Mastering NumPy: A Step-by-Step Learning Guide

Step 1: Installing NumPy

pip install numpy

Step 2: Importing NumPy

import numpy as np

Step 3: NumPy Arrays

1D Array

arr_1d = np.array([1, 2, 3])

2D Array

arr_2d = np.array([[1, 2, 3], [4, 5, 6]])

3D Array

arr_3d = np.array([[[1, 2, 3], [4, 5, 6]], [[7, 8, 9], [10, 11, 12]]])

Step 4: Array Operations

Element-wise Addition

result = arr_1d + arr_1d

Element-wise Multiplication

result = arr_2d * arr_2d

Dot Product of Matrices

result = np.dot(arr_2d, arr_2d.T)

Step 5: Saving and Loading Data

Saving Data

np.save('my_array', arr_1d)

Loading Data

loaded_array = np.load('my_array.npy')

Creating and Using Virtual Environments in Visual Studio Code on macOS

Virtual environments are crucial for managing Python project dependencies. In this tutorial, we'll explore how to create and activate a virtual environment within Visual Studio Code on macOS.

Step 1: Open Visual Studio Code

Launch Visual Studio Code and open your Python project.

Step 2: Open a New Terminal

Go to the "View" menu and select "Terminal" or press Ctrl + ` to open a new terminal in Visual Studio Code.

Step 3: Create a Virtual Environment

python3 -m venv venv

This creates a virtual environment named venv. Make sure you have Python 3 installed; if not, use Homebrew to install it (brew install python).

Step 4: Activate the Virtual Environment

source venv/bin/activate

Your terminal prompt should change, indicating that you are now in the virtual environment.

Step 5: Install Dependencies (Optional)

While in the virtual environment, use pip to install project-specific dependencies:

pip install package_name

Step 6: Deactivate the Virtual Environment

Once done, deactivate the virtual environment:

deactivate

This returns you to the global Python environment.

Conclusion

Creating and using virtual environments in Visual Studio Code provides a clean space for managing project dependencies, crucial for smooth development.

Happy coding!