This might be very basic but I am new to PowerBI.
How do I get average of values for unique ID into another table.
For eg. My Table 1 has multiple ID values. I have created another table for unique ID which I am planning to used to join other table.
I want a calculated column in table 2 which will give me average value of respective ID from table 1.
How do I get the calculated column like shown below
In stead of creating a new table with the averages per ID and then joining on that, you could also do it directly with a calculated column using the following DAX expression:
Average by ID = CALCULATE(AVERAGE('Table 1'[Values]),ALLEXCEPT('Table 1','Table 1'[ID]))
Not exactly what you asked for, but maybe it's useful anyway.
How's it going?
The quickest way I can think of doing this would be to use
SUMMARIZECOLUMNS
You can accomplish this by creating another table based on your initial fact table like so:
Table 2 =
SUMMARIZECOLUMNS ( 'Table 1'[ID], "Avg", AVERAGE ( 'Table 1'[Values] ) )
Once this table has been created, you can create a relationship.
This will work in either SSAS or in PowerBI directly.
Hope this helps!! Have a good one!!
Related
I'm a newbie in DAX and I'm trying to create a visual in Power BI that shows the top 10 customers by sales.
I tried to create a calculated column in the 'Food sales' table, but I couldn't figure out how to create the rank by client ID.
I ended up creating a summary table in the model:
Consolidation Ventes =
SUMMARIZE('Food Sales',
'Food Sales'[ID Client],
"Ventes",SUMX('Food Sales', 'Food Sales'[Quantité]*'Food Sales'[Prix de vente])
)
and adding the rank calculated column like that:
Rank = RANKX('Consolidation Ventes', 'Consolidation Ventes'[Ventes],,DESC,Dense)
I obtained what I was looking for:
But I'm pretty sure there's a better way to do it, without creating an extra table in the model.
I tried creating a measure instead, but it always returned "1" and I couldn't understand why...
Is there a better way to achieve the same result?
Is there a way to create a measure instead of a calculated column, to create dynamic ranks in order to slice the with more than one column (like for example, customer name and product type)?
I hope this helps:
#Orders := COUNTROWS(Sales)
SalesAmount := SUMX(Sales,Sales[Quantity]*Sales[Price])
TopN :=
COUNTROWS(INTERSECT(
CALCULATETABLE(
TOPN(5,VALUES(Customers[Name]),[SalesAmount],DESC),
ALL(Customers)
),
CALCULATETABLE(VALUES(Customers[Name]))
))
You add the TopN measure to "Filters on this visual" and define the filter condition to "TopN is 1".
I have a table Like this,
Table1
I want to create a column called as Row Number using DAX and not Query Editor (M).
So the Expected output is,
This can be done in M - Power Query Side.
But, I am looking for a solution using DAX- Calculated Column.
Additional source data
The RANKX function should work fine for this purpose.
Row Number = RANKX ( Table1, Table1[ColA] )
Recommended reading:
https://radacad.com/how-to-use-rankx-in-dax-part-1-of-3-calculated-columns
Trying to sort a column in my custom date table (a csv file) via a calculated column in the same table but am seeing an error. The calculated column does not reference the column I wish to sort by. Here's the DAX for the calculated column:
PeriodOffset =
Dates[Period] + Dates[FiscalYear] * 13
- CALCULATE ( VALUES ( Dates[Period] ), Dates[Date] = TODAY () )
- CALCULATE ( VALUES ( Dates[FiscalYear] ), Dates[Date] = TODAY () ) * 13
My date table has every date from 2003/4 to 2034/35, along with custom period numbers, calendar and fiscal years etc. The column I am trying to sort is called PeriodFiscalYear. Each value in that column has only one entry in the PeriodOffset column so it's not that.
The weird thing is, I have had this working in a previous report. In this instance, I was simply trying to recreate the functionality but it won't do it. Even stranger, if I create the PeriodFiscalYear column as a calculated column (currently it's hard-coded in the csv file), it works! So I have a sort-of workaround, I would just like to understand what is going on.
Thanks
I believe this has to do with the fact that data column are sorted when data are ingested into PBI. Calculated columns are calculated only at a later time.
Therefore:
you can sort data column only with other data columns (because calculated columns have not been calculated yet)
you can sort calculated column with both data column and calculated column
Solution:
A) PeriodFiscalYear becomes a calculated column
B) PeriodOffset becomes a data column (either in your CSV or Power Query)
I actually figured this out. The problem was with my data model - I had a circular relationship in there as I was deriving the Period column in one table using my calendar table then linking them back in the relationship!
I created a linking table with the keys in both to make the relationship, then hid it.
Thanks
I need help in calculating the cumulative frequencies row wise with minimum date and maximum date selection by users using sliders. Here is the table that I want to generate could you please guide me? I've tried various function and methods but nothing is giving me right answer. Thanks a lot in advance.
Below is the table that I've and I want to generate:
Original Table
Desired Table
To create a running total, create a new measure in your table like this (where Table is the name of your table):
Running Total = CALCULATE(
SUM('Table'[Values]);
FILTER(ALLSELECTED('Table'); 'Table'[Date] <= SELECTEDVALUE('Table'[Date]))
)
I have data from multiple countries on a monthly basis. Since the updates are not regular, I want to set up filter to visuals, so they would show the last month for which I have data from all the countries. I have data from each country loaded into a separate dataset, which then are merged into one big. Is there an easy way to place such filter? I managed to use "LASTDATE" function in each of country sets to find which date is last, but if I try to filter with that measure, I simply get nothing in a result. Thanks!
Well, this feels a little clunky to me but I believe it will work for you. There are two steps. The first is to create a summary table that reads through your data and counts the number of distinct countries that you have in each month. This will be a new table in your model, so go into the modeling tab, click 'New Table' and add this DAX. Obviously, correct for your table and column names.
SUMMARIZED_ROWS = SUMMARIZE(
'Table1'
,Table1[Month]
,"CountOfCountries"
,DISTINCTCOUNT(Table1[Country])
)
Now add a measure to the table (or anywhere) like this:
MonthWithMostCountries = CALCULATE(
LASTNONBLANK(SUMMARIZED_ROWS[Month], 1 )
, FILTER(SUMMARIZED_ROWS, SUMMARIZED_ROWS[CountOfCountries] = MAX(SUMMARIZED_ROWS[CountOfCountries]) ) )
This is going to give you the month where you have the most distinct countries in your data. You'll want to look at it in a card or similarly isolated visual as it is a measure and can be affected by filter context.
So, on the left is my mock data - 3 countries, 3 months each with a 1 month stagger. On the right you see the result of the Summarize table. Then the measure showing the final result.
Hope it helps.