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Release 8.2.1

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Returns the modulo value, which is the remainder of dividing 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

mod(14,3)

Output: Returns remainder of the value `14` divided by `3`, which is `2`

## Syntax and Arguments

mod(value1, value2)

ArgumentRequired?Data TypeDescription
value1YstringThe first value must be an Integer or Decimal literal, column reference, or expression that evaluates to one of those two numeric types.
value2YstringThe first value must be an Integer or Decimal literal, column reference, or expression that evaluates to one of those two numeric types.

### value1, value2

Integer or Decimal expressions, column references or literals.

• Missing or mismatched values generate missing string results.

Usage Notes:

Required?Data TypeExample Value
YesLiteral, function, or column reference returning an Integer or Decimal value`15`

## Examples

### Example - Numeric Functions

This example demonstrate the following numeric functions:

Source:

ValueAValueB
82
104
1510
56

Transformation:

Execute the following transformation steps:

Transformation Name `New formula` `Single row formula` `ADD(ValueA, ValueB)` `'add'`

Transformation Name `New formula` `Single row formula` `SUBTRACT(ValueA, ValueB)` `'subtract'`

Transformation Name `New formula` `Single row formula` `MULTIPLY(ValueA, ValueB)` `'multiply'`

Transformation Name `New formula` `Single row formula` `DIVIDE(ValueA, ValueB)` `'divide'`

Transformation Name `New formula` `Single row formula` `MOD(ValueA, ValueB)` `'mod'`

Transformation Name `New formula` `Single row formula` `NEGATE(ValueA)` `'negativeA'`

Transformation Name `New formula` `Single row formula` `LCM(ValueA, ValueB)` `'lcm'`

Results:

With a bit of cleanup, your dataset results might look like the following:

828-80416610
10420-1022.540614
151030-1551.5150525
5630-550.83333333330-111

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