Section - A
1. LAN
2. Data Theft
3. Unused Old computer
4. 12
5. 26000
6. Free
7. ii - SELECT COUNT (FEE) FROM STUDENT;
8. ROUND()
9. MIN()
10. iv - S1.tail()
11. student_df.sort_values(by=["marks"])
12. All of these
13. Avast
14.Dayname()
15. Patent
16. Digital Footprint
17. B
18. B
Section - B
19.
Static Website:
Static website is the basic type of website that is easy to create.
A static site is a website built with pages of static content, or plain html, JavaScript, or CSS code.
Dynamic Website:
Dynamic website is a collection of dynamic web pages whose content changes dynamically.
It accesses content from a database or Content Management System (CMS). Therefore, when you alter or update the content of the database, the content of the website is also altered or updated.
OR
Four networking goals are:
Resource sharing.
Reliability.
Cost-effective.
Fast data sharing.
20.
SELECT house, count(*) FROM Student group by house having house='Green' or house='Orange';
21.
Having Clause
The HAVING clause used in SQL with aggregate functions because the WHERE keyword cannot be used with aggregate functions.
Having clause is only used with the SELECT clause.
Having clause is generally used after GROUP BY.
SELECT column_name(s) FROM table_name WHERE condition GROUP BY column_name(s) HAVING condition ORDER BY column_name(s);
Example:
SELECT COUNT(CustomerID), Country FROM Customers GROUP BY Country HAVING COUNT(CustomerID) > 5;
22.
import pandas as pd
D={'H1':40,'H2':30,'H3':35,'H4':45}
A=pd.Series(D)
print(A)
H1 40
H2 30
H3 35
H4 45
dtype: int64
23.
IPR
Intellectual property rights are the rights given to persons over the creations of their minds.
There are four main types of intellectual property rights, including patents, trademarks, copyrights, and trade secrets.
OR
Net Etiquettes.
- Be respectful.
- Be aware of what you are commenting on social media.
- Be careful with humor and sarcasm.
- You should take care of how you are sharing your data and who can see this.
- Friend requests and group invites should be checked before you accept them.
24.
0 True
1 False
2 True
3 False
dtype: bool
25.
(a) Digital Footprints
A digital footprint is data that is left behind when users have been online. There are two types of digital footprints which are passive and active. A passive footprint is made when information is collected from the user without the person knowing this is happening. An active digital footprint is where the user has deliberately shared information about themselves either by using social media sites or by using websites.
(b) Phishing
Phishing is described as a fraudulent activity that is done to steal confidential user information such as credit card numbers, login credentials, and passwords. Phishing is described as a fraudulent activity that is done to steal confidential user information such as credit card numbers, login credentials, and passwords
26.
(I) Select Tname, Salary from Teacher;
(II) Select sum(salary) from Teacher;
(III) Select count(NoofPeriod) from Teacher;
OR
(I) ALL THE BEST
(II) INFOR
(III) INDIA
27.
import pandas as pd
D=[[110,'Gurman',98],[111,'Rajveer',95],[112,'Samar',96],[1113,'Yuvraj',88]]
DF=pd.DataFrame(D,columns=['Id','Name','Marks'])
print(DF)
Id Name Marks
0 110 Gurman 98
1 111 Rajveer 95
2 112 Samar 96
3 1113 Yuvraj 88
28.
import numpy as np
import pandas as pd
D={'Name':['Item1','Item2','Item3','Item4'],'Price':[150,180,225,500]}
DF=pd.DataFrame(D)
print(DF)
DF['Special_Price']=[135,150,200,440]
print(DF)
DF.loc[4] = ['The Secret',800,500]
print(DF)
del DF['Special_Price']
print(DF)
29
(I) - Cyber Bullying
(II) Report to local police station and cyber cell, E-FIR, Inform to parents
(III) IT Act 2000
OR
Free and open-source software (FOSS) is a term used to refer to groups of software consisting of both free software and open-source software where anyone is freely licensed to use, copy, study, and change the software in any way, and the source code is openly shared so that people are encouraged to voluntarily improve the design of the software
Example of FOSS:
GNU/Linux, Mozilla Firefox, VLC media player,SugarCRM,GIMP,VNC,Apache web server,LibreOffice.
30.
(I) select * from emp;
(II) select ename, sal, deptno from emp where comm is null;
(III) select empno, ename, sal, sal * 12 as 'Annual Salary' from emp;
31.
(I) SELECT MID("INDIASHINING", 7,7);
(II) SELECT INSTR("WELCOMEWORLD", 'COME') ;
(III) SELECT ROUND(23.78,1);
(IV) SELECT MOD(100,9);
(V) SELECT TRIM(userid) from users;
OR
UCASE()
The UCASE() function converts a string to upper-case.
Syntax
UCASE(text)
Ex:
SELECT UCASE("ram");
RAM
TRIM()
The TRIM() function removes leading and trailing spaces from a string.
Syntax
TRIM(string)
SELECT TRIM(' RAM ');
RAM
MID()
The MID() function extracts a substring from a string (starting at any position).
Syntax
MID(string, start, length)
SELECT MID("Manmohan", 5, 3);
oha
DAYNAME()
The DAYNAME() function returns the weekday name for a given date.
Syntax
DAYNAME(date)
SELECT DAYNAME("2022-12-30");
Friday
POWER()
The POWER() function returns the value of a number raised to the power of another number.
Syntax
POWER(x, y)
SELECT POWER(4, 2);
16
Q: 32
(I) Server should be installed in Admin department as it has maximum number of computers.
(II)
(III) Hub/Switch
(IV) Dynamic
(V) Video Conferencing
Q: 33.import matplotlib.pyplot as plt
MT=['Gold','Silver','Bronze']
M=[20,15,17.5]
plt.bar(MT, M)
plt.xlabel('Medal Type')
plt.ylabel('Medal')
plt.title('Indian Medal Tally in Olympics')
plt.show()
plt.savefig("abc.png")
OR
import matplotlib.pyplot as plt
Week=[1,2,3,4]
Avg_week_temp=[40,42,38,44]
plt.plot(Week, Avg_week_temp)
plt.show()
(I) select Lcase(CName)/lower(CName) from cloth;
(II) select min(price) from cloth;
(III) select count(size) from cloth where size = 'M';
OR
Select count(CName) from cloth where year(DOP) = '2022';
Q: 35
import numpy as np
import pandas as pd
D={'School':{'CO1':'PPS','CO2':'JPS','CO3':'GPS','CO4':'MPS','CO5':'BPS'},
'Tot_students':{'CO1':40,'CO2':30,'CO3':20,'CO4':18,'CO5':28},
'Topper':{'CO1':32,'CO2':18,'CO3':18,'CO4':10,'CO5':20},
'First_Runnerup':{'CO1':8,'CO2':12,'CO3':2,'CO4':8,'CO5':8}
}
DF=pd.DataFrame(D)
print(DF)
School Tot_students Topper First_Runnerup
CO1 PPS 40 32 8
CO2 JPS 30 18 12
CO3 GPS 20 18 2
CO4 MPS 18 10 8
CO5 BPS 28 20 8
print(DF.shape)
(5, 4)
print(DF[2:4])
School Tot_students Topper First_Runnerup
CO3 GPS 20 18 2
CO4 MPS 18 10 8
print(DF.iloc[2:5,2:3])
Topper
CO3 18
CO4 10
CO5 20
print(DF['Tot_students']-DF['First_Runnerup'])
CO1 32
CO2 18
CO3 18
CO4 10
CO5 20
dtype: int64
