How Can I Efficiently Identify and Extract Duplicate Elements from a Python List?

Identifying and Isolating Duplicates in a List

In many programming scenarios, it becomes necessary to identify and handle duplicate elements within a list. This article will explore various approaches to isolate duplicates in a list and create a new list containing only those duplicated values.

To find the duplicates in a list, one can take advantage of Python's built-in dictionary or set data structures. One approach is to utilize Counter, a built-in class from the collections module. By using Counter, you can count the occurrences of each element in the list. The keys with a count greater than 1 represent duplicates.

To create a list of duplicates, you can further process the output of Counter. The code provided in the answer demonstrates this approach. However, it's important to note that Counter is not considered the most efficient method.

For a more efficient solution, one can employ a set, which is a collection of unique elements. By iterating through the list, you can check if each element is already present in the set. If it is, the element is a duplicate and can be added to your duplicate list.

For lists containing non-hashable elements, you cannot use sets or dictionaries. In such cases, you must resort to a quadratic-time solution, which compares each element with all previous elements.

The provided code examples illustrate the implementation of these various approaches to finding and isolating duplicates in a list. By selecting the appropriate method based on the specific requirements and characteristics of your list, you can effectively handle duplicate values in your Python programs.

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