import numpy as np # 创建一个numpy数组 arr = np.array([3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]) # 使用numpy的sort函数对数组进行排序,并通过切片操作实现逆序排序 sorted_arr_desc = np.sort(arr)[::-1] # 输出排序后的数组 print("Sorted array in descending order using slicing:", so...
import numpy as np x = np.array([3, 1, 2]) ascending = np.argsort(x) descending = ascending[::-1] 有关np.argsort的排序方向的更多信息,您可以看看这篇文章是否可以按降序使用argsort? 编辑:我在这里找到了一个对numpy排序顺序的引用:https://numpy.org/doc/stable/reference/generated/numpy.sort...
A custom key function can be supplied to customize the sort order, and the reverse flag can be set to request the result in descending order. In [2]: help(list.sort) Help on method_descriptor: sort(...) L.sort(key=None, reverse=False) -> None -- stable sort *IN PLACE* # 一维...
"Sorting the input array by the" ,n , "column:" ) # Here in [:,n], ':' specifies all the rows and n specifies we need to sort by nth column # [::-1] slices the result in reverse order(descending order) print (inputArray ...
import numpy as np # 创建一个 NumPy 数组 arr = np.array([3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]) # 使用 numpy.sort 和切片操作进行降序排列 sorted_arr_descending = np.sort(arr)[::-1] print("使用 numpy.sort 和切片操作进行降序排列:") print(sorted_arr_descending) # 使用 numpy...
Ordered sequence is any sequence that has an order corresponding to elements, like numeric or alphabetical, ascending or descending.The NumPy ndarray object has a function called sort(), that will sort a specified array.ExampleGet your own Python Server Sort the array: import numpy as np arr ...
'quicksort':快速排序,升序排列。 'mergesort':归并排序,升序排列。 'heapsort':堆排序,升序排列。 示例代码如下: 代码语言:txt 复制 import numpy as np arr = np.array([3, 1, 2]) sorted_indices = np.argsort(arr, kind='mergesort') print(sorted_indices) # 输出:[1 2 0] 在上面的示例中,...
[ 2, 20, 300]]) >>> a[a[:,2].argsort()][::-1] #sort by the 3rd column descending array([[ 2, 20, 300], [ 1, 30, 200], [ 3, 10, 100]]) >>> a[a[:,1].argsort()] #sort by the 2nd column ascending array([[ 3, 10, 100], [ 2, 20, 300], [ 1, 30, ...
使用负索引切片排序 importnumpyasnparr=np.array([5,2,8,3,6,10])# get the indices that would sort the array in ascending orderascending_indices=arr.argsort()# [1 3 0 4 2 5]# reverse the ascending indices to get descending indicesdescending_indices=ascending_indices[::-1]# [5 2 4 0...
a=np.array(L1) a.astype("bool")#转换类型 #创建常用的数组 #np.zeros(shape,dtype)/np.zeros_like(a) np.zeros(3) np.zeros((4,5)) #创建一个全0数组 a1 = np.array([[1, 2, 3], [5, 7, 8], [4, 5, 6]]) np.zeros_like(a1) ##生成和a1数组形状相同的数组 ...