MongoDB Exercise - Find the count of restaurants for each cuisine

Write a MongoDB query to find the count of restaurants 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([{
  $group: {
    _id: "$cuisine",
    count: {
      $sum: 1
    }
  }
}])

Output:

{ _id: 'Mediterranean', count: 16 },
{ _id: 'Chinese/Cuban', count: 5 },
{ _id: 'Hamburgers', count: 159 },
{ _id: 'Asian', count: 10 },
{ _id: 'Café/Coffee/Tea', count: 1 },
{ _id: 'Japanese', count: 80 },
{ _id: 'Continental', count: 8 },
{ _id: 'Other', count: 4 },
{ _id: 'Indonesian', count: 2 },
{ _id: 'Salads', count: 1 },
{ _id: 'Bangladeshi', count: 1 },
{ _id: 'Mexican', count: 73 },
{ _id: 'French', count: 72 },
{ _id: 'Filipino', count: 3 },
{ _id: 'Greek', count: 25 },
.....

Explanation:

The given query in MongoDB returns a list of documents, each representing a cuisine and the count of restaurants in that cuisine.

The $group stage of the aggregation pipeline creates a new document for each distinct value of cuisine and calculates the count of restaurants in that cuisine using the $sum accumulator operator.

The resulting documents have two fields: _id and count. The _id field contains the distinct value of the cuisine field for each group, and the count field contains the count of restaurants in that cuisine.

Note: This output is generated using MongoDB server version 3.6

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