diff --git a/queries.js b/queries.js
index 99f09c5..47af6b0 100644
--- a/queries.js
+++ b/queries.js
@@ -4,4 +4,120 @@ print('Employees')
 
 // List all the employees.
 print('1. List all Employees')
-db.employees.find({}).forEach(printjsononeline)
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+
+// Test:
+
+// List all the employees.
+// Find the employee with whose name is Steve.
+// Find all employees whose age is greater than 30.
+// Find the employee whose extension is 2143.
+// Find all employees that are over 30.
+// Find all employees that are less than or equal to 30.
+// Find all the employees whose favorite food is pizza.
+// Change Willy’s personal phone number to "93-123-45-67".
+// Change Bob’s privilege to normal user.
+// Find all employees whose favorite artist is equal to Picasso.
+// Delete the user John.
+
+db.employees.find({}).forEach(printjsononeline)
+
+db.Employees.find({age: {$gt: 30}});
+
+db.Employees.find({name:"Steve"});
+
+db.Employees.find({age: {$gt: 30}});
+
+db.Employees.find({"phone.ext": "2143"});
+
+db.Employees.find({age: {$gte: 30}});
+
+db.Employees.find({age: {$lte: 30}});
+
+db.Employees.find({"favorites.food": "pizza"});
+
+db.Employees.updateOne({name:"Willy"}, {$set:{"phone.personal": "93-123-45-67"}});
+
+db.Employees.updateOne({name:"Bob"}, {$set:{"privileges": "normal user"}});
+
+db.Employees.find({"favorites.artist": "Picasso"});
+
+db.Employees.deleteOne({name:"John"});
+
+// Test:
+
+// List all the restaurants.
+// Find all the restaurants and display only the fields restaurant_id, name, borough and cuisine.
+// Find all the restaurants and display only the fields restaurant_id, name, borough and zip code.
+// Find the restaurants which are in the borough Bronx.
+// Find the restaurants which are in the borough Brooklyn with Steak cuisine.
+// Find the restaurants which have achieved a score bigger than 90.
+// Find the restaurants that do not prepare any Bakery cuisine and with a grade score equal or bigger than 70.
+// Find the restaurants which do not prepare any Chinese cuisine and have achieved a grade point A which do not belong to the borough Manhattan.
+// Update restaurants with 'American ' cuisine to 'American' (without the space!!!)
+// Update Morris Park Bake Shop address street to Calle falsa 123.
+// Delete all the restaurants with address zipcode 10466.
+
+db.restaurants.find();
+
+db.restaurants.find({}, {"_id": 1, "name": 1, "borough": 1, "cuisine":1});
+
+db.restaurants.find({}, {"_id": 1, "name": 1, "borough": 1, "address.zipcode":1});
+
+db.restaurants.find({borough:"Bronx"});
+
+db.restaurants.find({borough:"Brooklyn", cuisine:"Steak"});
+
+db.restaurants.find({'grades.score': {$gt: 90}});
+
+db.restaurants.find({$and:[{cuisine:{$ne: "Bakery"}}, {'grades.score': {$gte: 70}}]});
+
+db.restaurants.find({$and:[{cuisine:{$ne:"Chinese"}}, {"grades.grade": "A"}, {borough:{$ne:"Manhattan"}}]});
+
+db.restaurants.updateMany({cuisine: "American "}, { $set: {cuisine: "American"}});
+
+db.restaurants.updateOne({name: "Morris Park Bake Shop"}, { $set: {'address.street': 'Calle falsa 123'}});
+
+db.restaurants.deleteMany({'address.zipcode': '10466'});
+
+
+
+// Test:
+
+// Find all the companies that include 'Facebook' on the name field.
+// Let's do it one more together:
+// Find all the companies which category_code is 'web'. Retrive only their name field:
+// Find all the companies named "Twitter", and retrieve only their name, category_code and founded_year fields.
+// Find all the companies who have web as their category_code, but limit the search to 50 companies.
+// Find all the companies which category_code is 'enterprise' and have been founded in 2005. Retrieve only the name, category_code and founded_year fields.
+// Find all the companies that have been founded on the 2000 or have 20 employees. Sort them descendingly by their number_of_employees.
+// Find all the companies that do not include web nor social on their category_code. Limit the search to 20 documents and retrieve only their name and category_code.
+// Find all the companies that were not founded on 'June'. Skip the first 50 results and retrieve only the founded_month and name fields.
+// Find all the companies that have 50 employees, but do not correspond to the 'web' category_code.
+// Find all the companies that have been founded on the 1st of the month, but does not have either 50 employees nor 'web' as their category_code. Retrieve only the founded_day and name and limit the search to 5 documents.
+// Find all the companies which the price_amount of the acquisition was 40.000.000. Sort them by name.
+// Find all the companies that have been acquired on January of 2014. Retrieve only the acquisition and name fields.
+
+
+db.companies.find({name: "Facebook"});
+
+db.companies.find({category_code: "web"}, {"name": 1});
+
+db.companies.find({name: "Twitter"}, {"name": 1, "category_code": 1, "founded_year": 1});
+
+db.companies.find({category_code: "web"}).limit(50);
+
+db.companies.find({$and: [{category_code: "enterprise", founded_year: {$eq: 2005}}]}, {name: 1, category_code: 1, founded_year: 1});
+
+db.companies.find({$or:[{founded_year: {$eq: 2005}}, {number_of_employees: {$eq: 20}}]}, {"founded_year": 1, "number_of_employees": 1}).sort({"number_of_employees": -1})
+
+db.companies.find({$nor:[{category_code: 'web'}, {category_code: "social"}]}, { "name": 1, "category_code": 1}).limit(20);
+
+db.companies.find({founded_month: 6}, {"founded_month":1, "name": 1}).skip(50);
+
+db.companies.find({$and: [{number_of_employees: {$eq: 50}, category_code: {$ne: "web"}}]});
+
+db.companies.find({$and:[{founded_day: 1,number_of_employees: {$lt:50}, category_code: {$ne: "web"}}]}, {"founded_day": 1, "name": 1}).limit(5);
+
+db.companies.find({"acquisition.price_amount": {$eq: 40000000}}, {name: 1}).sort({"name": 1});
+
+db.companies.find({$and: [{"acquisition.acquired_month": {$eq: 1}}, {"acquisition.acquired_year": {$eq: 2014}}]}, {_id: 0, name: 1, "acquisition": 1})
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