data:image/png;base64,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 this for loop we find the smallest value left in the unsorted part of the list.temp"j" is the same as unsorted_index in the other example. Here it is just expressed as a for loop intead of a repeat until loop. In this for loop we find the smallest value left in the unsorted part of the list.tempOnce smallest value and its index are found, swap them into the first index of the unsorted list ("unsorted_index") and increase unsorted_index so that index is now considered sorted. unsorted_index1once unsorted_index reaches the end of the list, then everything must be the "sorted" part of the list and thus the list is sorted.1,2,3,4,5,6,7,8,9,10109109