I have a table containing a date field (from 1 March 2020 to now) that I need to filter to a specific date and the previous 6 days to give complete week's data. So if I chose 30 March I'd get a table of 24 March to 30 March. If I then chose 31 March the table would show 25 March to 31 March.
I can use a date slicer to choose a range of dates but I want to be able to pick a single date, with Power BI automatically selecting the earlier date.
Any pointers much appreciated.
Mark.
You can create two measure - one for Slicer selected date and Another one with 7 day minus from the selected date as below-
Considering your date table name is- Dates
selected_date = SELECTEDVALUE(Dates[Date])
seven_day_starts_from = DATEADD(Dates[Date],-7,DAY)
Now create your calculated measure first like-
total_sales = SUM(Sales[sale])
Here comes how you will always calculate last 7 days sales considering the selected date in the slicer-
7_day_sales =
(
CALCULATE(
[total_sales],
DATESBETWEEN(
'Dates'[Date],
[seven_day_starts_from],
[selected_date]
)
) + 0
)
Remember, this is just a sample flow showing how it should work. You should try to follow the steps with your data and table structure. Dates table is a calendar table and Sales table is connected to the Dates table using the Date column.
I have data for last 2 months of a year 2018.I have created all the necessary measures and columns as well as tables following this tutorial http://sqljason.com/2018/03/display-last-n-months-selected-month-using-single-date-dimension-in-powe....This is my dashboard.
but when i am choosing the date as August 2018 and selecting the slider to show the data for last 2( or any number) months then i am not getting the required result. This is the measure i am using
Scan (last n months) =
CALCULATE (
COUNT('Scan'[Data ID]),
DATESINPERIOD ('Date'[Date],MAX('Date'[Date]),-[N Value],MONTH )
)
No data for previous months for August 2018
No data for previous months of August 2018
I need to make a total for each of the months based on the working days.
So far i have working days set as 1 if the day in the month is during Monday - Friday and 0 for Saturday and Sunday. I now need to total up the 1's and make it so that it is a single value for the month.
E.g Going the weekdays is 1 and weekend is 0, January will have 22 days on each row on the table in the data mode - January 1 = 232 January 2 = 22 etc. so i can use it to divide against my target which is set to the 1st of every month.
How can i do this??
try this. i haven't tested it.
=GROUPBY( FILTER(table, table[Working_Day]=1) , table[Month], ["new col", SUMX( CURRENTGROUP(), table[Month_Order])])
filter gives working day 1's data as table,then group by performed by month, then month order has been added and returns table.
I'm building a Power BI dashboard that includes actual cost vs budget. Summarizing the cost is not a problem. The budget amount is entered in a table as a weekly amount, for example $1,000. We use a custom accounting calendar that dictates the number of weeks per month. The second month of each quarter is 5 weeks while all other months are 4 weeks. Here's what it looks like:
January is 4 weeks
February is 5 weeks
March is 4 weeks
April is 4 weeks
May is 5 weeks
June is 4 weeks
July is 4 weeks
August is 5 weeks
September is 4 weeks
October is 4 weeks
November is 5 weeks
December is 4 weeks
I need a looping variable in DAX that will simply count the number of weeks based on the months chosen with the month slicer. Then I can multiply the number of weeks by the weekly budget amount.
Here's a practical example:
If I choose Jan, Feb, Mar, Apr then the number of weeks should be 17 weeks. And the budget amount should be $17,000.
I figured this out in Crystal Reports. Here's the formula I wrote:
local datetimevar startdate:= {?BegMonth};
local numbervar numofWeeks;
While startdate <= {?EndMonth}
Do(
if month(startdate) in [2,5,8,11] then
numofWeeks := numofWeeks + 5
else
numofWeeks := numofWeeks + 4;
startdate := DATEADD("m",1,startdate);
);
numofWeeks
I've tried several approaches with DAX but I got nothing to work.
DAX doesn't exactly do looping. It does aggregations on filtered columns.
If you don't have a Month column, then create a calculated column.
TableName[Month] = MONTH ( TableName[Date] )
Once you have that, adding up weeks can be done with an iterator function.
Weeks =
SUMX (
VALUES ( TableName[Month] ),
IF ( TableName[Month] IN { 2, 5, 8, 11 }, 5, 4 )
)
The VALUES function is a list of unique values in the filter context, so if you selected Jan - Apr, then it would be {1,2,3,4}. Then SUMX iterates ("loops") over those four values and add 5 or 4 depending on the condition specified in the IF function.
I know similar questions have been asked and answered previous to this, but for the life of me, cannot get any of those working with my limited knowledge on Power BI.
I have a table which contains 8 weeks worth of data which for most parts, spans 3 months. I currently calculate the daily average which is the "total" divided by the "total in". However what I need to do, is to display the average based upon the calendar month. Therefore, September will have a difference average to that of October and that of November.
Here's a sample of the data:
Date,Total In,Total Out,Daily Average,Total,Month
27 September 2017,10773,264,97.61,11037,September
28 September 2017,11198,382,96.70,11580,September
29 September 2017,17753,1122,94.06,18875,September
30 September 2017,9568,649,93.65,10217,September
28 October 2017,11434,938,92.42,12372,October
29 October 2017,1541,60,96.25,1601,October
30 October 2017,918,4,99.57,922,October
31 October 2017,8565,24,99.72,8589,October
01 November 2017,11452,635,94.75,12087,November
02 November 2017,7785,531,93.61,8316,November
So for November I would like to have the figure as (11452 + 7785) / (12087 + 8316) * 100 = 94.29%. Obviously, that figure would be present for all dates in November as an extra column. For October it would be (11434 + 1541 + 918 + 8565) / (12372 + 1601 + 922 + 8589) * 100 = 95.63%. I would then use the extra column and plot it on a line/bar chart.
So the above data would become:
Date,Total In,Total Out,Daily Average,Total,Month,Monthly Average
27 September 2017,10773,264,97.61,11037,September,96.00
28 September 2017,11198,382,96.70,11580,September,96.00
29 September 2017,17753,1122,94.06,18875,September,96.00
30 September 2017,9568,649,93.65,10217,September,96.00
28 October 2017,11434,938,92.42,12372,October,95.63
29 October 2017,1541,60,96.25,1601,October,95.63
30 October 2017,918,4,99.57,922,October,95.63
31 October 2017,8565,24,99.72,8589,October,95.63
01 November 2017,11452,635,94.75,12087,November,94.29
02 November 2017,7785,531,93.61,8316,November,94.29
I am having trouble getting my head around the SUMMARIZE functions etc in order to get this working without any help. So any help and explanation would be greatly appreciated.
Thanks.
Create a DAX using the EARLIER function should do the trick:
Month Average =
VAR sum_total_in =
CALCULATE(
SUM('table'[Total In]),
FILTER(
'table',
'table'[Month] = EARLIER('table'[Month])
)
)
VAR sum_total =
CALCULATE(
SUM('table'[Total]),
FILTER(
'table',
'table'[Month] = EARLIER('table'[Month])
)
)
RETURN sum_total_in / sum_total
So basically it sums the Total In and Total within the same month and returns the division.
Results:
P.S. You'll need to add the year to the filter as well if you have data across years with the same month.
I see you're asking your question from a DAX perspective, but here's a Power Query based answer that's quite easy. Starting with your table in Power Query (Power BI's Query Editor):
Select the Month column, then Transform -> Group By, and set up the dialog box like this...
and click OK.
You'll see this:
Then click the button at the top of the
AllData column to expand the nested tables, and set up the dialog box like this...
and click OK.
You'll see this:
Now click Add Column -> Custom Column, and set up the dialog box like this...
and click OK.
You'll see this:
Now select the first three columns (Month, Sum Total In, Sum Total) and click Home -> Remove Columns.
You'll see this:
You can double-click the Month.1 column title and rename it if you like.