Distinct count basis condition for last 3 months - powerbi

Outlet ID
Outlet Name
Order Date
Product
Qty
Net Value
Mum_1
Prime Traders
12th Oct 2022
RoundBox
3
300
Mum_4
Avon Trading
13th Oct 2022
Slice 100
10
1000
I have date wise transaction data for past 20 months for retail outlets.
Any outlet that has been billed in the last 3 months can be classified as an 'Available Outlet'.
Eg: Available outlets for Sept 2022 are the ones that have been billed at least once across July, August & Sept 2022.
Similarly I need to have ,month wise availability count in a column chart. Can someone please guide as to how can I write a DAX query for the same ?

Related

Week number calculation in Power BI

I am new to Power BI.I have one year filter (Range filter) and one week number filter (Range filter). I want to calculate values such that when i select year 2021 to 2022 and week number 42 to 10 it will first show data for 42th weeks to 52th weeks for year 2021 and for 1st week to 10 th weeks for year 2022.

How do I calculate average from June 1 to June 30 annually and make it a dynamic function using DAX?

I have two tables in PowerBI, one modified date and one fact for customer scores. The relationship will be using the "Month Num" column. Score assessments take place every June, so I would like to be able to have the scores for 12 months (June 1 to June 30) averaged. Then I will just have a card comparing the Previous year score and Current year score. Is there a way to do this dynamically, so I do not have to change the year in the function every new year? I know using the AVERAGE function will be nested into the function somehow, but I am getting confused not using a calendar year and not seasoned enough to use Time Intelligence functions yet.
Customer Score Table
Month
Month Num
Year
Score
Customer #
June
6
2020
94.9
11111
July
7
2020
97
11111
months
continue
2020
100
June
6
2021
89
22222
July
7
2021
91
22222
months
continue
2021
100
June
6
2022
93
33333
July
7
2022
94
33333
Date Table
Month
Month Num
Month Initial
january
1
J
feb
2
F
march
3
M
other
months
continued

PowerBI and filtered sum calculation

I should be able to make a report concerning a relationship between sick leaves (days) and man-years. Data is on monthly level, consists of four years and looks like this (there is also own columns for year and business unit):
Month Sick leaves (days) Man-years
January 35 1,5
February 0 1,63
March 87 1,63
April 60 2,4
May 44 2,6
June 0 1,8
July 0 1,4
August 51 1,7
September 22 1,6
October 64 1,9
November 70 2,2
December 55 2
It has to be possible for the user to filter year, month, as well as business unit and get information about sick leave days during the filtered time period (and in selected business unit) compared to the total sum of man-years in the same period (and unit). Calculated from the test data above, the desired result should be 488/22.36 = 21.82
However, I have not managed to do what I want. The main problem is, that calculation takes into account only those months with nonzero sick leave days and ignores man-years of those months with zero days of sick leaves (in example data: February, June, July). I have tried several alternative functions (all, allselected, filter…), but results remain poor. So all information about a better solution will be highly appreciated.
It sounds like this has to do with the way DAX handles blanks (https://www.sqlbi.com/articles/blank-handling-in-dax/). Your context is probably filtering out the rows with blank values for "Sick-days". How to resolve this depends on how your data are structured, but you could try using variables to change your filter context or use "IF ( ISBLANK ( ... ) )" to make sure you're counting the blank rows.

What is the best way to do a matrix style reporting in a Django App?

I have a number of transactions in my model:
Transaction Date Category Amount
1 Jan Sales $1000
2 Feb Expense $500
3 Jan Expense $500
4 Mar Interest $100
What is the most efficient way to generate report in the template? However would you structure your queryset to get the data by month for a given year (knowing some category will be null/empty) and pass the context information in view.py? I know this is an easy questions but I'm curious what is the most efficient way to implement this matrix reporting?
Category Jan Feb Mar
Sales $1000
Expenses $500 $500
Interest $100
Total $500 -$500 $100

Calculate Variance in PowerBI using dax query

I am trying to create a variance measure in PowerBI.
This is the data that I have,
Month Year MonthNo Value
Jan 2016 1 700
Feb 2016 2 800
March 2016 3 900
April 2016 4 750
.
.
Jan 2017 13 690
Feb 2017 14 730
And My variance for the Month Number 7 should be like,
`{Avg(values(4,5,6) - Value(7)} / Value(7)`
i.e (Average of last 3 months value - current month value) / Current month value
How to do this in Power BI? Thanks.
If it is okay for you to use a column, I believe you could add one with this code to get what you want:
Variance = (CALCULATE(AVERAGEX(Sheet1,Sheet1[Value]),FILTER(FILTER(Sheet1,Sheet1[MonthNo]<=EARLIER(Sheet1[MonthNo])-1),Sheet1[MonthNo]>=EARLIER(Sheet1[MonthNo])-3))-Sheet1[Value])/Sheet1[Value]
You'll need to replace all instances of Sheet1 with the name of your table.
It'll give you something like this: