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$stdDevPop (aggregation)

$stdDevPop

5.0 版本中的更改

Calculates the population standard deviation of the input values. Use if the values encompass the entire population of data you want to represent and do not wish to generalize about a larger population. $stdDevPop ignores non-numeric values.

If the values represent only a sample of a population of data from which to generalize about the population, use $stdDevSamp instead.

$stdDevPop 可在以下阶段使用:

当在 $bucket$bucketAuto$group$setWindowFields 阶段使用时,$stdDevPop 具有以下语法:

{ $stdDevPop: <expression> }

When used in other supported stages, $stdDevPop has one of two syntaxes:

  • $stdDevPop将一个指定表达式作为其操作数:

    { $stdDevPop: <expression> }
  • $stdDevPop将指定表达式的列表作为其操作数:

    { $stdDevPop: [ <expression1>, <expression2> ... ] }

The argument for $stdDevPop can be any 表达式(expression) as long as it resolves to an array.

有关表达式的更多信息,请参阅表达式运算符。

$stdDevPop ignores non-numeric values. If all operands for a $stdDevPop are non-numeric, $stdDevPop returns null.

If the sample consists of a single numeric value, $stdDevPop returns 0.

In the $group and $setWindowFields stages, if the expression resolves to an array, $stdDevPop treats the operand as a non-numerical value and has no effect on the calculation.

在其他支持的阶段:

  • 使用单个表达式作为其操作数,如果表达式解析为大量,则$stdDevPop 会遍历该大量,对大量的数字元素进行操作以返回单个值。

  • 将表达式列表作为其操作数,如果任何表达式解析为大量,$stdDevPop 不会遍历该大量,而是将该大量视为非数字值。

Behavior with values in a $setWindowFields stage 窗口:

  • 忽略窗口中的非数字值、 null值和缺失字段。

  • 如果窗口为空,则返回null

  • 如果窗口包含NaN值,则返回null

  • If the window contains Infinity values, returns null.

  • 如果前面的点都不适用,则返回double值。

Create a collection called users with the following documents:

db.users.insertMany( [
{ _id : 1, name : "dave123", quiz : 1, score : 85 },
{ _id : 2, name : "dave2", quiz : 1, score : 90 },
{ _id : 3, name : "ahn", quiz : 1, score : 71 },
{ _id : 4, name : "li", quiz : 2, score : 96 },
{ _id : 5, name : "annT", quiz : 2, score : 77 },
{ _id : 6, name : "ty", quiz : 2, score : 82 }
] )

The following example calculates the standard deviation of each quiz:

db.users.aggregate( [
{ $group: { _id: "$quiz", stdDev: { $stdDevPop: "$score" } } }
] )

操作返回以下结果:

{ "_id" : 2, "stdDev" : 8.04155872120988 }
{ "_id" : 1, "stdDev" : 8.04155872120988 }

使用以下文档创建名为quizzes的示例collection:

db.quizzes.insertMany( [
{
_id : 1,
scores : [
{ name : "dave123", score : 85 },
{ name : "dave2", score : 90 },
{ name : "ahn", score : 71 }
]
},
{
_id : 2,
scores : [
{ name : "li", quiz : 2, score : 96 },
{ name : "annT", score : 77 },
{ name : "ty", score : 82 }
]
}
] )

The following example calculates the standard deviation of each quiz:

db.quizzes.aggregate( [
{ $project: { stdDev: { $stdDevPop: "$scores.score" } } }
] )

操作返回以下结果:

{ _id : 1, stdDev : 8.04155872120988 }
{ _id : 2, stdDev : 8.04155872120988 }

版本 5.0 中的新增功能

创建cakeSales集合,其中包含加利福尼亚州 ( CA ) 和华盛顿州 ( WA ) 的蛋糕销售情况:

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 $stdDevPop in the $setWindowFields stage to output the population standard deviation of the cake sales quantity for each state:

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

在示例中:

  • partitionBy: "$state"state 对集合中的文档分区CAWA 都有分区。

  • sortBy: { orderDate: 1 }orderDate 升序 (1) 对每个分区中的文档进行排序,因此最早的 orderDate 位于最前面。

  • output sets the stdDevPopQuantityForState field to the quantity population standard deviation value using $stdDevPop that is run in a 文档 window.

    The 窗口 contains documents between an unbounded lower limit and the current document in the output. This means $stdDevPop returns the quantity population standard deviation value for the documents between the beginning of the partition and the current document.

In this example output, the quantity population standard deviation value for CA and WA is shown in the stdDevPopQuantityForState field:

{ _id : 4, type : "strawberry", orderDate : ISODate("2019-05-18T16:09:01Z"),
state : "CA", price : 41, quantity : 162, stdDevPopQuantityForState : 0 }
{ _id : 0, type : "chocolate", orderDate : ISODate("2020-05-18T14:10:30Z"),
state : "CA", price : 13, quantity : 120, stdDevPopQuantityForState : 21 }
{ _id : 2, type : "vanilla", orderDate : ISODate("2021-01-11T06:31:15Z"),
state : "CA", price : 12, quantity : 145, stdDevPopQuantityForState : 17.249798710580816 }
{ _id : 5, type : "strawberry", orderDate : ISODate("2019-01-08T06:12:03Z"),
state : "WA", price : 43, quantity : 134, stdDevPopQuantityForState : 0 }
{ _id : 3, type : "vanilla", orderDate : ISODate("2020-02-08T13:13:23Z"),
state : "WA", price : 13, quantity : 104, stdDevPopQuantityForState : 15 }
{ _id : 1, type : "chocolate", orderDate : ISODate("2021-03-20T11:30:05Z"),
state : "WA", price : 14, quantity : 140, stdDevPopQuantityForState : 15.748015748023622 }