如何在阵列中找到第二个最常见的数字?

时间:2015-07-22 18:45:39

标签: python scipy

我尝试使用scipy.stats模式查找最常用的值。我的矩阵包含很多零,所以这总是模式。

例如,如果我的矩阵如下所示:

array = np.array([[0, 0, 3, 2, 0, 0],
             [5, 2, 1, 2, 6, 7],
             [0, 0, 2, 4, 0, 0]])

我希望返回2的值。

3 个答案:

答案 0 :(得分:5)

尝试collections.Counter

import numpy as np
from collections import Counter

a = np.array(
  [[0, 0, 3, 2, 0, 0],
   [5, 2, 1, 2, 6, 7],
   [0, 0, 2, 4, 0, 0]]
)

ctr = Counter(a.ravel())
second_most_common_value, its_frequency = ctr.most_common(2)[1]

答案 1 :(得分:0)

正如一些评论中提到的,你可能会谈到numpy数组。

在这种情况下,屏蔽您想要避免的值非常简单:

import numpy as np
from scipy.stats import mode

array = np.array([[0, 0, 3, 2, 0, 0],
                 [5, 2, 1, 2, 6, 7],
                 [0, 0, 2, 4, 0, 0]])
flat_non_zero = array[np.nonzero(array)]
mode(flat_non_zero)

返回(array([2]), array([ 4.]))表示出现最多的值是2,它出现4次(有关详细信息,请参阅doc)。因此,如果您只想获得2,则只需要获取模式返回值的第一个索引:mode(flat_non_zero)[0][0]

编辑:如果你想从数组中过滤另一个特定值x而不是零,你可以使用array[array != x]

答案 2 :(得分:0)

original_list = [1, 2, 3, 1, 2, 5, 6, 7, 8]  #original list
noDuplicates = list(set(t))                  #creates a list of all the unique numbers of the original list

most_common = [noDuplicates[0], original_list.count(noDuplicates[0])]  #initializes most_most common to 
                                                                       #the first value and count so we have something to start with


for number in noDuplicates:         #loops through the unique numbers
    if number != 0:                 #makes sure that we do not check 0
        count = original_list.count(number)     #checks how many times that unique number appears in the original list
        if count > most_common[1]   #if the count is greater than the most_common count
            most_common = [number, count] #resets most_common to the current number and count


print(str(most_common[0]) + " is listed " + str(most_common[1]) + "times!")

这将遍历您的列表并查找最常用的数字,并使用原始列表中的出现次数进行打印。