Now you’re in the Jupyter Notebook interface, and you can see all of the files in your current directory. All Jupyter Notebooks are identifiable by thenotebook iconnext to their name. If you already have a Jupyter Notebook in your current directory that you want to view, find it in your files list and click it to open.

directoryl

How to create a new notebook in Jupyter

To create a new notebook, go toNewand selectNotebook - Python 3. If you have other Jupyter Notebooks on your system that you want to use, you can clickUploadand navigate to that particular file.

Notebooks currently running will have a green icon, while non-running ones will be grey. To find all currently running notebooks, click on theRunningtab to see a list.

running

How to use cells, markdown, and code execution in Jupyter Notebooks

When you open a new Jupyter notebook, you’ll notice that it contains acell.

empty_cell

Cells are how notebooks are structured and are the areas where you write your code. To run a piece of code, click on the cell to select it, then pressShift+Enteror press the play button in the toolbar above. Additionally, theCelldropdown menu has several options to run cells, including running one cell at a time or running all cells at once.

cell

After you run a cell, the output of the cell’s code will appear in the space below. To stop running a piece of code, press the stop button.

cell_output

To create new cells, use the plus (+) button in the toolbar or hitShift+Enteron the last cell in the Notebook. To cut, copy, delete, or just generally edit cells - select the cell you want to modify and go to theEditbutton in the navigation bar to see your options.

edit

In addition to running lines of code, you can also includetext-onlycells that use Markdown to format and organize your notebooks.

better_markdown

When you create a new cell, it will default to being aCodecell. To create a cell that uses markdown, click on theCellmenu from the navigation bar, scroll down toCell Type, and choose Markdown.

add_markdown

Occasionally, you might need to restart the kernel. Head to theKerneldropdown and hitRestart. To shut down a kernel, you can clickShutdown, which will have a dialogue process asking if that’s what you would like to do. To force an immediate shutdown, go to theFiledropdown and clickClose and Halt, and the browser window will close itself. Restarting and shutting down kernels will affect your variables, so be careful.

kernel

In theHelpdropdown, you’ll find useful information such as keyboard shortcuts as well as links to different documentation for modules such as Numpy, SciPy, and Matplotlib.

help

Thetoolbarhas several shortcut buttons for popular actions. From left to right: save, add a new cell, cut selected cells, copy selected cells, paste cells below, move selected cells up, move selected cells down, run, interrupt the kernel, restart the kernel, a dropdown that allows you to change the cell type, and a shortcut to open the command palette.

toolbar

Jupyter Notebook files are saved as you go. They will exist in your directory as aJSONfile with the extension.ipynb. You can also export Jupyter Notebooks in other formats, such as HTML. To do so, go to the File menu, scroll down toDownload as, and select the type of file you’re looking for. A pop-up will appear asking where you would like this new file to download. Once you’ve navigated to the appropriate directory, clickSave and Checkpoint.

file

Conclusion

Jupyter Notebooks offer an intuitive and flexible environment for writing, testing, and organizing Python code. Whether you’re running code in cells, adding markdown notes, or managing kernels, Jupyter makes it easy to experiment and build projects efficiently—all in one interface.

To practice using Jupyter Notebooks with real data, explore Codecademy’sLearn Python for Data Sciencecourse. It’s a great way to apply your skills and work with data directly inside notebooks.

Frequently asked questions

1. What is Jupyter Notebook mainly used for?

Jupyter Notebook is mainly used for writing and running code interactively. It’s popular in data science and machine learning for combining code, visuals, and text in one workspace.

2. How to run a Python file in Jupyter Notebook?

To run a Python file (.py) in Jupyter Notebook, you can use the%runmagic command. First, make sure the.pyfile is in the same directory as your notebook. Then, in a code cell, type:

%run your_script.py 
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%run your_script.py

3. How do I import code into Jupyter?

You can import functions, classes, or variables from other Python files using the standardimportstatement. For example, if you have a file namedhelper.py, you can write:

import helper 
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import helper

Or use from helperimport function_nameto import specific elements. Make sure the file is in the same directory or in your Python path so Jupyter can access it.

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