NumPy: Access last two columns of a multidimensional columns
Access Last Two Columns of 2D Array
Write a NumPy program to access the last two columns of a multidimensional column.
Sample Solution:
Python Code:
# Importing the NumPy library and aliasing it as 'np'
import numpy as np
# Creating a NumPy array 'arra' with nested lists as elements
arra = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
# Printing the original array 'arra'
print(arra)
# Extracting specific columns (index 1 and index 2) using numpy array slicing
# ':' indicates all rows, '[1,2]' indicates columns at indices 1 and 2
result = arra[:, [1, 2]]
# Printing the extracted columns from the original array 'arra'
print(result)
Sample Output:
[[1 2 3] [4 5 6] [7 8 9]] [[2 3] [5 6] [8 9]]
Explanation:
In the above code –
arra = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]): This line creates a 3x3 NumPy array and stores in the variable ‘arra’ with values from 1 to 9.
result = arra[:, [1, 2]]: Select all rows (indicated by the colon :) and columns with indices 1 and 2 (the second and third columns) from the array arra. The notation [:, [1, 2]] means that we are selecting all rows and the columns with indices specified in the list [1, 2].
Finally print() function prints the resulting array.
Pictorial Presentation:
For more Practice: Solve these Related Problems:
- Write a NumPy program to slice a 2D array and extract its last two columns using negative indexing.
- Create a function that returns the last two columns of any given 2D array regardless of its shape.
- Test the slicing on arrays with varying numbers of columns to ensure robust extraction of the final two.
- Implement an alternative approach using np.take to retrieve the last two columns of an array.
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