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Computes the sum of all numeric values found in input array. Input can be an array literal, a column of arrays, or a function returning an array. Input values must be of Integer or Decimal type.

When this function is invoked, all of the values in the input array are passed to the corresponding columnar function. Some restrictions may apply. See SUM Function.

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

Literal example:

listsum([0,0,2,4,6,8,10,12,14,16,18,20])

Output: Returns the sum of all values in the literal array: 110.

Column example:

listsum(myArray)

Output: Returns the sum of all values in the arrays of the myArray column.

## Syntax and Arguments

listsum(array_ref)

ArgumentRequired?Data TypeDescription
array_refYArrayArray literal, reference to column containing arrays, or function returning an array

### array_ref

Reference to an array can be an array literal, function returning an array, or a single column containing arrays.

• If the input is not a valid numeric array, null values are returned.
• Non-numerical values within an input array are not factored in the computation.
• Multiple columns and wildcards are not supported.

Usage Notes:

Required?Data TypeExample Value
Yes

Array

myArray

## Examples

### Example - Math functions for lists (arrays)

This example describes how to generate random array (list) data and then to apply the following math functions to your arrays.

Source:

For this example, you can generate some randomized data using the following steps. First, you need to seed an array with a range of values using the RANGE function:

Transformation Name New formula Single row formula RANGE(5, 50, 5) 'myArray1'

Then, unpack this array, so you can add a random factor:

Transformation Name Unnest Objects into columns myArray1 '[0]', '[1]', '[2]', '[3]', '[4]', '[5]', '[6]', '[7]', '[8]', '[9]' true true

Add the randomizing factor. Here, you are adding randomization around individual values:  x-1 < x < x+4.

Transformation Name Edit column with formula myArray1_0~myArray1_8 IF(RAND() > 0.5, \$col + (5 * RAND()), \$col - RAND())

To make the numbers easier to manipulate, you can round them to two decimal places:

Transformation Name Edit column with formula myArray1_0~myArray1_8 ROUND(\$col, 2)

Renest these columns into an array:

Transformation Name Nest columns into Objects myArray1_0, myArray1_1, myArray1_2, myArray1_3, myArray1_4, myArray1_5, myArray1_6, myArray1_7, myArray1_8 Array 'myArray2'

Delete the unused columns:

Transformation Name Delete columns myArray1_0~myArray1_8,myArray1 Delete selected columns

Your data should look similar to the following:

myArray2
["8.29","9.63","14.63","19.63","24.63","29.63","34.63","39.63","44.63"]
["8.32","14.01","19.01","24.01","29.01","34.01","39.01","44.01","49.01"]
["4.55","9.58","14.58","19.58","24.58","29.58","34.58","39.58","44.58"]
["9.22","14.84","19.84","24.84","29.84","34.84","39.84","44.84","49.84"]
["8.75","13.36","18.36","23.36","28.36","33.36","38.36","43.36","48.36"]
["8.47","14.76","19.76","24.76","29.76","34.76","39.76","44.76","49.76"]
["4.93","9.99","14.99","19.99","24.99","29.99","34.99","39.99","44.99"]
["4.65","14.98","19.98","24.98","29.98","34.98","39.98","44.98","49.98"]
["7.80","14.62","19.62","24.62","29.62","34.62","39.62","44.62","49.62"]
["9.32","9.96","14.96","19.96","24.96","29.96","34.96","39.96","44.96"]

Transformation:

These steps demonstrate the individual math functions that you can apply to your list data without unnesting it:

NOTE: The NUMFORMAT function has been wrapped around each list function to account for any floating-point errors or additional digits in the results.

Sum of all values in the array (list):

Transformation Name New formula Single row formula NUMFORMAT(LISTSUM(myArray2), '#.##') 'arraySum'

Minimum of all values in the array (list):

Transformation Name New formula Single row formula NUMFORMAT(LISTMIN(myArray2), '#.##') 'arrayMin'

Maximum of all values in the array (list):

Transformation Name New formula Single row formula NUMFORMAT(LISTMAX(myArray2), '#.##') 'arrayMax'

Average of all values in the array (list):

Transformation Name New formula Single row formula NUMFORMAT(LISTAVERAGE(myArray2), '#.##') 'arrayAvg'

Variance of all values in the array (list):

Transformation Name New formula Single row formula NUMFORMAT(LISTVAR(myArray2), '#.##') 'arrayVar'

Standard deviation of all values in the array (list):

Transformation Name New formula Single row formula NUMFORMAT(LISTSTDEV(myArray2), '#.##') 'arrayStDv'

Mode (most common value) of all values in the array (list):

Transformation Name New formula Single row formula NUMFORMAT(LISTMODE(myArray2), '#.##') 'arrayMode'

Results:

Results for the first four math functions:

myArray2arrayAvgarrayMaxarrayMinarraySum
["8.29","9.63","14.63","19.63","24.63","29.63","34.63","39.63","44.63"]25.0444.638.29225.33
["8.32","14.01","19.01","24.01","29.01","34.01","39.01","44.01","49.01"]28.9349.018.32260.4
["4.55","9.58","14.58","19.58","24.58","29.58","34.58","39.58","44.58"]24.5844.584.55221.19
["9.22","14.84","19.84","24.84","29.84","34.84","39.84","44.84","49.84"]29.7749.849.22267.94
["8.75","13.36","18.36","23.36","28.36","33.36","38.36","43.36","48.36"]28.448.368.75255.63
["8.47","14.76","19.76","24.76","29.76","34.76","39.76","44.76","49.76"]29.6249.768.47266.55
["4.93","9.99","14.99","19.99","24.99","29.99","34.99","39.99","44.99"]24.9844.994.93224.85
["4.65","14.98","19.98","24.98","29.98","34.98","39.98","44.98","49.98"]29.3949.984.65264.49
["7.80","14.62","19.62","24.62","29.62","34.62","39.62","44.62","49.62"]29.4249.627.8264.76
["9.32","9.96","14.96","19.96","24.96","29.96","34.96","39.96","44.96"]25.4444.969.32229

Results for the statistical functions:

myArray2 arrayModearrayStDvarrayVar
["8.29","9.63","14.63","19.63","24.63","29.63","34.63","39.63","44.63"] 12.32151.72
["8.32","14.01","19.01","24.01","29.01","34.01","39.01","44.01","49.01"] 13.03169.78
["4.55","9.58","14.58","19.58","24.58","29.58","34.58","39.58","44.58"] 12.92166.8
["9.22","14.84","19.84","24.84","29.84","34.84","39.84","44.84","49.84"] 13.02169.46
["8.75","13.36","18.36","23.36","28.36","33.36","38.36","43.36","48.36"] 12.84164.95
["8.47","14.76","19.76","24.76","29.76","34.76","39.76","44.76","49.76"] 13.14172.56
["4.93","9.99","14.99","19.99","24.99","29.99","34.99","39.99","44.99"] 12.92166.93
["4.65","14.98","19.98","24.98","29.98","34.98","39.98","44.98","49.98"] 13.9193.16
["7.80","14.62","19.62","24.62","29.62","34.62","39.62","44.62","49.62"] 13.23175.08
["9.32","9.96","14.96","19.96","24.96","29.96","34.96","39.96","44.96"] 12.21149.17

Since all values are unique within an individual array, there is no most common value in any of them, which yields empty values for the arrayMode column.

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