jupyter notebook vs python

Jupyter Notebook and Python are both essential tools in the field of data science and programming. While Python is a powerful programming language, Jupyter Notebook provides an interactive and user-friendly environment for data analysis, visualization, and documentation. In this tutorial, we'll explore the differences between Jupyter Notebook and Python and provide code examples to illustrate their functionalities.
Python is a versatile, high-level programming language known for its readability and simplicity. It is widely used for various applications, including web development, automation, machine learning, and scientific computing. Here's a simple Python script:
Jupyter Notebook is an open-source web application that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It supports various programming languages, but we'll focus on its usage with Python.
To install Jupyter Notebook, you can use the following command in your terminal or command prompt:
Once installed, launch Jupyter Notebook by running:
This will open a new tab in your web browser displaying the Jupyter Notebook dashboard.
Jupyter Notebook supports Markdown cells, allowing you to add formatted text, headers, and images. Use them to create documentation and explanations within your code.
Code cells allow you to write and execute Python code interactively. Here's an example:
You can run the code cell by selecting it and pressing Shift + Enter. The output will be displayed below the cell.
Both Python scripts and Jupyter Notebooks have their own strengths and use cases. Python scripts are great for traditional software development, while Jupyter Notebooks provide an interactive environment for data science and analysis. Choose the tool that best suits your specific needs and workflow.