CumProd
CumProd calculates a cumulative product in an updateBy table operation.
Syntax
CumProd(pairs...)
Parameters
| Parameter | Type | Description |
|---|---|---|
| pairs | String... | The column(s) to be operated on. These can include expressions to rename the output columns (e.g., |
Returns
An UpdateByOperation to be used in an updateBy table operation.
Examples
The following example performs an updateBy on the source table using the CumProd operation. No grouping columns are given, so the cumulative product is calculated across all rows of the table.
source = emptyTable(10).update("Letter = (i % 2 == 0) ? `A` : `B`", "X = i + 1")
result = source.updateBy(CumProd("ProdX = X"))
- source
- result
The following example builds on the previous by specifying Letter as a grouping column. Thus, the cumulative product in the result table is calculated on a per-letter basis.
source = emptyTable(10).update("Letter = (i % 2 == 0) ? `A` : `B`", "X = i + 1")
result = source.updateBy(CumProd("ProdX = X"), "Letter")
- source
- result
The following example builds on the previous by calculating the cumulative product of two columns using the same UpdateByOperation.
source = emptyTable(10).update("Letter = (i % 2 == 0) ? `A` : `B`", "X = i + 1", "Y = randomInt(1, 7)")
result = source.updateBy(CumProd("ProdX = X", "ProdY = Y"), "Letter")
- source
- result
The following example builds on the previous by specifying two grouping columns: Letter and Truth. Thus, groups consist of unique combinations of letter in Letter and boolean in Truth.
source = emptyTable(10).update("Letter = (i % 2 == 0) ? `A` : `B`", "Truth = randomBool()", "X = i + 1", "Y = randomInt(1, 7)")
result = source.updateBy(CumProd("ProdX = X", "ProdY = Y"), "Letter", "Truth")
- source
- result