Solutions R week 3

3.1 Multiples of 3 and 5

# 1. For loop: print numbers

for (num in 1:50) {
  # Check if num is divisible by 3 or 5
  if (num %% 3 == 0 || num %% 5 == 0) {
    print(num)
  }
}



# 2. While loop: cumulative sum

cum_sum <- 0  # cumulative sum starts at 0
i <- 1        # start at number 1

while (cum_sum <= 200 && i <= 50) {
  if (i %% 3 == 0 || i %% 5 == 0) {
    cum_sum <- cum_sum + i
  }
  
  i <- i + 1  # go to the next number
}

# Print the final cumulative sum
cum_sum

3.2

data <- data.frame(
  Region      = c("A", "B", "A", "C", "B", "C", "A"),
  EnergyUsage = c(10, 20, 30, 40, 50, 60, 70),
  Sustainable = c(TRUE, FALSE, TRUE, FALSE, TRUE, FALSE, TRUE)
)

for (i in 1:nrow(data)) {
  if (data$Sustainable[i] == TRUE && data$EnergyUsage[i] > 20) {
    print(data[i, ])
  }
}

cumulative_usage <- 0              # cumulative EnergyUsage
i <- 1                      # start at first row
used_rows <- c()            # to remember which rows contributed

while (cumulative_usage <= 50 && i <= nrow(data)) {
  if (data$Sustainable[i] == TRUE) {
    cumulative_usage <- cumulative_usage + data$EnergyUsage[i]
    used_rows <- c(used_rows, i)
  }
  
  i <- i + 1
}

# Print the total cumulative EnergyUsage
cumulative_usage

3.3

secret_number <- floor(runif(1, min = 1, max = 21))
# 2. Set up the game variables
attempts <- 0
max_attempts <- 5
guessed_correctly <- FALSE

# 3. While loop for user guesses
while (attempts < max_attempts && guessed_correctly == FALSE) {
  
  cat("Guess the number (between 1 and 20): ")
  
  # Read user input as text, then convert to numeric
  guess <- as.integer(readline(prompt = "Guess a number between 1 and 20: "))
  
  # Increase attempt counter
  attempts <- attempts + 1
  
  # Check the guess
  if (guess == secret_number) {
    cat("Correct!")
    guessed_correctly <- TRUE
  } else if (guess > secret_number) {
    cat("Too high!")
  } else if (guess < secret_number) {
    cat("Too low!")
  } else {
    # This happens if the input is not a number (NA)
    cat("That was not a valid number.")
  }
}

# 4. Check if the game ended without a correct guess
if (guessed_correctly == FALSE) {
  cat("Game Over! The secret number was:", secret_number, "\n")
}

3.4 working with real data

# Load the data
DAFS_owid_energy_data <- read_delim("~/Downloads/DAFS_owid_energy_data.csv",   delim = ";", escape_double = FALSE, trim_ws = TRUE)

# display first 10 rows
DAFS_owid_energy_data[1:10,]

# Identify columns and data stucture
summary(DAFS_owid_energy_data)

# subset the data
EU_data = subset(DAFS_owid_energy_data, DAFS_owid_energy_data$country %in% c('Netherlands', 'France', 'Belgium', 'Germany', 'Luxemburg', 'Poland', 'Denmark', 'Sweden', 'Finland','Estonia', 'Latvia','Lithuania','Czechia','Slovakia','Hungary','Romania','Bulgaria','Greece','Italy','Croatia','Slovenia','Austria','Spain', 'Portugal','Ireland'))
# we remove missing data observations
EU_data = na.omit(EU_data)
# we make sure the values are numbers
EU_data$biofuel_electricity = as.numeric(EU_data$biofuel_electricity)
EU_data$low_carbon_electricity = as.numeric(EU_data$low_carbon_electricity)
EU_data$nuclear_electricity = as.numeric(EU_data$nuclear_electricity)
EU_data$other_renewable_electricity= as.numeric(EU_data$other_renewable_electricity)
# create a new column called renewable_percentage
EU_data$renewables <- EU_data$biofuel_electricity + EU_data$low_carbon_electricity + EU_data$nuclear_electricity + EU_data$other_renewable_electricity
# we do the same for the other sources
EU_data$gas_electricity = as.numeric(EU_data$gas_electricity)
EU_data$coal_electricity = as.numeric(EU_data$coal_electricity)
EU_data$fossil_electricity = as.numeric(EU_data$fossil_electricity)

# compute the total
EU_data$total <- EU_data$biofuel_electricity +
  EU_data$low_carbon_electricity +
  EU_data$nuclear_electricity +
  EU_data$other_renewable_electricity +
  EU_data$gas_electricity +
  EU_data$coal_electricity +
  EU_data$fossil_electricity

# compute the %
EU_data$pct_renew = EU_data$renewables / EU_data$total


# classify the countries

EU_data$class_renew <- ifelse(
  EU_data$pct_renew > 50, "High Renewable",
  ifelse(EU_data$pct_renew >= 20, "Medium Renewable", "Low Renewable")
)

# group and summarize

EU_data_grouped = EU_data %>% group_by(class_renew) %>% summarise(mean(pct_renew))

Exercises part 4:

Exercise 1:

factorials <- list()
# Create an empty list called 'factorials'.

for (n in 1:10) {
  # Start a for-loop where n goes from 1 to 10.

  fact <- 1
  # Set 'fact' to 1.

  counter <- n
  # Set 'counter' to the current value of n.

  while (counter > 1) {
    # Start a while-loop that keeps going as long as 'counter' is greater than 1.

    fact <- fact * counter
    # Multiply 'fact' by the current value of 'counter'.

    counter <- counter - 1
    # Decrease 'counter' by 1 so we move towards 1 and eventually stop the loop.
  }

  factorials[[as.character(n)]] <- fact
  # Store the result in the list 'factorials'.
  # Use the current number 'n' (turned into text with as.character) as the name of the element.

}

print(factorials)
# Print the whole list of factorials for the numbers 1 to 10.

Exercise 2

discounted_prices <- c()
# Create an empty vector called 'discounted_prices'.


for (i in 1:nrow(products)) {
  # Start a for-loop that goes through each row of the 'products' dataframe.


  price <- products$Price[i]
  # Take the value from the 'Price' column in row i and store it in 'price'.

  in_stock <- products$InStock[i]
  # Take the value from the 'InStock' column in row i and store it in 'in_stock'.


  if (price > 50 && in_stock) {
    # If the price is greater than 50 AND the product is in stock (TRUE)...

    new_price <- price * 0.9
    # ...give a 10% discount (multiply by 0.9).

  } else if (price <= 50 && in_stock) {
    # Otherwise, if the price is 50 or less AND the product is in stock...

    new_price <- price * 0.95 
    # ...give a 5% discount (multiply by 0.95).

  } else {
    # In all other cases (for example, not in stock)...

    new_price <- price
    # ...do not change the price (no discount).
  }

  discounted_prices <- c(discounted_prices, new_price)
  # Add the new_price to the end of the 'discounted_prices' vector.
  # After the loop, this vector will have one discounted price per product.
}

products$DiscountedPrice <- discounted_prices
# Create a new column in the 'products' dataframe called 'DiscountedPrice'
# and fill it with all the values from 'discounted_prices'.

print(products)
# Print the 'products' dataframe so we can see the original and discounted prices.

writing code

# Set the correct password
correct_password <- "mypassword"

# Start with 0 attempts
attempts <- 0
success <- FALSE

# Allow up to 3 attempts
while (attempts < 3 && success == FALSE) {
  
  cat("Enter password: ")
  guess <- as.string(readline(prompt = "Guess the password: "))
  
  if (user_input == correct_password) {
    cat("success!")
    success <- TRUE
  } else {
    cat("Incorrect password.")
    attempts <- attempts + 1
  }
}

# If the user never succeeded in 3 tries:
if (success == FALSE) {
  cat("Too many failed attempts. System locked.")
}