I have a table that looks like this:
+------------+-----------+---------------+
| Invoice_ID | Charge_ID | Charge_Amount |
+------------+-----------+---------------+
| 1 | A | $10 |
| 1 | B | $20 |
| 2 | A | $10 |
| 2 | B | $20 |
| 2 | C | $30 |
| 3 | C | $30 |
| 3 | D | $40 |
+------------+-----------+---------------+
In Tableau, how can I have a field that SUMs the Charge_Amount for the Charge_IDs B, C and D, where the invoice has a Charge_ID of A? The result would be $70.
My datasource is SQL Server, so I was thinking that I could add a field (called Has_ChargeID_A) to the SQL Server Table that tells if the invoice has a Charge_ID of A, and then in Tableau just do a SUM of all the rows where Has_ChargeID_A is true and Charge_ID is either B, C or D. But I would prefer if I can do this directly in Tableau (not this exactly, but anything that will get me to the same result).
Your intuition is steering you in the right direction. You do want to filter to only Invoices that contain row with a Charge_ID of A, and you can do this directly in Tableau.
First place Invoice_ID on the filter shelf, then select the Condition tab for the filter. Then select the "By formula" option on the condition tab and enter the formula you wish to use to determine which invoice_ids are included by the filter.
Here is a formula for your example:
count(if Charge_ID = 'A' then 'Y' end) > 0
For each data row, it will calculate the value of the expression inside the parenthesis, and then only include invoice_ids with at least one non-null value for the internal expression. (The implicit else for the if statement, "returns" null).
The condition tab for a dimension field equates to a HAVING clause in SQL.
If condition formulas get complex, it's often a good a idea to define them with a calculated field -- or a combination of several simpler calculated fields, just to keep things manageable.
Finally, if you end up working with sets of dimensions like this frequently, you can define them as sets. You can still drop sets on the filter shelf, but then can reuse them in other ways: like testing set membership in a calculated field (like a SQL IN clause), or by creating new sets using intersection and union operators. You can think of sets like named filters, such as the set of invoices that contain type A charge.
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