The algorithm sorts values by repeatedly comparing neighboring elements in the list and swapping their position if they are not in order relative to each other. insertion sort O selection sort merge sort O bubble sort

The algorithm sorts values by repeatedly comparing neighboring elements in the list and swapping their position if they are not in order relative to each other. insertion sort O selection sort merge sort O bubble sort

Programming Logic & Design Comprehensive

9th Edition

ISBN:9781337669405

Author:FARRELL

Publisher:FARRELL

Chapter8: Advanced Data Handling Concepts

Section: Chapter Questions

Problem 10RQ

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java data structure
An unordered search method is one that looks at each element in turn until the desired result is discovered.
- The operation of processing each element in a list is known as A Sorting B Searching C Indexing D Traversal
Need to complete the intersection method. cant use the regular library and sort method. Please type answer note write by hend.
Pull down your neighbours def eliminate_neighbours(items): Given the sequence of integer items that are guaranteed to be some permutation of positive integers from 1 to n where n is the length of the list, find the smallest number among those that still remain in the list, and remove from the list both that number and whichever of its current immediate neighbours is larger. The function should repeat this basic operation until the largest number in the original list gets eliminated. Return the number of removal operations that were needed to achieve this goal.For example, given the list [5, 2, 1, 4, 6, 3], the operation would remove element 1 and its current larger neighbour 4, resulting in the list [5, 2, 6, 3]. Applied again, that operation would remove 2 and its current larger neighbour 6, thus reaching the goal in two steps. items Expected result [1, 6, 4, 2, 5, 3] 1 [8, 3, 4, 1, 7, 2, 6, 5] 3 [8, 5, 3, 1, 7, 2, 6, 4] 4 [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 5 range(1,…
Data structures concatenate_dict(dict_list:list)->dict This function will be given a single parameter known as the Dictionary List. Your job is to combine all the dictionaries found in the dictionary list into a single dictionary and return it. There are two rules for adding values to the dictionary: 1. You must add key-value pairs to the dictionary in the same order they are found in the Dictionary List. 2. If the key already exists, it cannot be overwritten. In other words, if two or more dictionaries have the same key, the key to be added cannot be overwritten by the subsequent dictionaries. Example: Dictionary List: [{'Z': 6, 'k': 10, 'w': 3, 'I': 8, 'Y': 5}, {'Y': 1, 'Z': 4}, {'X': 2, 'L': 5}] Expected: {'Z': 6, 'k': 10, 'w': 3, 'I': 8, 'Y': 5, 'X': 2, 'L': 5} Dictionary List: [{'z': 0}, {'z': 7}] Expected: {'z': 0} Dictionary List: [{'b': 7}, {'b': 10, 'A': 8, 'Z': 2, 'V': 1}] Expected: {'b': 7, 'A': 8, 'Z': 2, 'V': 1}
A ____ supports manipulation of items at any point within a linear collection. Question 5 options: dictionary list stack queue
Nearest smaller element def nearest_smaller(items): Given a list of integer itema, create and return a new list of the same length but where each element has been replaced with the nearest element in the original list whose value is smaller. If no smaller elements exist because that element is the minimum of the original list, the element in the result list should remain as that same minimum element. If there exist smaller elements equidistant in both directions, you must resolve this by using the smaller of these two elements. This again makes the expected results unique for every possible value of items, which is necessary for the automated testing framework to work at all. Being permissive in what yvou accept while being restrictive in what you emit is a pretty good principle to follow in all walks of life, not just in programming. Expected result items [42, 42, 421 [42, 42, 42] [42, 1, 17] (1, 1, 1] [42, 17, 1] [17, 1, 1] [6, 9, 3, 2] [3, 3, 2, 2] [5, 2, 10, 1, 13, 15, 14, 5, 11,…
Nearest smaller element def nearest_smaller(items): Given a list of integer items, create and return a new list of the same length but where each element has been replaced with the nearest element in the original list whose value is smaller. If no smaller elements exist because that element is the minimum of the original list, the element in the result list should remain as that same minimum element.If there exist smaller elements equidistant in both directions, you must resolve this by using the smaller of these two elements. This again makes the expected results unique for every possible value of items, which is necessary for the automated testing framework to work at all. Being permissive in what you accept while being restrictive in what you emit is a pretty good principle to follow in all walks of life, not just in programming. items Expected result [42, 42, 42] [42, 42, 42] [42, 1, 17] [1, 1, 1] [42, 17, 1] [17, 1, 1] [6, 9, 3, 2] [3, 3, 2, 2] [5, 2, 10, 1, 13, 15,…
def eliminate_neighbours (items): Given the sequence of integer items that are guaranteed to be some permutation of positive integers from 1 to n where n is the length of the list, find the smallest number among those that still remain in the list, and remove from the list both that number and whichever of its current immediate neighbours is larger. The function should repeat this basic operation until the largest number in the original list gets eliminated. Return the number of removal operations that were needed to achieve this goal. For example, given the list [5, 2, 1, 4, 6, 31, the operation would remove element 1 and its current larger neighbour 4, resulting in the list [5, 2, 6, 3]. Applied again, that operation would remove 2 and its current larger neighbour 6, thus reaching the goal in two steps. items Expected result [1, 6, 4, 2, 5, 3] 1 [8, 3, 4, 1, 7, 2, 6, 5] 3 [8, 5, 3, 1, 7, 2, 6, 4] 4 [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] 5 range (1, 10001) 5000 [1000] + list(range (1, 1000))…
A factor chainis a list where each previous element is a factor of the next consecutive element. The following is a factor chain: [3, 6, 18, 72] Example: is_factor_chain ([2, 4, 8, 9]) → False is_factor_chain ([2, 22, 66, 110]) → True WRITE IN PYTHON PLEASE
That's enough of you! def remove_after_kth(items, k=1): Given a list of items, some of which may be duplicated, create and return a new list that is otherwise the same as items, but only up to k occurrences of each element are kept, and all occurrences of that element after those first k are discarded.Hint: loop through the items, maintaining a dictionary that remembers how many times you have already seen each element. Update this count as you go, and append each element to the result list only if its count is still at most equal to k. items k Expected result [42, 42, 42, 42, 42, 42, 42] 3 [42, 42, 42] ['tom', 42, 'bob', 'bob', 99, 'bob', 'tom', 'tom', 99] 2 ['tom', 42, 'bob', 'bob', 99, 'tom', 99] [1, 2, 3, 4, 5, 4, 3, 2, 1, 2, 3, 4, 5, 4, 3, 2, 1] 1 [1, 2, 3, 4, 5] [1, 2, 3, 4, 5, 4, 3, 2, 1, 2, 3, 4, 5, 4, 3, 2, 1, 2, 3, 4, 5] 3 [1, 2, 3, 4, 5, 4, 3, 2, 1, 2, 3, 4, 5, 1, 5] [42, 42, 42, 99, 99, 17] 0 []