DAX if else for measure - if-statement

How to use if else for DAX in the measure. If row value =1 then take the var a calculated value else take the var b calculated value
x:=var a=[DATA1]
var b=[DATA2]
return(if([HOUR]=1),a,b)
I get error using above formula

It seems your problem is that you are not aggregating the columns while creating the measure. Measures only works aggregating data in a given context, generally if you want to perform calculations per row you should use a calculated column instead of a measure.
And the DAX expression for a calculated column should be:
MyColumn = IF([HOUR] = 1, [DATA1], [DATA2])
Otherwise if you want to use a measure you have to explicitely aggregate the column values in the given context, i.e:
MyMeasure =
VAR a =
FIRSTNONBLANK ( ExampleTable[Data1], 0 )
VAR b =
FIRSTNONBLANK ( ExampleTable[Data2], 0 )
RETURN
IF ( SUM ( ExampleTable[Hour] ) = 1, a, b )
Or simply:
MyMeasure =
IF (
SUM ( [Hour] ) = 1,
FIRSTNONBLANK ( ExampleTable[Data1], 0 ),
FIRSTNONBLANK ( ExampleTable[Data2], 0 )
)
Let me know if this helps.

Related

DAX Measure to count Rows if relation may not exist

I am looking for a DAX measure to solve the following problem:
Count the number of rows in the dimension table where the Fact table either has no rows or the score is 0.
Table A (Dimension Table)
ID
name
1
a
2
b
3
c
Table B (Fact Table)
ID
score
1
0
1
1
1
2
2
5
Expected Result
In this example, I would expect 2, as ID=1 has one row with score=0 and ID=3 as no corresponding row in the Fact Table.
I came up with this measure which gives me the number of rows that have no corresponding row in the fact table, but I am not able to integrate the first condition:
CALCULATE(COUNTROWS('Dimension'), FILTER ('Dimension', ISBLANK ( CALCULATE ( COUNT ('Fact'[id]) ) )))
Probably much more straightforward methods, but try this measure for now:
MyMeasure =
VAR MyTable =
ADDCOLUMNS(
Table_A,
"Not in Table_B", NOT (
Table_A[ID]
IN DISTINCT( Table_B[ID] )
),
"Zero Score in Table_B",
CALCULATE(
COUNTROWS( Table_B ),
Table_B[score] = 0
) > 0
)
RETURN
SUMX(
MyTable,
[Not in Table_B] + [Zero Score in Table_B]
)
You can also try this
CountID =
VAR ScoreZero =
COUNTROWS ( FILTER ( TableB, [score] = 0 ) )
VAR NonExistentIDs =
COUNTROWS ( EXCEPT ( DISTINCT ( TableA[ID] ), DISTINCT ( TableB[ID] ) ) )
RETURN
ScoreZero + NonExistentIDs
This also works, not sure it's a good idea to nest CALCULATE:
CALCULATE(COUNTROWS('Table_A'), FILTER ('Table_A', ISBLANK ( CALCULATE ( COUNT ('Table_B '[id]) ) ) || CALCULATE(COUNTAX(Filter('Table_B ','Table_B '[score]=0),'Table_B '[id])>=1)))

Sum of occurrence - measure - power bi

I have the dataset:
I've checked the occurrence of each id and if it was the first occurrence per the id, I assigned the value 0, otherwise 1.
If I create a pivot table and sum of occurrence, I will get :
So, my final desired outcome is:
I can achieve it with the countrows and sum of countrows as a calculated column but it is static and as soon as I start using the date filter, the formula doesn't work. Is there a way to achieve it with a measure?
Create these below 2 Measures-
Note: Considered ordering using column ticket_id
occ =
VAR current_ticket_id = MIN(your_table_name[ticket_id])
VAR current_id = MIN(your_table_name[id])
VAR count_id =
CALCULATE(
COUNTROWS(your_table_name),
FILTER(
ALL(your_table_name),
your_table_name[id] = current_id
&& your_table_name[ticket_id] <= current_ticket_id
)
)
RETURN
IF(
count_id = 1,
0,
1
)
sum of occ =
CALCULATE(
COUNTROWS(your_table_name),
FILTER(
ALLEXCEPT(your_table_name,your_table_name[id]),
[occ] = 1
)
) + 0
Here is the output-

DAX Measure: group by min & if condition

I have several dataset tables in PowerBI report. The column country comes from TABLE1 while the column name comes from TABLE2.
So firstly I want to calculate min_number based on country and name, and then if min_number = number, the min will be 1; otherwise, 0. So the result table looks like:
This is my code for min
min =
VAR min_number =
CALCULATE (
MIN ( [number] ),
ALLEXCEPT ( TABLE1, TABLE1[country] ), ALLEXCEPT (TABLE2, TABLE2[name])
)
RETURN
IF ( [number] = Min_number,1, 0 )
I got an error: the MIN function only accepts a column reference as the argument number 1. Does it mean if it has to be one condition? how to fix it? Thank you
I would solve it by just making two separate measures, since we want to see the both results in the final table anyway.
First the min_number calculation:
min_number = CALCULATE(MIN('Table'[number]);ALLEXCEPT('Table';'Table'[country];'Table'[name]))
And the min measure:
min = IF(MAX('Table'[number]) = [min_number];1;0)
As we are using a measure, we can use MAX, so it will know what number to reference in the IF. It will still use the MAX number per row, so results are correct.
You can try with this below measure-
min =
VAR current_row_country = MIN(table1[country])
VAR current_row_name = MIN(table1[name])
VAR current_row_number = MIN(table1[number])
VAR min_number =
CALCULATE (
MIN (table1[number]),
FILTER(
ALL(table1),
table1[country] = current_row_country
&& table1[name] = current_row_name
)
)
RETURN IF (min_number = current_row_number,1, 0 )

Sum of a measure per date range

I have the following Table Visualization.
I'd like the table to look like the following. Column C should be averaging the range of Column B.
For example:
C2 = AVERAGE(B2:B2)
C3 = AVERAGE(B2:B3)
C4 = AVERAGE(B2:B4)
and so on.
The Year-Month column is from my MonthTable. The schema is as follows,
And the Sum measure DAX is as follows,
For the CumulativeSum measure, I have tried the following.
CumulativeSum =
CALCULATE(
[Sum],FILTER(AppendedTables,AppendedTables[Year-Month] <= MAX(AppendedTables[Year-Month]))
)
I'm guessing the issue is my CALCULATE([SUM]) area. I wanted to wrap [SUM] in a SUM() method, but that doesn't work. It gives the error "The SUM function only accepts a column reference as the argument number 1".
Please enlighten me.
I've been able to produce your desired results by creating a calculated column using the following code:
CumSum =
VAR CntRow =
COUNTROWS ( FILTER ( Sheet1, [Year-Month] >= EARLIER ( [Year-Month] ) ) )
VAR CumSum =
CALCULATE (
SUMX ( Sheet1, Sheet1[Sum] ),
FILTER ( Sheet1, Sheet1[Year-Month] >= EARLIER ( Sheet1[Year-Month] ) )
)
RETURN
DIVIDE ( CumSum, CntRow )
Hope this helps!!

Intersection of Customer product purchase (powerBI)

I need help with producing a count of the intersections between customers and which items they have purchased. For example, if there are 5 products, a customer can purchase any single product or any combination of the 5. Customers can also re-purchase a product at any date - this is where my problem arises as an end user wants to be able to see the intersections for any selected date range.
I have managed to come up with a solution which includes the use of parameters but this is not ideal as the end user does not have access to change any parameters of the report.
I'm open to any solution that does not involve parameters, ideally a slicer with dates would be the best solution
The fields I have on the table are customer_ID, date_ID, and product
Example Data
customer_id date_id product
1 9/11/2018 A
1 10/11/2018 A
1 10/11/2018 B
1 11/11/2018 C
1 11/11/2018 A
2 9/11/2018 C
2 10/11/2018 D
2 11/11/2018 E
2 11/11/2018 A
3 10/11/2018 A
3 10/11/2018 B
3 11/11/2018 A
3 11/11/2018 B
3 11/11/2018 B
4 10/11/2018 A
4 11/11/2018 A
5 9/11/2018 A
5 10/11/2018 B
5 10/11/2018 E
5 10/11/2018 D
5 11/11/2018 C
5 11/11/2018 A
6 9/11/2018 A
6 10/11/2018 A
6 11/11/2018 A
Possible output with different slicer selections
Any help at all would be greatly appreciated
This is pretty tricky since I can't think of a way to use the values of a dynamically calculated table as a field in a visual. (You can create calculated tables, but those aren't responsive to slicers. You can also create dynamically calculated tables inside of a measure, but measures don't return tables, just single values.)
The only way I can think of to do this requires creating a table for every possible product combination. However, if you have N products, then this table has 2N rows and that blows up fast.
Here's a calculated table that will output all the combinations:
Table2 =
VAR N = DISTINCTCOUNT(Table1[product])
VAR Products = SUMMARIZE(Table1,
Table1[product],
"Rank",
RANKX(ALL(Table1),
Table1[product],
MAX(Table1[product]),
ASC,
Dense
)
)
VAR Bits = SELECTCOLUMNS(GENERATESERIES(1, N), "Bit", [Value])
VAR BinaryString =
ADDCOLUMNS(
GENERATESERIES(1, 2^N),
"Binary",
CONCATENATEX(
Bits,
MOD( TRUNC( [Value] / POWER(2, [Bit]-1) ), 2)
,,[Bit]
,DESC
)
)
RETURN
ADDCOLUMNS(
BinaryString,
"Combination",
CONCATENATEX(Products, IF(MID([Binary],[Rank],1) = "1", [product], ""), "")
)
Then add a calculated column to get the column delimited version:
Delimited =
VAR Length = LEN(Table2[Combination])
RETURN
CONCATENATEX(
GENERATESERIES(1,Length),
MID(Table2[Combination], [Value], 1),
","
)
If you put Delimited the Rows section on a matrix visual and the following measure in the Values section:
customers =
VAR Summary = SUMMARIZE(Table1,
Table1[customer_id],
"ProductList",
CONCATENATEX(VALUES(Table1[product]), Table1[product], ","))
RETURN SUMX(Summary, IF([ProductList] = MAX(Table2[Delimited]), 1, 0))
And filter out any 0 customer values, you should get something like this:
So yeah... not a great solution, especially when N gets big, but maybe better than nothing?
Edit:
In order to work for longer product names, let's use a delimiter in the Combination concatenation:
CONCATENATEX(Products, IF(MID([Binary],[Rank],1) = "1", [product], ""), ",")
(Note the "" to "," change at the end.)
And then rewrite the Delimited calculated column to remove excess commas.
Delimited =
VAR RemoveMultipleCommas =
SUBSTITUTE(
SUBSTITUTE(
SUBSTITUTE(
SUBSTITUTE(Table2[Combination], ",,", ","),
",,", ","),
",,", ","),
",,", ",")
VAR LeftComma = (LEFT(Table2[Combination]) = ",")
VAR RightComma = (RIGHT(Table2[Combination]) = ",")
RETURN
IF(RemoveMultipleCommas <> ",",
MID(RemoveMultipleCommas,
1 + LeftComma,
LEN(RemoveMultipleCommas) - RightComma - LeftComma
), "")
Finally, let's modify the customers measure a bit so it can subtotal.
customers =
VAR Summary = SUMMARIZE(Table1,
Table1[customer_id],
"ProductList",
CONCATENATEX(VALUES(Table1[product]), Table1[product], ","))
VAR CustomerCount = SUMX(Summary, IF([ProductList] = MAX(Table2[Delimited]), 1, 0))
VAR Total = IF(ISFILTERED(Table2[Delimited]), CustomerCount, COUNTROWS(Summary))
RETURN IF(Total = 0, BLANK(), Total)
The Total variable gives the total customer count for the total. Note that I've also set zeros to return as blank so that you don't need to filter out zeros (it will automatically hide those rows).
You can also try this measure to calculate the result.
[Count Of Customers] :=
VAR var_products_selection_count = DISTINCTCOUNT ( Sales[product] )
VAR var_customers = VALUES ( Sales[customer_id] )
VAR var_customers_products_count =
ADDCOLUMNS(
var_customers,
"products_count",
VAR var_products_count =
COUNTROWS (
FILTER (
CALCULATETABLE ( VALUES ( Sales[product] ) ),
CONTAINS (
Sales,
Sales[product],
Sales[product]
)
)
)
RETURN var_products_count
)
RETURN
COUNTROWS (
FILTER (
var_customers_products_count,
[products_count] = var_products_selection_count
)
)
I think I've found a better solution/workaround that doesn't require precomputing all possible combinations. The key is to use a rank/index as a base column and then built off of that.
Since the customer_id is already nicely indexed starting from 1 with no gaps, in this case, I will use that, but if it weren't, then you'd want to create an index column to use instead. Note that there cannot be more distinct product combinations within a given filter context than there are customers since each customer only has a single combination.
For each index/rank we want to find the product combination that is associated with it and the number of customers for that combination.
ProductCombo =
VAR PerCustomer =
SUMMARIZE (
ALLSELECTED ( Table1 ),
Table1[customer_id],
"ProductList",
CONCATENATEX ( VALUES ( Table1[product] ), Table1[product], "," )
)
VAR ProductSummary =
SUMMARIZE (
PerCustomer,
[ProductList],
"Customers",
DISTINCTCOUNT ( Table1[customer_id] )
)
VAR Ranked =
ADDCOLUMNS (
ProductSummary,
"Rank",
RANKX (
ProductSummary,
[Customers] + (1 - 1 / RANKX ( ProductSummary, [ProductList] ) )
)
)
VAR CurrID =
SELECTEDVALUE ( Table1[customer_id] )
RETURN
MAXX ( FILTER ( Ranked, [Rank] = CurrID ), [ProductList] )
What this does is first create a summary table that computes the product list for each customer.
Then you take that table and summarize over the distinct product lists and counting the number of customers that have each particular combination.
Then I add a ranking column to the previous table ordering first by the number of customers and tiebreaking using a dictionary order of the product list.
Finally, I extract the product list from this table where the rank matches the index/rank of the current row.
You could do a nearly identical measure for the customer count, but here's the measure I used that's a bit simpler and handles 0 values and the total:
Customers =
VAR PerCustomer =
SUMMARIZE (
ALLSELECTED ( Table1 ),
Table1[customer_id],
"ProductList",
CONCATENATEX ( VALUES ( Table1[product] ), Table1[product], "," )
)
VAR ProductCombo = [ProductCombo]
VAR CustomerCount =
SUMX ( PerCustomer, IF ( [ProductList] = ProductCombo, 1, 0 ) )
RETURN
IF (
ISFILTERED ( Table1[customer_id] ),
IF ( CustomerCount = 0, BLANK (), CustomerCount ),
DISTINCTCOUNT ( Table1[customer_id] )
)
The result looks like this