I have 4 values collected daily.
I want to graph the average of the 4 values on a time series graph.
If I was to plot this.
1/03/2021 will show an average value of 15 and 2/03/2021 will show an average value of 35.
I tried using quick measure that says rolling average of 1 day before 0 days after, it gives me an error.
The Dax which I've tried didn't work either - getting "too many arguments were passed to the Values Function. the maximum argument count for the function is 1". This is me trying to follow some instructions online for the first time.
Day Avg = AVERAGEX(VALUES([Date], [Values]))
Thanks for the input.
Gem
Assuming your data looks like this
Table
Date
Time
Value
01/03/2021
00:01:00
10
01/03/2021
06:00:00
20
01/03/2021
12:00:00
15
01/03/2021
18:00:00
15
02/03/2021
00:01:00
30
02/03/2021
06:00:00
20
02/03/2021
12:00:00
40
02/03/2021
18:00:00
50
It seems your row context is at the table level, so you don't need to use VALUES.
AVG =
AVERAGEX ( 'Table', 'Table'[Value] )
Related
I'm quite new to Power Bi and DAX in general and I have some problems calculating how much of each month was of the whole year.
Example:
Year 2021:
Month Value Percentage
Jan. 100 10
Feb. 50 5
Mar. 250 25
Apr. 30 3
Etc...
Total 1000 100
I have calculated the percentage column in dax as:
=
[Value] /
CALCULATE(
[Value],
ALLEXCEPT(Calendar, Calendar[Year])
)
This gives me the correct result for the chosen year, the problem I have is when trying to compare it to last year's result.
I've tried to add
"SAMEPERIODLASTYEAR(Calendar[Key_Calendar])" and "PARALLELLPERIOD(CALENDAR[Key_Calendar],-12,Month)"
but neither of them gives me the result I am looking for.
I'd appreciate any help that I can get on the issue.
First you need to create such a model:
If you want to create a simple calendar table, create new table and paste this code:
Calendar =
VAR BaseTable = CALENDAR(DATE(2020,01,01), DATE(2021,12,31))
RETURN
ADDCOLUMNS(
BaseTable,
"Year", YEAR([Date]),
"Month", MONTH([Date]),
"MonthName", FORMAT([Date],"mmm"),
"Quarter", QUARTER([Date]),
"Period", FORMAT([Date],"yyyy-mm")
)
Your resulting Date table:
Then create a fact table with some data:
Date Value
01/01/2021 100
01/02/2021 50
01/03/2021 250
01/04/2021 30
01/05/2021 25
01/06/2021 50
01/07/2021 65
01/08/2021 75
01/09/2021 70
01/10/2021 35
01/11/2021 40
01/12/2021 20
01/01/2020 10
01/02/2020 25
01/03/2020 65
01/04/2020 85
01/05/2020 35
01/06/2020 25
01/07/2020 35
01/08/2020 10
01/09/2020 30
01/10/2020 50
01/11/2020 30
01/12/2020 20
Then we can create 2 new measures!
Percentage =
DIVIDE(SUM(FactTable[Value]),CALCULATE(SUM(FactTable[Value]),ALL(FactTable)))
Percentage_LastYear =
CALCULATE(
[Percentage],
SAMEPERIODLASTYEAR('Calendar'[Date])
)
Then create a table visual and put it like you see in the below screenshot:
And you are Good to go! I hope It solves your problem!
Assuming that your Calendar dimension has a date column called Date, the following would get the value for the prior year:
Value PY =
CALCULATE ( [Value], SAMEPERIODLASTYEAR ( 'Calendar'[Date] ) )
I have a dataset containing the duration (in minutes) of occupancy events over a period of 1 hour in my rooms:
# room date duration
--- ---- ------------------- --------
0 A1 2022-01-01 08:00:00 30
1 A1 2022-01-01 10:00:00 5
2 A1 2022-01-01 16:00:00 30
3 A1 2022-01-02 10:00:00 60
4 A1 2022-01-02 16:00:00 60
...
My date column is linked to a date table in which I have:
# datetime year month monthName day dayOfWeek dayName hour
--- ------------------- ---- ----- --------- --- --------- -------- ----
...
k 2022-01-01 08:00:00 2022 1 January 1 5 Saturday 8
k+1 2022-01-01 09:00:00 2022 1 January 1 5 Saturday 9
...
n 2022-03-01 22:00:00 2022 3 March 1 1 Tuesday 22
I am trying to retrieve the following percentage: duration/timeperiod through a measure. The idea behind using a measure is :
Being able to use a time slicer and see my percentage being updated
Using, for example, a bar chart with my date hierarchy, and being able to see a percentage in my different level of hierarchy (datetime -> year -> month -> dayOfWeek -> hour)
Attempt
My idea was to create a first measure that would return the number of minutes between the first and the last date currently chosen. Here is what I came up with:
Diff minutes = DATEDIFF(
FIRSTDATE( 'date'[date] ),
LASTDATE( 'date'[date] ),
MINUTE
)
The idea was then to create a second measure that would divide the SUM of the durations by the Diff minutes' measure:
My rate = DIVIDE(
SUM( 'table'[duration] ),
[Diff minutes]
)
I currently face a few issues:
The slicer is set to (2022-01-02 --> 2022-01-03) and if I check in a matrix, I have datetime between 2022-01-02 0:00:00 and 2022-01-03 23:00:00, but my measure returns 1440 which is the number of minutes in a day but not in my selected time period
The percentage is also wrong unfortunately. Let's take the example that I highlighted in the capture. There are 2 values for the 10h slot, 5min and 60min. But the percentage shows 4.51% instead of 54.2%. It actually is the result of 65/1440, 1440 being the total of minutes for my whole time period, not my 10h slot.
Examples
1- Let's say I have a slicer over a period of 2 days (2022-01-01 --> 2022-01-02) and my dataset is the one provided before:
I would have a total duration of 185 minutes (30+5+30+60+60)
My time period would be 2 days = 48h = 2880 minutes
The displayed ratio would be: 6.4% (185/2880)
2- With the same slicer, a matrix with hours and percentage would give me:
hour rate
---- -----
0 0.0%
1 0.0%
...
8 25.0% <--- 30 minutes on the 1st of January and 0 minutes on the 2nd
9 0.0% <--- (5+0)/120
10 54.2% <--- (5+60)/120
...
16 75.0% <--- (30+60)/120
Constraints
The example I provided only has 1 room. In practice, there are n rooms and I would like my measure to return the percentage as the mean of all my rooms.
Would it be possible ? Have I chosen the right method ?
The DateDiff function you have created should work, I have tested it on a report and when I select some dates, it gives me the difference between the first and last selected dates.
Make sure your slicer is interacting with the measure.
In the meantime, I think I found a simpler and easier way to do it.
First, I added a new column to my date table, that seems dubious but is actually helpful:
minutes = 60
This allows me to get rid of the DATEDIFF function. My rate measure now looks like this:
My rate = DIVIDE(
SUM( table[duration] ),
[Number of minutes],
0
)
Here, I use the measure Number of minutes which is simply a SUM of the values in the minutes column. In order to provide accurate results when I have multiple rooms selected, I multiplied the number of minutes by the number of rooms:
Number of minutes = COUNTROWS( rooms ) * SUM( 'date'[minutes] )
This now works perfectly with my date hierarchy!
I am having problems with a distinctcount calculated by week. I have the pivot table below. I want to calculate the distinct number of vendors that have sold more than $2400 per week.
I have the following data table "sales" (only the first rows, but it has several vendors and other weeks as well):
sales day sales week vendor ID Total Sales
02.11.2020 45 vendor 1 405
03.11.2020 45 vendor 1 464
04.11.2020 45 vendor 1 466
05.11.2020 45 vendor 1 358
06.11.2020 45 vendor 1 420
07.11.2020 45 vendor 1 343
I have tried to calculate it as such:
= [vendor] =distinctcount('Sales'[vendor ID])
= [Total_sales] = sum('Sales'[Total Sales])
= [# vendors - 2400] =calculate([vendor],filter('Sales',[Total_sales]>2400))
I know that this calculation considers the sales per day, not per week. so, if instead of using $2400 I used $300, for instance, then both vendors would be marked, since in at least one day, the sales of both are higher than $300. But I only want to consider the sales in a weekly basis.
What I expect (check pivot table below): Vendor 2 would be marked (sales = 2456), but not vendor 1 (sales = 1341), i.e., total number of vendors = 1. However, none of the vendors are being counted, since no daily sales are higher then $2400
Row Labels # Vendors (distinct) total sales
Store A 3797
week 45 3797
Vendor 1 1341
02.11.2020 348
04.11.2020 202
05.11.2020 335
06.11.2020 308
07.11.2020 148
Vendor 2 2456
02.11.2020 405
03.11.2020 464
04.11.2020 466
05.11.2020 358
06.11.2020 420
07.11.2020 343
I also tried to create a column of sales in which I removed the day filter, like this:
=calculate([total_sales],ALL('sales'[sales day]))
and then recalculated the [# vendors - 2400], but it still gets me the same result as above.
The question is: how do I get to consider the total sales value per week (and not per day) for the distinctcount. Thank you for the help!
Do you have a Date calendar in your file? if no try to make one, then have a relationship from date to sales day (assuming this has your dates). That way you should be able to summarize by any date grouping eg, Month, Day, Week, Quarter etc...Or you can try parsing the other date field and add new columns to your table = weeknum(Tablename[sales day])
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.
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: