Average entries by month, week and day

[fabiomanniti]

I would like to know, given a certain date range, how many entries do I have, on average, per day, week and month.

So far I am creating three measures like this

average_ticket_perDay =

var nOfDays = DATEDIFF(Min(issues[created]), Max(issues[created]),Day)

var nOfRows = COUNTROWS(Issues)

Return DIVIDE(nOfRows,nOfDays)

average_ticket_perWeek =

var nOfWeeks = DATEDIFF(Min(issues[created]), Max(issues[created]),Week)

var nOfRows = COUNTROWS(Issues)

Return DIVIDE(nOfRows,nOfWeeks)

average_ticket_perMonth =

var nOfMonths = DATEDIFF(Min(issues[created]), Max(issues[created]),Month)

var nOfRows = COUNTROWS(Issues)

Return DIVIDE(nOfRows,nOfMonths)

And then I put three visuals with the tree informations.

Question:

Is it possibile to get this information only with a single visual?

Alternative question:

Is it possible to create only one measure and the DateDiff interval changes Dinamically?

[v-janeyg-msft · Accepted solution]

Hi, @fabiomanniti 

According to your description, I think you can create a singe table column as slicer, then you can choose day,week,month you want to control the result dynamically.

Like this:

average_ticket =
VAR nOfRows =
    COUNTROWS ( Issues )
VAR nOfDays =
    DATEDIFF ( MIN ( issues[created] ), MAX ( issues[created] ), DAY )
VAR nOfWeeks =
    DATEDIFF ( MIN ( issues[created] ), MAX ( issues[created] ), WEEK )
VAR nOfMonths =
    DATEDIFF ( MIN ( issues[created] ), MAX ( issues[created] ), MONTH )
VAR nofRD =
    DIVIDE ( nOfRows, nOfDays )
VAR nofRW =
    DIVIDE ( nOfRows, nOfWeeks )
VAR nofRM =
    DIVIDE ( nOfRows, nOfMonths )
RETURN
    SWITCH (
        TRUE (),
        SELECTEDVALUE ( table[date] ) = "Day", nofRD,
        SELECTEDVALUE ( table[date] ) = "Week", nofRW,
        SELECTEDVALUE ( table[date] ) = "Month", nofRM
    )

Did I answer your question ? Please mark my reply as solution. Thank you very much.
If not, please upload some insensitive data samples and expected output.

Best Regards,
Community Support Team _ Janey