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NumPy tricks for beginners : 👉 Reshaping arrays: NumPy provides the np.reshape() function, which allows you to change the shape of an array while preserving its data. This can be useful for converting between different data formats, such as converting a one-dimensional array into a two-dimensional matrix. For example, the following code reshapes a one-dimensional array into a two-dimensional matrix with two rows and three columns: import numpy as np # Create a one-dimensional NumPy array x = np.array([1, 2, 3, 4, 5, 6]) # Reshape the array into a two-dimensional matrix with 2 rows and 3 co

Basic NumPy for beginners: Creating a NumPy array: To create a NumPy array from a list or tuple, you can use the np.array() function. For example, the following code creates a NumPy array from a list of numbers: import numpy as np # Create a NumPy array from a list of numbers numbers = [1, 2, 3, 4, 5] numbers_array = np.array(numbers) # Print the array print(numbers_array) output: [1 2 3 4 5] Basic mathematical operations: NumPy provides functions for performing mathematical operations on arrays, such as addition, subtraction, multiplication, and division. These operations can be perform