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Timsort is a hybrid, stable sorting algorithm, derived from merge sort and insertion sort, designed to perform well on many kinds of real-world data. It was implemented by Tim Peters in 2002 for use in the Python programming language. The algorithm finds subsequences of the data that are already ordered (runs) and uses them to sort the ...
Radix sort is a sorting algorithm that works for larger keys than pigeonhole sort or counting sort by performing multiple passes over the data. Each pass sorts the input using only part of the keys, by using a different sorting algorithm (such as pigeonhole sort or counting sort) that is suited only for small keys.
One application for stable sorting algorithms is sorting a list using a primary and secondary key. For example, suppose we wish to sort a hand of cards such that the suits are in the order clubs (♣), diamonds (♦), hearts (♥), spades (♠), and within each suit, the cards are sorted by rank. This can be done by first sorting the cards by ...
Bitonic mergesort is a parallel algorithm for sorting. It is also used as a construction method for building a sorting network.The algorithm was devised by Ken Batcher.The resulting sorting networks consist of ( ()) comparators and have a delay of ( ()), where is the number of items to be sorted. [1]
For example, addresses could be sorted using the city as primary sort key, and the street as secondary sort key. If the sort key values are totally ordered, the sort key defines a weak order of the items: items with the same sort key are equivalent with respect to sorting. See also stable sorting. If different items have different sort key ...
For example, to sort the table by the "Text" column and then by the "Numbers" column, you would first click on and sort by the "Numbers" column, the secondary key, and then click on and sort by the "Text" column, primary key. Another method for multi-key sorting is to hold down the ⇧ Shift key while clicking on column headings.
Bucket sort can be seen as a generalization of counting sort; in fact, if each bucket has size 1 then bucket sort degenerates to counting sort. The variable bucket size of bucket sort allows it to use O( n ) memory instead of O( M ) memory, where M is the number of distinct values; in exchange, it gives up counting sort's O( n + M ) worst-case ...
Here input is the input array to be sorted, key returns the numeric key of each item in the input array, count is an auxiliary array used first to store the numbers of items with each key, and then (after the second loop) to store the positions where items with each key should be placed, k is the maximum value of the non-negative key values and ...