Data structure

Vectors

A vector is a collection of values that all have the same data type. It can be a numeric or character vector depending on the data type of the elements.

numbers <- 1:8  ; numbers   # numeric vector

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

colors <- c("red", "yellow", "blue", "red", "blue")  ; colors    # character vector

## [1] "red"    "yellow" "blue"   "red"    "blue"

is.vector(numbers)     # returns TRUE if 'numbers' is a vector

## [1] TRUE

is.vector(colors)      # returns TRUE if 'colors' is a vector

## [1] TRUE

# as.vector(object) : this attempts to coerce 'object' into a vector

You can also select a specific elements in the vector. Below are some examples.

numbers[3]     # selects the third element in 'numbers'

## [1] 3

colors[c(1, 4)]    # selects the first and fourth elements in 'colors'

## [1] "red" "red"

Factors

A factor can be viewed as a special case of a vector. We usually use factors to represent categorical data (which has a fixed set of possible values). A set of possible categories in the data is referred to as levels of the factor.

size <- factor(c("small", "large", "small", "medium", "medium")) ; size

## [1] small  large  small  medium medium
## Levels: large medium small

is.factor(size)      # returns TRUE is 'size' is a factor

## [1] TRUE

is.factor(colors)    # returns TRUE is 'colors' is a factor

## [1] FALSE

colors <- as.factor(colors)    # attempts to coerce 'colors' vector into a factor
is.factor(colors)

## [1] TRUE

Matrices

A matrix is a two-dimensional generalization of a vector. The values are arranged in rows and columns, and the elements must have the same data type.

m <- matrix(1:8, nrow = 4, ncol = 2) ; m  # creates a matrix with 4 rows and 2 columns

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

is.matrix(m)    # returns TRUE if 'm' is a matrix

## [1] TRUE

You can also combine vectors by rows or columns to create a matrix .

a <- 1:5
b <- 11:15
ab <- cbind(a, b)  ; ab   # combine 'a' and 'b' by columns

##      a  b
## [1,] 1 11
## [2,] 2 12
## [3,] 3 13
## [4,] 4 14
## [5,] 5 15

is.matrix(ab)

## [1] TRUE

ab2 <- rbind(a, b)  ; ab2   # combine 'a' and 'b' by rows

##   [,1] [,2] [,3] [,4] [,5]
## a    1    2    3    4    5
## b   11   12   13   14   15

is.matrix(ab2)

## [1] TRUE

size <- as.matrix(size)    # attempts to coerce 'size' into a matrix

To select specific elements in the matrix, you can do:

ab[3, 2]    # selects the element in row 3 and column 2 of 'ab'

##  b 
## 13

ab[1:3, ]   # selects rows 1-3 of 'ab'

##      a  b
## [1,] 1 11
## [2,] 2 12
## [3,] 3 13

ab[, 1:2]   # selects columns 1-2 of 'ab'

##      a  b
## [1,] 1 11
## [2,] 2 12
## [3,] 3 13
## [4,] 4 14
## [5,] 5 15

Dataframes

A dataframe is a collection of vectors with the same length (but they can be of different data types). We usually use a dataframe to represent an entire dataset.

dataset <- data.frame(shape=c("circle", "triangle", "rectangle", "circle", "circle"), 
                      size = size, color = colors, 
                      score = c(5, 4, 2, 9, 8))
dataset

##       shape   size  color score
## 1    circle  small    red     5
## 2  triangle  large yellow     4
## 3 rectangle  small   blue     2
## 4    circle medium    red     9
## 5    circle medium   blue     8

is.data.frame(dataset)

## [1] TRUE

is.data.frame(ab)

## [1] FALSE

ab <- as.data.frame(ab)  # attempts to coerce 'size_col' matrix into a dataframe
is.data.frame(ab)

## [1] TRUE

To select a specific variable (vector) or a subset of the dataframe, do:

dataset[4, 3]      # selects the element in row 4 and column 3

## [1] red
## Levels: blue red yellow

dataset[[3]]    # selects the third variable in 'dataset'

## [1] red    yellow blue   red    blue  
## Levels: blue red yellow

dataset[["colors"]]   # selects 'colors' variable in 'dataset'

## NULL

dataset$shape   # selects 'shape' variable in 'dataset'

## [1] "circle"    "triangle"  "rectangle" "circle"    "circle"

dataset$shape[3]   # selects the third element of 'shape' variable in 'dataset'

## [1] "rectangle"

subset(dataset, size=="medium")  # selects a subset of data that satisfies 'size=medium'

##    shape   size color score
## 4 circle medium   red     9
## 5 circle medium  blue     8

Lists

A list is a collection of data objects. The components can have different data types and lengths.

all_combined <- list(names = c("Bob", "Anne"), 
                     age = c(26, 43), 
                     numbers = numbers, samples = dataset)
all_combined

## $names
## [1] "Bob"  "Anne"
## 
## $age
## [1] 26 43
## 
## $numbers
## [1] 1 2 3 4 5 6 7 8
## 
## $samples
##       shape   size  color score
## 1    circle  small    red     5
## 2  triangle  large yellow     4
## 3 rectangle  small   blue     2
## 4    circle medium    red     9
## 5    circle medium   blue     8

is.list(all_combined)

## [1] TRUE

You can extract specific components/elements of the list in various ways.

all_combined$names   # returns 'names' component

## [1] "Bob"  "Anne"

all_combined[['names']]

## [1] "Bob"  "Anne"

all_combined[[1]]    # returns the first component

## [1] "Bob"  "Anne"

all_combined$names[1]   # returns the first element of 'names'

## [1] "Bob"

all_combined[['names']][2]  # returns the second element of 'names'

## [1] "Anne"

all_combined[[2]][1]     # returns the first element of the second component

## [1] 26