Python MongoDB - $group (aggregation)
Last Updated :
02 Jul, 2025
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In PyMongo, the aggregate() method processes data through a pipeline of stages to produce aggregated results. One key stage is $group, which groups documents based on a specified identifier like a field name and applies accumulator operations e.g., $sum, $avg, $max. It then outputs a new set of documents representing the grouped and processed data.
Syntax
{
$group: {
_id: <grouping field>,
<newField>: { <accumulator>: <expression> }
}
}
Parameters:
- _id: The field to group the documents by (e.g., group by "product name" or "category").
- <newField>: The result field where you store the output (like total, average, etc.).
- <accumulator>: The operation to perform on each group.
- <expression>: The value to apply the operation on (e.g., the "amount" field).
Here is our sample data.
from pymongo import MongoClient
c = MongoClient("mongodb://localhost:27017/")
db = c['grpDB']
col = db['sales']
data = [
{"_id": 1, "user": "Amit", "product": "Pen", "amount": 5},
{"_id": 2, "user": "Drew", "product": "Pencil", "amount": 3},
{"_id": 3, "user": "Amit", "product": "Notebook", "amount": 15},
{"_id": 4, "user": "Cody", "product": "Pen", "amount": 7},
{"_id": 5, "user": "Drew", "product": "Notebook", "amount": 12},
{"_id": 6, "user": "Cody", "product": "Eraser", "amount": 2},
{"_id": 7, "user": "Amit", "product": "Pen", "amount": 10}
]
col.delete_many({})
col.insert_many(data)
print("Data inserted.")
Output
Data inserted.
Explanation:
- MongoClient() connects to the local server and selects grpDB.sales.
- insert_many(data) loads sample orders into the sales collection.
- delete_many({}) clears previous data to avoid duplicates.
Examples
Example 1: Average amount per user
from pymongo import MongoClient
c = MongoClient("mongodb://localhost:27017/")
db = c['groupExampleDB']
collection = db['sales']
res = collection.aggregate([
{
"$group": {
"_id": "$user",
"average_amount": { "$avg": "$amount" }
}
}
])
for doc in res:
print(doc)
Output
Explanation:
- $group groups documents by user.
- $avg calculates average amount spent by each user.
Example 2: Total amount per product
from pymongo import MongoClient
c = MongoClient("mongodb://localhost:27017/")
db = c['grpDB']
col = db['sales']
res = col.aggregate([
{
"$group": {
"_id": "$product",
"total_amount": { "$sum": "$amount" }
}
}
])
for doc in res:
print(doc)
Output
Explanation:
- $group organizes documents by product.
- $sum computes the total sales amount for each product.
Example 3: Max amount spent per user
from pymongo import MongoClient
c = MongoClient("mongodb://localhost:27017/")
db = c['grpDB']
col = db['sales']
res = col.aggregate([
{
"$group": {
"_id": "$user",
"max_spent": { "$max": "$amount" }
}
}
])
for doc in res:
print(doc)
Output
Explanation:
- $group groups orders by user.
- $max finds the highest amount spent by each user in a single transaction.
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