如何对 Numpy 数组进行排序| Python
原文:https://www . geeksforgeeks . org/how-sort-a-numpy-array-python/
在本文中，我们将学习如何对 Numpy 数组进行排序。根据需求，Numpy 中有多种方法对数组进行排序。让我们借助例子来试着理解它们。
示例#1: 使用 sort()方法基于轴对给定数组进行简单排序。
# importing libraries
import numpy as np
# sort along the first axis
a = np.array([[12, 15], [10, 1]])
arr1 = np.sort(a, axis = 0)
print ("Along first axis : \n", arr1)
# sort along the last axis
a = np.array([[10, 15], [12, 1]])
arr2 = np.sort(a, axis = -1)
print ("\nAlong first axis : \n", arr2)
a = np.array([[12, 15], [10, 1]])
arr1 = np.sort(a, axis = None)
print ("\nAlong none axis : \n", arr1)
输出:
Along first axis :
[[10 1]
[12 15]]
Along first axis :
[[10 15]
[ 1 12]]
Along none axis :
[ 1 10 12 15]
示例#2: 使用 argsort()方法获取可以返回排序数组的索引
# Python code to demonstrate
# working of numpy.argsort
import numpy as np
# Numpy array created
a = np.array([9, 3, 1, 7, 4, 3, 6])
# unsorted array print
print('Original array:\n', a)
# Sort array indices
b = np.argsort(a)
print('Sorted indices of original array->', b)
# To get sorted array using sorted indices
# c is temp array created of same len as of b
c = np.zeros(len(b), dtype = int)
for i in range(0, len(b)):
c[i]= a[b[i]]
print('Sorted array->', c)
输出:
Original array:
[9 3 1 7 4 3 6]
Sorted indices of original array-> [2 1 5 4 6 3 0]
Sorted array-> [1 3 3 4 6 7 9]
示例#3: 使用一系列键获得稳定的排序。
import numpy as np
# Numpy array created
# First column
a = np.array([9, 3, 1, 3, 4, 3, 6])
# Second column
b = np.array([4, 6, 9, 2, 1, 8, 7])
print('column a, column b')
for (i, j) in zip(a, b):
print(i, ' ', j)
# Sort by a then by b
ind = np.lexsort((b, a))
print('Sorted indices->', ind)
输出:
column a, column b
9 4
3 6
1 9
3 2
4 1
3 8
6 7
Sorted indices-> [2 3 1 5 4 6 0]
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