What type of data can quicksort effectively handle?

Quicksort is a highly efficient sorting algorithm that excels at handling any data type that can be compared. This characteristic is essential for the algorithm to determine the order of elements. Quicksort relies on a "divide and conquer" strategy, where it selects a pivot element and partitions the dataset into elements less than and greater than the pivot. This process requires a defined method of comparison to ascertain the relative order of the data elements, making it versatile for various data types, including integers, floats, strings, and even complex objects, as long as a comparison operation is defined.

The algorithm is particularly valuable because it generally operates in average-case time complexity of O(n log n), making it suitable for larger datasets as well. However, it is less effective on partially sorted data than some other algorithms, yet it is still able to sort it efficiently. The assertion that quicksort can only handle numeric data types, small datasets, or sorted lists would limit its utility and does not reflect its true capabilities in sorting diverse data types effectively.