Part - A
#1. Create a matrix StudentMarks which stores the marks scored by 5 students in 4 courses.
marks=c(56,34,90,45,22,66,90,97,55,48,85,85,84,87,56,32,68,95,49,50)
StudentMarks = matrix(marks,nrow=5,ncol=4,byrow=TRUE,dimnames=list(c("Kaarthika","Harry","Hermoine","Alexa","Ron"),c("c1","c2","c3","c4")))
StudentMarks ## c1 c2 c3 c4
## Kaarthika 56 34 90 45
## Harry 22 66 90 97
## Hermoine 55 48 85 85
## Alexa 84 87 56 32
## Ron 68 95 49 50#Find the class average of each course.
colMeans(StudentMarks)## c1 c2 c3 c4
## 57.0 66.0 74.0 61.8#3. Find the total score of each student.
rowSums(StudentMarks)## Kaarthika Harry Hermoine Alexa Ron
## 225 275 273 259 262#4. Print the marks scored by all the students in subject 1 and subject4.
colSums(StudentMarks[,c(1,4)])## c1 c4
## 285 309#5. Include the marks scored by a new student in all the courses.
Angel=c(55,89,67,34)
rbind(StudentMarks,Angel)## c1 c2 c3 c4
## Kaarthika 56 34 90 45
## Harry 22 66 90 97
## Hermoine 55 48 85 85
## Alexa 84 87 56 32
## Ron 68 95 49 50
## Angel 55 89 67 34PART-B
#6. Create a matrix A with sequence of numbers from 21 to 32 in row major with 3 rows.
A = matrix(c(21:32),3,byrow=TRUE)
A## [,1] [,2] [,3] [,4]
## [1,] 21 22 23 24
## [2,] 25 26 27 28
## [3,] 29 30 31 32#7 Check whether A is symmetric
isSymmetric(StudentMarks)## [1] FALSE#8. Create matrix B by slicing only the first three columns of Matrix A
B = A[,c(1:3)]
B## [,1] [,2] [,3]
## [1,] 21 22 23
## [2,] 25 26 27
## [3,] 29 30 31#9. Find the mean, determinant and rank of Matrix B
mean(B)## [1] 26det(B)## [1] -4.263256e-14qr(B)## $qr
## [,1] [,2] [,3]
## [1,] -43.6692111 -45.3866683 -4.710413e+01
## [2,] 0.5724857 0.2243677 4.487353e-01
## [3,] 0.6640834 0.9743183 2.609024e-15
##
## $rank
## [1] 2
##
## $qraux
## [1] 1.480888e+00 1.225175e+00 2.609024e-15
##
## $pivot
## [1] 1 2 3
##
## attr(,"class")
## [1] "qr"#10. Find the trace of Matrix B
print(sum(diag(B)))## [1] 78PART - C
#11. Create a matrix by following the statements
#Create a vector named Rohith with three values.
# Create a vector named Bharath with three values.
# Create a vector named Kevin with three values.
Rohith = c(45,66,35)
Bharath = c(78,34,77)
Kevin = c(90,56,98)#From the above three vectors construct a row major matrix named Marks with 3 rows.
#Print the Marks matrix
Marks = matrix(c(Rohith, Bharath, Kevin),nrow = 3,byrow=TRUE)
print(Marks)## [,1] [,2] [,3]
## [1,] 45 66 35
## [2,] 78 34 77
## [3,] 90 56 98#Create a vector named Names with values - Rohith, Bharath and Kevin
Names <- c("Rohith","Bharath","Kevin")
print(Names)## [1] "Rohith" "Bharath" "Kevin"#Create a vector named Headings with values - CAT-1, CAT-2, FAT
Headings = c("CAT1","CAT2","FAT")
print(Headings)## [1] "CAT1" "CAT2" "FAT"#Assign Names vector as row names to the Marks Matrix
#Assign Headings vector as column names to the Marks Matrix
#Print the Marks matrix
rownames(Marks) = Names
colnames(Marks) = Headings
print(Marks)## CAT1 CAT2 FAT
## Rohith 45 66 35
## Bharath 78 34 77
## Kevin 90 56 98#12 Find the following from the above matrix.
#Find the total score of each person and name it as Total
Total = rowSums(Marks)
print(Total)## Rohith Bharath Kevin
## 146 189 244#Add that column to the existing matrix and name the new matrix as Final_Marks
Marks <-cbind(Marks, Total)
Marks## CAT1 CAT2 FAT Total
## Rohith 45 66 35 146
## Bharath 78 34 77 189
## Kevin 90 56 98 244#Find the average score of all the components of Final_marks matrix(CAT-1, CAT-2, FAT and Total). Round it to 2 decimal places.[Note: use round function]
Column_Means <- colMeans(Marks)
print(Column_Means)## CAT1 CAT2 FAT Total
## 71 52 70 193rounded_means <- round(Column_Means,2)
print(rounded_means)## CAT1 CAT2 FAT Total
## 71 52 70 193#Append the avg score in Final_Marks
Marks = rbind(Marks,rounded_means)
Marks## CAT1 CAT2 FAT Total
## Rohith 45 66 35 146
## Bharath 78 34 77 189
## Kevin 90 56 98 244
## rounded_means 71 52 70 193PART - D
#Create a data frame with 6 students and the marks scored by them in 5 different courses.
#Each course has a maximum score of 100. If a student is present for the exam, its entry contains the score value and 0 otherwise.
students = c("Kaarthika","Praba","Divya","Sudharsha","Thiru","Ramya")
c1 = c(87,34,0,56,35,90)
c2 = c(56,78,96,0,67,45)
c3 = c(89,56,87,99,34,89)
c4 = c(23,65,45,83,90,95)
c5 = c(67,84,49,0,76,20)
df = data.frame(Name = students, C1=c1,C2=c2,C3=c3,C4=c4,C5=c5)#View the contents of the data frame.
View(df)#Find the total score of each student.
#Append a column to include the total score of the students and view the data frame.
df$Total = rowSums(df[,c("C1","C2","C3","C4","C5")])
View(df)#Find the maximum score and display the name of the student who scored it.
print(df$Name[which.max(df$Total)])## [1] "Ramya"#Compute the average score of each course and append it as a new row in the data frame.
df <- rbind(df, c("Avg", colMeans(df[, -c(1, ncol(df))]), NA))
print(df)## Name C1 C2 C3 C4
## 1 Kaarthika 87 56 89 23
## 2 Praba 34 78 56 65
## 3 Divya 0 96 87 45
## 4 Sudharsha 56 0 99 83
## 5 Thiru 35 67 34 90
## 6 Ramya 90 45 89 95
## 7 Avg 50.3333333333333 57 75.6666666666667 66.8333333333333
## C5 Total
## 1 67 322
## 2 84 317
## 3 49 277
## 4 0 238
## 5 76 302
## 6 20 339
## 7 49.3333333333333 <NA>df[, 2:6] <- lapply(df[, 2:6], as.numeric)#Access the scores of students in course3 using the column name.
print(df$C3)## [1] 89.00000 56.00000 87.00000 99.00000 34.00000 89.00000 75.66667#Use index number to retrieve the same data.
print(df[,4])## [1] 89.00000 56.00000 87.00000 99.00000 34.00000 89.00000 75.66667#Extract the score of third student in course4.
print(df[3,5])## [1] 45#Extract the scores of the first and second student in all the courses.
print(df[c(1,2),])## Name C1 C2 C3 C4 C5 Total
## 1 Kaarthika 87 56 89 23 67 322
## 2 Praba 34 78 56 65 84 317#Display the names and total scores of all students.
print(df[,c(1,7)])## Name Total
## 1 Kaarthika 322
## 2 Praba 317
## 3 Divya 277
## 4 Sudharsha 238
## 5 Thiru 302
## 6 Ramya 339
## 7 Avg <NA>