arr = np.array([3, 1, 4, 1, 5, 9, 2, 6, 5, 3, 5]) 使用numpy的排序函数对数组进行降序排列: NumPy提供了多种方法对数组进行排序。对于降序排列,可以使用np.sort函数结合[::-1]切片操作,或者使用np.argsort结合负索引。 使用np.sort和切片操作: python sorted_arr_descending = np.sort(arr)...
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...
1. numpy.sort() # numpy.sort() In [3]: help(np.sort) Help on function sortinmodule numpy.core.fromnumeric: sort(a, axis=-1, kind='quicksort', order=None) Return a sorted copy of an array. Parameters---a : array_like Array to be sorted. axis : intorNone, optional Axis along...
"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 ...
[ 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, ...
;参数sort_index可选,用来指示排序依据的行或列的数字;参数sort_order可选,指示想要排序顺序的数,1代表升序(默认),-1代表降序;参数by_col可选,指示想要排序方向的逻辑值,FALSE...;参数by_array1必需,要排序的数组或单元格区域;参数sort_order1可选,用于排序的顺序,1代表升序,-1代表降序,默认升序;参数by_arra...
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 ...