ViewTube

TOPIC: Creating 2D & 3D Arrays using NumPy arange. PROCESS: Combine np.arange() to generate data and .reshape() to set ...

import numpy as np # Base 2D Array (4x3) arr_2d = np.array([ [1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12] ]) print(f"Base 2D ...

Creating 1D & 2D Identity Arrays using NumPy. The np.identity(n, dtype=None) function is used to create identity square arrays. n ...

The NumPy eye function for creating 2D arrays and beyond. The syntax is np.eye(N, M=None, k=0, dtype = "float".) where the 'k' ...

import numpy as np # Base 3D Array (2x2x3) arr_3d = np.array([ [[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]] ]) print(f"Base 3D ...

import numpy as np # Base Array (12 elements) arr = np.arange(1, 13) print(f"Base Array: {arr}\n") # Example 1: Reshape 1D to 2D ...

import numpy as np # --- 2D Identity Matrices --- print("1. 3x3 Identity (Float):") print(np.identity(3)) print("\n2. 4x4 Identity (Integer):") ...

import numpy as np # --- 2D Arrays with arange() and reshape() --- print("1. 2D Array (3x4):") print(np.arange(12).reshape(3, ...

Learn how to use NumPy boolean indexing to select entire subarrays based on conditions applied to their elements, preserving ...