Made changes to names, company name in sample data and made minor visual fixes.
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@ -5,6 +5,7 @@
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```mongodb
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use empDB
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db.createCollection("Employee")
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```
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## Inserting data
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@ -13,131 +14,131 @@ db.createCollection("Employee")
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db.Employee.insertMany([
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{
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Empid: 1,
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Name: { FName: "Rahul", LName: "Sharma" },
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Company_name: "TCS",
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Name: { FName: "Ayush", LName: "Kalaskar" },
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Company_name: "Oscorp",
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Salary: 50000,
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Designation: "Programmer",
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Age: 28,
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Expertise: ["Java", "Spring", "MongoDB"],
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DOB: "1995-04-15",
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Email_id: "rahul.sharma@example.com",
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Email_id: "ayush.kalaskar@oscorp.com",
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Contact: "9876543210",
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Address: [{ PAddr: "123, Street A, Pune", LAddr: "Maharashtra" }]
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},
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{
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Empid: 2,
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Name: { FName: "Sita", LName: "Patel" },
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Company_name: "Infosys",
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Name: { FName: "Himanshu", LName: "Patil" },
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Company_name: "Hammer Industries",
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Salary: 60000,
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Designation: "Developer",
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Age: 30,
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Expertise: ["JavaScript", "React", "Node.js"],
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DOB: "1993-06-25",
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Email_id: "sita.patel@example.com",
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Email_id: "himanshu.patil@hammerindustries.com",
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Contact: "9876543211",
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Address: [{ PAddr: "234, Street B, Bangalore", LAddr: "Karnataka" }]
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},
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{
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Empid: 3,
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Name: { FName: "Anil", LName: "Kumar" },
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Company_name: "Wipro",
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Name: { FName: "Mehul", LName: "Patil" },
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Company_name: "Lex Corp.",
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Salary: 45000,
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Designation: "Tester",
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Age: 29,
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Expertise: ["Selenium", "Python"],
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DOB: "1994-08-12",
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Email_id: "anil.kumar@example.com",
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Email_id: "mehul.patil@lexcorp.org",
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Contact: "9876543212",
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Address: [{ PAddr: "345, Street C, Hyderabad", LAddr: "Telangana" }]
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},
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{
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Empid: 4,
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Name: { FName: "Priya", LName: "Verma" },
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Company_name: "Infosys",
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Name: { FName: "Tanmay", LName: "Machkar" },
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Company_name: "Wayne Industries",
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Salary: 70000,
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Designation: "Project Manager",
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Age: 35,
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Expertise: ["Agile", "Scrum"],
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DOB: "1988-02-20",
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Email_id: "priya.verma@example.com",
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Email_id: "tanmay.machkar@batmobile.com",
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Contact: "9876543213",
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Address: [{ PAddr: "456, Street D, Chennai", LAddr: "Tamil Nadu" }]
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},
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{
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Empid: 5,
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Name: { FName: "Raj", LName: "Singh" },
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Company_name: "TCS",
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Name: { FName: "Rajendra", LName: "Patil" },
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Company_name: "Stark Industries",
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Salary: 32000,
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Designation: "Programmer",
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Age: 27,
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Expertise: ["Java", "Angular"],
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DOB: "1996-03-30",
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Email_id: "raj.singh@example.com",
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Email_id: "rajendra.patil@starkindustries.com",
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Contact: "9876543214",
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Address: [{ PAddr: "567, Street E, Delhi", LAddr: "Delhi" }]
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},
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{
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Empid: 6,
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Name: { FName: "Neha", LName: "Iyer" },
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Company_name: "HCL",
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Name: { FName: "Rajesh", LName: "Patil" },
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Company_name: "Roxonn",
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Salary: 50000,
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Designation: "Designer",
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Age: 32,
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Expertise: ["Photoshop", "Illustrator"],
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DOB: "1991-11-11",
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Email_id: "neha.iyer@example.com",
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Email_id: "rajesh.patil@roxonn.com",
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Contact: "9876543215",
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Address: [{ PAddr: "678, Street F, Kolkata", LAddr: "West Bengal" }]
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},
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{
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Empid: 7,
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Name: { FName: "Karan", LName: "Bansal" },
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Company_name: "TCS",
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Name: { FName: "Prashant", LName: "Kalaskar" },
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Company_name: "Y-Space",
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Salary: 45000,
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Designation: "Tester",
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Age: 26,
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Expertise: ["Selenium", "Java"],
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DOB: "1997-07-07",
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Email_id: "karan.bansal@example.com",
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Email_id: "prashant.kalaskar@y-space.com",
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Contact: "9876543216",
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Address: [{ PAddr: "789, Street G, Pune", LAddr: "Maharashtra" }]
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},
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{
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Empid: 8,
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Name: { FName: "Aarti", LName: "Mehta" },
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Company_name: "Accenture",
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Name: { FName: "Aditya", LName: "Gundeti" },
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Company_name: "SNASA",
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Salary: 80000,
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Designation: "Architect",
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Age: 33,
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Expertise: ["Cloud", "Microservices"],
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DOB: "1990-01-01",
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Email_id: "aarti.mehta@example.com",
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Email_id: "aditya.gundeti@snasa.org",
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Contact: "9876543217",
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Address: [{ PAddr: "890, Street H, Noida", LAddr: "Uttar Pradesh" }]
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},
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{
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Empid: 9,
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Name: { FName: "Vikram", LName: "Yadav" },
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Company_name: "Infosys",
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Name: { FName: "Manoj", LName: "Patil" },
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Company_name: "MEPA",
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Salary: 40000,
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Designation: "Developer",
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Age: 31,
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Expertise: ["C#", ".NET"],
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DOB: "1992-05-05",
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Email_id: "vikram.yadav@example.com",
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Email_id: "manoj.patil@mepa.com",
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Contact: "9876543218",
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Address: [{ PAddr: "901, Street I, Jaipur", LAddr: "Rajasthan" }]
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},
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{
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Empid: 10,
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Name: { FName: "Sneha", LName: "Dutta" },
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Company_name: "Wipro",
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Name: { FName: "Afan", LName: "Shaikh" },
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Company_name: "Vought",
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Salary: 39000,
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Designation: "HR",
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Age: 29,
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Expertise: ["Recruitment", "Employee Relations"],
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DOB: "1994-09-09",
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Email_id: "sneha.dutta@example.com",
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Email_id: "afan.shaikh@vought.com",
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Contact: "9876543219",
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Address: [{ PAddr: "1234, Street J, Ahmedabad", LAddr: "Gujarat" }]
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}
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@ -154,54 +155,63 @@ db.Employee.find({ Designation: "Programmer", Salary: { $gt: 30000 } })
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2. Create a new document if no document contains `{Designation: "Tester", Company_name: "TCS", Age: 25}`:
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```mongodb
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db.Employee.update(
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{ Designation: "Tester", Company_name: "TCS", Age: 25 },
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{ $setOnInsert: { Empid: 11, Name: { FName: "New", LName: "Tester" }, Salary: 30000, DOB: "1998-01-01", Email_id: "new.tester@example.com", Contact: "9876543220", Address: [{ PAddr: "New Address", LAddr: "New City" }] } },
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{ Designation: "Tester", Company_name: "Y-Space", Age: 25 },
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{ $setOnInsert: { Empid: 11, Name: { FName: "Anil", LName: "Salvi" }, Salary: 30000, DOB: "1998-01-01", Email_id: "anil.salvi@y-space.com", Contact: "9876543220", Address: [{ PAddr: "123 Street", LAddr: "Mumbai" }] } },
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{ upsert: true }
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)
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```
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3. Select all documents where Age < 30 or Salary > 40000:
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```mongodb
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db.Employee.find({ $or: [{ Age: { $lt: 30 } }, { Salary: { $gt: 40000 } }] })
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```
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4. Match documents where Address contains city "Pune" and Pin_code "411001":
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```mongodb
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db.Employee.find({ Address: { $elemMatch: { city: "Pune", Pin_code: "411001" } } })
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```
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5. Find all documents with Company_name "TCS" and modify their salary by 2000:
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```mongodb
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db.Employee.updateMany(
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{ Company_name: "TCS" },
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{ Company_name: "Oscorp" },
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{ $inc: { Salary: 2000 } }
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)
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```
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6. Find documents where Designation is not equal to "Developer":
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```mongodb
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db.Employee.find({ Designation: { $ne: "Developer" } })
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```
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7. Find _id, Designation, Address, and Name where Company_name is "Infosys":
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```mongodb
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db.Employee.find(
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{ Company_name: "Infosys" },
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{ Company_name: "Wayne Industries" },
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{ _id: 1, Designation: 1, Address: 1, Name: 1 }
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)
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```
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8. Select all documents where Designation is either "Developer" or "Tester":
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```mongodb
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db.Employee.find({ Designation: { $in: ["Developer", "Tester"] } })
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```
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9. Find all documents with exact match on Expertise array:
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```mongodb
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db.Employee.find({ Expertise: { $all: ['Mongodb', 'Mysql', 'Cassandra'] } })
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```
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10. Drop single documents where Designation is "Developer":
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```mongodb
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db.Employee.deleteMany({ Designation: "Developer" })
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```
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