Key Takeaways
- Understanding the difference between command and edit modes is essential for working with Jupyter Notebook. Each mode provides different functionalities and shortcuts.
- Accessing and using keyboard shortcuts can save you time by avoiding a series of steps for each operation. Make sure you’re in the right mode when executing shortcuts.
- Jupyter Notebook allows for customization through extensions or manual customization. Use extensions for easier customization or manually customize by creating a CSS file. Restart the notebook for changes to take effect.
Jupyter Notebook is a web-based interactive computing environment that you can use for data analysis and collaborative coding. It allows the integration of code, text, and visualizations into a single document. It has an extensive ecosystem of libraries available for accomplishing different tasks.
It dominates the data science world when it comes to data analysis, data preprocessing, and feature engineering. Here are some essential tips and tricks to help you make the most out of your notebook experience.
1. Difference Between Command Mode and Edit Mode
Understanding the difference between the command and edit modes is one of the fundamental aspects of working with a Jupyter Notebook. This is because each mode provides different functionalities and shortcuts.
The edit mode is indicated by a green border and is the default mode when you select a cell for editing.
In this mode, you can type and edit code within the cell. To enter edit mode, double-click on a cell or press enter when you select one.
The command mode is indicated by a blue cell border. It is also the default mode when you are not actively editing a cell.
In this mode, you can perform notebook-level operations such as creating, deleting, changing, or executing cells. To switch from edit mode to command mode press the ESc key.
2. Accessing and Using the Keyboard Shortcuts
Jupyter Notebooks has a Keyboard shortcuts dialog that helps you view all available shortcuts. To access it make sure you are in command mode. Then press the H key. A pop-up window such as the one below should appear.
Each shortcut has an explanation of what it does next to it. The commands are divided into those that you can use in command mode and edit mode. Make sure you are in the right mode when executing the respective shortcut. Using these shortcuts will help you save a lot of time as you won’t have to follow a series of steps to accomplish each operation.
3. Using Magic Commands
Magic commands provide additional functionalities that you can use for executing tasks. To use them, prefix the command with a % for line magics and two %% for cell-level magic. Instead of memorizing a few, you can access all the available magic commands by using the %lsmagic command.
On a new cell, run the %lsmagic command. This will display all the available magic commands both in the edit and command mode. To understand what each command does, run the command with a postfix question mark to get its documentation. For example, to understand what the %alias magic command does, run %alias?.
Make sure you understand the mode a command runs on before using it.
4. Customizing the Notebook
Jupyter Notebook allows for user customization if you do not like the default look. You can customize it in one of two ways. You can either customize it manually or use extensions. The easier alternative is to use extensions.
To use extensions, run the following command on a new cell. This command will install jupyter-themes, an extension that comes with predefined themes.
!pip install jupyterthemes
Then proceed to your terminal or CMD to apply configurations. Start by listing the available themes using the code below.
jt -l
Then use the following command to apply a theme. Replace the theme name with your desired one.
jt -t <theme_name>
After applying the theme, restart the Jupyter Notebook for the changes to take place. The output of applying the oceans16 theme is as follows:
If you would like to restore the notebook back to default, use the following command.
jt -r
The command reverts the Jupyter Notebook to its initial default theme.
To manually customize your notebook, follow the following steps.
Go to the directory where you installed Jupyter Notebook. Find the directory with the name .jupyter. Create a new folder inside it and name it custom. Then create a CSS file in the custom directory and name it custom.css. Finally, open the CSS file with an editor and add your CSS customization code.
After adding the code, restart your Jupyter Notebook for the changes to take effect.
5. Collaboration and Sharing
When you are coding you may want to collaborate with other developers. To achieve this in Jupyter Notebook, you can use version control such as Git. To use Git, initialize a Git repository on your project’s root directory. Then add and commit each change you make to the Jupyter Notebook to the Git repository.
Finally, share the repository with the people you want to collaborate with by pushing it to GitHub. This will allow the collaborators to clone the repository hence accessing your Jupyter Notebook files.
Widget and interactive features aid in helping you create dynamic user interfaces within your notebook.
They give you a way to interact and visualize with your data. Jupyter Notebooks support a few widgets by default. To use more widgets you need to install the ipywidgets library using the following command.
!pip install ipywidgets
After installing, import the widgets module to use its functionalities.
import ipywidgets as widgets
You now need to create the widget of your choice. For example, to create a slider widget use the following code:
slider = widgets.IntSlider(min=0, max=100, value=50, description='Slider:')
Then display the slider.
display(slider)
The output is as follows:
You can use the slider for user input and selection of a numeric value within a specified range. There are many widgets that the library supports. To list them use the following line of code:
dir(widgets)
Look for the widget that supports your requirements from the list.
To improve the efficiency and performance of your notebook, the following tips come in handy:
- Limit the output and use progress indicators: This will help you avoid cluttering your notebook with excessive output. Use progress indicators to track the progress of the computation. The tqdm library can be useful for this purpose.
- Minimize cell execution: Execute only the necessary cells to save on resources. You can achieve this by using Run All Above to run the selected cells.
- Optimize loops and data processing: Use vectorized operations and optimized libraries. Also, avoid unnecessary loops, especially nested loops. They can impact performance. Instead, utilize built-in functions and methods available in data manipulation libraries.
- Use cached results: If you have time-consuming computations or data loading, consider caching the results to avoid redundant calculations. Use tools like joblib or Pickle for caching.
In the data science world, there are many tools that can help you increase your throughput. It can be libraries that you can install in your development environment, IDEs tailored for data analysis, or even browser extensions. Strive to research more on the available tools out there as they can help you simplify your work and save you a lot of time.