# Load the dataset
cat("Task 1: Load Dataset\n")
data <- read.csv('WestRoxbury.csv', header = TRUE) # Enable Heading

# Task 2: Extract the row numbers of the dataset
row_numbers <- row.names(data)
cat("Task 2: Row numbers extracted.\n\n")

# Task 3: Partition row numbers into subsets
set.seed(123)  # For reproducibility
row_numbers_shuffled <- sample(row_numbers)  # Shuffle row numbers

# Number of subsets (10 subsets)
num_subsets <- 10

# Calculate the subset size and the remainder
subset_size <- floor(length(row_numbers_shuffled) / num_subsets)
cat("Subset size default is: ", subset_size, "\n")
remainder <- length(row_numbers_shuffled) %% num_subsets
cat("Remainder is: ", remainder, "\n")

# Create a list of partitioned row numbers
# the subnet stop at near ending for remainder rows, reserve final subset for adding remainder
partitioned_row_numbers <- list()
start_index <- 1
for (i in 1:(num_subsets - 1)) {  # For the first (num_subsets - 1) subsets. Reserve final subset.
  end_index <- start_index + subset_size - 1
  partitioned_row_numbers[[i]] <- row_numbers_shuffled[start_index:end_index] # load row to subset
  start_index <- end_index + 1 # bump up index for next subset in loop.
}
# end_index will be recorded for final run on new subset
# Add the remainder rows to the last subset (subset num_subsets) 
partitioned_row_numbers[[num_subsets]] <- row_numbers_shuffled[start_index:(start_index + subset_size + remainder - 1)]

cat("Task 3: Row numbers partitioned into 10 subsets with the remainder in subset 10.\n")

# Task 4: Partition the dataset into 10 subsets using the partitioned row numbers
partitioned_data <- list()
for (i in 1:num_subsets) {
  # Check if partitioned_row_numbers[[i]] exists and is not empty
  if (length(partitioned_row_numbers[[i]]) > 0) {
    partitioned_data[[i]] <- data[partitioned_row_numbers[[i]], ]
  }
}

cat("Task 4: Dataset partitioned into 10 subsets.\n\n")

# Task 5: Display the number of observations in each subset
for (i in 1:num_subsets) {
  cat("Number of observations in subset", i, "=", nrow(partitioned_data[[i]]), "\n")
}