Update Q1 and Q2 to Q5 requirements

app.py

@@ -20,7 +20,143 @@
         }
 }
 
+aggregation_1 = db.books_selling_data.aggregate([stage_1])
+
+
+# print(list(aggregation_1))
+
 # 2. For books with more than 15000 total copies sold, return all the titles in a single array
+
+stage_2_1 = {
+    "$group":
+        {
+            "_id": "$isbn",
+            "total_copies": { "$sum": "$copies_sold" }
+
+        }
+}
+
+stage_2_2 = {
+    "$match":
+        {
+            "total_copies_sold": { "$gt": 15000 }
+        }
+
+}
+
+stage_2_3 = {
+    "$lookup": {
+        "from": "books",
+        "localField": "_id",
+        "foreignField": "isbn",
+        "as": "book_info"
+    }
+}
+
+stage_2_4 = {
+    "$project": {
+        "_id": 0,
+        "total_copies_sold": 0,
+        "title": 1
+    }
+}
+
+
+aggregation_2 = db.books_selling_data.aggregate([stage_2_1, stage_2_2, stage_2_3, stage_2_4])
+
+# print(list(aggregation_2))
+
 # 3. Find the number of books by John Doe, sorted by isbn (but isbn is not returned)
+
+stage_3_1 = {
+    "$match": {
+        "author": "John Doe"
+    }
+}
+
+
+stage_3_2 = {
+    "$sort": {
+        "$isbn": 1
+    }
+}
+
+stage_3_3 = {
+    "$project": {
+        "isbn": 0, 
+        "title": 1, 
+        "author": 1
+    }
+}
+
+
+
+aggregation_3 = db.books.aggregate([stage_3_1, stage_3_2, stage_3_3])
+
+# print(len(list(aggregation_3)))
+
 # 4. Return the price per book for each order
-# 5. Return the average price per book for each order supplied from titan (we want to sum up all the total copies sold and total price of all copies sold where titan is a supplier, but average.like weighted average for the number of bookd)
+
+
+stage_4_1 = {
+    "$addFields": {
+        "price_per_book": {
+            "$round": [{"$divide": ["$total_price", "$copies_sold"]}, 2]
+            }
+    }
+}
+
+stage_4_2 = {
+    "$project": {
+        "_id": 0,
+        "order_id": 1,
+        "copies_sold": 0,
+        "total_price": 0,
+        "supplier": 0
+    }
+}
+
+
+aggregation_4 = db.books_selling_data.aggregate([stage_4_1, stage_4_2])
+
+# print(list(aggregation_4))
+
+# 5. Return the average price per book for each order supplied from titan (we want to sum up all the total copies sold and total price of all copies sold where titan is a supplier, but average.like weighted average for the number of bookd)
+
+stage_5_1 = {
+    "$unwind": "$supplier"
+}
+
+stage_5_2 = {
+    "$group": {
+        "_id": "$supplier",
+        "overall_sale": {"$sum": "$copies_sold"},
+        "overall_price": {"$sum": "total_price"}
+    }
+}
+
+stage_5_3 = {
+    "$match": {
+        "supplier": "titan"
+    }
+}
+
+
+
+stage_5_4 = {
+    "addFields": {
+            "average_price_per_book": {"round": [{"divide":["overall_price", "overall_sale"]}, 2]}
+        }
+}
+
+stage_5_5 = {
+    "$project": {
+        "$_id": 1,
+        "$average_price_per_book": 1
+    }
+}
+
+
+aggregation_5 = db.books_selling_data.aggregate([stage_5_1, stage_5_2, stage_5_3, stage_5_4, stage_5_5])
+
+# print(list(aggregation_5))