Aggregation for reporting dashboards in MongoDB - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to group documents by the "category" field.

MongoDB

db.sales.aggregate([{ $group: { _id: "$"[1] } }])

Drag options to blanks, or click blank then click option'

Acategory

Bdate

Camount

Dregion

Attempts:

3 left

💡 Hint

Common Mistakes

Forgetting the dollar sign before the field name.

Using a field that doesn't exist in the documents.

The $group stage groups documents by the specified field. Here, grouping by category collects sales per category.

2fill in blank

medium

Complete the code to calculate the total sales amount per category.

MongoDB

db.sales.aggregate([{ $group: { _id: "$category", totalSales: { $[1]: "$amount" } } }])

Drag options to blanks, or click blank then click option'

Aavg

Bsum

Cmax

Dmin

Attempts:

3 left

💡 Hint

Common Mistakes

Using $avg instead of $sum for totals.

Missing the dollar sign before the operator name.

The $sum operator adds up all values of the specified field, here summing amount per category.

3fill in blank

hard

Fix the error in the pipeline to filter sales greater than 100 before grouping.

MongoDB

db.sales.aggregate([{ $match: { amount: { $[1]: 100 } } }, { $group: { _id: "$category", totalSales: { $sum: "$amount" } } }])

Drag options to blanks, or click blank then click option'

Aeq

Blt

Cgt

Dne

Attempts:

3 left

💡 Hint

Common Mistakes

Using $lt which means less than.

Using $eq which means equal to.

The $gt operator filters documents where amount is greater than 100.

4fill in blank

hard

Fill both blanks to calculate average sales per region for sales above 50.

MongoDB

db.sales.aggregate([{ $match: { amount: { $[1]: 50 } } }, { $group: { _id: "$"[2], avgSales: { $avg: "$amount" } } }])

Drag options to blanks, or click blank then click option'

Agt

Blt

Cregion

Dcategory

Attempts:

3 left

💡 Hint

Common Mistakes

Using $lt instead of $gt for filtering.

Grouping by category instead of region.

First, filter sales with $gt 50, then group by region to find average sales per region.

5fill in blank

hard

Fill all three blanks to create a pipeline that filters sales in 2023, groups by product, and counts sales.

MongoDB

db.sales.aggregate([{ $match: { year: [1] } }, { $group: { _id: "$"[2], count: { $[3]: 1 } } }])

Drag options to blanks, or click blank then click option'

A2023

Bproduct

Csum

Dcategory

Attempts:

3 left

💡 Hint

Common Mistakes

Using a string '2023' instead of number 2023.

Grouping by category instead of product.

Using $avg instead of $sum for counting.

The pipeline filters documents where year is 2023, groups by product, and counts sales by summing 1 for each document.