# 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") }