本文為英文版的機器翻譯版本，如內容有任何歧義或不一致之處，概以英文版為準。
$stdDevSamp
8.0.1 版的新功能。
Amazon DocumentDB 中的$stdDevSamp運算子會計算數值的範例標準差。作為累積器，它會計算彙總管道$group階段中群組內文件之間的範例標準差。做為表達式，它會計算數字陣列的樣本標準差。範例標準差使用 N-1 做為除數 (Bessel 的校正）。會忽略非數值。如果少於兩個數值，則會傳回 null。
參數
範例 (MongoDB Shell)
下列範例示範如何使用 $stdDevSamp 運算子來計算每個主題的分數範例標準差。
建立範例文件
db.scores.insertMany([
{ subject: "math", score: 80 },
{ subject: "math", score: 90 },
{ subject: "math", score: 85 },
{ subject: "math", score: 95 },
{ subject: "science", score: 70 },
{ subject: "science", score: 75 },
{ subject: "science", score: 80 },
{ subject: "science", score: 85 }
]);
查詢範例
db.scores.aggregate([
{ $group: {
_id: "$subject",
stdDev: { $stdDevSamp: "$score" }
}}
]);
輸出
[
{ "_id": "math", "stdDev": 6.454972243679028 },
{ "_id": "science", "stdDev": 6.454972243679028 }
]
表達式用量範例 (MongoDB Shell)
運算$stdDevSamp子也可以用作$project階段內的表達式，以計算陣列欄位的範例標準差。
建立範例文件
db.experiments.insertMany([
{ _id: 1, measurements: [10, 12, 14, 16, 18] },
{ _id: 2, measurements: [5, 5, 5, 5, 5] },
{ _id: 3, measurements: [2, 4, 6, 8, 10] }
]);
查詢範例
db.experiments.aggregate([
{ $project: {
stdDev: { $stdDevSamp: "$measurements" }
}}
]);
輸出
[
{ "_id": 1, "stdDev": 3.1622776601683795 },
{ "_id": 2, "stdDev": 0 },
{ "_id": 3, "stdDev": 3.1622776601683795 }
]
程式碼範例
若要檢視使用 $stdDevSamp 運算子的程式碼範例，請選擇您要使用的語言標籤。下列範例顯示累積器用量 （在 中$group) 和表達式用量 （在 中$project)：
- Node.js
-
const { MongoClient } = require('mongodb');
async function example() {
const uri = 'mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false';
const client = new MongoClient(uri);
try {
await client.connect();
const db = client.db('test');
// Accumulator usage: stdDevSamp across grouped documents
const scores = db.collection('scores');
const accumulatorResult = await scores.aggregate([
{ $group: {
_id: "$subject",
stdDev: { $stdDevSamp: "$score" }
}}
]).toArray();
console.log('Accumulator result:', accumulatorResult);
// Expression usage: stdDevSamp of an array field
const experiments = db.collection('experiments');
const expressionResult = await experiments.aggregate([
{ $project: {
stdDev: { $stdDevSamp: "$measurements" }
}}
]).toArray();
console.log('Expression result:', expressionResult);
} finally {
await client.close();
}
}
example();
- Python
-
from pymongo import MongoClient
def example():
client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
try:
db = client['test']
# Accumulator usage: stdDevSamp across grouped documents
scores = db['scores']
accumulator_result = list(scores.aggregate([
{ '$group': {
'_id': '$subject',
'stdDev': { '$stdDevSamp': '$score' }
}}
]))
print('Accumulator result:', accumulator_result)
# Expression usage: stdDevSamp of an array field
experiments = db['experiments']
expression_result = list(experiments.aggregate([
{ '$project': {
'stdDev': { '$stdDevSamp': '$measurements' }
}}
]))
print('Expression result:', expression_result)
finally:
client.close()
example()
