Lecture 5:- Numpy - Creating Numpy Array

NumPy is a fundamental Python library for numerical computing. It provides support for arrays and matrices, along with a wide range of mathematical functions to operate on these arrays. Creating NumPy arrays is a straightforward process. Here are some common methods to create NumPy arrays:

From Python Lists or Tuples:

Using NumPy Functions: NumPy provides several functions to create arrays with specific properties.

Random Number Arrays: NumPy provides functions to generate arrays with random numbers.

These are just a few examples of how to create NumPy arrays. NumPy offers various other functions and methods to manipulate and operate on arrays efficiently, making it a powerful tool for numerical computations in Python.

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import numpy as np # Creating a 1-dimensional array with random values between 0 and 1 random_array = np.random.rand(5)  # Creates an array of 5 random numbers # Creating a 2-dimensional array with random integers between 0 and 10 random_int_array = np.random.randint(0, 11, (3, 4))  # Creates a 3x4 array of random integers # Creating a 2-dimensional array with random values from a standard normal distribution random_normal_array = np.random.randn(2, 3)  # Creates a 2x3 array of random values

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import numpy as np # Creating a 1-dimensional array of zeros zeros_array = np.zeros(5)  # Creates [0., 0., 0., 0., 0.] # Creating a 2-dimensional array of ones ones_array = np.ones((3, 4))  # Creates a 3x4 array of ones # Creating a 1-dimensional array with a range of values range_array = np.arange(0, 10, 2)  # Creates [0, 2, 4, 6, 8] # Creating a 1-dimensional array with evenly spaced values linspace_array = np.linspace(0, 1, 5)  # Creates [0., 0.25, 0.5, 0.75, 1.] # Creating a 2-dimensional identity matrix identity_matrix = np.eye(3)  # Creates a 3x3 identity matrix

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import numpy as np # Creating a 1-dimensional array from a Python list array1d = np.array([1, 2, 3, 4, 5]) # Creating a 2-dimensional array from a Python list of lists array2d = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # Creating a 1-dimensional array from a Python tuple array_from_tuple = np.array((10, 20, 30, 40))

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