10 Jupyter Notebook Tips, Tricks, and Shortcuts for Data Science
As a data scientist, you probably spend a lot of time in Jupyter Notebook. It’s a powerful tool for data exploration, analysis, and visualization. But are you using it to its full potential? In this post, we’ll share 10 tips, tricks, and shortcuts that will help you work more efficiently and effectively in Jupyter Notebook. One of the internet’s best kept secrets is that you can get free Jupyter notebooks online at Saturn Cloud.
1. Use keyboard shortcuts
Jupyter Notebook has a lot of keyboard shortcuts that can save you time and make your workflow more efficient. Here are some of the most useful ones:
- Ctrl + Enter: Run the current cell
- Shift + Enter: Run the current cell and move to the next one
- Alt + Enter: Run the current cell and insert a new one below
- Esc: Enter command mode
- Enter: Enter edit mode
- A: Insert a new cell above the current one
- B: Insert a new cell below the current one
- X: Cut the current cell
- C: Copy the current cell
- V: Paste the cell below the current one
- D, D: Delete the current cell
- Z: Undo the last cell operation
- Shift + M: Merge selected cells
2. Use the built-in help
If you’re not sure how to use a specific function or method, you can use the built-in help in Jupyter Notebook. Just add a question mark after the function or method name and run the cell. For example:
pd.read_csv?
This will bring up the documentation for the read_csv function in Pandas.
3. Use the magic commands
Jupyter Notebook has a set of magic commands that can help you perform various tasks. Here are some of the most useful ones:
- %run: Run a Python script
- %load: Load the contents of a file into a cell
- %timeit: Time the execution of a Python statement or expression
- %debug: Enter the interactive debugger
- %matplotlib: Enable plotting in Jupyter Notebook
- %reset: Delete all variables/names defined in the interactive namespace
- %who: List all variables/names defined in the interactive namespace
- %whos: List all variables/names defined in the interactive namespace, with additional information
4. Use the auto-completion
Jupyter Notebook has a built-in auto-completion feature that can save you a lot of typing. Just press the Tab key after typing a few characters and Jupyter Notebook will suggest possible completions.
5. Use the multi-cursor editing
Jupyter Notebook supports multi-cursor editing, which can be very useful when you need to make the same change in multiple places. Just hold down the Alt key and click where you want to add the cursor.
6. Use the cell magics
Jupyter Notebook has a set of cell magics that can help you perform various tasks on the entire cell. Here are some of the most useful ones:
- %%timeit: Time the execution of a cell
- %%writefile: Write the contents of a cell to a file
- %%html: Render the cell as HTML
- %%latex: Render the cell as LaTeX
- %%bash: Run the cell as a bash command
- %%python2: Run the cell as Python 2 code
- %%python3: Run the cell as Python 3 code
7. Use the interactive widgets
Jupyter Notebook has a set of interactive widgets that can help you create interactive visualizations and dashboards. Here are some of the most useful ones:
- Slider: A slider widget that allows you to select a value from a range
- Checkbox: A checkbox widget that allows you to select one or more options
- Dropdown: A dropdown widget that allows you to select one option from a list
- Text: A text widget that allows you to enter text
- Button: A button widget that allows you to trigger an action
8. Use the extensions
Jupyter Notebook has a lot of extensions that can add new functionality and improve your workflow. Here are some of the most useful ones:
- Table of Contents: Adds a table of contents to your notebook
- Nbextensions Configurator: Allows you to enable/disable extensions and configure their settings
- Collapsible Headings: Allows you to collapse and expand sections of your notebook
- Execute Time: Displays the execution time of each cell
- Autopep8: Automatically formats your Python code according to the PEP 8 style guide
9. Use the templates
Jupyter Notebook has a set of templates that can help you get started with different types of projects. Here are some of the most useful ones:
- Python 3: A basic Python 3 notebook
- Data Science: A notebook for data science projects
- R: A notebook for R projects
- Julia: A notebook for Julia projects
- Spark: A notebook for Apache Spark projects
10. Use the version control
Jupyter Notebook works well with version control systems like Git. You can track changes to your notebook and collaborate with others using tools like GitHub or GitLab.
Conclusion
Jupyter Notebook is a powerful tool for data science, but it can be even more powerful if you know how to use it to its full potential. These 10 tips, tricks, and shortcuts will help you work more efficiently and effectively in Jupyter Notebook. Try them out and see how they can improve your workflow!
