This repository contains files which I have created for learning the basics of NumPy. It includes a Jupyter notebook that offers step-by-step guidance, along with a data.txt file, which will be useful for executing certain Python commands.
Ensure that both the data.txt file and the Jupyter notebook are located in the same directory.
If they are stored in different locations, please update the code to provide the correct path to the data.txt file for proper execution.
NumPy (Numerical Python) is a powerful library used for numerical computing in Python. It provides support for large, multi-dimensional arrays and matrices, along with a variety of mathematical functions to operate on these arrays.
NumPy is a fundamental package for scientific computing in Python, often used in fields such as data science, machine learning, and artificial intelligence due to its high performance and extensive functionalities.
This repository will help you get started with the basics of NumPy, including:
Array Creation: Learn how to create NumPy arrays, both from Python lists and using built-in functions.
Array Indexing and Slicing: Understand how to access and modify elements of NumPy arrays.
Mathematical Operations: Perform various mathematical operations on NumPy arrays, such as addition, subtraction, and matrix multiplication.
Array Reshaping: Learn how to reshape NumPy arrays for efficient data handling.
Statistical Functions: Use NumPy to calculate statistical metrics like mean, median, and standard deviation.
You can install Jupyter Notebook by following the instructions provided on the official website: https://jupyter.org/install.
Alternatively, you can use Visual Studio Code with the Jupyter extension for running Jupyter notebooks.