Summing by groups in beast mode?
I'm running on 2 hours of sleep so I think I am just overthinking this right now but I essentially have a large dataset of event attendance by members
Here is a sample of my data:
Event Date | Event Name | Member ID | Member is Registered for Event | Parent Group | Location Type |
---|---|---|---|---|---|
Apr-25 | Event 1 | 1 | 0 | Primary | Primary |
Apr-25 | Event 1 | 2 | 1 | Primary | Primary |
Apr-25 | Event 1 | 3 | 0 | Primary | Primary |
Apr-25 | Event 1 | 4 | 0 | Primary | Primary |
Apr-25 | Event 1 | 5 | 1 | Primary | Primary |
Sep-24 | Event 2 | 1 | 1 | Primary | Primary |
Sep-24 | Event 2 | 2 | 1 | Primary | Primary |
Sep-24 | Event 2 | 3 | 0 | Primary | Primary |
Sep-24 | Event 2 | 4 | 1 | Primary | Primary |
Sep-24 | Event 2 | 5 | 0 | Primary | Primary |
Apr-23 | Event 3 | 1 | 1 | Primary | Primary |
Apr-23 | Event 3 | 2 | 1 | Primary | Primary |
Apr-23 | Event 3 | 3 | 0 | Primary | Primary |
Apr-23 | Event 3 | 4 | 1 | Primary | Primary |
Apr-23 | Event 3 | 5 | 1 | Primary | Primary |
But as you can see the member ID is going to repeat for every single event so its producing 40000 instances instead of 200 out of 1200 possible members for this event and 450 out of 1200 possible members for this event didnt attend.
I know I can pivot table this to count how many are 0, but is there a way to incorporate this into metrics too? Im hoping to create this in a card level since its coming from a federated source
Or like these metrics/table
People who have never attended an event
1
or
People who havent attended an event in the last year
3
or
Event Name | People that did not attend but could have | People that attended |
---|---|---|
Event 1 | 3 | 2 |
Event 2 | 2 | 3 |
Event 3 | 1 | 4 |
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