Functions

1- Create a function named calculate_area_of_circle that takes one parameter, radius, representing the radius of a circle. The function should calculate and return the area using the formula:

area = đťś‹ Ă— radius^2

Test your function with at least two different radii and print the results.

# Create function to calculate the area of a circle
calculate_area_of_circle <- function(radius) {
  area <- pi * radius^2
  return(area)
}

# Test the function with different radius
radius1 <- 3
radius2 <- 5

# Printing the results
cat("Area of circle with radius", radius1, "=", 
    calculate_area_of_circle(radius1), "\n")
## Area of circle with radius 3 = 28.27433
cat("Area of circle with radius", radius2, "=", 
    calculate_area_of_circle(radius2), "\n")
## Area of circle with radius 5 = 78.53982

2- Write a function called check_temperature that takes a single numeric input temp. If temp > 30, print “Hot” If temp >= 15 & temp <= 30, print “Warm” Otherwise, print “Cold” Test the function on three different values (e.g., 10, 20, 35).

# Function to check temperature 
check_temperature <- function(temp) {
    if (temp > 30) {
      print("Hot")
    } 
    else if (temp >= 15 && temp <= 30) {
      print("warm")
     } else {
    print("Cold")      
  }
}
# Testing the function with different temperature
check_temperature (35) #Hot
## [1] "Hot"
check_temperature (20) #Warm
## [1] "warm"
check_temperature (10) #Cold
## [1] "Cold"
check_temperature (30) #Warm 
## [1] "warm"
check_temperature (14) #cold 
## [1] "Cold"
#checked edge cases like 30 and 14 to ensure code is working fine"

3- Write a function named sum_odd_numbers that uses a for loop to calculate the sum of all even numbers from 1 to n. The function should return the total sum.

Test the function with n = 9 and n = 39.

# Writing a function to use for loop to caluclate the sum of all even numbers from 1 to N
sum_odd_numbers <- function(n){
  total <- 0
for(i in 1:n) {
  if ( i %% 2 == 0){ #checking for even number
    total <- total + i
}
}
return(total)
}
 
# Pass the value to the parameter to test/print the function
print(sum_odd_numbers(9))
## [1] 20
print(sum_odd_numbers(39))
## [1] 380

EDA

For this section, use the built-in mtcars dataset (instead of airquality). Perform the following: - Check the structure of the dataset. - Display the summary statistics. - Check for any missing values. Ask a simple question that can be answered with a basic function (e.g., What is the mean miles per gallon (mpg) across all cars?). Write the code and output the answer.

# Using the built-in mtcars dataset
str(mtcars)
## 'data.frame':    32 obs. of  11 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: num  4 4 1 1 2 1 4 2 2 4 ...
# Check the structure of the dataset
summary(mtcars)
##       mpg             cyl             disp             hp       
##  Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0  
##  1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5  
##  Median :19.20   Median :6.000   Median :196.3   Median :123.0  
##  Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7  
##  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0  
##  Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0  
##       drat             wt             qsec             vs        
##  Min.   :2.760   Min.   :1.513   Min.   :14.50   Min.   :0.0000  
##  1st Qu.:3.080   1st Qu.:2.581   1st Qu.:16.89   1st Qu.:0.0000  
##  Median :3.695   Median :3.325   Median :17.71   Median :0.0000  
##  Mean   :3.597   Mean   :3.217   Mean   :17.85   Mean   :0.4375  
##  3rd Qu.:3.920   3rd Qu.:3.610   3rd Qu.:18.90   3rd Qu.:1.0000  
##  Max.   :4.930   Max.   :5.424   Max.   :22.90   Max.   :1.0000  
##        am              gear            carb      
##  Min.   :0.0000   Min.   :3.000   Min.   :1.000  
##  1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:2.000  
##  Median :0.0000   Median :4.000   Median :2.000  
##  Mean   :0.4062   Mean   :3.688   Mean   :2.812  
##  3rd Qu.:1.0000   3rd Qu.:4.000   3rd Qu.:4.000  
##  Max.   :1.0000   Max.   :5.000   Max.   :8.000
# Check for missing values 
sum(is.na(mtcars))
## [1] 0
# Mean mileage per gallon (mpg) across all cars?
mean_mpg <- mean(mtcars$mpg)
# Display the answer
print(mean_mpg)
## [1] 20.09062