在Python中如何找到列表的中值?列表可以是任意大小的,并且数字不保证是任何特定的顺序。

如果列表包含偶数个元素,则函数应返回中间两个元素的平均值。

以下是一些例子(为了便于展示,进行了排序):

median([1]) == 1
median([1, 1]) == 1
median([1, 1, 2, 4]) == 1.5
median([0, 2, 5, 6, 8, 9, 9]) == 6
median([0, 0, 0, 0, 4, 4, 6, 8]) == 2

当前回答

import numpy as np
def get_median(xs):
        mid = len(xs) // 2  # Take the mid of the list
        if len(xs) % 2 == 1: # check if the len of list is odd
            return sorted(xs)[mid] #if true then mid will be median after sorting
        else:
            #return 0.5 * sum(sorted(xs)[mid - 1:mid + 1])
            return 0.5 * np.sum(sorted(xs)[mid - 1:mid + 1]) #if false take the avg of mid
print(get_median([7, 7, 3, 1, 4, 5]))
print(get_median([1,2,3, 4,5]))

其他回答

sorted()函数对此非常有用。使用排序函数 要对列表排序,只需返回中间值(或两个中间值的平均值) 如果列表包含偶数个元素,则为。

def median(lst):
    sortedLst = sorted(lst)
    lstLen = len(lst)
    index = (lstLen - 1) // 2
   
    if (lstLen % 2):
        return sortedLst[index]
    else:
        return (sortedLst[index] + sortedLst[index + 1])/2.0

如果您需要关于列表分布的额外信息,百分位数方法可能会很有用。中位数对应于列表的第50个百分位数:

import numpy as np
a = np.array([1,2,3,4,5,6,7,8,9])
median_value = np.percentile(a, 50) # return 50th percentile
print median_value 

中值函数

def median(midlist):
    midlist.sort()
    lens = len(midlist)
    if lens % 2 != 0: 
        midl = (lens / 2)
        res = midlist[midl]
    else:
        odd = (lens / 2) -1
        ev = (lens / 2) 
        res = float(midlist[odd] + midlist[ev]) / float(2)
    return res

试试这个

import math
def find_median(arr):
    if len(arr)%2==1:
        med=math.ceil(len(arr)/2)-1
        return arr[med]
    else:
        return -1
print(find_median([1,2,3,4,5,6,7,8]))

实现它:

def median(numbers):
    """
    Calculate median of a list numbers.
    :param numbers: the numbers to be calculated.
    :return: median value of numbers.

    >>> median([1, 3, 3, 6, 7, 8, 9])
    6
    >>> median([1, 2, 3, 4, 5, 6, 8, 9])
    4.5
    >>> import statistics
    >>> import random
    >>> numbers = random.sample(range(-50, 50), k=100)
    >>> statistics.median(numbers) == median(numbers)
    True
    """
    numbers = sorted(numbers)
    mid_index = len(numbers) // 2
    return (
        (numbers[mid_index] + numbers[mid_index - 1]) / 2 if mid_index % 2 == 0
        else numbers[mid_index]
    )


if __name__ == "__main__":
    from doctest import testmod

    testmod()

来源