Using issue count twice in a chart

[Bobby Moyini]

New to using analytics ....

I am trying to build a analytics chart that shows project name , tasks filtered by a specific label, and all tasks for each project. Ultimately I want to see the percentage total of tasks that are using a specific label by project. 

Currently I'm using project name, unique count of issue key (limited to bugs and stories). I can't figure out how to add two columns based on unique count of issue key with one showing the count for the specific label only and the other for the count of all tasks (my last column would be a calculated field to find out the percent total). 

End result would be :

Project name , Tasks with specific Label, Total tasks, % of total using the specific label

[Arumugam M · Accepted solution]

Hey @Bobby Moyini 

Thank you for your question. You're on the right track. To add another column that shows the total number of tasks, you need to incorporate it as a subquery and then join the results.

Here's an example:

First Query: Select the "Name" column from the "Project" table and count the unique "Issue Key" from the "Issue" table, applying any necessary filters for specific labels.

This query should return the project name along with the number of issues/tasks that have a specific label.

Second Query: Perform a similar selection as above, but without any label filters or conditions.

Since both queries have the same first column, you can use a left join based on this column. The result will include:

• Column 1: Project Name

• Column 2: Count of issues with a specific label

• Column 3: Count of total issues

Percentage Calculation: Finally, calculate the percentage difference between column 2 and column 3 using a formula column step. The formula will look like this:

100.0 * "Count of unique Issue key" / "Count of unique Issue key:1"

I've attached a screenshot for reference. Feel free to reach out to support if you have any specific questions.

Thanks, 

Arumugam

[Bobby Moyini]

Ya thank you , the part I was missing was creating a second query and using the outer join to bring them together and do the calc.