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Problem background:
What I’m trying to do:
I want to create a histogram of weekly throughput. In other words:
conceptually, this is the desired output...
What I’ve tried so far:
I have this measure that calculates resolved issues dynamically
resolved_count =
CALCULATE(
DISTINCTCOUNT(issues[issue_key]),
issues[status]="Done",
issue_dates[date_type]="Resolved"
)
Then I started trying to dynamically identify the count of weeks, BUT I can’t figure out how to filter this by if the resolved_count is = throughput_value. Maybe I need to go in a completely different direction.
throughput_weeks_count =
COUNTROWS(
ADDCOLUMNS(
VALUES(issue_dates_calendar[Calendar Week End Date]),
"throughput",[resolved_count]
)
)
Normally I would use a filter function (logically, something like below), but I can’t figure out how to use that when I’m not referencing a real table.
FILTER(
“throughput_weeks_count”,
“throughput” = throughput_ranges[throughput_value]
)
Any help is appreciated!
Solved! Go to Solution.
I was able to resolve this by adding a "last day of week" calendar table to my data model then using this measure to calculate the count of weeks. Also added a min/max boundary to the throughput_range table.
VAR weeks =
COUNTROWS(
FILTER(
issue_dates_calendar_weeks,
AND(
[resolved_count] >= MIN (throughput_ranges[value_min]),
[resolved_count] <= MAX (throughput_ranges[value_max])
)
)
)
I was able to resolve this by adding a "last day of week" calendar table to my data model then using this measure to calculate the count of weeks. Also added a min/max boundary to the throughput_range table.
VAR weeks =
COUNTROWS(
FILTER(
issue_dates_calendar_weeks,
AND(
[resolved_count] >= MIN (throughput_ranges[value_min]),
[resolved_count] <= MAX (throughput_ranges[value_max])
)
)
)
Can you create a calculated table at load time basically with your syntax...
throughput_weeks_count =
ADDCOLUMNS(
VALUES(issue_dates_calendar[Calendar Week End Date]),
"throughput",[resolved_count]
)
(SUMMARIZECOLUMNS might be better)
That then materialises the count as a column which you can use as filter on your x axis.
No, can't do that even though that would be a lot easier. The weekly throughput values need to calculate dynamically because they are filterable by team_issue and issue attributes selections.
Alternatively. Take a disconnected table with numbers 0 through 52 (or higher)
Put that on x axis.
Then in your last measure read the value with selectedvalue and wrap your count rows in a filtered version of the dynamic table. Can write the dax tomorrow if you want.
Maybe, not sure I completely follow.
How would that work for date periods that cross a year boundary or extend longer than a single year? Not sure how the weeks match up in that scenario.
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