jupyter python version
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Jupyter Notebooks are interactive computing environments that allow you to create and share documents containing live code, equations, visualizations, and narrative text. In this tutorial, we'll explore the basics of using Jupyter Notebooks with Python, covering installation, navigation, and code execution.
Before using Jupyter Notebooks, you need to have Python installed on your machine. You can install Python from python.org. Once Python is installed, you can install Jupyter using the following command:
After installation, you can launch Jupyter Notebooks by running the following command in your terminal or command prompt:
This will open a new tab in your web browser with the Jupyter Notebook dashboard.
The Jupyter Notebook interface consists of the menu bar, toolbar, code cells, and markdown cells. The main components are the cells, which can contain either code or markdown content.
Code cells are where you write and execute your Python code. To create a new code cell, click the "+" button on the toolbar and select "Code" from the dropdown menu. You can then type or paste your Python code into the cell.
To execute a code cell, you can click the "Run" button in the toolbar or use the keyboard shortcut Shift + Enter.
Markdown cells allow you to include formatted text, images, and links in your notebook. To create a new markdown cell, click the "+" button on the toolbar and select "Markdown" from the dropdown menu. You can then type your text using Markdown syntax.
To execute code in a cell, select the cell and click the "Run" button in the toolbar or use Shift + Enter. The output will be displayed below the code cell.
Jupyter Notebooks support magic commands, which are special commands that provide additional functionality. They start with % for single-line commands and %% for multi-line commands.
To save your notebook, click the "Save" button in the toolbar or use Ctrl + S. You can export your notebook to various formats, such as HTML, PDF, or slides, by selecting "File" - "Download as" in the menu.
This tutorial covered the basics of using Jupyter Notebooks with Python, from installation to code execution and exporting. Jupyter Notebooks are a powerful tool for data analysis, machine learning, and interactive coding. Experiment with the features mentioned here and explore additional functionalities to enhance your coding experience.
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