1) Create a matrix named m1 with three rows and five columns and all the numeric (integer) values from 6 to 20!
m1 <- matrix(6:20, nrow = 3, ncol = 5) m1 ## [,1] [,2] [,3] [,4] [,5] ## [1,] 6 9 12 15 18 ## [2,] 7 10 13 16 19 ## [3,] 8 11 14 17 20
2) Multiply all elements in m1 by 0.5! Overwrite the matrix m1 with the result!
m1 <- m1 * 0.5
3) Create another matrix m2 with one row and five columns and all the numeric (integer) values from 1 to 5!
m2 <- matrix(1:5, nrow = 1, ncol = 5) m2 ## [,1] [,2] [,3] [,4] [,5] ## [1,] 1 2 3 4 5
4) Calculate the sum of all elements in m2!
sum(m2) ## [1] 15
5) Combine m1 and m2 with rbing(). Save the result as m3 and check the dimension of the new matrix!
m3 <- rbind(m1, m2) m3 ## [,1] [,2] [,3] [,4] [,5] ## [1,] 3.0 4.5 6.0 7.5 9.0 ## [2,] 3.5 5.0 6.5 8.0 9.5 ## [3,] 4.0 5.5 7.0 8.5 10.0 ## [4,] 1.0 2.0 3.0 4.0 5.0 dim(m3) ## [1] 4 5
6) Index the 5th column of m3!
m3[ , 5] ## [1] 9.0 9.5 10.0 5.0
7) Index the 2nd and 4th lines of m3!
m3[ c(2, 4), ] ## [,1] [,2] [,3] [,4] [,5] ## [1,] 3.5 5 6.5 8 9.5 ## [2,] 1.0 2 3.0 4 5.0
8) Calculate the sums for all columns in m3!
colSums(m3) ## [1] 11.5 17.0 22.5 28.0 33.5
9) Calculate the standard deviation for the 3rd column in m3!
sd( m3[ , 3] ) ## [1] 1.796988
10) From m3, index the element in the 2nd column and 2nd line and all eight adjacent elements! Save the result as m4 and examine its object class!
m4 <- m3[2:4, 2:4] m4 ## [,1] [,2] [,3] ## [1,] 5.0 6.5 8.0 ## [2,] 5.5 7.0 8.5 ## [3,] 2.0 3.0 4.0 class(m4) ## [1] "matrix"