I'm trying to write a DAX function to find the maximum value in one column based on a condition in another, but have this condition change dynamically based on the row value.
With this code:
CALCULATE(MAX(RankOfArea[count]),filter(RankOfArea,RankOfArea[Line]="Pic"))
I get this table:
count | Line | Max
7220 | Pic | 7220
283 | Dis | 7220
3557 | Pic | 7220
317 | Met | 7220
500 | Met | 7220
And I'd like this result:
count | Line | Max
7220 | Pic | 7220
283 | Dis | 283
3557 | Pic | 7220
317 | Met | 500
500 | Met | 500
Of course I have to remove the ="Pic", but not sure what to replace it with? Many thanks
There are a couple ways to do this for a calculated column.
One way is to remove all row context and explicitly define your condition:
Max = CALCULATE(MAX(RankOfArea[Count]),
ALL(RankOfArea),
RankOfArea[Line] = EARLIER(RankOfArea[Line]))
(The EARLIER function refers to the earlier row context.)
Another way is to remove just the [Count] row context:
Max = CALCULATE(MAX(RankOfArea[Count]), ALL(RankOfArea[Count])
In this case, since there are only two columns, this is equivalent to removing all row context except for the [Line] value:
Max = CALCULATE(MAX(RankOfArea[Count]), ALLEXCEPT(RankOfArea, RankOfArea[Line]))
I recommend this latter approach in case your table acquires more columns.
Related
will be very grateful if you could share your experience and advice on the following problem in Power BI:
3 Tables given in the data model:
calendar dimension table
fact table on sessions
fact table on spending
| CW | Total cost | Sessions | Expected Column 1 | Expected Column 2 |
+----+-------------+-----------+-------------------+-------------------+
| 1 | 1200 | 50 | | |
| 2 | 1500 | 60 | 1200 | 50 |
| 3 | 1700 | 48 | 1500 | 60 |
| 4 | 1150 | 36 | 1700 | 48 |
| 5 | 900 | 29 | 1150 | 36 |
+----+-------------+-----------+-------------------+-------------------+
CW column indicates the calendar week and it is from calendar table. Sessions and Total cost are from sessions and spending tables respectively. Data is aggregated and visualized on calendar week level.
Problem: I need to create measures to derive Expected column 1 and expected column 2 based on total cost and sessions columns. Basically getting next values for each row similar to lead window function.
I have checked power BI community and there are several ideas (for example here https://community.powerbi.com/t5/Desktop/DAX-Query-to-Find-Next-Value/td-p/833896).
But these solution assume all columns are from the same table, however in the above described case
all 3 columns are from different tables.
Will the be possible to get expected columns 1 and 2 and how? Many thanks in advance!
As a continuation to this question:
I would like to have a measure that will sum the Value only for the max version of each house.
So following this example table (data table):
|---------------------|------------------|------------------|------------------|
| House_Id | Version_Id | Color_Id | Value |
|---------------------|------------------|------------------|------------------|
| 1 | 1 | 1 (Green) | 1000 |
|---------------------|------------------|------------------|------------------|
| 1 | 2 | 2 (Red) | 2000 |
|---------------------|------------------|------------------|------------------|
| 2 | 1 | 1 (Green) | 3000 |
|---------------------|------------------|------------------|------------------|
| 3 | 1 | 1 (Green) | 5000 |
|---------------------|------------------|------------------|------------------|
The result of this measure should be: 10.000 because the house_id 1 version 1 is ignored as there's another version higher.
If there were more versions, the measure should only take into account the highest of each house.
By House_id the result should be (Again, House_Id 1 / Version 1 is ignored):
|---------------------|------------------|
| House_Id | Value |
|---------------------|------------------|
| 1 | 2000 |
|---------------------|------------------|
| 1 | 3000 |
|---------------------|------------------|
| 2 | 5000 |
|---------------------|------------------|
| Total | 10000 |
|---------------------|------------------|
I also want this measure to be capable of showing the result when using another variable of the Data table (or related tables), but maintaining the logic of Max version per House.
As shown on the example table before I have the Color_Id column.
This Color_Id in the main table is connected to a Color table that contains the color name.
If I add a visual table with ColorName (from the ColorTable) and the measure, the result should be as follows:
|---------------------|------------------|
| ColorName | Value |
|---------------------|------------------|
| Green | 8000 |
|---------------------|------------------|
| Red | 2000 |
|---------------------|------------------|
| Total | 10000 |
|---------------------|------------------|
With the solution provided in the other question, the result is correct on the Total row, but is wrong because it does not show the correct value for each color.
The following table is the result of applying the measure in the question provided (wrong result):
|---------------------|------------------|
| ColorName | Value |
|---------------------|------------------|
| Green | 9000 | <- Error Here
|---------------------|------------------|
| Red | 2000 |
|---------------------|------------------|
| Total | 10000 |
|---------------------|------------------|
This result is wrong per ColorName as 9000 + 2000 is 11000 and not 10000.
The measure should ignore the rows with an old version per house.
In the example before this is the row for House_Id 1 and Color_Id Green because the version is old (there's a newer version for that House_Id).
So:
How can I change the measure so it shows the correct value per Color_Id as well as per House_Id and as a total?
In the data table I have more columns. What If I want to filter by another column from (or related to) the Data table such as Location_Id? It is posible to define the measure in such a way that could work for any given number splits for columns in the main Data table?
Help is greatly appreciated here
EDIT:
The solution provided by Alexis Olson works when the Data table is imported. When the Data table is connected with DirectQuery mode, it won't work.
In RADO's answer, the issue is with the first variable.
Sum of Latest Values =
VAR Latest_Versions =
SUMMARIZE ( Data, Data[House_id], "Latest_Version", MAX ( Data[Version_Id] ) )
VAR Latest_Values =
TREATAS ( Latest_Versions, Data[House_id], Data[Version_Id] )
VAR Result =
CALCULATE ( SUM ( Data[Value] ), Latest_Values )
RETURN Result
The Data table as the first argument in the SUMMARIZE is not the whole table but evaluated within the local filter context. This means that when you are in the Green row in your table, it doesn't see Version_ID = 2 and thus includes the first version in the Green row but not in the total (which sees all of the rows).
The fix is quite simple -- remove the local filter context from that first table argument. One way to do this is to use ALL ( Data ) instead of just Data. This is likely not the most memory-efficient though and you may prefer to write something like this instead:
Sum of Latest Values =
VAR Latest_Versions =
ADDCOLUMNS (
VALUES ( Data[House_Id] ),
"Latest_Version",
CALCULATE ( MAX ( Data[Version_Id] ), ALLEXCEPT ( Data, Data[House_Id] ) )
)
VAR Latest_Values =
TREATAS ( Latest_Versions, Data[House_id], Data[Version_Id] )
VAR Result =
CALCULATE ( SUM ( Data[Value] ), Latest_Values )
RETURN
Result
I'm struggling having this measure to work.
I would like to have a measure that will sum the Value only for the max version of each house.
So following this example table:
|---------------------|------------------|------------------|
| House_Id | Version_Id | Value |
|---------------------|------------------|------------------|
| 1 | 1 | 1000 |
|---------------------|------------------|------------------|
| 1 | 2 | 2000 |
|---------------------|------------------|------------------|
| 2 | 1 | 3000 |
|---------------------|------------------|------------------|
| 3 | 1 | 5000 |
|---------------------|------------------|------------------|
The result of this measure should be: 10.000 because the house_id 1 version 1 is ignored as there's another version higher.
By House_id the result should be:
|---------------------|------------------|
| House_Id | Value |
|---------------------|------------------|
| 1 | 2000 |
|---------------------|------------------|
| 1 | 3000 |
|---------------------|------------------|
| 2 | 5000 |
|---------------------|------------------|
Can anyone help me?
EDIT:
Given the correct answer #RADO gave, now I want to further enhance this measure:
Now, my main Data table in reality has more columns.
What if I want to add this measure to a table visual that splits the measure by another column from (or related to) the Data table.
For example (simplified data table):
|---------------------|------------------|------------------|------------------|
| House_Id | Version_Id | Color_Id | Value |
|---------------------|------------------|------------------|------------------|
| 1 | 1 | 1 (Green) | 1000 |
|---------------------|------------------|------------------|------------------|
| 1 | 2 | 2 (Red) | 2000 |
|---------------------|------------------|------------------|------------------|
| 2 | 1 | 1 (Green) | 3000 |
|---------------------|------------------|------------------|------------------|
| 3 | 1 | 1 (Green) | 5000 |
|---------------------|------------------|------------------|------------------|
There's a Color_Id in the main table that is connected to a Color table.
Then I add a visual table with ColorName (from the ColorTable) and the measure (ColorId 1 is Green, 2 is Red).
With the given answer the result is wrong when filtered by ColorName. Although the Total row is indeed correct:
|---------------------|------------------|
| ColorName | Value |
|---------------------|------------------|
| Green | 9000 |
|---------------------|------------------|
| Red | 2000 |
|---------------------|------------------|
| Total | 10000 |
|---------------------|------------------|
This result is wrong per ColorName as 9000 + 2000 is 11000 and not 10000.
The measure should ignore the rows with an old version. In the example before this is the row for House_Id 1 and Color_Id Green because the version is old (there's a newer version for that House_Id).
So:
How can I address this situation?
What If I want to filter by another column from (or related to) the Data table such as Location_Id? It is posible to define the measure in such a way that could work for any given number splits for columns in the main Data table?
I use "Data" as a name of your table.
Sum of Latest Values =
VAR Latest_Versions =
SUMMARIZE ( Data, Data[House_id], "Latest_Version", MAX ( Data[Version_Id] ) )
VAR Latest_Values =
TREATAS ( Latest_Versions, Data[House_id], Data[Version_Id] )
VAR Result =
CALCULATE ( SUM ( Data[Value] ), Latest_Values )
RETURN Result
Measure output:
How it works:
We calculate a virtual table of house_ids and their max versions, and store it in a variable "Latest_Versions"
We use the table from the first step to filter data for the latest versions only, and establish proper data lineage
(https://www.sqlbi.com/articles/understanding-data-lineage-in-dax/)
We calculate the sum of latest values by filtering data for the latest values only.
You can learn more about this pattern here:
https://www.sqlbi.com/articles/propagate-filters-using-treatas-in-dax/
I'm building a sales dashboard in PowerBI.
I have a Sales table.
My source of data is declarative, so I have a few extreme values caused by human errors and mistypes, etc.
Let's say I want to build a histogram with:
On the X axis, the stock aging of any sales. Which is "how long the product has been in stock at the time of sale". It is given by the [Product_Age] column
On values, the number of sales.
What I want to do is exclude the top 1% extreme values from my calculations (average, etc.) and vizualisations.
I've created a measure :
SalesByAge_Adjusted =
VAR TEMP =
FILTER(
SALES;
VAR StockAgingMAX =
PERCENTILE.INC(
SALES[Sales_Age];
0,99
)
RETURN
SALES[Sales_Age] < StockAgingMAX
)
RETURN
COUNTROWS(TEMP)
It uses PERCENTILE.INC to get the 99th percentile of Sales_Age values in the current context and I try to use it as a filter.
However, it just won't work.
I can diplay the measure on its own. How many sales I have. But as soon as I drag and drop "Sales_Age" to summarize the values. It shows nothing.
I have created the following table as an example.
+-------+--------+
| Axis | Values |
+-------+--------+
| 1 | 1067 |
| 2 | 1725 |
| 4 | 298 |
| 8 | 402 |
| 16 | 1848 |
| 32 | 1395 |
| 64 | 1116 |
| 128 | 1027 |
| 256 | 1948 |
| 512 | 790 |
| 1024 | 2173 |
| 2048 | 2025 |
| 4096 | 104 |
| 8192 | 1243 |
| 16384 | 1676 |
| 32768 | 1285 |
| 65536 | 806 |
+-------+--------+
For filtering the values that are out the 99% percentile I've created the following measure. Basically it gets an overall percentile without filter context and compares to each Axis value.
Filter = IF(CALCULATE(PERCENTILE.INC('Table'[Axis],0.99),ALL('Table'))>=MAX('Table'[Axis]),1,0)
In the visual of the chart, you use the filter measure to exclude your outliers
In this case, it will filter the last value of table: 65,536
I am trying to accomplish something, but don't know how to do it.
I have a Dimension (Table called TEntry) that represents time entries for employees like so :
Id | EmployeeId | EntryDT | TimeInMinutes | PriceAgreementId
------ | ---------- | ---------- | ------------- | ----------------
1 | 1 | 2017-03-20 | 100 | 1
2 | 1 | 2017-03-31 | 50 | null
3 | 2 | 2017-03-21 | 100 | 1
4 | 2 | 2017-03-23 | 125 | 2
5 | 3 | 2017-03-15 | 90 | null
6 | 3 | 2017-03-25 | 60 | 1
Sometimes they work on "PriceAgreements", and sometimes they don't.
In my Dashboard, i have a Table that groups the table TEntry by EmployeeId and Sums the TimeInMinutes. I also have a Slicer for EntryDT :
EmployeeId | TimeInMinutes
-------------- | -------------
1 | 150
2 | 225
3 | 150
I need to create 2 new columns that represent :
The total TimeInMinutes an Employee has worked on all PriceAgreements
So for EmployeeId #1, the Total would be 100.
The total TimeInMinutes ALL Employees have worked, but only for the PriceAgreements the current Employee (current row) has worked on.
The Table would look like this (without the PriceAgreementIds in parenthesis) :
EmployeeId | TimeInMinutes | TimeInMinutes on PriceAgreements | TimeInMinutes on PriceAgreements ALL other EmployeeIds
-------------- | ------------- | -------------------------------- | ------------------------------------------------------
1 | 150 | 100 (PriceAgreementId=1) | 260 (PriceAgreementId=1)
2 | 225 | 225 (PriceAgreementId=1 and 2) | 385 (PriceAgreementId=1 and 2)
3 | 150 | 150 (PriceAgreementId=1) | 260 (PriceAgreementId=1)
Column "TimeInMinutes on PriceAgreements" is quite easy, but the other one, i cannot find a solution...
I have this DAX expression I started, but it is not complete:
CALCULATE(SUM(TEntry[TimeInMinutes]), NOT ISBLANK(TEntry[PriceAgreementId]), ALL(TEmployee))
TEmployee is a Dimension linked to the main TEntry Table.
Any help would be appreciated.
Thank you
I'm throwing this on as an answer because (a) it might get you (or someone else) going in the right direction and (b) if it's guaranteed that an Employee would only ever have time entries corresponding to 2 price agreements, this would work - which is unlikely the case for you, but might be the case for others trying to accomplish a similar thing.
Measure =
CALCULATE (
SUM ( TEntry[TimeInMinutes] ),
FILTER (
ALL ( TEntry ),
(
TEntry[PriceAgreementID] = MIN ( TEntry[PriceAgreementID] )
|| TEntry[PriceAgreementID] = MAX ( TEntry[PriceAgreementID] )
)
&& TEntry[PriceAgreementID] <> BLANK ()
)
)
This measure is saying: SUM the TimeInMinutes for all records in the TEntry table where the PriceAgreementID matches either the minimum OR maximum PriceAgreementID (in the context of the current row) AND the PriceAgreementID isn't blank.
The fatal flaw in this answer is in the MIN and MAX. For Employee ID 2, who has 2 PriceAgreementIDs (1 & 2) - the MIN will calculate the minutes for PriceAgreementID 1 and the MAX will calculate the minutes for PriceAgreementID 2. However, to expand to a case where there might be more than 2 PriceAgreements...I don't know how to do that.
It does work on the sample data in your question, though (since there is a max of 2 price agreements per employee):
Typically when I'm faced with a problem like this that isn't easy to solve, I think about my data model and make sure that it conforms to a star schema as closely as possible.
In your case, an employee can have multiple price agreements, and a price agreement can be associated with many employees. That, to me, suggests a many-to-many relationship. I'd strongly recommend reading more about many-to-many relationships and whether restructuring the underlying tables (e.g. to include a bridge table) would help get you closer to the answer you need.
A good starting point might be: https://www.sqlbi.com/articles/many-to-many-relationships-in-power-bi-and-excel-2016/