NumPy: Sort an along the first, last axis of an array
Sort Array Along Axes
Write a NumPy program to sort along the first and last axes of an array.
Sample array: [[2,5],[4,4]]
Sample Solution:
Python Code:
# Importing the NumPy library with an alias 'np'
import numpy as np
# Creating a NumPy array 'a'
a = np.array([[4, 6], [2, 1]])
# Displaying the original array 'a'
print("Original array: ")
print(a)
# Sorting along the first axis (axis 0)
print("Sort along the first axis: ")
x = np.sort(a, axis=0)
print(x)
# Sorting along the last axis (axis 1) of the previously sorted array 'x'
print("Sort along the last axis: ")
y = np.sort(x, axis=1)
print(y)
Sample Output:
Expected Output: Original array: [[4 6] [2 1]] Sort along the first axis: [[2 1] [4 6]] Sort along the last axis: [[1 2] [4 6]]
Explanation:
In the above code -
a = np.array([[4, 6],[2, 1]]): A 2D NumPy array a is created with the shape (2, 2) and the elements are [[4, 6], [2, 1]].
x = np.sort(a, axis=0): The np.sort function sorts the input array a along the specified axis, which is 0 (columns) in this case. The result is stored in the variable ‘x’, which is an array with the same shape as a, but with the elements sorted along each column. The resulting array ‘x’ is [[2, 1], [4, 6]].
y = np.sort(x, axis=1): The np.sort function is called again, this time with the input array ‘x ‘ and the specified axis set to 1 (rows). The function sorts the elements along each row, and the result is stored in the variable ‘y’. The resulting array y is [[1, 2], [4, 6]].
For more Practice: Solve these Related Problems:
- Sort a 2D array along its first axis and then along its last axis using np.sort.
- Create a function that accepts an axis parameter and returns the array sorted along that axis.
- Compare the sorted result of np.sort with the indices returned by np.argsort to validate order.
- Test sorting on a multi-dimensional array and verify that the original array remains unaltered.
Python-Numpy Code Editor:
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