# LISTSUM 函式

## 基本用法

`derive type:single value:LISTSUM([0,0,2,4,6,8,10,12,14,16,18,20]) as:'myArraySum'`

`derive type:single value:LISTSUM(myArray) as:'myArraySum'`

## 語法

`derive type:single value:LISTSUM(array_ref)`

array_ref陣列陣列常值、含有陣列之資料欄的參照，或傳回陣列的函式

### array_ref

• 如果輸入了無效的數字陣列，則會傳回空值。
• 在輸入陣列中，數字以外的值皆不列入計算。
• 不支援多個資料欄和萬用字元。

`myArray`

## 範例

### 範例 - 清單 (陣列) 的數學函式

• `LISTSUM` - 對陣列的所有值進行加總。請參閱 LISTSUM 函式一文。
• `LISTMIN` - 陣列所有值的最小值。請參閱 LISTMIN 函式一文。
• `LISTMAX` - 陣列所有值的最大值。請參閱 LISTMAX 函式一文。
• `LISTAVERAGE` - 陣列所有值的平均值。請參閱 LISTAVERAGE 函式一文。
• `LISTVAR` - 陣列所有值的變異數。請參閱 LISTVAR 函式一文。
• `LISTSTDEV` - 陣列所有值的標準差。請參閱 LISTSTDEV 函式一文。
• `LISTMODE` - 陣列所有值中最常見的值。請參閱 LISTMODE 函式一文。

`derive type: single value: RANGE(5, 50, 5) as: 'myArray1'`

`unnest col: myArray1 keys: '[0]', '[1]', '[2]', '[3]', '[4]', '[5]', '[6]', '[7]', '[8]', '[9]' pluck: true markLineage: true`

`set col: myArray1_0~myArray1_8 value: IF(RAND() > 0.5, \$col + (5 * RAND()), \$col - RAND())`

`set col: myArray1_0~myArray1_8 value: ROUND(\$col, 2)`

`nest col: myArray1_0, myArray1_1, myArray1_2, myArray1_3, myArray1_4, myArray1_5, myArray1_6, myArray1_7, myArray1_8 into: array as: 'myArray2'`

`drop col: myArray1_0~myArray1_8,myArray1 action: Drop`

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"]

`derive type: single value: NUMFORMAT(LISTSUM(myArray2), '#.##') as: 'arraySum'`

`derive type: single value: NUMFORMAT(LISTMIN(myArray2), '#.##') as: 'arrayMin' `

` derive type: single value: NUMFORMAT(LISTMAX(myArray2), '#.##') as: 'arrayMax'`

` derive type: single value: NUMFORMAT(LISTAVERAGE(myArray2), '#.##') as: 'arrayAvg'`

` derive type: single value: NUMFORMAT(LISTVAR(myArray2), '#.##') as: 'arrayVar'`

` derive type: single value: NUMFORMAT(LISTSTDEV(myArray2), '#.##') as: 'arrayStDv'`

` derive type: single value: NUMFORMAT(LISTMODE(myArray2), '#.##') as: 'arrayMode'`

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

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