This repository contains a Jupyter notebook file that covers the basics of working with the Numpy library for numerical computing in Python. It covers various topics such as array creation, array manipulation, linear algebra, statistics and more.
- Introduction to the Numpy library
- Array creation with numpy
- Array manipulation and indexing
- Linear algebra with Numpy
- Statistics with Numpy
- Random sampling with Numpy
To use the notebooks in this repository, you will need to have a working installation of Python and Jupyter Notebook. You can download the latest version of Python from the official website (https://www.python.org/) and install Jupyter Notebook by running pip install jupyter. You will also need to install Numpy library by running pip install numpy
Once you have the necessary software installed, you can clone or download this repository to your local machine. Then, open a terminal or command prompt and navigate to the directory where you downloaded the repository. Run the command jupyter notebook to launch the Jupyter Notebook application.
In the Jupyter Notebook interface, navigate to the Numerical Computing with Numpy repository and open the notebook files to begin working through the tutorials.
Here's an example of how you can use the numpy library to create an array:
import numpy as np
# Create an array with numpy
a = np.array([1, 2, 3, 4, 5])
# Print the array
print(a)