Here's an overview of Python with Jupyter

Jupyter Notebook

Jupyter Notebooks provide an interactive computing environment where you can write and execute code in cells.


You can install Jupyter along with Python using package managers like pip or conda.

Launching Jupyter

After installation, you can launch the Jupyter Notebook server by running the following command in your terminal or command prompt

Creating a Jupyter Notebook

Once the Jupyter server is running, you can create a new notebook and choose the Python kernel.

Data Science and Visualization

Jupyter is widely used in the data science community for tasks like data exploration, data cleaning, statistical analysis, and machine learning.

Sharing Notebook

Jupyter Notebooks can be saved and shared in various formats, including HTML, PDF, and slides.

Jupyter Extension

Jupyter supports extensions that enhance its functionality. These extensions provide additional features such as code folding, table of contents, and more.


JupyterLab is an enhanced version of Jupyter Notebook that provides a more flexible and feature-rich interface.

Python with Jupyter has become a standard tool in various fields, particularly in data science, research, and education.