MongoDB Exercise - Find the average score for each cuisine

Write a MongoDB query to find the average score for each cuisine.

Structure of 'restaurants' collection :

{
  "address": {
     "building": "1007",
     "coord": [ -73.856077, 40.848447 ],
     "street": "Morris Park Ave",
     "zipcode": "10462"
  },
  "borough": "Bronx",
  "cuisine": "Bakery",
  "grades": [
     { "date": { "$date": 1393804800000 }, "grade": "A", "score": 2 },
     { "date": { "$date": 1378857600000 }, "grade": "A", "score": 6 },
     { "date": { "$date": 1358985600000 }, "grade": "A", "score": 10 },
     { "date": { "$date": 1322006400000 }, "grade": "A", "score": 9 },
     { "date": { "$date": 1299715200000 }, "grade": "B", "score": 14 }
  ],
  "name": "Morris Park Bake Shop",
  "restaurant_id": "30075445"
}

Query:

db.restaurants.aggregate([
  {
    $unwind: "$grades"
  },
  {
    $group: {
      _id: "$cuisine",
avgScore: { $avg: "$grades.score" }
    }
  }
])

Output:

_id: 'Korean', avgScore: 14.106194690265486 },
{ _id: 'Ethiopian', avgScore: 10 },
{ _id: 'Hamburgers', avgScore: 9.125854993160054 },
{ _id: 'Egyptian', avgScore: 12.727272727272727 },
{ _id: 'Soups & Sandwiches', avgScore: 8.394736842105264 },
{ _id: 'English', avgScore: 9.714285714285714 },
{ _id: 'Chicken', avgScore: 10.46 },
{ _id: 'Italian', avgScore: 12.212588310854207 },
{ _id: 'Pizza', avgScore: 11.489733840304183 },
{ _id: 'Steak', avgScore: 10.019607843137255 },
{ _id: 'Afghan', avgScore: 9.7 },
{ _id: 'Filipino', avgScore: 9.6875 },
.....

Explanation:

The said query in MongoDB provides a convenient way to calculate the average score for each cuisine in the restaurants collection.

The $unwind stage is used to break down the grades array and creates a separate document for each element in the grades array.

The $group stage is used to group the documents by the cuisine field and calculate the average score for each group. The $avg operator is used to calculate the average of the score field in the grades subdocument for each group.

Note: This output is generated using MongoDB server version 3.6

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