def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_l = sorted(l)
if len(l) % 2 == 1:
return sorted_l[len(l) // 2]
else:
return (sorted_l[len(l) // 2 - 1] + sorted_l[len(l) // 2]) / 2
[[[3, 1, 2, 4, 5]], [[-10, 4, 6, 1000, 10, 20]], [[5]], [[6, 5]], [[8, 1, 3, 9, 9, 2, 7]]] [[[10, 20, 30, 40, 50]], [[-5, -3, 0, 3, 5]], [[1, 3, 7, 8, 10, 10]], [[2, 2, 2, 2, 2, 2]], [[2, 5, 8, 11, 14]], [[1, 1, 1, 2, 3, 4]], [[-1, 0, 1]], [[100]], [[7, 9, 3, 5]], [[0, 0, 0, 0, 0, 0, 1]], [[1, 11, 3, 7, 8, 10, 10]], [[1, 1, 1, 3, 4]], [[0, 0, 0, 0, 1]], [[1, 1, 2, 2, 3, 4, 1]], [[100, 100]], [[1, 3, -1, 7, 8, 8, 10, 10, 8, 8]], [[1, 1, 1, 2, 2, 3, 4, 1, 1]], [[1, 3, 8, 10, 10]], [[1, 1, 2, 2, 3, 4, 1, 4]], [[1, 3, -1, 7, 8, 8, 10, 10, 8]], [[0, 0, 0, 0, 0, 0, 1, 0]], [[1, 11, 1, 3, 7, 8, 10, 10, 7]], [[1, 3, -1, 7, 8, 0, 10, 10, 8]], [[1, 1, 1, 2, 2, 3, 4, 1, 1, 1]], [[0, 0, 0, 1]], [[0, 0, 0, 11, 0, -1, 0, 1, 0]], [[0, 0, 10, 9, 0]], [[14, 100]], [[13, 15, 100]], [[10, 20, 4, 30, 40, 50]], [[1, 11, 4, 7, 8, 10, 7, 10]], [[7, 5, 9, 3, 5]], [[10, 20, -1, 30, 40, 50]], [[13, 0, 0, 1, 1, 0]], [[0, 0, 100, 1]], [[-5, -3, 0, 3, 5, 0]], [[1, 1, 1, 3, 4, 1]], [[14, 1, 3, 7, 8, 10, 10]], [[10, 20, 4, 30, 13, 2, 40, 50]], [[1, 1, 1, 4, 9, 1]], [[10, 20, 4, 30, 13, 2, 40, 50, 30]], [[14, 15, 100]], [[1, 11, 4, 7, 8, 10, 7, 10, 8]], [[100, 99, 100]], [[1, 1, 1, 2, 3, 4, 4]], [[10, 4, 30, 40, 51]], [[1, 1, 1, 3, 1, 1, 4]], [[0, 0, 2, 0, 0, 0, 0, 1, 0]], [[0, 2, 2, 2, 2, 2, 2]], [[7, 9, 3, 3, 5, 3]], [[-5, -3, 0, 3, 6]], [[1, 1, 2, 2, 3, 4, 1, 4, 4]], [[7, 10, 3, 3, 5, 3, 3]], [[7, 5]], [[7, 10, 3, 3, 3, 5, 3, 3, 3]], [[1, 1, 1, 2, 3, 4, 1, 4, 4]], [[1, 1, 1, 0, 9, 1]], [[1, 1, 8, 2, 8, 3, 5, 1]], [[1, 1, 2, 2, 3, 4, 1, 3, 4]], [[1, 1, 1, 2, 3, 6, 99, 4, 4]], [[1, 1, 4, 8, 8, 3, 5, 1]], [[1, 30, 2, 3, 4, 1, 3, 4, 4]], [[1, 3, 7, 8, 8, 10, 8]], [[6, 1, 3, -1, 7, 8, 8, 10, 10, 8, 8]], [[0, 0, 40, 2]], [[2, 5, 40, 8, 11, 14]], [[-5, -3, 0, 3, 5, -5]], [[-5, -3, 0, 4, 5]], [[0, 0, 0, 11, 0, -1, 0, 1, 6, 0]], [[0, 0, 14, -1, 0, 1]], [[-5, -3, 0, 4, 5, 0]], [[10, 1, 1, 1, 3, 4]], [[-5, 50, 0, 3, 6]], [[1, 3, -1, 9, 7, 8, 0, 10, 10, 8]], [[1, 4, 1, 8, 2, 8, 3, 5, 1]], [[1, 1, 20, 2, 3, 6, 99, 4, 4, 1, 2]], [[1, 1, 1, 3, 1, 4]], [[1, 3, 7, 8, 3, 10]], [[1, 1, 1, 2, 2, 3, 4, 1, 1, 3]], [[-1, -3, 0, 3, 5, -6, 0, 0]], [[1, 1, 2, 3, 4, 4]], [[1, 51, 1, 1, 4, 9, 1]], [[10, 20, 30, 40, 50, 50]], [[1, 4, 30, 8, 2, 8, 3, 5, 1]], [[-5, -3, 0, 3, -5]], [[7, 8, 5]], [[1, 1, 1, 14, 2, 2, 3, 4, 1, 4]], [[0, 0, 9, 0, 0, 0]], [[19, 7, 9, 3, 5]], [[1, 1, 2, 5, 2, 3, 4, 1, 3, 4]], [[7, 5, 9, 3, 5, 5]], [[1, 3, -1, 7, 8, 8, 10, 10, -3]], [[10, 20, -1, 40, 50, -1]], [[9, 3, 5]], [[0, 2, 2, 1, 2, 2, 2, 2]], [[7, 5, 9, 3, 5, 4]], [[-5, 51, 50, 0, 3, 6]], [[2, 5, 8, 11, 14, 14]], [[-5, 51, 50, 0, 6]], [[9, 11, 1, 2, 6, 8, 3, 15, 15]], [[10, 9, 8, 7, 6, 5, 4, 3]], [[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10]], [[2, 4, 5, 6, 8, 10, 12, 14, 20, 22]], [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]], [[20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]], [[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], [[3.5, 5.7, 6.1, 7.2, 10.0, 12.5, 13.0, 14.5, 16.8, 19.7]], [[2.7, 3.8, 7, 13, 74, 108.3]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99]], [[2, 4, 5, 6, 8, 10, 12, 14, 20, 22, 8]], [[10, 9, 8, 6, 5, 4, 3, 4]], [[20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 4, 3, 2, 1]], [[2, 4, 5, 6, 8, 10, 12, 14, 20, 22, 8, 2]], [[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10]], [[3.5, 5.7, 6.1, 7.2, 10.0, 13.0, 14.5, 16.8, 19.7, 6.1]], [[2, 4, 5, 6, 8, 10, 14, 20, 22, 8, 2, 8]], [[20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 2, 9, 8, 7, 6, 4, 3, 2, 1]], [[10, 8, 6, 5, 4, 3]], [[1, 2, 3, 4, 5, 6, 8, 9, 10, 77, 12, 13, 14, 15, 16, 17, 18, 19, 20, 2]], [[2, 3, 5, 6, 8, 10, 12, 14, 20, 22]], [[2, 5, 6, 8, 10, 12, 14, 19, 22, 8, 2]], [[10, 8, 6, 5, 4, 3, 4]], [[2, 4, 5, 99, 8, 10, 12, 14, 20, 22, 8, 6]], [[3.5, 5.7, 6.1, 7.2, 13.0, 14.5, 19.7, 6.1]], [[3, 4, 5, 8, 12, 14, 20, 22, 8, 2, 4]], [[2, 4, 65, 5, 6, 8, 12, 14, 20, 22, 8, 2]], [[2, 8, 5, 6, 8, 10, 12, 14, 19, 23, 8, 2]], [[10, 9, 8, 7, 4, 6, 5, 4, 3]], [[2, 4, 6, 8, 10, 12, 14, 20, 22]], [[10, 9, 8, 6, 5, 4, 11, 3, 4, 8]], [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 55, 20]], [[49, 2, 6, 5, 6, 8, 10, 12, 14, 20, 22, 8, 2, 14, 14]], [[49, 2, 6, 5, 6, 10, 12, 14, 20, 22, 8, 2, 14, 14]], [[2, 5, 6, 8, 10, 12, 14, 19, 22, 8, 2, 12]], [[2, 8, 5, 6, 8, 10, 12, 14, 19, 23, 8, 2, 5]], [[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17, 18, 19, 20]], [[2, 4, 5, 6, 8, 10, 14, 20, 22, 8, 2, 8, 6]], [[3.5, 5.7, 108.3, 6.1, 7.2, 10.0, 13.0, 14.5, 16.8, 19.7, 6.1]], [[2, 4, 6, 10, 12, 47, 20, 22]], [[10, 9, 8, 7, 4, 6, 6, 4, 3]], [[10, 9, 8, 8, 4, 6, 5, 4, 3]], [[2, 4, 5, 6, 8, 10, 12, 14, 20, 22, 10]], [[6, 5, 4, 3]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 81]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 59, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 81]], [[2, 4, 5, 65, 5, 6, 8, 12, 14, 20, 22, 8, 66, 2]], [[10, 9, 8, 6, 5, 63, 4, 3, 4]], [[2, 4, 5, 6, 8, 25, 12, 14, 20, 22]], [[20, 19, 18, 17, 16, 15, 14, 13, 12, 13, 10, 2, 9, 8, 7, 6, 4, 3, 2, 1]], [[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10]], [[6, 5, 4, 2, 77, 77]], [[2, 4, 5, 6, 8, 10, 12, 14, 21, 21, 22, 8, 2, 21, 8]], [[20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 4, 3, 0, 2, 1]], [[10, 3, 8, 17, 6, 5, 63, 4, 3, 4]], [[3.5, 5.7, 6.1, 7.2, 13.0, 14.5, 19.7, 20.313196843325887, 6.1]], [[2, 4, 5, 6, 8, 10, 14, 20, 22, 8, 2, 8, 6, 10]], [[2, 5, 6, 8, 10, 12, 14, 19, 23, 8, 2, 5]], [[19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]], [[2, 4, 5, 6, 8, 10, 14, 20, 22, 8, 2, 8, 6, 4]], [[3.5, 5.7, 6.1, 7.2, 10.0, 12.5, 13.0, 16.8, 19.7]], [[1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]], [[2, 5, 6, 8, 10, 12, 14, 19, 22, 8, 12]], [[10, 9, 8, 6, 5, 4, 3]], [[2, 4, 5, 6, 11, 8, 10, 12, 14, 20, 22, 8, 2]], [[6, 5, 4, 2, 77, 7, 77, 7]], [[10, 9, 8, 7, 6, 5, 4, 3, 5]], [[10, 9, 74, 8, 6, 5, 63, 4, 3, 4]], [[2, 4, 5, 8, 10, 14, 11, 20, 22, 8, 2, 6, 4]], [[11, 10, 9, 8, 6, 4, 3, 6]], [[2, 5, 6, 8, 10, 12, 13, 19, 22, 8, 2, 8]], [[20, 19, 33, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 4, 3, 0, 2, 1]], [[10, 3, 8, 17, 6, 5, 63, 4, 4]], [[2, 3, 5, 6, 8, 10, 12, 14, 20, 22, 8]], [[20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 17]], [[10, 9, 2, 74, 8, 6, 5, 63, 4, 3, 4]], [[20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 95, 6, 5, 4, 3, 2, 17]], [[3.5, 5.7, 6.1, 21.08302178845001, 7.2, 13.0, 14.5, 19.7, 20.313196843325887, 6.1]], [[49, 2, 6, 5, 69, 6, 10, 12, 14, 20, 22, 8, 2, 14, 14, 6]], [[2, 5, 6, 8, 25, 12, 14, 20, 22]], [[10, 9, 2, 35, 74, 8, 6, 5, 63, 3, 3, 4]], [[4, 5, 6, 8, 10, 14, 21, 20, 22, 8, 2]], [[10, 9, 7, 8, 7, 4, 6, 5, 4, 3]], [[2, 5, 6, 8, 10, 12, 14, 19, 53, 8, 2, 5]], [[2, 4, 6, 8, 12, 14, 20, 22, 10]], [[2, 5, 8, 10, 14, 11, 20, 22, 8, 2, 6, 4]], [[49, 2, 6, 5, 6, 10, 12, 14, 20, 22, 8, 33, 2, 14, 14]], [[2, 4, 5, 65, 5, 6, 12, 14, 20, 22, 8, 66, 2, 14]], [[2, 4, 65, 8, 5, 6, 8, 12, 14, 20, 22, 8, 2]], [[10, 9, 74, 6, 5, 63, 4, 3, 4]], [[10, 9, 8, 7, 6, 5, 83, 4, 3]], [[2, 4, 65, 5, 6, 8, 12, 14, 20, 22, 8, 2, 14]], [[2, 5, 6, 8, 10, 12, 13, 19, 22, 8, 8]], [[2, 4, 6, 8, 10, 13, 14, 20, 22, 8]], [[10, 9, 7, 6, 5, 45, 83, 4, 3]], [[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5, 79, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10]], [[2, 31, 5, 65, 5, 6, 12, 14, 73, 22, 8, 66, 2, 14]], [[10, 9, 8, 6, 5, 4, 3, 6]], [[7, 2, 5, 6, 8, 10, 12, 13, 19, 22, 8, 8]], [[3.5, 8.444288359340977, 6.1, 7.2, 10.0, 12.209142157602413, 13.0, 16.8, 19.7]], [[9, 8, 8, 4, 6, 5, 4, 3]], [[7, 8, 7, 55, 4, 6, 5, 4, 3]], [[2, 13, 4, 65, 8, 5, 6, 8, 12, 14, 20, 4, 22, 8, 2]], [[2, 4, 6, 8, 12, 14, 91, 20, 22, 10]], [[2, 5, 6, 8, 10, 12, 14, 19, 53, 8, 2, 5, 14]], [[20, 19, 33, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 4, 3, 0, 2, 1, 0, 10]], [[2, 4, 5, 6, 11, 8, 10, 12, 14, 20, 8, 12, 2]], [[10, 9, 7, 7, 7, 4, 6, 5, 4, 3]], [[2, 4, 6, 8, 10, 13, 14, 20, 22, 8, 10]], [[10, 9, 74, 6, 5, 63, 5, 3, 4, 3]], [[10, 9, 8, 0, 6, 5, 4, 3, 9]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 16, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 81]], [[19, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]], [[2, 4, 6, 8, 12, 14, 20, 22, 10, 2]], [[2, 4, 5, 6, 8, 10, 12, 14, 20, 22, 6]], [[2, 4, 6, 8, 10, 14, 20, 22, 8, 10, 2]], [[4, 5, 6, 8, 10, 14, 21, 20, 8, 2]], [[10, 3, 8, 17, 6, 5, 4, 4]], [[2, 4, 5, 6, 8, 10, 14, 20, 8, 2, 6]], [[14, 5, 6, 8, 10, 14, 20, 22, 8, 5, 8, 6]], [[6, 5, 4, 2, 77, 7, 53, 7]], [[10, 3, 8, 17, 6, 5, 4, 4, 3, 4]], [[3.5, 5.7, 5.94681395028438, 7.2, 10.0, 14.5, 16.8, 19.7, 6.1]], [[10, 3, 8, 17, 6, 5, 18, 4, 4]], [[2, 4, 5, 6, 8, 10, 14, 20, 22, 8, 2, 8, 6, 10, 14]], [[10, 9, 8, 7, 5, 83, 4, 3]], [[10, 9, 8, 7, 4, 6, 6, 4, 3, 9]], [[2, 4, 5, 6, 8, 3, 12, 14, 20, 22, 8, 5, 3]], [[20, 19, 18, 17, 16, 15, 14, 13, 13, 10, 2, 9, 8, 7, 6, 4, 3, 2, 1]], [[2, 4, 5, 8, 6, 8, 10, 14, 20, 22, 8, 2, 8]], [[2, 4, 5, 6, 8, 10, 14, 20, 22, 8, 2, 8, 5]], [[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0]], [[3.5, 4.972052479951237, 5.7, 5.94681395028438, 7.2, 10.0, 14.5, 16.8, 19.7, 6.1]], [[2, 4, 5, 11, 8, 10, 12, 14, 20, 22, 8, 2]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 31, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99]], [[2, 4, 5, 8, 6, 8, 10, 14, 20, 8, 2, 15, 8]], [[2, 4, 6, 8, 87, 13, 14, 20, 22, 8, 8]], [[1, 2, 3, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]], [[9, 8, 8, 4, 6, 5, 4, 67, 3]], [[2, 5, 6, 8, 10, 12, 14, 19, 22, 67, 2, 12, 2]], [[63, 9, 8, 7, 6, 5, 4, 3, 5]], [[3.5, 5.7, 5.94681395028438, 7.2, 10.0, 14.5, 16.8, 19.7, 6.1, 14.5]], [[2, 4, 5, 11, 8, 10, 12, 14, 22, 8, 2]], [[1, 2, 3, 4, 5, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20]], [[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 5, 79, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 4]], [[10.12356677785131, 3.5, 5.128879860111899, 108.3, 6.1, 7.2, 10.0, 13.0, 14.5, 16.8, 19.7, 3.660183044477323, 6.1]], [[2, 5, 6, 8, 10, 12, 14, 19, 53, 8, 2, 5, 10, 14]], [[0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], [[2, 8, 5, 6, 8, 10, 12, 14, 19, 23, 8, 2, 14]], [[10, 9, 8, 8, 4, 6, 5, 4, 3, 6]], [[2, 4, 6, 8, 10, 13, 14, 20, 22, 8, 20]], [[2, 8, 5, 6, 8, 10, 12, 14, 19, 23, 8, 2, 14, 12]], [[1, 2, 3, 2, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 7]], [[10, 9, 8, 7, 6, 5, 4, 3, 9]], [[4, 6, 8, 10, 12, 14, 20, 22, 22]], [[2, 4, 6, 11, 8, 10, 12, 14, 20, 8, 12, 2]], [[2, 31, 5, 65, 5, 6, 12, 14, 73, 22, 8, 66, 2]], [[2, 5, 4, 6, 8, 10, 12, 14, 19, 53, 8, 2, 5]], [[10, 9, 8, 7, 6, 5, 83, 9, 4, 3]], [[2, 4, 5, 6, 11, 8, 10, 12, 20, 8, 12, 2]], [[2, 4, 5, 6, 8, 10, 12, 14, 15, 22]], [[6, 4, 2, 77, 77]], [[8, 4, 5, 7, 8, 57, 12, 14, 15, 22]], [[19, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 6, 1]], [[1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20]], [[20, 19, 18, 17, 16, 15, 14, 13, 13, 10, 2, 9, 8, 7, 6, 4, 3, 2]], [[9, 8, 7, 6, 5, 4, 3, 5, 5]], [[3, 8, 17, 6, 5, 4, 4, 3, 4]], [[2, 77, 3, 5, 6, 8, 10, 12, 14, 20, 22, 8]], [[2, 31, 5, 65, 5, 6, 12, 14, 73, 22, 8, 66, 2, 12]], [[2, 5, 6, 8, 25, 12, 14, 20, 22, 5]], [[2, 4, 5, 6, 8, 10, 14, 20, 22, 8, 2, 8, 83, 4]], [[3.5, 5.7, 108.3, 6.1, 7.2, 10.0, 14.5, 16.8, 19.7, 6.1]], [[7, 5, 4, 2, 77, 7, 53, 7]], [[4, 5, 6, 9, 8, 10, 14, 21, 20, 22, 8, 2]], [[2, 9, 4, 5, 8, 10, 14, 20, 22, 8, 2, 8]], [[2, 5, 6, 8, 10, 12, 14, 19, 53, 8, 2, 5, 10]], [[2, 8, 5, 6, 8, 10, 12, 14, 19, 23, 2, 5, 8]], [[3.5, 5.7, 6.1, 13.0, 13.0, 14.5, 16.8, 19.7, 6.1]], [[10, 9, 8, 7, 4, 6, 6, 4, 3, 9, 6, 6]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 41, 87, 89, 91, 93, 95, 97, 99]], [[2, 8, 5, 6, 8, 10, 12, 14, 19, 59, 8, 2, 14]], [[2, 4, 5, 6, 11, 8, 10, 12, 20, 5, 12, 2]], [[39, 2, 3, 5, 6, 7, 8, 9, 10, 11, 12, 49, 13, 14, 15, 17, 18, 19, 20]], [[20, 20, 18, 17, 16, 15, 14, 13, 12, 11, 10, 9, 8, 7, 95, 6, 5, 4, 3, 2, 17, 18]], [[10, 9, 7, 7, 7, 4, 5, 4, 3]], [[10, 3, 8, 6, 5, 4, 5, 3, 4]], [[10, 9, 8, 6, 5, 4, 3, 17, 5]], [[1, 2, 5, 6, 8, 10, 12, 14, 19, 53, 8, 2, 5]], [[2, 71, 5, 6, 8, 10, 12, 13, 19, 8, 2, 8]], [[2, 5, 8, 10, 14, 11, 20, 22, 8, 2, 6, 4, 5]], [[5, 6, 5, 4, 2, 77, 7, 53, 7, 5]], [[2, 4, 65, 6, 8, 12, 14, 20, 22, 8, 2, 14]], [[10, 9, 63, 8, 7, 4, 6, 35, 6, 4, 3]], [[3.5, 8.444288359340977, 6.1, 7.2, 10.0, 12.209142157602413, 13.0, 16.8, 19.7, 19.7]], [[2.7, 3.8, 7, 13, 74, 108.3, 108.3]], [[2, 5, 6, 2, 8, 10, 12, 14, 19, 23, 8, 2, 5]], [[2, 8, 5, 6, 8, 10, 12, 14, 19, 59, 8, 99, 14]], [[9, 12, 1, 79, 12, 6, 8, 3, 15, 15]], [[2, 4, 5, 65, 11, 8, 10, 12, 14, 20, 8, 12, 2]], [[10, 9, 2, 35, 74, 8, 6, 51, 63, 3, 3, 4]], [[63, 19, 18, 17, 16, 15, 14, 13, 12, 11, 9, 8, 7, 6, 5, 4, 3, 2, 1, 18]], [[2, 8, 6, 8, 10, 12, 14, 19, 23, 8, 2]], [[2, 5, 4, 6, 8, 13, 12, 14, 19, 53, 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-1, 74, 108.3, 74]], [[20, 19, 18, 17, 16, 15, 8, 14, 51, 12, 11, 10, 9, 8, 7, 6, 17, 4, 3, 2, 1, 4]], [[3, 5, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 16, 29, 31, 33, 35, 37, 31, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 16, 93, 97, 99, 27, 57]], [[20, 19, 18, 17, 16, 15, 14, 51, 12, 11, 10, 9, 8, 7, 6, 16, 4, 3, 2, 1, 4, 8, 16]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 81, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 47, 49, 51, 53, 55, 57, 59, 61, 63, 66, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 25, 97, 91]], [[3.5, 6.906137655178807, 6.1, 7.2, 10.0, 3.1081725885917266, 7.2, 12.5, 13.0, 16.8, 12.5]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 89, 91, 93, 95, 97, 99, 25, 97, 91, 49]], [[3.6937336190229844, 6.1, 7.2, 10.0, 13.0, 14.47378456555137, 108.3, 14.213498962327462, 19.7, 108.3]], [[3.5, 6.1, 7.2, 13.0, 10.0, 4.136783373043628, 7.2, 12.5, 13.0, 16.8, 14.213498962327462, 19.7]], [[20, 19, 18, 17, 14, 16, 15, 14, 27, 12, 11, 10, 9, 7, 6, 4, 3, 2, 1]], [[20, 19, 16, 18, 17, 16, 15, 14, 27, 12, 11, 10, 9, 7, 47, 6, 4, 3, 2, 89, 11]], [[3.5, 6.1, 7.2, 9.803592607783843, 10.0, 12.5, 13.0, 5.657718598667383, 13.881537995629861, 16.8, 14.213498962327462, 14.42427393794269, 6.1]], [[2, 4, 75, 6, 61, 6, 83, 20, 22]], [[20, 19, 18, 17, 16, 15, 14, 51, 12, 81, 11, 10, 9, 8, 97, 57, 7, 6, 16, 4, 3, 2, 1, 4, 16, 12]], [[0, 0, 55, 0, 0, 1, 2, 5, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 5, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 4, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 9, 6]], [[2.945266333073926, 3.9717541945283297, 13.0, 7, 8, 74, 3.8]], [[20, 19, 18, 17, 16, 15, 14, 13, 13, 11, 9, 8, 7, 6, 5, 4, 3, 2, 1]], [[0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10]], [[9, 11, 1, 2, 6, 8, 3, 18, 15, 15, 1, 15, 15]], [[3.5, 6.1, 7.2, 9.803592607783843, 10.0, 12.5, 5.657718598667383, 13.881537995629861, 16.8, 14.213498962327462, 14.42427393794269, 6.1, 9.803592607783843, 3.5]], [[2.7, 13.0, 8, 74, 3.8]], [[3.5, 5.7, 6.1, 7.2, 10.0, 13.0, 14.5, 16.8, 14.213498962327462, 19.7, 13.0, 7.2, 16.8]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 16, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 85, 87, 41, 89, 91, 93, 95, 97, 99, 27]], [[3.5, 5.7, 6.1, 7.2, 10.0, 14.42427393794269, 12.5, 13.0, 16.8, 12.5]], [[0, 0, 11, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 75, 3, 3, 5, 4, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10]], [[20, 19, 18, 17, 16, 15, 14, 13, 13, 11, 11, 10, 9, 8, 7, 5, 4, 3, 2, 1, 18, 3, 9]], [[2.7, 13.0, 7, 77, 8, 13, 74, 13]], [[2, 3, 4, 5, 6, 7, 65, 9, 10, 12, 13, 14, 15, 17, 18, 19, 20, 16, 2]], [[3.5, 5.7, 5.027102188026641, 7.2, 9.922115344671733, 12.5, 14.5, 16.8, 19.7, 7.2, 3.5]], [[9, 11, 1, 2, 91, 6, 8, 4, 15, 2, 14, 1, 1, 9, 1]], [[20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 11, 9, 8, 7, 6, 6, 16, 4, 3, 2, 1, 7, 14, 7, 12, 16]], [[0, 0, 11, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 75, 3, 3, 5, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 9]], [[9, 11, 1, 2, 92, 6, 8, 4, 15, 2, 15, 6]], [[3.5, 6.1, 7.2, 13.0, 10.0, 4.136783373043628, 12.4139453493653, 12.5, 13.0, 14.47378456555137, 16.8, 14.213498962327462, 19.7]], [[20, 19, 18, 17, 16, 15, 14, 0, 27, 12, 11, 10, 9, 8, 7, 6, 4, 3, 2, 3]], [[9, 11, 1, 2, 5, 3, 47, 15, 15, 5]], [[3.5, 5.7, 8.697319710424937, 7.2, 5.913667772046774, 10.0, 12.5, 11.133332587842302, 13.0, 16.8, 12.5]], [[2, 4, 75, 19, 6, 61, 6, 8, 83, 20, 22]], [[20, 19, 18, 17, 16, 15, 13, 14, 13, 3, 13, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 15]], [[3.5, 5.7, 6.1, 7.2, 9.002985377555673, 4.837062573049252, 12.5, 13.0, 14.5, 16.8, 19.7, 19.7, 7.2]], [[13.407092269148752, 3.5, 5.7, 6.1, 7.2, 7.606098776477131, 10.0, 12.5, 13.0, 14.5, 16.8, 7.575286371007363, 7.083773361754937, 14.213498962327462, 19.7, 13.0, 14.42427393794269, 13.0]], [[2.7, 15, 74, 108.3, 74]], [[3.5, 6.1, 16.68010840495699, 7.2, 10.0, 12.5, 13.0, 16.8, 12.5]], [[9, 11, 1, 2, 6, 8, 3, 15, 15, 2, 15, 2]], [[20, 19, 18, 17, 16, 15, 8, 14, 51, 12, 11, 10, 9, 8, 7, 6, 17, 4, 4, 3, 2, 1, 4]], [[20, 19, 18, 16, 15, 14, 27, 11, 10, 8, 7, 6, 4, 3, 2, 1, 6, 7]], [[83, 20, 31, 19, 18, 17, 16, 15, 13, 14, 13, 13, 11, 10, 9, 8, 6, 5, 4, 3, 2, 1]], [[20, 19, 67, 18, 17, 16, 15, 14, 0, 27, 12, 11, 10, 77, 5, 8, 3, 7, 6, 4, 3, 2, 1, 16]], [[10, 9, 8, 7, 6, 3, 4, 4, 3]], [[20, 20, 18, 17, 16, 15, 8, 27, 83, 11, 10, 9, 6, 4, 3, 2, 1, 16]], [[9, 11, 1, 2, 91, 6, 8, 4, 15, 2, 14, 1, 1, 9, 2, 65, 9, 2]], [[2.7, 3.8, 7, 8, 81, 75, 69]], [[2, 4, 75, 6, 6, 8, 83, 12, 20, 22, 22]], [[10, 2, 7, 3, 6, 4, 4, 3, 7]], [[9, 11, 0, 2, 6, 8, 3, 15, 15, 0]], [[12.4139453493653, 3.5, 6.1, 10.0, 12.5, 14.412035246301148, 14.47378456555137, 16.8, 14.213498962327462, 19.7, 16.8]], [[20, 19, 18, 77, 16, 15, 14, 27, 12, 11, 10, 8, 8, 6, 4, 3, 71, 1, 18, 8]], [[20, 8, 51, 18, 17, 74, 16, 16, 14, 51, 12, 11, 10, 9, 8, 7, 16, 4, 3, 2, 1]], [[9, 9, 8, 8, 7, 9, 18, 6, 5, 4, 3, 6]], [[1, 3, 5, 7, 9, 13, 15, 17, 19, 21, 23, 25, 91, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 85, 87, 89, 91, 93, 95, 97, 99, 55, 51]], [[1, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 87, 89, 91, 93, 95, 97, 99]], [[3.5, 5.7, 6.1, 7.2, 10.0, 13.0, 14.5, 16.8, 19.7, 13.0, 7.2]]] claude-3-haiku-20240307. fail_base: False, fail_plus: False
Here's the completed code to find the median of a list of elements:
```python
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_list = sorted(l)
length = len(sorted_list)
if length % 2 == 0:
# If the length of the list is even, the median is the average of the two middle elements
middle1 = sorted_list[length // 2 - 1]
middle2 = sorted_list[length // 2]
return (middle1 + middle2) / 2
else:
# If the length of the list is odd, the median is the middle element
return sorted_list[length // 2]code-millenials-34b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l."""
n = len(l)
s = sorted(l)
return (sum(s[n//2-1:n//2+1])/2.0, s[n//2])[n%2] if n else Nonespeechless-coding-7b-16k-tora. fail_base: False, fail_plus: False
def median(l: list):
n = len(l)
l.sort()
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]
# Test cases
print(median([3, 1, 2, 4, 5])) # Output: 3
print(median([-10, 4, 6, 1000, 10, 20])) # Output: 15.0claude-3-opus-20240229. fail_base: False, fail_plus: False
Here's the code to complete the `median` function, wrapped in a markdown block:
```python
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_list = sorted(l)
length = len(sorted_list)
mid = length // 2
if length % 2 == 0:
return (sorted_list[mid - 1] + sorted_list[mid]) / 2
else:
return sorted_list[mid]mixtral-8x7b-instruct. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
# Sort the list
l.sort()
# Calculate the middle index
middle_index = len(l) // 2
# If the list has an odd length, return the middle element
if len(l) % 2 == 1:
return l[middle_index]
# If the list has an even length, return the average of the two middle elements
else:
return (l[middle_index - 1] + l[middle_index]) / 2mixtral-8x22b-instruct-v0.1. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_l = sorted(l)
length = len(sorted_l)
middle = length // 2
if length % 2 == 0:
return (sorted_l[middle - 1] + sorted_l[middle]) / 2
else:
return sorted_l[middle]
# Test cases
assert median([3, 1, 2, 4, 5]) == 3
assert median([-10, 4, 6, 1000, 10, 20]) == 15.0
assert median([1, 2, 3]) == 2
assert median([1, 2, 3, 4]) == 2.5
assert median([1]) == 1
assert median([]) == Nonecode-llama-multi-34b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
if len(l) % 2 == 0:
return (l[len(l) // 2] + l[len(l) // 2 - 1]) / 2
else:
return l[len(l) // 2]
if __name__ == "__main__":
import doctest
doctest.testmod()
Qwen--Qwen1.5-72B-Chat. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_l = sorted(l)
length = len(sorted_l)
mid = length // 2
if length % 2 == 0:
return (sorted_l[mid - 1] + sorted_l[mid]) / 2.0
else:
return sorted_l[mid]
# Test cases
assert median([3, 1, 2, 4, 5]) == 3
assert median([-10, 4, 6, 1000, 10, 20]) == 15.0mistral-large-latest. fail_base: False, fail_plus: False
Sure, here is the Python code to solve the problem:
```python
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]
```
This code first sorts the list, then calculates the median. If the length of the list is even, it returns the average of the two middle numbers. If the length of the list is odd, it returns the middle number.HuggingFaceH4--starchat2-15b-v0.1. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
n = len(l)
s = sorted(l)
return (s[n//2] if n % 2 == 1 else (s[n//2 - 1] + s[n//2]) / 2)
# Test casescodegemma-7b. fail_base: True, fail_plus: True
To find the median of a list of numbers, you first sort the list in ascending order and then return the middle number if list size is odd or the average of two middle numbers if list size is even. Here is the Python implementation:
code-llama-multi-13b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 1:
return l[n // 2]
else:
return (l[n // 2] + l[n // 2 - 1]) / 2
def mean(l: list):
"""Return mean of elements in the list l.
>>> mean([3, 1, 2, 4, 5])
3.0
>>> mean([-10, 4, 6, 1000, 10, 20])
150.0
"""
return sum(l) / len(l)
def mode(l: list):
"""Return mode of elements in the list l.
>>> mode([3, 1, 2, 4, 5])
3
>>> mode([-10, 4, 6, 1000, 10, 20])
10
"""
d = {}
for i in l:
if i in d:
d[i] += 1
else:
d[i] = 1
m = max(d.values())
for k, v in d.items():
if v == m:
return k
def variance(l: list):
"""Return variance of elements in the list l.
>>> variance([3, 1, 2, 4, 5])
2.0
>>> variance([-10, 4, 6, 1000, 10, 20])
100000.0
"""
m = mean(l)
return sum([(i - m) ** 2 for i in l]) / len(l)
def standard_deviation(l: list):
"""Return standard deviation of elements in the list l.
>>> standard_deviation([3, 1, 2, 4, 5])
1.4142135623730951
>>> standard_deviation([-10,deepseek-coder-6.7b-instruct. fail_base: True, fail_plus: True
Sure, here is the Python function in a markdown style code block:
```markdown
```python
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
```
```
Please note that the actual implementation of the function is not included in the code block.
open-hermes-2.5-code-290k-13b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]speechless-coder-ds-6.7b. fail_base: False, fail_plus: False
def median(l: list):
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2] + l[n//2 - 1]) / 2
else:
return l[n//2]codegemma-7b-it. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]deepseek-coder-33b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
if len(l) % 2 == 0:
return (l[len(l) // 2] + l[len(l) // 2 - 1]) / 2
else:
return l[len(l) // 2]
mistralai--Mistral-7B-Instruct-v0.2. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
def median(l):
"""Return median of elements in the list l.
"""
l = sorted(l)
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]
xwincoder-34b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_l = sorted(l)
n = len(sorted_l)
if n % 2 == 0:
return (sorted_l[n // 2 - 1] + sorted_l[n // 2]) / 2
else:
return sorted_l[n // 2]
# Test cases
print(median([3, 1, 2, 4, 5])) # Output: 3
print(median([-10, 4, 6, 1000, 10, 20])) # Output: 15.0code-13b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
n = len(l)
s = sorted(l)
return (s[n//2] if n % 2 == 1 else (s[n//2 - 1] + s[n//2]) / 2)
print(median([3, 1, 2, 4, 5]))
print(median([-10, 4, 6, 1000, 10, 20]))wizardcoder-15b. fail_base: True, fail_plus: True
Here's the Python script for the problem:
```python
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]
```
The function `median` takes a list `l` as input and returns the median of its elements. The median is the middle value of a sorted list. If the list has an even number of elements, the median is the average of the two middle values.
The function first computes the length of the list `l` and checks if it's even or odd. If it's even, it computes the average of the two middle values and returns it. If it's odd, it returns the middle value.
The function uses integer division `//` to compute the middle index of the list. If the list has an odd number of elements, the middle index is simply `n//2`. If the list has an even number of elements, the middle index is the average of `n//2 - 1` and `n//2`. This is because the list is zero-indexed, so the middle index of an odd-length list is `n//2`, and the middle index of an even-length list is the average of `n//2 - 1` and `n//2`.mistral-7b-codealpaca. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2] + l[n//2 - 1]) / 2
else:
return l[n//2]
deepseek-coder-33b-instruct. fail_base: False, fail_plus: False
Here is the Python function for calculating the median of a list of numbers:
```python
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_l = sorted(l)
len_l = len(l)
mid = len_l // 2
if len_l % 2 == 0:
return (sorted_l[mid - 1] + sorted_l[mid]) / 2
else:
return sorted_l[mid]
```
This function first sorts the list in ascending order. If the length of the list is even, it calculates the average of the two middle numbers. If the length of the list is odd, it returns the middle number.
<|EOT|>phi-2. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]
def mean(l: list):
"""Return mean of elements in the list l.
>>> mean([3, 1, 2, 4, 5])
3.0
>>> mean([-10, 4, 6, 1000, 10, 20])
-103.33333333333333
"""
return sum(l) / len(l)
def mode(l: list):
"""Return mode of elements in the list l.
>>> mode([3, 1, 2, 4, 5])
3
>>> mode([-10, 4, 6, 1000, 10, 20])
Traceback (most recent call last):
...
ValueError: no unique mode
"""
d = {}
for i in l:
if i in d:
d[i] += 1
else:
d[i] = 1
m = max(d.values())
modes = [k for k, v in d.items() if v == m]
if len(modes) == 1:
return modes[0]
else:
raise ValueError("no unique mode")
def variance(l: list):
"""Return variance of elements in the list l.
>>> variance([3, 1, 2, 4, 5])
2.5
>>> variance([-10, 4, 6, 1000, 10, 20])
833.3333333333334
"""
m = mean(l)
return sum((x - m)**2 for x in l) / len(l)
def standard_deviation(l: list):
"""Return standard deviation of elements in the list l.
>>> standard_deviation([3, 1, 2, 4, 5])
1.5811388300841898
>>> standard_deviation([-10, 4, 6, 1000, 10, 20])
833.0
"""
return variancebigcode--starcoder2-15b-instruct-v0.1. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 1:
return l[n // 2]
else:
return (l[n // 2 - 1] + l[n // 2]) / 2white-rabbit-neo-33b-v1. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_list = sorted(l)
length = len(sorted_list)
if length % 2 == 0:
# If the length is even, take the average of the two middle elements
mid_index = length // 2
return (sorted_list[mid_index - 1] + sorted_list[mid_index]) / 2
else:
# If the length is odd, take the middle element
mid_index = length // 2
return sorted_list[mid_index]microsoft--Phi-3-mini-4k-instruct. fail_base: False, fail_plus: False
def median(l: list) -> float:
"""Return median of elements in the list l.
Args:
l (list): A list of numbers.
Returns:
float: The median of the elements in the list.
Examples:
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
10.0
"""
l.sort()
n = len(l)
mid = n // 2
if n % 2 == 0:
return (l[mid - 1] + l[mid]) / 2
else:
return l[mid]
# Test casesspeechless-codellama-34b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]
```
This script defines a function `median` that takes a list `l` as input and returns the median of its elements. The function first sorts the list in ascending order, then checks if the length of the list is even or odd. If it's even, it returns the average of the two middle elements; if it's odd, it returns the middle element.
meta-llama-3-70b-instruct. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l."""
sorted_l = sorted(l)
n = len(sorted_l)
midpoint = n // 2
if n % 2 == 1:
# if length of list is odd, return middle element
return sorted_l[midpoint]
else:
# if length of list is even, return average of two middle elements
return (sorted_l[midpoint - 1] + sorted_l[midpoint]) / 2
# Test cases
print(median([3, 1, 2, 4, 5])) # 3
print(median([-10, 4, 6, 1000, 10, 20])) # 15.0code-llama-70b-instruct. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n // 2 - 1] + l[n // 2]) / 2
else:
return l[n // 2]
if __name__ == "__main__":
import doctest
doctest.testmod()opencodeinterpreter-ds-33b. fail_base: False, fail_plus: False
```python
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
n = len(l)
s = sorted(l)
return (sum(s[n//2-1:n//2+1])/2.0, s[n//2])[n % 2] if n else Noneopenchat. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]deepseek-coder-7b-instruct-v1.5. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
length = len(l)
if length % 2 == 0:
return (l[length // 2] + l[length // 2 - 1]) / 2
else:
return l[length // 2]speechless-starcoder2-7b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
length = len(l)
if length % 2 == 0:
return (l[length//2 - 1] + l[length//2]) / 2
else:
return l[length//2]wizardcoder-7b. fail_base: False, fail_plus: False
Here's the Python script for the given problem:
```python
def median(l: list):
"""Return median of elements in the list l."""
n = len(l)
l.sort()
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]
```
Explanation:
The function takes a list `l` as input and first sorts it in ascending order. Then, it checks if the length of the list is even or odd. If it's even, it returns the average of the two middle elements. If it's odd, it returns the middle element. The `//` operator is used to perform integer division, which returns the floor value of the division. This ensures that we get the middle element of the list. octocoder. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n // 2] + l[n // 2 - 1]) / 2
else:
return l[n // 2]
gemma-1.1-7b-it. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
mid = len(l) // 2
if len(l) % 2 == 1:
return l[mid]
else:
return (l[mid] + l[mid - 1]) / 2gpt-3.5-turbo. fail_base: False, fail_plus: False
Here's the code to complete the problem:
```python
def median(l: list):
"""Return median of elements in the list l."""
sorted_list = sorted(l)
n = len(sorted_list)
if n % 2 == 0:
return (sorted_list[n//2 - 1] + sorted_list[n//2]) / 2
else:
return sorted_list[n//2]
```
This code sorts the input list `l` and then calculates the median based on the sorted list. If the length of the list is even, it returns the average of the two middle elements. If the length is odd, it returns the middle element.codebooga-34b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
n = len(l)
if n % 2 == 1:
return sorted(l)[n // 2]
else:
return sum(sorted(l)[n // 2 - 1:n // 2 + 1]) / 2
deepseek-coder-1.3b-instruct. fail_base: False, fail_plus: False
Here is the implementation of the function in markdown style:
```python
def median(l: list):
"""
Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
n = len(l)
s = sorted(l)
return (s[n//2] if n % 2 == 1 else (s[n//2 - 1] + s[n//2]) / 2)
```
This function first sorts the list in ascending order, then checks if the length of the list is odd or even. If it's odd, it returns the middle element. If it's even, it returns the average of the two middle elements.
speechless-mistral-7b. fail_base: False, fail_plus: False
def median(l: list):
l.sort()
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]
print(median([3, 1, 2, 4, 5])) # Output: 3
print(median([-10, 4, 6, 1000, 10, 20])) # Output: 15.0
```
xdan-l1-chat. fail_base: False, fail_plus: False
def median(l: list):
l = sorted(l)
n = len(l)
if n % 2 == 0:
return (l[n//2 - 1] + l[n//2]) / 2
else:
return l[n//2]solar-10.7b-instruct. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
def median(l: list) -> float:
# First, sort the list in ascending order
l = sorted(l)
# Find the length of the list
n = len(l)
# Check if the list has an even number of elements
if n % 2 == 0:
# Calculate the median as the average of the middle two elements
return (l[n // 2] + l[n // 2 - 1]) / 2
else:
# For odd number of elements, the median is the middle element
return l[n // 2]claude-3-sonnet-20240229. fail_base: False, fail_plus: False
Here's the code to find the median of a list in Python:
```python
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort() # Sort the list in ascending order
n = len(l)
if n % 2 == 0: # If the list has an even number of elements
mid1 = l[n//2 - 1]
mid2 = l[n//2]
return (mid1 + mid2) / 2 # Return the average of the two middle elements
else: # If the list has an odd number of elements
return l[n//2] # Return the middle elementcode-33b. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
n = len(l)
s = sorted(l)
return (sum(s[n//2-1:n//2+1])/2.0, s[n//2])[n % 2] if n else Nonestarcoder2-15b-oci. fail_base: False, fail_plus: False
def median(l: list):
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
l.sort()
n = len(l)
if n % 2 == 1:
return l[n // 2]
else:
return (l[n // 2 - 1] + l[n // 2]) / 2
def mode(l: list):
"""Return mode of elements in the list l.
>>> mode([1, 2, 3, 4, 5, 5, 5, 5, 5, 6, 7, 8, 9])
5
>>> mode([1, 2, 3, 4, 5, 6, 7, 8, 9])
None
"""
counts = {}
for x in l:
counts[x] = counts.get(x, 0) + 1
max_count = max(counts.values())
if max_count == 1:
return None
else:
return [x for x, count in counts.items() if count == max_count]
def variance(l: list):
"""Return variance of elements in the list l.
>>> variance([1, 2, 3, 4, 5])
2.0
>>> variance([1, 2, 3, 4, 5, 6, 7, 8, 9])
6.666666666666667
"""
n = len(l)
mean = sum(l) / n
return sum((x - mean) ** 2 for x in l) / n
def standard_deviation(l: list):
"""Return standard deviation of elements in the list l.
>>> standard_deviation([1, 2, 3, 4, 5])
1.4142135623730951
>>> standard_deviation([1, 2, 3, 4, 5, 6, 7, 8, 9])
2.581988897471611
"""
return variance(l) ** 0.5
def main():
l = [1, 2, 3, 4, 5]
print(f"speechless-starcoder2-15b. fail_base: False, fail_plus: False
def median(l: list):
n = len(l)
s = sorted(l)
return (s[n//2] if n % 2 == 1 else (s[n//2 - 1] + s[n//2]) / 2)python-code-13b. fail_base: False, fail_plus: False
def median(l: list) -> float:
"""Return median of elements in the list l.
>>> median([3, 1, 2, 4, 5])
3
>>> median([-10, 4, 6, 1000, 10, 20])
15.0
"""
sorted_list = sorted(l)
length = len(sorted_list)
mid = length // 2
if length % 2 == 0:
return (sorted_list[mid - 1] + sorted_list[mid]) / 2
else:
return sorted_list[mid]opencodeinterpreter-ds-6.7b. fail_base: False, fail_plus: False
Here is the Python code to solve the problem:
```python
def median(l: list):
l.sort()
n = len(l)
m = n - 1
if n % 2:
return l[n//2]
else:
return (l[m//2] + l[m//2 + 1]) / 2