Set Analysis - Set Modifier difference not working as expected
Seems like I misunderstood how the Set Modifier is meant to work. Would appreciate if someone can clear things up for me. I'm attaching a sample application which I'm working from. In the application is a simple data model with a table for games, a table for invites, and a table for participant.
What I'm trying to count is the number of times a person has chosen to ignore their invite and not participate in the game in a table format where the dimension is the person. Should be pretty simple.
The number of games they have been invited to is : sum({<NumInvites = {1}>} NumGames)
The number of games they participated in is : sum({<NumParticipations = {1}>}NumGames)
Shouldn't the number of games they chose not to participate in be the difference between the two sets?
Hi, set analysis is calculated before the table, so dimensions don't affect when creating the subset, it applies after the subset is created. Also it applies to the used fields, and NumGames is on the games table, so the access to NumGames is in a direct relation with gameid.
When you do sum({<NumInvites = {1}>} NumGames), the subset has access to the 3 games, and then applies each person filter to the row.
But when you do <NumInvites= {1}> - <NumParticipations={1}>, and all games has at least one participation, you are removing all games from the subset. and the empty subset is applied to each person, so it returns 0 for all.
If you merge all 3 tables in one using joins it will work as you expect.
Hi, set analysis is calculated before the table, so dimensions don't affect when creating the subset, it applies after the subset is created. Also it applies to the used fields, and NumGames is on the games table, so the access to NumGames is in a direct relation with gameid.
When you do sum({<NumInvites = {1}>} NumGames), the subset has access to the 3 games, and then applies each person filter to the row.
But when you do <NumInvites= {1}> - <NumParticipations={1}>, and all games has at least one participation, you are removing all games from the subset. and the empty subset is applied to each person, so it returns 0 for all.
If you merge all 3 tables in one using joins it will work as you expect.
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