$stdDevSamp (aggregation)

Non-numeric Values非数字值

$stdDevSamp ignores non-numeric values. 忽略非数值。If all operands for a sum are non-numeric, $stdDevSamp returns null.如果求和的所有操作数都是非数字的，$stdDevSamp将返回null。

Single Value单一值

If the sample consists of a single numeric value, $stdDevSamp returns null.如果样本由单个数值组成，$stdDevSamp将返回null。

Array Operand数组操作数

In the $group and $setWindowFields stages, if the expression resolves to an array, $stdDevSamp treats the operand as a non-numerical value.在$group和$setWindowFields阶段中，如果表达式解析为数组，则$stdDevSamp将操作数视为非数值。

In the other supported stages:在其他支持阶段：

• With a single expression as its operand, if the expression resolves to an array, $stdDevSamp traverses into the array to operate on the numerical elements of the array to return a single value.以单个表达式作为其操作数，如果表达式解析为数组，则$stdDevSamp遍历数组，对数组的数字元素进行运算，以返回单个值。
• With a list of expressions as its operand, if any of the expressions resolves to an array, $stdDevSamp does not traverse into the array but instead treats the array as a non-numerical value.以表达式列表作为操作数，如果任何表达式解析为数组，$stdDevSamp不会遍历到该数组中，而是将该数组视为非数值。

Window Values窗口值

Behavior with values in a $setWindowFields stage window:在$setWindowFields阶段窗口中具有值的行为：

• Ignores non-numeric values, null values, and missing fields in a window.忽略窗口中的非数值、null值和缺少的字段。
• If the window is empty, returns null.如果窗口为空，则返回null。
• If the window contains a NaN value, returns null.如果窗口包含NaN值，则返回null。
• If the window contains Infinity values, returns null.如果窗口包含Infinity值，则返回null。
• If none of the previous points apply, returns a double value.如果前面的点都不适用，则返回一个double值。

Use in $group Stage在$group阶段中使用

A collection users contains documents with the following fields:集合users包含具有以下字段的文档：

{_id: 0, username: "user0", age: 20}
{_id: 1, username: "user1", age: 42}
{_id: 2, username: "user2", age: 28}
...

To calculate the standard deviation of a sample of users, following aggregation operation first uses the $sample pipeline to sample 100 users, and then uses $stdDevSamp calculates the standard deviation for the sampled users.为了计算用户样本的标准偏差，以下聚合操作首先使用$sample管道对100个用户进行采样，然后使用$stdDevSamp计算采样用户的标准偏差。

db.users.aggregate(
   [
      { $sample: { size: 100 } },
      { $group: { _id: null, ageStdDev: { $stdDevSamp: "$age" } } }
   ]
)

The operation returns a result like the following:该操作返回如下结果：

{ "_id" : null, "ageStdDev" : 7.811258386185771 }

Use in $setWindowFields Stage在$setWindowFields阶段中使用

Create a cakeSales collection that contains cake sales in the states of California (CA) and Washington (WA):创建一个包含加利福尼亚州（CA）和华盛顿州（WA）蛋糕销售的cakeSales系列：

db.cakeSales.insertMany( [
   { _id: 0, type: "chocolate", orderDate: new Date("2020-05-18T14:10:30Z"),
     state: "CA", price: 13, quantity: 120 },
   { _id: 1, type: "chocolate", orderDate: new Date("2021-03-20T11:30:05Z"),
     state: "WA", price: 14, quantity: 140 },
   { _id: 2, type: "vanilla", orderDate: new Date("2021-01-11T06:31:15Z"),
     state: "CA", price: 12, quantity: 145 },
   { _id: 3, type: "vanilla", orderDate: new Date("2020-02-08T13:13:23Z"),
     state: "WA", price: 13, quantity: 104 },
   { _id: 4, type: "strawberry", orderDate: new Date("2019-05-18T16:09:01Z"),
     state: "CA", price: 41, quantity: 162 },
   { _id: 5, type: "strawberry", orderDate: new Date("2019-01-08T06:12:03Z"),
     state: "WA", price: 43, quantity: 134 }
] )

This example uses $stdDevSamp in the $setWindowFields stage to output the sample standard deviation of the quantity values of the cake sales for each state:本例使用$setWindowFields阶段中的$stdDevSamp来输出每个state蛋糕销售quantity值的样本标准差：

db.cakeSales.aggregate( [
   {
      $setWindowFields: {
         partitionBy: "$state",
         sortBy: { orderDate: 1 },
         output: {
            stdDevSampQuantityForState: {
               $stdDevSamp: "$quantity",
               window: {
                  documents: [ "unbounded", "current" ]
               }
            }
         }
      }
   }
] )

In the example:在示例中：

• partitionBy: "$state" partitions the documents in the collection by state. 按state对集合中的文档进行分区。There are partitions for CA and WA.CA和WA有分区。
• sortBy: { orderDate: 1 } sorts the documents in each partition by orderDate in ascending order (1), so the earliest orderDate is first.按orderDate按升序（1）对每个分区中的文档进行排序，因此最早的orderDate是第一个。

• output sets the stdDevSampQuantityForState field to the sample standard deviation of the quantity values using $stdDevSamp that is run in a documents window.output使用在文档窗口中运行的$stdDevSamp将stdDevSampQuantityForState字段设置为quantity值的样本标准偏差。

  The window contains documents between an unbounded lower limit and the current document in the output. 该窗口包含在unbounded下限和输出中的current文档之间的文档。This means $stdDevSamp returns the sample standard deviation of the quantity values for the documents between the beginning of the partition and the current document.这意味着$stdDevSamp返回分区开始和当前文档之间文档quantity值的样本标准差。

In this output, the sample standard deviation quantity value for CA and WA is shown in the stdDevSampQuantityForState field:在该输出中，CA和WA的样本标准偏差数量值显示在stdDevSampQuantityForState字段中：

{ "_id" : 4, "type" : "strawberry", "orderDate" : ISODate("2019-05-18T16:09:01Z"),
  "state" : "CA", "price" : 41, "quantity" : 162, "stdDevSampQuantityForState" : null }
{ "_id" : 0, "type" : "chocolate", "orderDate" : ISODate("2020-05-18T14:10:30Z"),
  "state" : "CA", "price" : 13, "quantity" : 120, "stdDevSampQuantityForState" : 29.698484809834994 }
{ "_id" : 2, "type" : "vanilla", "orderDate" : ISODate("2021-01-11T06:31:15Z"),
  "state" : "CA", "price" : 12, "quantity" : 145, "stdDevSampQuantityForState" : 21.1266025033211 }
{ "_id" : 5, "type" : "strawberry", "orderDate" : ISODate("2019-01-08T06:12:03Z"),
  "state" : "WA", "price" : 43, "quantity" : 134, "stdDevSampQuantityForState" : null }
{ "_id" : 3, "type" : "vanilla", "orderDate" : ISODate("2020-02-08T13:13:23Z"),
  "state" : "WA", "price" : 13, "quantity" : 104, "stdDevSampQuantityForState" : 21.213203435596427 }
{ "_id" : 1, "type" : "chocolate", "orderDate" : ISODate("2021-03-20T11:30:05Z"),
  "state" : "WA", "price" : 14, "quantity" : 140, "stdDevSampQuantityForState" : 19.28730152198591 }