Consider the perfume dataset in the file, it contains the strength of the smell of 20 perfumes measured by an odor meter throughout 25 seconds, so each second (column) is a new measurement. Write a program to group these perfumes based on the similarity in the strength of their smell. You should use k-means clustering algorithm. The final output of your program should show k lists of perfumes, and show outlier perfume’s records (if exists).

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A potential method of analysis

The complexity of the algorithm model emphasizes the potential method. This method is useful for examining a data structure's amortized time and space complexity.