NumPy: Rearrange columns of a given numpy 2D array using given index positions
Rearrange columns of a 2D array using indices.
Write a NumPy program to rearrange columns of a given numpy 2D array using given index positions.
Sample Solution:
Python Code:
# Importing the NumPy library and aliasing it as 'np'
import numpy as np
# Creating a NumPy array
array1 = np.array([[11, 22, 33, 44, 55],
[66, 77, 88, 99, 100]])
# Displaying the original array
print("Original arrays:")
print(array1)
# Creating a list of indices for reordering columns
i = [1, 3, 0, 4, 2]
# Rearranging the columns of the original array based on the given indices
result = array1[:, i]
# Displaying the new array formed by rearranging columns
print("New array:")
print(result)
Sample Output:
Original arrays: [[ 11 22 33 44 55] [ 66 77 88 99 100]] New array: [[ 22 44 11 55 33] [ 77 99 66 100 88]]
Explanation:
In the above exercise -
- array1 = np.array([[11, 22, 33, 44, 55], [66, 77, 88, 99, 100]]): Create a 2D NumPy array with given values.
- i: Define a list of column indices representing the desired order of columns.
- array1[:,i]: Rearrange the columns of array1 according to the specified order in i. Here, the colon : means to select all rows and ‘i’ is the list of column indices in the desired order.
- result: Store the resulting NumPy array.
Pictorial Presentation:
For more Practice: Solve these Related Problems:
- Write a NumPy program to rearrange the columns of a 2D array according to a given permutation of indices using advanced indexing.
- Create a function that accepts a 2D array and a list of column indices, then returns the array with rearranged columns.
- Implement a solution that uses np.take along axis 1 to reorder the columns based on a provided index array.
- Test the column rearrangement on matrices with duplicate and unsorted indices to verify correct ordering.
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