A First R Session

Let’s create the simplest object in R, a vector x, that consists of the numbers 1, 2, and 4:

x <- c(1,2,4)

The c() operator concatenates the three one-element vectors 1, 2, and 4. Also, note the assignment operator <- -it works much like =, but there are special circumstances where the two are different so we want to make sure we always use the former. Now, let’s see what happens when we concatenate vectors that contain more than one element:

q <- c(x,x,8)
q

## [1] 1 2 4 1 2 4 8

What type of R object is q? > Vector q is a numeric vector

The dimension (or length) of a vector corresponds to its number of elements. The dimension of x is 3. What is the dimension of q?

There are 7 elements in the numeric vector q

A vector is a special case of a matrix. Think of a matrix for now as an object whose rows (or columns) are made up by vectors of the same length-each of the vectors is a row (or a column) in the matrix. When we describe the dimensions of a matrix, we indicate the number of rows and columns as: rxc. What are the dimensions of y? Of z?

y <- cbind(x,x)
z <- rbind(x,x)
dim(y)

## [1] 3 2

The dimension of y is a matrix of 3 rows and 2 columns

dim(z)

## [1] 2 3

The dimension of z is a matrix of 2 rows and 3 columns

One of the datasets is called Orange and contains data on the growth of orange trees. Let’s investigate it:

names(Orange) ## What are the variable names in the dataset?

names(Orange)

## [1] "Tree"          "age"           "circumference"

Tree, age, circumference are the variables in dataset orange

Orange$age ## How to indicate a variable that is in a dataset

Orange$age

##  [1]  118  484  664 1004 1231 1372 1582  118  484  664 1004 1231 1372 1582
## [15]  118  484  664 1004 1231 1372 1582  118  484  664 1004 1231 1372 1582
## [29]  118  484  664 1004 1231 1372 1582

attach(Orange) ## In short, so I can just ask for ‘age’ instead of having ## to tell R both the dataset name and the variable name

attach(Orange)

mean(age) ## Asking for the mean of the variable ‘age’

mean(age)

## [1] 922.1429

The mean age is 922.1429

sd(age) ## Standard deviation of ‘age’

sd(age)

## [1] 491.8645

The standard deviation is 491.8645

hist(age) ## Plot a histogram of the data

hist(age)

We can make this basic graph look a little better by using some of R’s graphical parameters. I’m going to change the label of the x-axis:

hist(age, xlab="Age (in years)")

Working with R Objects

Vector Manipulation

Is a vector of integers starting at 5 and endind at 1 in descending order, and assign them as x:

x <- 5:1
print(x)

## [1] 5 4 3 2 1

Print after dividing the elements of the vector by half:

x/2

## [1] 2.5 2.0 1.5 1.0 0.5

Print the squares the elements of the vector:

x^2

## [1] 25 16  9  4  1

Print the result of matrix multiplication for vector x by vector x:

x%*%x

##      [,1]
## [1,]   55

Print the square root of each element in x:

sqrt(x)

## [1] 2.236068 2.000000 1.732051 1.414214 1.000000

Print the minimum value in the vector:

min(x)

## [1] 1

Print the second element of vector x:

x[2]

## [1] 4

Print the second and third elements of vector x:

x[2:3]

## [1] 4 3

Print the second and third elements of vector x:

x[c(2,3)]

## [1] 4 3

Print vector x without the third element:

x[-3]

## [1] 5 4 2 1

Print a vector x with the smallest element first ordered to the largest element:

sort(x)

## [1] 1 2 3 4 5

Is vector of integers from 20 to 40; assign them to x:

x <- 20:40 
print(x)

##  [1] 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

Print the first 5 elements of vector x:

x[1:5]

## [1] 20 21 22 23 24

Print vector x without the first 5 elements:

x[-(1:5)]

##  [1] 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

Print the concatenated vector, add 1 to the first element, and procude a warning for varying vector length:

c(1,2,3) + 1

## [1] 2 3 4

Print the addition of the two vectors together:

c(1,2,3) + c(0,1)

## Warning in c(1, 2, 3) + c(0, 1): longer object length is not a multiple of
## shorter object length

## [1] 1 3 3

Print the addition of the two vectors together:

c(1,2,3) + c(1,2)

## Warning in c(1, 2, 3) + c(1, 2): longer object length is not a multiple of
## shorter object length

## [1] 2 4 4

Print the addition of two vectors:

c(1,2,3,4) + c(0,1)

## [1] 1 3 3 5

Print the addition of the two vectors together:

c(1,2,3,4) + c(1,2,3)

## Warning in c(1, 2, 3, 4) + c(1, 2, 3): longer object length is not a
## multiple of shorter object length

## [1] 2 4 6 5

Print the modulo operation:

5%%2

## [1] 1

Print the modulo operation:

6%%2

## [1] 0

Print the modulo operation:

7%%2

## [1] 1

Print the modulo operation:

10%%4

## [1] 2

Print the modulo operation:

10%%5

## [1] 0

Print the modulo operation:

10%%6

## [1] 4

Assign vector <1,2,4> to x:

x <- c(1,2,4) 
print(x)

## [1] 1 2 4

Print the names for vector x:

names(x)

## NULL

Assign (a, b, ab) as the names for vector x:

names(x) <- c("a","b","ab") 
print(names(x))

## [1] "a"  "b"  "ab"

Print x with the names for a given element:

##  a  b ab 
##  1  2  4

Print the names of vector x:

names(x)

## [1] "a"  "b"  "ab"

Print the name and element assigned to that name:

x["b"]

## b 
## 2

Assign elements from 1 to 10 to vector x:

x <- c(1:10)
print(x)

##  [1]  1  2  3  4  5  6  7  8  9 10

Assign elements from 10 to 1 to vector y:

y <- c(10:1) 
print(y)

##  [1] 10  9  8  7  6  5  4  3  2  1

Print a matrix with columns of 1 for the length of elements in x, elements of x, elements of y as the values of the columns:

cbind(1,x,y)

##          x  y
##  [1,] 1  1 10
##  [2,] 1  2  9
##  [3,] 1  3  8
##  [4,] 1  4  7
##  [5,] 1  5  6
##  [6,] 1  6  5
##  [7,] 1  7  4
##  [8,] 1  8  3
##  [9,] 1  9  2
## [10,] 1 10  1

Print a matrix with rows of 1 for the length of elements in x, elements of x, elements of y as the values of the rows:

rbind(1,x,y)

##   [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
##      1    1    1    1    1    1    1    1    1     1
## x    1    2    3    4    5    6    7    8    9    10
## y   10    9    8    7    6    5    4    3    2     1

Create a list of lists for 1, elements of x, elements of y, and assign them to variable x:

x <- list(1,x,y) 
print(x)

## [[1]]
## [1] 1
## 
## [[2]]
##  [1]  1  2  3  4  5  6  7  8  9 10
## 
## [[3]]
##  [1] 10  9  8  7  6  5  4  3  2  1

Matrix Manipulation

Create a 2x2 matrix with column vectors (1,2) and (3,4), and assign them to A:

A <- matrix(nrow=2,ncol=2,c(1:4)) 
print(A)

##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4

Create a 2x2 matrix with column vectors (1,2) and (3,4), and assign them to B:

B <- matrix(nrow=2,ncol=2,c(1:4)) 
print(B)

##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4

Create a vector (2,2) and assign them to variable x:

x <- c(2,2) 
print(x)

## [1] 2 2

Print a matrix with column vectors (2,4) and (6,8) through matrix addition:

A + B

##      [,1] [,2]
## [1,]    2    6
## [2,]    4    8

Print a matrix with column vectors (0,0) and (0,0) through matrix subtraction:

A - B

##      [,1] [,2]
## [1,]    0    0
## [2,]    0    0

Print a transpose of matrix A:

t(A)

##      [,1] [,2]
## [1,]    1    2
## [2,]    3    4

Print matrix A through cancelling transpose operations:

t(t(A))

##      [,1] [,2]
## [1,]    1    3
## [2,]    2    4

Print a matrix with column vectors (1,4) and (9,16) through element-wise multiplication:

A*B

##      [,1] [,2]
## [1,]    1    9
## [2,]    4   16

Print a matrix with column vectors (7,10) and (15,22) through matrix multiplication:

A%*%B

##      [,1] [,2]
## [1,]    7   15
## [2,]   10   22

Print a matrix with column vector (8,12) through matrix multiplication with a matrix of small dimension:

A%*%x

##      [,1]
## [1,]    8
## [2,]   12

Print a matrix with column vector (40) through matrix multiplication with two matrix of small dimension:

x%*%A%*%x

##      [,1]
## [1,]   40

Print the inverse of A:

solve(A)

##      [,1] [,2]
## [1,]   -2  1.5
## [2,]    1 -0.5

Create a 4x4 matrix with column vectors (1,2,3,4),(5,6,7,8),(9,10,11,12), and (13,14,15,16) and assign them to C:

C <- matrix(nrow=4,ncol=4,c(1:16)) 
print(C)

##      [,1] [,2] [,3] [,4]
## [1,]    1    5    9   13
## [2,]    2    6   10   14
## [3,]    3    7   11   15
## [4,]    4    8   12   16

Assign the first row of matrix A to a1:

a1 <- A[1,] 
print(a1)

## [1] 1 3

Assign the second row of matrix A to a2:

a2 <- A[2,] 
print(a2)

## [1] 2 4

Assign the first column of matrix B to b1:

b1 <- B[,1] 
print(b1)

## [1] 1 2

Assign the second column of matrix B to b1:

b2 <- B[,2]

Print the second and third columns of matrix C:

c_c <- C[,2:3] 
print(c_c)

##      [,1] [,2]
## [1,]    5    9
## [2,]    6   10
## [3,]    7   11
## [4,]    8   12

Print the first and second rows of matrix C:

c_r <- C[1:2,] 
print(c_r)

##      [,1] [,2] [,3] [,4]
## [1,]    1    5    9   13
## [2,]    2    6   10   14

Create a 2x4 matrix with every element being 1, and assign it to variable C[c(1,3),]:

C[c(1,3),] <- matrix(nrow=2,ncol=4,c(rep(1,8))) 
print(C[c(1,3),])

##      [,1] [,2] [,3] [,4]
## [1,]    1    1    1    1
## [2,]    1    1    1    1

Create a vector (4,5,2,3) and transforms it into a 2x2 matrix with columns (4,5) and (2,3), and assign it to y:

y <- matrix(c(4,5,2,3), nrow = 2) 
print(y)

##      [,1] [,2]
## [1,]    4    2
## [2,]    5    3

Print the first row of matrix y:

y[-2,]

## [1] 4 2

Create a 3x2 matrix with column vectors (1,2,3),(4,5,6), and assign it to x:

x <- matrix(nrow=3,ncol=2,c(1:6)) 
print(x)

##      [,1] [,2]
## [1,]    1    4
## [2,]    2    5
## [3,]    3    6

Print the addition of vector (0,1) staring at [1,1] and wrapping through the second column:

x + c(0,1)

##      [,1] [,2]
## [1,]    1    5
## [2,]    3    5
## [3,]    3    7

Create a 3x2 matrix with column vectors (1,2,3),(4,5,6), and assign it to z:

z <- matrix(nrow=3,ncol=2,c(1:6)) 
print(z)

##      [,1] [,2]
## [1,]    1    4
## [2,]    2    5
## [3,]    3    6

Print the mean of each row:

apply(z,1,mean)

## [1] 2.5 3.5 4.5

Print the mean of each column:

apply(z,2,mean)

## [1] 2 5

Character Strings

Create a character vector (“abc”) and assign it to y:

y <- "abc" 
print(y)

## [1] "abc"

Print the length of vector y:

length(y)

## [1] 1

Print the storage type of the object:

mode(y)

## [1] "character"

Create a character vector (“abc”, “29 88”) and assign it to z:

z <- c("abc", "29 88") 
print(z)

## [1] "abc"   "29 88"

Print the length of vector z which is 2:

length(z)

## [1] 2

Print the storage type of the object:

mode(z)

## [1] "character"

Add elements together in on string and assigns to w_w:

w_w <- paste("Wonder", "Woman") 
print(w_w)

## [1] "Wonder Woman"

Splits elements into separate strings and assigns to list ww:

ww <- strsplit(w_w, " ") 
print(ww)

## [[1]]
## [1] "Wonder" "Woman"

Print a logical operator for list:

is.list(ww)

## [1] TRUE

Print the location of the matching elements to the input string:

grep("West", c("North","South","South East","North West","West"))

## [1] 4 5

Print the count of characters in the string:

nchar("You're gonna need a bigger boat.")

## [1] 32

Print the the substring of the desired characters:

substr("Jaws",2,3)

## [1] "aw"

Print the regular expression format for character matching inside a string:

regexpr("aw","Jaws")

## [1] 2
## attr(,"match.length")
## [1] 2
## attr(,"useBytes")
## [1] TRUE

Print the split of the string into elements by delimited value:

strsplit("6-16-2011", split="-")

## [[1]]
## [1] "6"    "16"   "2011"

Sequences

Assign the value 10 to vector n:

n <- 10 
print(x)

##      [,1] [,2]
## [1,]    1    4
## [2,]    2    5
## [3,]    3    6

Print a vector of elements from 0 up to vector n but not n:

1:n-1

##  [1] 0 1 2 3 4 5 6 7 8 9

Print a vector of elements from 1 up to vector n but not n:

1:(n-1)

## [1] 1 2 3 4 5 6 7 8 9

Create a vector with sequence from -10 to 10 by 2 and assign it to sequence.1:

seq(-10, 10, by = 2) -> sequence.1
print(sequence.1)

##  [1] -10  -8  -6  -4  -2   0   2   4   6   8  10

Create a vector with sequence from -10 by 2 for ll elements and assign it to sequence.2:

sequence.2 <- seq(length = 11, from = -10, by = 2) 
print(sequence.2)

##  [1] -10  -8  -6  -4  -2   0   2   4   6   8  10

Create a vector with sequence from 1 to 6 (since x as assigned as vector [3,2]) then replicates five times and assign it to sequence.3:

sequence.3 <- rep(x, 5) 
print(sequence.3)

##  [1] 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6

Create a vector with sequence (5,2,7) then replicates three times and assign it to sequence.4:

sequence.4 <- rep(c(5,2,7),3) 
print(sequence.4)

## [1] 5 2 7 5 2 7 5 2 7

Create a vector with sequence (5,2,7) then replicates each element three times inorder and assign it to sequence.5:

sequence.5 <- rep(c(5,2,7),each=3)
print(sequence.5)

## [1] 5 5 5 2 2 2 7 7 7

Logicals

Create vector (TRUE,TRUE,FALSE,FALSE) and assign it a:

a <- c(TRUE,TRUE,FALSE,FALSE) 
print(a)

## [1]  TRUE  TRUE FALSE FALSE

Create vector (FALSE,TRUE,TRUE,FALSE) and assign it b:

b <- c(FALSE,TRUE,TRUE,FALSE) 
print(b)

## [1] FALSE  TRUE  TRUE FALSE

Print the OR operation on if an element in other list is true:

a|b

## [1]  TRUE  TRUE  TRUE FALSE

Print the AND operation on if an element in other list is true:

a&b

## [1] FALSE  TRUE FALSE FALSE

Print the AND operation on if an element in (NOT a and b) list is true:

!a&b

## [1] FALSE FALSE  TRUE FALSE

Print the AND operation on if an element in (NOT a and NOT b) list is true:

!a&!b

## [1] FALSE FALSE FALSE  TRUE

Print the AND operation on if an element in NOT (a and b) list is true:

!(a&b)

## [1]  TRUE FALSE  TRUE  TRUE

Print the addition of boolean bits for a + b:

a+b

## [1] 1 2 1 0

Assign TRUE values to matrix x if they are greater than 3 otherwise FALSE to dummy.1:

dummy.1 <- x > 3 
print(dummy.1)

##       [,1] [,2]
## [1,] FALSE TRUE
## [2,] FALSE TRUE
## [3,] FALSE TRUE

Assign TRUE values to matrix x if they are equal 3 otherwise FALSE to dummy.2:

dummy.2 <- x == 3 
print(dummy.2)

##       [,1]  [,2]
## [1,] FALSE FALSE
## [2,] FALSE FALSE
## [3,]  TRUE FALSE

Assign a vector from 1 to 10 to x:

x <- 1:10 
print(x)

##  [1]  1  2  3  4  5  6  7  8  9 10

Print a TRUE if any element is greater than 8:

any(x>8)

## [1] TRUE

Print a TRUE if any element is greater than 88:

any(x>88)

## [1] FALSE

Print a TRUE if all element is greater than 88:

all(x>88)

## [1] FALSE

Print a TRUE if all element is greater than 0:

all(x>0)

## [1] TRUE

Assign a vector from 1 to 3 to x:

x <- 1:3
print(x)

## [1] 1 2 3

Assign a vector (1,3,4) to y:

y <- c(1,3,4) 
print(y)

## [1] 1 3 4

Print TRUE if elements between the two vectors match:

x == y

## [1]  TRUE FALSE FALSE

Print TRUE if all elements between the two vectors match:

all(x == y)

## [1] FALSE

Print TRUE the two vectors are identical:

identical(x,y)

## [1] FALSE

Assign a vector from 1 to 2 to x:

x <- 1:2 
print(y)

## [1] 1 3 4

Assign a vector (1,2) to y:

y <- c(1,2) 
print(y)

## [1] 1 2

Print x and y:

x;y

## [1] 1 2

## [1] 1 2

Print TRUE the two vectors are identical:

identical(x,y)

## [1] FALSE

Print the type of vector :

typeof(x)

## [1] "integer"

Print the type of vector:

typeof(y)

## [1] "double"

Missing Data

Assign a vector from 1 to 3 and element NA to z:

z <- c(1:3,NA) 
print(z)

## [1]  1  2  3 NA

Assign TRUE if the element is NA to z.dummy:

z.dummy <- is.na(z) 
print(z.dummy)

## [1] FALSE FALSE FALSE  TRUE

Assign all the elements to NA for a vector of length z to z.dummy2:

z.dummy2 <- z==NA 
print(z.dummy2)

## [1] NA NA NA NA

Print NaN for not a number:

0/0

## [1] NaN

Print TRUE for is NA:

is.na(0/0)

## [1] TRUE

Print TRUE for is NaN:

is.nan(0/0)

## [1] TRUE

Print TRUE for any element in z not a number:

is.nan(z)

## [1] FALSE FALSE FALSE FALSE

Print NA since one element is NA:

mean(z)

## [1] NA

Print 2 for the mean of vector z excluding elements of value NA:

mean(z,na.rm=T)

## [1] 2

Assign a vector (88,NULL,12,168,13) to x:

x <- c(88,NULL,12,168,13) 
print(x)

## [1]  88  12 168  13

Print mean of vector x which is 70.25 since null is not counted:

mean(x)

## [1] 70.25

Assign null to u:

u <- NULL 
print(u)

## NULL

Print 0 since null values have no length:

length(u)

## [1] 0

Assign NA to v:

v <- NA 
print(v)

## [1] NA

Print the length vector v:

length(v)

## [1] 1

Simple Subsetting

Create a vector from 1 to 5 and NA replicated 3 times and assign it to x:

x <- c(c(1:5),c(rep(NA,3))) 
print(x)

## [1]  1  2  3  4  5 NA NA NA

Print TRUE if the value in vector x is NA:

is.na(x)

## [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE

Print the NA elements in vector x:

x[is.na(x)]

## [1] NA NA NA

Print the not NA elements in vector x:

x[!is.na(x)]

## [1] 1 2 3 4 5

Print TRUE for values greater than 2, FALSE for less than or equal to 2, and NA for NA values:

x > 2

## [1] FALSE FALSE  TRUE  TRUE  TRUE    NA    NA    NA

Print TRUE for values greater than 2, otherwise FALSE:

!is.na(x)&x > 2

## [1] FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE

Print the values greater than 2 from vector x:

x[!is.na(x)&x > 2]

## [1] 3 4 5

Assign a 2x3 matrix with columns (1,2),(3,4),and (5,6) to x:

x <- matrix(1:6,2,3) 
print(x)

##      [,1] [,2] [,3]
## [1,]    1    3    5
## [2,]    2    4    6

Assign a list with list one (1,2,3,4,5), list two (0.6), and list three (“HI”) to w:

w <- list(one = 1:5, two = 0.6, three = "HI") 
print(w)

## $one
## [1] 1 2 3 4 5
## 
## $two
## [1] 0.6
## 
## $three
## [1] "HI"

Print list one from w:

w$one

## [1] 1 2 3 4 5

Print list one from w:

w[["one"]]

## [1] 1 2 3 4 5

Print list one from w:

w[[1]]

## [1] 1 2 3 4 5

Print the first and third elements from list one from w:

w[[c(1,3)]]

## [1] 3

Print the third element from list one from w:

w[[1]][[3]]

## [1] 3

Print list one and three from w:

w[c(1,3)]

## $one
## [1] 1 2 3 4 5
## 
## $three
## [1] "HI"

Assign vector (5,2,-3,8) to z:

z <- c(5,2,-3,8) 
print(z)

## [1]  5  2 -3  8

Print z:

## [1]  5  2 -3  8

Print TRUE for values greater than 8 after the vector is squared:

z*z > 8

## [1]  TRUE FALSE  TRUE  TRUE

Print the values that when squared are greater than 8:

z[z*z > 8]

## [1]  5 -3  8

Assign the values that when squared are greater than 8 to w:

w <- z[z*z > 8] 
print(w)

## [1]  5 -3  8

Assign vector of 6,1,2,3,NA,12 to x:

x <- c(6,1:3,NA,12) 
print(x)

## [1]  6  1  2  3 NA 12

Print the values greater than 5 and NA in the vector x:

x[x>5]

## [1]  6 NA 12

Print a subset of values greater than 5 without NA:

subset(x,x>5)

## [1]  6 12

Assign the named numeric(0) to x[x>3]:

x[x>3] <- 0 
print(x[x>3])

## [1] NA

Print the location of TRUE values in vector z where the square of the element is greater than 8:

which(z*z > 8)

## [1] 1 3 4

Arrays

Assign a 3x2 matrix with columns (46,21,50) and (30,25,50) to first_test:

first_test <- matrix(nrow = 3, ncol = 2, c(46,21,50,30,25,50)) 
print(first_test)

##      [,1] [,2]
## [1,]   46   30
## [2,]   21   25
## [3,]   50   50

Assign a 3x2 matrix with columns (46,41,50) and (43,35,50) to second_test:

second_test <- matrix(nrow = 3, ncol = 2, c(46,41,50,43,35,50)) 
print(second_test)

##      [,1] [,2]
## [1,]   46   43
## [2,]   41   35
## [3,]   50   50

Create an array of matrices first_test and second_test and assign it to tests:

tests <- array(data=c(first_test,second_test),dim=c(3,2,2)) 
print(tests)

## , , 1
## 
##      [,1] [,2]
## [1,]   46   30
## [2,]   21   25
## [3,]   50   50
## 
## , , 2
## 
##      [,1] [,2]
## [1,]   46   43
## [2,]   41   35
## [3,]   50   50

Print the dimensions of the array tests:

attributes(tests)

## $dim
## [1] 3 2 2

Print the element of the third row, second column for matrix 1 in the array:

tests[3,2,1]

## [1] 50

Print the element of the third row, second column for matrix 2 in the array:

tests[3,2,2]

## [1] 50

Print the array tests:

tests

## , , 1
## 
##      [,1] [,2]
## [1,]   46   30
## [2,]   21   25
## [3,]   50   50
## 
## , , 2
## 
##      [,1] [,2]
## [1,]   46   43
## [2,]   41   35
## [3,]   50   50

Write the Code

Create a vector of length 10 and fill it with a sequence of integers.

a <- seq(10)

Coerce the vector into a matrix of 5 rows and 2 columns.

a <- matrix(a,nrow = 5, ncol = 2)

Name the columns of the matrix “A” and “B”.

colnames(a) <- c("A","B")

Generate 12 random numbers from a uniform distribution and store them in a matrix of 4 rows and 3 columns.

b <- matrix(1:12,nrow = 4, ncol = 3)

Name the rows of the matrix “1st Row”, “2nd Row”, “3rd Row”, and “4th Row”.

rownames(b) <- c("1st Row", "2nd Row", "3rd Row", "4th Row")

Using bracket notation (i.e., X[r,c] where r is the row index and c is the column index), print the element of the matrix that is in the 2nd row, 1st column. Assign the entire 2nd column of the matrix to a new object r.

b[2,1]; c <- b[,2]

## 2nd Row 
##       2

Assume that we have recorded the names and ages for four people: James is 27, Art is 42, Kate is 29, and Alex is 33. Create a vector of names and a vector of ages from the data, making sure that you keep the ordering of the elements consistent. Use the class() function to print the class metadata R has stored for each vector. Using data.frame(), combine the two vectors into a dataframe and name the columns something informative. Print out the dataframe.

d <- c("James", "Art", "Kate", "Alex"); e <- c(27,42,29,33)
class(d)

## [1] "character"

class(e)

## [1] "numeric"

df<-data.frame(d,e);names(df) <- c("Name", "Age");df

##    Name Age
## 1 James  27
## 2   Art  42
## 3  Kate  29
## 4  Alex  33

Assume that we have the following observations of temperature: 23°C, 30°C, 19°C, 27°C. Create a vector C concatenating these values. Recall the relationship between Celsius and Fahrenheit temperatures: °F = °C × 9/5 + 32. Using a single line of code that includes arithmetic operations, create a new vector F that contains the temperatures transformed to Fahrenheit scale.

C <- c(23,30,19,27)
F <- c(C*(9/5)+32)

Suppose we have a sample of 15 plants from all across the country and their state of origin is specified by a character vector:

state <- c(“MO”,“KS”,“KS”,“KS”,“MO”,“NE”,“OK”,“MO”,“KS”,“NE”,“NE”,“OK”,“MO”,“KS”,“KS”)

Use the factor() function to change the character vector state to a factor and produce a frequency table that represents the number of observations in our sample from each state. Use the levels option within factor() to reorder the state categories to: Oklahoma, Kansas, Missouri, Nebraska.

state <- c("MO","KS","KS","KS","MO","NE","OK","MO","KS","NE","NE","OK","MO","KS","KS")
orderState <- factor(state,labels=c("Oklahoma","Kansas","Missouri","Nebreska"))
table(orderState)

## orderState
## Oklahoma   Kansas Missouri Nebreska 
##        6        4        3        2

Suppose, further, that we have a measure of production for the plans in another vector:

prod <- c(2341, 9873, 23933, 1999, 7214, 9089, 10999, 2389, 5435, 5757,2521, 7333, 21909, 15110, 4369)

Use the help to investigate the tapply() function. Write the command line that will produce the mean production for each state using tapply(). Write similar command lines that will produce the minimum and maximum production for each state.

prod <- c(2341,9873,23933,1999,7214,9089,10999,2389,5435,5757,2521,733,21909,15110,4369)
tapply(prod,state,mean)

##       KS       MO       NE       OK 
## 10119.83  8463.25  5789.00  5866.00

tapply(prod,state,min)

##   KS   MO   NE   OK 
## 1999 2341 2521  733

tapply(prod,state,max)

##    KS    MO    NE    OK 
## 23933 21909  9089 10999

Document Information

All of the statistical analyses in this document will be performed using R version 3.4.1 (2017-06-30). R packages used will be maintained using the packrat dependency management system.

sessionInfo()

## R version 3.4.1 (2017-06-30)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 15063)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=English_United States.1252 
## [2] LC_CTYPE=English_United States.1252   
## [3] LC_MONETARY=English_United States.1252
## [4] LC_NUMERIC=C                          
## [5] LC_TIME=English_United States.1252    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] DT_0.2        rmarkdown_1.6 knitr_1.16   
## 
## loaded via a namespace (and not attached):
##  [1] htmlwidgets_0.9 compiler_3.4.1  backports_1.1.0 magrittr_1.5   
##  [5] rprojroot_1.2   tools_3.4.1     htmltools_0.3.6 yaml_2.1.14    
##  [9] Rcpp_0.12.10    stringi_1.1.5   stringr_1.2.0   digest_0.6.12  
## [13] evaluate_0.10

Dynamic Documents with rmarkdown

Jordan Winemiller

2017-06-19

A First R Session

Working with R Objects

Vector Manipulation

Matrix Manipulation

Character Strings

Sequences

Logicals

Missing Data

Simple Subsetting

Arrays

Write the Code

Document Information