Dont Forget This

mongoimport --host localhost:27017 --db mydb --collection Restaurants --type json Restaurants.json

Python Packages

pip install pymongo

MongoDB

Write a MongoDB query to display all the documents in the collection restaurants.

db.Rest.find().pretty()

** Write a MongoDB query to display the fields , restaurant_id, name, borough and cuisine for all the documents in the collection restaurant. **

(A) Import Restaurant.json into MongoDb and perform the followingqueries

1. Write a MongoDB query to display all the documents in thecollection restaurants.

QUERY: db.Restaurants.find().pretty()

2. Write a MongoDB query to display the fields , restaurant_id, name, borough and cuisine for all the documents in the collectionrestaurant.

Query : db.Restaurants.find({},{'restaurant_id':1,'name':1,'cuisine':1,'borough':1}).pretty()

3. Write a MongoDB query to display the fields restaurant_id, name, borough and cuisine, but exclude the field _id for all the documents in thecollection restaurant.

Query: db.Restaurants.find({},{'restaurant_id':1,'name':1,'_id':0,'cuisine':1,'borough':1}).pretty()

4. Write a MongoDB query to display the fields restaurant_id, name, borough and zip code, but exclude the field _id for all the documents in the collection restaurant.

Query: db.Restaurants.find({},{'restaurant_id':1,'name':1,'_id':0,'cuisine':1,'address.zipcode':1,'borough':1}).pretty()

5. Write a MongoDB query to display all the restaurant which is in theborough Bronx.

Query: db.Restaurants.find({'borough':'Bronx'}).pretty()

6. Write a MongoDB query to find the restaurant name,borough, longitude and attitude and cuisine for those restaurants which contains 'mon' as three letters somewhere in itsname.

Query:db.Restaurants.find({'name':/mon.*/i},{'name':1,'borough':1,'address.cord':1,'cuisine':1}).pretty()

7. Write a MongoDB query to find the restaurant name,borough, longitude and latitude and cuisine for those restaurants which contain 'Mad' as first three letters of itsname.

Query: db.Restaurants.find({'name':/^Mad/i},{'name':1,'borough':1,'address.cord':1,'cuisine':1}).pretty()

8. Write a MongoDB query to find the restaurants which locatein latitude value less than-95.754168.

Query: db.Restaurants.find({"address.coord":{$lt:-95.754168}}).pretty()

9. Write a MongoDB query to find the restaurant Id, name,borough and cuisine for those restaurants which contain 'Wil' as first three letters for itsname.

Query: db.Restaurants.find({'name':/^Mad/},{},{'restaurant_id':1,'name':1,'borough':1,'cuisine':1}).pretty().

10. Write a MongoDB query to find the restaurant Id, name,borough and cuisine for those restaurants which contain 'ces' as last three letters for itsname.\

Query: db.Restaurants.find({'name':/ces$/},{},{'restaurant_id':1,'name':1,'borough':1,'cuisine':1}).pretty()

11. Write a MongoDB query to find the restaurant Id, name,and cuisine for those restaurants which contains 'Reg' as three letters somewhere in itsname.

Query: db.Restaurants.find({'name':/Reg.*/i},{'restaurant_id':1,'name':1,'cuisine':1}).pretty()

12. Write a MongoDB query to find the restaurants which belong to the borough Bronx and prepared either American or Chinese.

Query db.Restaurants.find({"borough":"Bronx",$or:[{"cuisine":"American "},{"cuisine":"Chinese"}]}).pretty()

13. Write a MongoDB query to find the restaurant Id, name,borough and cuisine for those restaurants which belong to the borough Staten Island or Queens or Bronx or Brooklyn.

Query:db.Restaurants.find({'borough':{$in:['Staten Island','Queens','Bronx','Brookly']}},{'restaurant_id':1,'name':1,'cuisine':1,'borough':1}).pretty()

14. Write a MongoDB query to find the restaurant Id, name,borough and cuisine for those restaurants which are not belonging to the borough Staten Island or Queens or Bronx or Brooklyn.

Query:db.Restaurants.find({'borough':{$nin:['Staten Island','Queens','Bronx','Brookly']}},{'restaurant_id':1,'name':1,'cuisine':1,'borough':1}).pretty()

15. Write a MongoDB query to find the restaurant Id, name,borough and cuisine for those restaurants which achieved a score which is not more than 10.

db.Restaurants.find({"grades.score":{$lt:10}}).pretty()

(B) Create a collection Employee with the following fields

(Eid, EName, Sal, City, Hobbies) where hobbies is an array. Perform the following queries based on the collection.

Use emp

db.Employee.insert({'E_id':1,'E_Name':'Ajay','Sal':20000,'City':'Ahemdabaad','Hobbies':'reading'})

db.Employee.insert({'E_id':2,'E_Name':'Anil','Sal':22000,'City':'Ahemdabaad','Hobbies':['reading','runing']})

db.Employee.insert({'E_id':3,'E_Name':'Dhruw','Sal':30000,'City':'Ahemdabaad','Hobbies':'gaming'})

A. Write a MongoDB query to use sum, avg, min and max expression.

Sum:db.Employee.aggregate({$group:{_id:"$City",totalEmployee:{$sum:1}}})

Avg:db.Employee.aggregate({$group:{_id:"$City",avg_Sal:{$avg:"$Sal"}}})

Max:db.Employee.aggregate({$group:{_id:"$City",avg_Sal:{$avg:"$Sal"}}})

Min: db.Employee.aggregate({$group:{_id:"$City",min_Sal:{$min:"$Sal"}}})

B. Write a MongoDB query to use push and addToSet expression.

**Push: **db.Employee.aggregate([{$group:{_id:"$City",Sal:{$push:"$Sal"}}}])

**AddtoSet :**db.Employee.aggregate([{$group:{_id:"$City",Sal:{$addToSet:"$Sal"}}}])

C. Write a MongoDB query to use first and last expression.

First: db.Employee.aggregate({$group:{_id:"City",E_Name:{$first:"$E_Name"}}})

**Last: **db.Employee.aggregate({$group:{_id:"$City",E_Name:{$last:"$E_Name"}}})

** **

(C) Connect Python with MongoDB and also insert, retrieve, update and delete

documents.

JQUERY

1. Write a jQuery to create fade-in and fade-outeffect.

2. Write a jQuery effect method with a callbackfunction.

3. Write a jQuery to Select elements by class name,id and elementname.

4. Write a jQuery to Create slide-up, slide-down and slide-Toggleeffect.

5. Write a jQuery to insert multiple HTML elements at the beginning and end of the documents.

6. Write a jQuery effect method without a callbackfunction.

7. Write a jQuery to create animation effect.

8. Write a jQuery to perform Method chaining.

JSON

1. Create a JSON file and parseit.

2. Create a JSON file and persist it in any database.