active users = CALCULATE( DISTINCTCOUNT(data_table[id]), ( FILTER ( VALUES ( data_table[id] ), DATEDIFF(IF( ISBLANK(SELECTEDVALUE(data_table[login_date])),[Min range date],SELECTEDVALUE(data_table[login_date])),[Max range date],DAY) < 90 ) ))
You can't have a dynamically calculated column, but you can use a measure to do this. The issue that you have with your calculation is that it needed to do a row by row evaluation, rather than over a column. That is why you get an 'A single value for column 'login_date' in table 'data_table' cannot be determined' error.
In this case you can use SUMX, as this is a iterator and it will do row by row. So using the following measures:
Selected Date = SELECTEDVALUE('Calendar'[Date])
This reads the date selected. You can wrap it with a MIN/MAX if needed depending on how your slicer is set up. You can change the slicer to single select, it you just want one value.
Date Calc = SUMX('Table', DATEDIFF('Table'[Login_date], [Selected Date], DAY))
This uses SUMX to calculate on a row by row level.
You can then use this measure to drive your visual. In this example I've filtered out those over 30 days since the login
If you choose a new date, it will recalculate straight away. This should set you on the right path for your use case.
I currently have a raw data table called Score Table which has three columns: (1) an entity ID, (2) a score, and (3) a date.
I also have a Measure for a single dynamic date (I can't use date slicers for this for reasons that I won't bore you with).
My goal is to have a measure tell me what the last score is before the date indicated by the Measure.
I for some reason am unable to pull this off in DAX. Whenever I try to use Calculate( functions in DAX, I end up only pulling the final date in the 'Score Table' [Date] column (not before the Measure date and not different by ID.
Any help on this would be greatly appreciated.
I still miss some information to give you a specific answer, but something like this should work.
PreviousScore =
CALCULATE(
LASTNONBLANK('Table'[Score])
,FILTER(
ALL('Calendar')
,'Calendar'[Date] < [YourDateMeasure]
)
)
Note that I'm assuming you have a Calendar table to manage the dates (you usually want one of those in your model)
I need to create a calculated column that is based on another column but depends on the date filter the report is run for.
If the item is own for more than a year it is 'Comparable' if less than a year it is 'Non Comparable'.
I have Item, DateOfPurchase in T1 and Date in T2 (Period table)
I have come up with DAX using today() but it only works if we report on today's date.
This didn't work (no idea why)
=if( dateadd( 'Item'[PurchaseDate],1,year)<today(),"Comp","Non-Comp")
This worked but only for current period
=DATEDIFF('Item'[PurchaseDate],today(),MONTH)
= if('Item'[DateDiff]>12,"Comp","NonComp")
However, I can not use that column when running report for a different period, because attribute is not valid for prior periods.
Since calculated columns are computed only once, when the table is processed/refreshed, you cannot use a calculated column for your scenario.
Instead, consider using a disconnected parameter table. In your case, this would be a table with 1 column and just 2 rows: "Comp" and "NonComp". You can create this as a calculated table like so:
ParameterTable = DATETABLE("Value", STRING, {{"Comp", "NonComp"}})
Based on what the user selects on this table - which you can find using SELECTEDVALUE(ParameterTable[Value]) - you apply the relevant logic in a measure instead:
BaseMeasure =
// Whatever you are trying to calculate
SUM(Item[Amount])
Measure =
// This measure will respect the user selection (Comp / NonComp) and the current period:
VAR compValue = SELECTEDVALUE(ParameterTable[Value])
VAR today = MAX('Date'[Period])
RETURN
SWITCH(
compValue,
"Comp", CALCULATE( [BaseMeasure] , DATEDIFF('Item'[PurchaseDate], today, MONTH) > 12),
"NonComp", CALCULATE( [BaseMeasure] , DATEDIFF('Item'[PurchaseDate], today, MONTH) < 12),
[BaseMeasure] // Fallback, in case user didn't select Comp/NonComp
)
If you have multiple base measures in your report, you will need to implement this pattern for each of your base measures.