I am a newbie to Power BI and DAX.
I have a dataset as attached. I need to find the maximum value for each person for each week. I have written the formula in Excel.
=MAX(IF(A$2:A$32=A2,IF(D$2:D$32=D2,IF(B$2:B$32=1,C$2:C$32))))
How can I convert it to DAX or write the same formula in Power BI? I tried the DAX Code as below, But it did not work(ALLEXCEPT Function expects table).
Weekly Maximum =
CALCULATE ( MAX ( PT[Value] ), ALLEXCEPT ( PT, PT[person], PT[Week],
PT[category] ==1 ) )
Once I calculate this, then I need to calculate the Expected value for each week, that has the maximum value of the previous week * 2.85, as shown in the screenshot. How can I put the previous week's maximum value for this week?
Any corrections/solutions, please?
TIA
The Max Value for Category 1 can be written like this:
= CALCULATE(MAX(PT[Value]),
ALLEXCEPT(PT, PT[Person], PT[Week]),
PT[Category] = 1)
(The Category filter doesn't go inside ALLEXCEPT().)
For your Expected Value column, you can do something similar:
= CALCULATE(2.85 * MAX(PT[Value]),
ALLEXCEPT(PT, PT[Person]),
PT[Category] = 1,
PT[Week] = EARLIER(PT[Week]) - 1)
(The EARLIER function gives you the value for the row you are in. The name refers to the earlier row context.)
Related
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 have following simple relationship:
I have created following visuals in Power BI:
I want to show Store Name, Orders (by Salesman selected in slicer) and Total Orders in that Store (ignoring Salesman selected in slicer). I have created two very simple measure (can be seen in above visual) and used in matrix visuals. Visual is showing All stores while I want to show only those stores where Salesman X (selected salesman in slicer) have orders i.e. I don't want Store B row.
while solving, I suspected that it is due to fact that visual is not cross filtering. I used crossfilter but it made no difference. data can be seen in below image:
Please guide. Thanks in advance.
Try to change [Total Orders] to this measure, but keep [Total Orders].
IF( ISBLANK([Orders Count]), BLANK(), [Total Orders])
By Adding VALUES('Order'[Store ID]) in measure solved the problem. complete measure definition is as follows:
Total Orders = CALCULATE(
count('Order'[Order ID]),
REMOVEFILTERS(Salesman[Salesman Name]),
VALUES('Order'[Store ID]))
This issues the problem but I could not understand how? Because VALUES bring only those stores where salesman has Order. But when salesman removed from the filter context by REMOVEFILTERS, then how come VALUES bring only stores where salesman have orders?
a) You intend to utilize Store.salesmanName from Store in a slicer, meaning whatever is selected from there, you intend that selection to be applied on Order to give you the Order.StoreName. So when X is selected only A and C are returned.
b) Once that selection happens, you intend DAX to return the total count of each Order.StoreName whether it has a corresponding Store.salesmanID in Order.salesmanID or not. In other words, in this layer of the analysis, you want the previous selection to remain applied in the outer loop but to be ignored in the inner loop.
To be able to do that, you can do this,
totalCount =
VAR _store =
MAX ( 'Order'[storeID] ) //what is the max store ID
VAR _count =
CALCULATE (
COUNT ( 'Order'[SalesmanId] ),
FILTER ( ALL ( 'Order' ), 'Order'[storeID] = _store ) //remove any filters and apply the value from above explicitly in the filter
)
RETURN
_count
I am trying to calculate month over month difference but it makes data negative.
I created a measure, but it makes source data negative.
CALCULATE (
COUNTA ( SOURCE_DATA[COLUMN] ),
FILTER ( SOURCE_DATA, SOURCE_DATA[YYYYMM] = "201906" )
)
- (
CALCULATE (
COUNTA ( SOURCE_DATA[COLUMN] ),
FILTER ( SOURCE_DATA, SOURCE_DATA[YYYYMM] = "201905" )
)
)
The outcome is correct, but it changes data in previous month to negative.
This is due to the filter context and the way you've written the measure.
Look at the visual table. For the field corresponding to Column = 201905 and row = GA you get -16 813. This is because the context of the visual table tells CALCULATE to COUNTA(SOURCE_DATA[Column]) only when MtM = GA and Columns = 201905. However, adding the FILTER you also tell CALCULATE to keep these criteria AND also make sure that SOURCE_DATA[Column] = 201906 in the first calculate and 201905 in the second one.
This results in CALCULATE looking for rows where Column is both 201905 and 201906 at the same time. Or in other words you generate a venn diagram with no overlapping fields. Therefore the first calculate evaluates to 0 and the second to 16 813, so that the measure is actually evaluating 0-16813 = -16 813.
Since you didn't post any description of your data model I can inly guess what it looks like. However, since you're filtering on the SOURCE_DATA table I guess you don't use a Calendar table. This you should do! Have a calendar with a 1:* (1-to-many) relationship with the SOURCE_DATA and do filtering on the calendar. In addition you can have dynamically calculated day/week/month/year offsets so that you can create measures which don't have to be updated when there's a new month.
I think this video can be helpful: sqlbi videolecture
Also, have a look at this article: sqlbi filter in calculate
I have a list of products and would like to get a 50 day simple moving average of its volume using Power Query (M).
The table is sorted by product name and date. I add a custom column and applied the code below.
if [date] >= #date(2018,1,29)
then List.Average(List.Range(Source[Volume],[Volume]-1,-50))
else ""
Since it is already sorted by date and name, an if statement was applied with a date as criteria/filter. However, an error occurs that says
'Volume' column not found in the table.
I expect to have an added column in the power query with volume 50 day moving average per product. the calculation to be done if date is greater than or equal Jan 29, 2018.
We don't know what your columns are, but assuming you have [product], [date] and [volume] in Source, this would average the last 50 days of [volume] for the identical [product] based on each [date], and place in a new column
AvgAmountAdded = Table.AddColumn(Source, "AverageAmount", (i) => List.Average(Table.SelectRows(Source, each ([product] = i[product] and [date]<=i[date] and [date]>=Date.AddDays(i[date],-50)))[volume]), type number)
Finally! found a solution.
First, apply Index by product see this post for further details
Then index again without criteria (index all rows)
Then, apply below code
= Table.AddColumn(#"Previous Step", "Volume SMA(50)", each if [Index_byProduct] >= 50 then List.Average(List.Range(#"Previous Step"[Volume], ([Index_All]-50),50)) else 0),
For large dataset, Table.Buffer function is recommended after index-expand step to improve PQ calculation speed
I am trying to use power pivot to analyze a stock portfolio at any point in time.
The data model is:
transactions table with buy and sell transactions
historical_prices table with the closing price of each stock
security_lookup table with the symbol and other information about the stock (whether it’s a mutual fund, industry, large cap, etc.).
One to many relationships link the symbol column in security_lookup to the transactions and historical_prices tables.
I am able to get the cost basis to work correctly by doing sumx(transactions, quantity*price). However, I’m not able to get the current value of my holdings. I have a measure called “Current Price” which finds the most recent closing price by
Current Price :=
CALCULATE (
LASTNONBLANK ( Historical_prices[close], min[close] ),
FILTER (
Historical_Prices,
Historical_prices[date] = LASTDATE ( historical_prices[date] )
)
)
However, when I try to find the current value of a security by using
Current Value = sumx(transactions,transactions[quantity]*[Current Price])
the total is not accurate. I'd appreciate suggestions on a way to find the current value of a position. Preferably using sumx or an iterator function so that the subtotals are accurate.
The problem with your Current Value measure is that you are evaluating [Current Price] within the row context of the transactions table (since SUMX is an iterator), so it's only seeing the date associated with that row instead of the last date. Or more precisely, that row's date is the last date in the measure's filter context.
The simplest solution is probably to calculate the Current Price outside of the iterator using a variable and then pass that constant in so you don't have to worry about row and filter contexts.
Current Value =
VAR CurrentPrice = [Current Price]
RETURN SUMX(transactions, transactions[quantity] * CurrentPrice)