Exercise 1_2_1: Data Types

1

Create a numeric vector with at least 6 numbers.

Clues

To create a vector you need the c() function.

solution

cool_numeric_vector <-
  c(4, 8, 15, 16, 23, 42)

cool_numeric_vector

## [1]  4  8 15 16 23 42

2

Now, create a character vector with four distinct strings.

Clues

Strings or characters have to be enclosed by quotation marks ("" or '').

solution

cool_character_vector <-
  c("I", "like", "bananas", "and", "rhubarb", "pie")

cool_character_vector

## [1] "I"       "like"    "bananas" "and"     "rhubarb" "pie"

3

Let’s turn to more complex data structures. Create a matrix with two columns using the matrix() function based on the numeric vector you built in the first exercise.

Clues

You have to either define the nrow or ncol option to get the proper layout of the matrix.

solution

cool_matrix <- matrix(cool_numeric_vector, nrow = 3)

cool_matrix

##      [,1] [,2]
## [1,]    4   16
## [2,]    8   23
## [3,]   15   42

4

Create a list that includes all of the objects you have created in the previous tasks in this set of exercises.

Clues

Just wrap all elements in the list() function

solution

cool_list <-
  list(
    cool_numeric_vector,
    cool_character_vector,
    cool_matrix
  )

cool_list

## [[1]]
## [1]  4  8 15 16 23 42
## 
## [[2]]
## [1] "I"       "like"    "bananas" "and"     "rhubarb" "pie"    
## 
## [[3]]
##      [,1] [,2]
## [1,]    4   16
## [2,]    8   23
## [3,]   15   42

5

Extract the matrix from the list and convert it to a data frame using the as.data.frame() function .

Clues

List elements are accessed with [[]].

solution

cool_data_frame <- as.data.frame(cool_list[[3]])

6

Add some column names (e.g., “first” and “second”) for the two columns of the data frame.

Clues

You can use the same function for setting/changing names as for viewing them.

solution

names(cool_data_frame) <- c("one", "two")

cool_data_frame

##   one two
## 1   4  16
## 2   8  23
## 3  15  42