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

`LISTSUM`

- Sum all values in the array. See LISTSUM Function.`LISTMIN`

- Minimum value of all values in the array. See LISTMIN Function.`LISTMAX`

- Maximum value of all values in the array. See LISTMAX Function.`LISTAVERAGE`

- Average value of all values in the array. See LISTAVERAGE Function.`LISTVAR`

- Variance of all values in the array. See LISTVAR Function.`LISTSTDEV`

- Standard deviation of all values in the array. See LISTSTDEV Function.`LISTMODE`

- Most common value of all values in the array. See LISTMODE Function.

**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` |
---|---|

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 | `Unnest Objects into columns` |
---|---|

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 | `Edit column with formula` |
---|---|

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 | `Edit column with formula` |
---|---|

Parameter: Columns | `myArray1_0~myArray1_8` |

Parameter: Formula | `ROUND($col, 2)` |

Renest these columns into an array:

Transformation Name | `Nest columns into Objects` |
---|---|

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 | `Delete columns` |
---|---|

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:

**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` |
---|---|

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 | `New formula` |
---|---|

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 | `New formula` |
---|---|

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 | `New formula` |
---|---|

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 | `New formula` |
---|---|

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 | `New formula` |
---|---|

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 | `New formula` |
---|---|

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.

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