EXERCISE 1

Author

Nur Aisyah Afifah

EXERCISE 1

create a numeric variable “num_var” with variable with the value “42.5”.
```
num_var <- 42.5
num_var
```
```
[1] 42.5
```
create a character variable “char_var” with the value “R is fun!”
```
char_var <- "R is fun!"
char_var
```
```
[1] "R is fun!"
```

Print the data type “char_var”
```
class(char_var)
```
```
[1] "character"
```

Create a list “student_info” with the following elements: “name” : “Mohammad Nasir Abdullah”,“age” : 18,“grades” : a numeric vector with values “99,100,89’.

student_info <- list(
  name = c("Mohammad Nasir Abdullah"),
  age = c(18),
  grades = c(99, 100, 89)
)
student_info

$name
[1] "Mohammad Nasir Abdullah"

$age
[1] 18

$grades
[1]  99 100  89

Create a data frame “df_students” with the following columns : “Name” : “John”, “Pablo”, “Age” : “22”,“30”, “Grade” : “A”,“C”

df_students <- data.frame(
  Name = c("John", "Pablo"),
  Age = c(22, 30),
  Grade = c("A", "C")
)

df_students

   Name Age Grade
1  John  22     A
2 Pablo  30     C

Create a numeric vector “vec_num” with the values “5,10,15,20”.
```
vec_num <- c(5,10,15,20)
vec_num
```
```
[1]  5 10 15 20
```

Extract the second and third elements from “vec_num”.

vec_num <- c(5, 10, 15, 20)
vec_num[c(2, 3)]

[1] 10 15

Create a vector “vec_seq” that contains a sequence of number from 1 to 10.
```
vec_seq <- seq(1,10, by = 1)
vec_seq
```
```
 [1]  1  2  3  4  5  6  7  8  9 10
```

Create a vector “vec_rad” with 5 random numbers between 1 and 100.

vec_rad <- sample(1:100, size = 5, replace = TRUE)
vec_rad

[1] 22 76 22 18 44

Create a character vector “vec_char’ with the values”apple”, “banana’,”cherry”.
```
vec_char <- c("apple", "banana", "cherry")
vec_char
```
```
[1] "apple"  "banana" "cherry"
```
Use the substr( ) function to extract the first 3 characters from each elements of “vec_char”.
```
vec_char <- substr(vec_char, 1, 3)
vec_char
```
```
[1] "app" "ban" "che"
```

Create a character vector “vec_colors” with the values “red”, “blue”,“green”,“red”,“blue”.

vec_colors <- c("red", "blue", "green", "red", "blue")
vec_colors

[1] "red"   "blue"  "green" "red"   "blue"

Convert “vec_colors” into a factor vector “factor_colors”.

factor_colors <- as.factor(vec_colors)
factor_colors

[1] red   blue  green red   blue 
Levels: blue green red

Print the levels of “factor_colors”.

levels(factor_colors)

[1] "blue"  "green" "red"

Given a numeric vector “vec_bonus” = c(10,20,30,40,50)“, write a code snippet to: Extract all elements greater than 25, Calculate the mean of the extracted elements.
```
vec_bonus <- c(10, 20, 30, 40, 50)
extracted_elements <- vec_bonus[vec_bonus > 25]
extracted_elements
```
```
[1] 30 40 50
```
```
mean(extracted_elements)
```
```
[1] 40
```
Given the following vectors:
```
weights <- c(55,68,72, 61,58,75,64,70)
names <- c("Alice","Bob","Charlie","Daisy", "Eve", "Frank","Grace", "Henry")
```
Identity the names of individuals whose weight is greater than 65kg.
```
names[weights > 65]
```
```
[1] "Bob"     "Charlie" "Frank"   "Henry"  
```
Find the average weight of individuals weighting less than or equal to 60 kg.
```
mean(weights[weights <= 60])
```
```
[1] 56.5
```
Extract the weights of individuals whose names start with the letter ‘A’ od ‘D’.
```
weights[names %in% c("Alice", "Daisy")]
```
```
[1] 55 61
```
Determine the number of individuals whose weight is between 60kg and 70kg (inclusive)
```
sum(weights >= 60 & weights <= 70)
```
```
[1] 4
```
Given the following vector of daily temperatures ( in Celcius ) for a week.
```
temperatures <- c(22,25,19,21,18,24,23)
days <- c("Monday","Tuesday","Wednesday","Thursday","Friday","Saturday","Sunday")
```
Identify the days when the temperatures was below 20C
```
days[temperatures < 20]
```
```
[1] "Wednesday" "Friday"   
```
Calculate the difference between the highest an lowest temperatures of the week.
```
max(temperatures) - min(temperatures)
```
```
[1] 7
```
Determine the number of days when the temperature was between 20c and 24c ( inclusive).
```
sum(temperatures >= 20 & temperatures <= 24)
```
```
[1] 4
```

Given the following vector of exam scores:

scores <- c(85,78,92,65,88,70,95,80,60,90)
students <- c("Anna","Ben","Cara","Dan","Ella","Finn","Grace","Hank","Ivy")

Identify the students who scored above 90.

students[scores > 90]

[1] "Cara"  "Grace"

Find the average score of students who scored below 80.

mean(scores[scores < 80])

[1] 68.25

Extract the scores of students whose names start with a vowel (A,E,I,O,U).

scores[substr(students,1,1) %in% c("A","E","I","O","U")]

[1] 85 88 60 90

TAKE HOME EXERCISE

Create a numeric vector containing the numbers from 10 to 20 and a character vector containing the days of the week.Display both vectors.

num_vector <- 10:20
days_vector <- c("Monday", "Tuesday", "Wednesday", "Thursday", "Friday", "Saturday", "Sunday")
num_vector

 [1] 10 11 12 13 14 15 16 17 18 19 20

days_vector

[1] "Monday"    "Tuesday"   "Wednesday" "Thursday"  "Friday"    "Saturday" 
[7] "Sunday"

Given two vectors : a<- c(1,2,3) and b <- c(4,5,6).Concatenate them to form a single vector.

a <- c(1, 2, 3)
b <- c(4, 5, 6)
combined_vector <- c(a, b)
combined_vector

[1] 1 2 3 4 5 6

Given the vector temperatures <- c (15,18,20,22,19,17,16), extract the temperatures for the 2nd, 4th and 6th days.

temperatures <- c(15, 18, 20, 22, 19, 17, 16)
extracted_temps <- temperatures[c(2, 4, 6)]
extracted_temps

[1] 18 22 17

From the same temperatures vector, omit the temperature of the 5th day.
```
omitted_temp <- temperatures[-5]
omitted_temp
```
```
[1] 15 18 20 22 17 16
```

Given the vector prices <- c(10,20,30,40,50), calculate the new prices after a 10% discount.

prices <- c(10, 20, 30, 40, 50)
new_prices <- prices * 0.9
new_prices

[1]  9 18 27 36 45

Create a vector that contains the numbers from 5 to 50, but only includes every 5th number (i.e, 5, 10, 15, …).
```
new_vector <- seq(5, 50, by = 5)
new_vector
```
```
 [1]  5 10 15 20 25 30 35 40 45 50
```

Simulate the results of rolling a sided die 10 times.

dice_rolls <- sample(1:6, size = 10, replace = TRUE)
dice_rolls

 [1] 3 1 4 4 1 6 2 6 2 2

Given the vector fruits <- c(“apple”, “banana”, “cherry’). extract the first letters of each fruit.

fruits <- c("apple", "banana", "cherry")
first_three <- substr(fruits, 1, 1)
first_three

[1] "a" "b" "c"

Given the vector ages <- c(25,30,35,40,45,50), identify which ages are greater than 30 and less than 50.

ages <- c(25, 30, 35, 40, 45, 50)
selected_ages <- ages[ages > 30 & ages < 50]
selected_ages

[1] 35 40 45

Given two vector: vector1 <- c(5,10,15) and vector2 <- c(10,10,20), determine which elements of vector1 are less than or equal to the corresponding elements in vector2.
```
vector1 <- c(5, 10, 15)
vector2 <- c(10, 10, 20)
comparison_result <- vector1 <= vector2
comparison_result
```
```
[1] TRUE TRUE TRUE
```