Solution to the exercise of session 3 in the Data Science course at the EUF. The task was to write a function that normalizes numeric vectors into the range of zero and one.

solution.R

#' Normalize a numeric vector into zero-one-range
#' 
#' This simple function covers simple cases: when you have a vector of numbers
#'  larger or equal to zero, then this function normalizes these numbers into
#'  the range between zero and one.
#' @param input_vector A vector of numeric values greater or equal to zero
#' @return A vector of the same length as `input_vector`, the elements are 
#'  normalized into the range between zero and one
normalize_vector <- function(input_vector){
  min_max_diff <- max(input_vector) - min(input_vector)
  diff_vec <- input_vector - min(input_vector)
  normalized_vector <- diff_vec / min_max_diff
  return(normalized_vector)
  }

normalize_vector(input_vector = c(1,2,3,4))

normalize_vector(input_vector = c(2, 5, 10, 1000))