MULTIPLY Function
Returns the value of multiplying the first argument by the second argument. Equivalent to the * operator.
Each argument can be a literal Integer or Decimal number, a function returning a number, or a reference to a column containing numeric values.
Note
Within an expression, you might choose to use the corresponding operator, instead of this function. For more information, see Numeric Operators.
Wrangle vs. SQL: This function is part of Wrangle, a proprietary data transformation language. Wrangle is not SQL. For more information, see Wrangle Language.
Basic Usage
multiply(10,4)
Output: Returns the multiplication of 10 and 4, which is 40.
Syntax and Arguments
multiply(value1, value2)
Argument | Required? | Data Type | Description |
|---|---|---|---|
value1 | Y | string | The first value must be an Integer or Decimal literal, column reference, or expression that evaluates to one of those two numeric types. |
value2 | Y | string | The second value must be an Integer or Decimal literal, column reference, or expression that evaluates to one of those two numeric types. |
For more information on syntax standards, see Language Documentation Syntax Notes.
value1, value2
Integer or Decimal expressions, column references or literals to multiply together.
Missing or mismatched values generate missing string results.
Usage Notes:
Required? | Data Type | Example Value |
|---|---|---|
Yes | Literal, function, or column reference returning an Integer or Decimal value | 15 |
Examples
Tip
For additional examples, see Common Tasks.
Example - Numeric Functions
This example demonstrate the following numeric functions:
See ADD Function.
See SUBTRACT Function.
See MULTIPLY Function.
See DIVIDE Function.
See MOD Function.
See NEGATE Function.
See LCM Function.
Source:
ValueA | ValueB |
|---|---|
8 | 2 |
10 | 4 |
15 | 10 |
5 | 6 |
Transformation:
Execute the following transformation steps:
Transformation Name |
|
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | ADD(ValueA, ValueB) |
Parameter: New column name | 'add' |
Transformation Name |
|
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | SUBTRACT(ValueA, ValueB) |
Parameter: New column name | 'subtract' |
Transformation Name |
|
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | MULTIPLY(ValueA, ValueB) |
Parameter: New column name | 'multiply' |
Transformation Name |
|
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | DIVIDE(ValueA, ValueB) |
Parameter: New column name | 'divide' |
Transformation Name |
|
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | MOD(ValueA, ValueB) |
Parameter: New column name | 'mod' |
Transformation Name |
|
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | NEGATE(ValueA) |
Parameter: New column name | 'negativeA' |
Transformation Name |
|
|---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | LCM(ValueA, ValueB) |
Parameter: New column name | 'lcm' |
Results:
With a bit of cleanup, your dataset results might look like the following:
ValueA | ValueB | lcm | negativeA | mod | divide | multiply | subtract | add |
|---|---|---|---|---|---|---|---|---|
8 | 2 | 8 | -8 | 0 | 4 | 16 | 6 | 10 |
10 | 4 | 20 | -10 | 2 | 2.5 | 40 | 6 | 14 |
15 | 10 | 30 | -15 | 5 | 1.5 | 150 | 5 | 25 |
5 | 6 | 30 | -5 | 5 | 0.833333333 | 30 | -1 | 11 |