How to Install and Use Jupyter Notebook

1 year ago
Emily Johnson
2 minutes

Jupyter is an open-source interactive computing environment that supports multiple programming languages such as Python, R, and Julia. Its main component is the Notebook, which allows users to combine code, documents, and visualizations in an interactive interface.

Here is a detailed explanation of how to install and use Jupyter.

  1. Install Jupyter
  2. To install Jupyter using pip, simply enter the following command in the command line: pip install jupyter.
  3. To install Jupyter using Anaconda, simply run the command: conda install jupyter if Anaconda is already installed.
  4. Start Jupyter.
  5. To start Jupyter, type the following command in the command line: jupyter notebook.
  6. Jupyter will open a new interface in the default browser, displaying a list of files in the current directory.
  7. Create and edit Notebook.
  8. Click on the “New” button in the Jupyter interface and choose the programming language for the notebook you want to create.
  9. In the newly created Notebook, you can input code, text, and visualization results.
  10. Pressing Shift + Enter can run the code in the current cell or render the Markdown text.
  11. Save and export the Notebook
  12. Click on “File” in the Jupyter interface and then select “Save and Checkpoint” to save the Notebook.
  13. You can save Notebook files in “.ipynb” format to reopen and edit them later.
  14. Notebooks can also be exported to other formats, such as HTML, PDF, or Python scripts.
  15. Other features and plugins
  16. Jupyter offers a variety of additional features and plugins, such as auto-completion, syntax highlighting, and code evaluation.
  17. You can customize the interface and functionality of Jupyter by editing its configuration file.
  18. Common plugins, such as jupyter_contrib_nbextensions, can also be installed to enhance the functionality of Jupyter.

By following the above steps, you have successfully installed and learned the basics of using Jupyter. Now you can start writing and running code, creating documents and visualizations, and sharing and collaborating with others in Jupyter.

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