EXAMPLE - LIST Math Functions
This example describes how to generate random array (list) data and then to apply statistical functions specifically created for arrays.
Functions:
Item | Description |
---|---|
LISTSUM Function | 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. |
LISTMIN Function | Computes the minimum 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. |
LISTMAX Function | Computes the maximum 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. |
LISTAVERAGE Function | Computes the average 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. |
LISTVAR Function | Computes the variance 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. |
LISTSTDEV Function | Computes the standard deviation 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. |
LISTMODE Function | Computes the most common value 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. |
Also:
Item | Description |
---|---|
RANGE Function | Computes an array of integers, from a beginning integer to an end (stop) integer, stepping by a third parameter. |
RAND Function | The |
ROUND Function | Rounds input value to the nearest integer. Input can be an Integer, a Decimal, a column reference, or an expression. Optional second argument can be used to specify the number of digits to which to round. |
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 | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | RANGE(5, 50, 5) |
Parameter: New column name | 'myArray1' |
Then, unpack this array, so you can add a random factor:
Transformation Name | |
---|---|
Parameter: Column | myArray1 |
Parameter: Paths to elements | '[0]', '[1]', '[2]', '[3]', '[4]', '[5]', '[6]', '[7]', '[8]', '[9]' |
Parameter: Remove elements from original | true |
Parameter: Include original column name | true |
Add the randomizing factor. Here, you are adding randomization around individual values: x-1 < x < x+4.
Transformation Name | |
---|---|
Parameter: Columns | myArray1_0~myArray1_8 |
Parameter: Formula | IF(RAND() > 0.5, $col + (5 * RAND()), $col - RAND()) |
To make the numbers easier to manipulate, you can round them to two decimal places:
Transformation Name | |
---|---|
Parameter: Columns | myArray1_0~myArray1_8 |
Parameter: Formula | ROUND($col, 2) |
Renest these columns into an array:
Transformation Name | |
---|---|
Parameter: Columns | myArray1_0, myArray1_1, myArray1_2, myArray1_3, myArray1_4, myArray1_5, myArray1_6, myArray1_7, myArray1_8 |
Parameter: Nest columns to | Array |
Parameter: New column name | 'myArray2' |
Delete the unused columns:
Transformation Name | |
---|---|
Parameter: Columns | myArray1_0~myArray1_8,myArray1 |
Parameter: Action | 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:
Nota
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 | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | NUMFORMAT(LISTSUM(myArray2), '#.##') |
Parameter: New column name | 'arraySum' |
Minimum of all values in the array (list):
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | NUMFORMAT(LISTMIN(myArray2), '#.##') |
Parameter: New column name | 'arrayMin' |
Maximum of all values in the array (list):
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | NUMFORMAT(LISTMAX(myArray2), '#.##') |
Parameter: New column name | 'arrayMax' |
Average of all values in the array (list):
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | NUMFORMAT(LISTAVERAGE(myArray2), '#.##') |
Parameter: New column name | 'arrayAvg' |
Variance of all values in the array (list):
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | NUMFORMAT(LISTVAR(myArray2), '#.##') |
Parameter: New column name | 'arrayVar' |
Standard deviation of all values in the array (list):
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | NUMFORMAT(LISTSTDEV(myArray2), '#.##') |
Parameter: New column name | 'arrayStDv' |
Mode (most common value) of all values in the array (list):
Transformation Name | |
---|---|
Parameter: Formula type | Single row formula |
Parameter: Formula | NUMFORMAT(LISTMODE(myArray2), '#.##') |
Parameter: New column name | 'arrayMode' |
Results:
Results for the first four math functions:
myArray2 | arrayAvg | arrayMax | arrayMin | arraySum |
---|---|---|---|---|
["8.29","9.63","14.63","19.63","24.63","29.63","34.63","39.63","44.63"] | 25.04 | 44.63 | 8.29 | 225.33 |
["8.32","14.01","19.01","24.01","29.01","34.01","39.01","44.01","49.01"] | 28.93 | 49.01 | 8.32 | 260.4 |
["4.55","9.58","14.58","19.58","24.58","29.58","34.58","39.58","44.58"] | 24.58 | 44.58 | 4.55 | 221.19 |
["9.22","14.84","19.84","24.84","29.84","34.84","39.84","44.84","49.84"] | 29.77 | 49.84 | 9.22 | 267.94 |
["8.75","13.36","18.36","23.36","28.36","33.36","38.36","43.36","48.36"] | 28.4 | 48.36 | 8.75 | 255.63 |
["8.47","14.76","19.76","24.76","29.76","34.76","39.76","44.76","49.76"] | 29.62 | 49.76 | 8.47 | 266.55 |
["4.93","9.99","14.99","19.99","24.99","29.99","34.99","39.99","44.99"] | 24.98 | 44.99 | 4.93 | 224.85 |
["4.65","14.98","19.98","24.98","29.98","34.98","39.98","44.98","49.98"] | 29.39 | 49.98 | 4.65 | 264.49 |
["7.80","14.62","19.62","24.62","29.62","34.62","39.62","44.62","49.62"] | 29.42 | 49.62 | 7.8 | 264.76 |
["9.32","9.96","14.96","19.96","24.96","29.96","34.96","39.96","44.96"] | 25.44 | 44.96 | 9.32 | 229 |
Results for the statistical functions:
myArray2 | arrayMode | arrayStDv | arrayVar |
---|---|---|---|
["8.29","9.63","14.63","19.63","24.63","29.63","34.63","39.63","44.63"] | 12.32 | 151.72 | |
["8.32","14.01","19.01","24.01","29.01","34.01","39.01","44.01","49.01"] | 13.03 | 169.78 | |
["4.55","9.58","14.58","19.58","24.58","29.58","34.58","39.58","44.58"] | 12.92 | 166.8 | |
["9.22","14.84","19.84","24.84","29.84","34.84","39.84","44.84","49.84"] | 13.02 | 169.46 | |
["8.75","13.36","18.36","23.36","28.36","33.36","38.36","43.36","48.36"] | 12.84 | 164.95 | |
["8.47","14.76","19.76","24.76","29.76","34.76","39.76","44.76","49.76"] | 13.14 | 172.56 | |
["4.93","9.99","14.99","19.99","24.99","29.99","34.99","39.99","44.99"] | 12.92 | 166.93 | |
["4.65","14.98","19.98","24.98","29.98","34.98","39.98","44.98","49.98"] | 13.9 | 193.16 | |
["7.80","14.62","19.62","24.62","29.62","34.62","39.62","44.62","49.62"] | 13.23 | 175.08 | |
["9.32","9.96","14.96","19.96","24.96","29.96","34.96","39.96","44.96"] | 12.21 | 149.17 |
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.