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It’s important to remember that Jupyter Notebook, unlike many other text editors and integrated development environments (IDEs), defaults to a white background. This can prove irksome for individuals engaged in extended coding sessions. Nevertheless, the solution lies in modifying your notebook’s theme, and there’s an extensive array of options at your disposal.
Jupyter Notebook, although not categorized as an integrated development environment, has garnered substantial favor among data scientists. This is particularly true for those engaged in data analysis, visualization, and data communication. According to the Python Developer Survey of 2019, Jupyter Notebook ranked only slightly behind PyCharm and VS Code in the category of most popular text editors/IDEs. Over time, it has become the preferred choice for data scientists due to its user-friendliness and adaptability across various environments, whether they be constructed via Conda, Docker, or Virtualenv.
Nevertheless, it is worth noting that Jupyter Notebook’s popularity has waned somewhat as data scientists increasingly embrace IDEs capable of handling end-to-end machine learning workflows. However, it still retains its appeal for researchers more inclined toward innovation than crafting production-ready code.
Further Exploration: Top 5 Online Resources for Mastering Jupyter Notebook
Exploring Jupyter Themes These themes extend beyond altering the background color; they encompass the stylistic attributes of the text as well. Moreover, you can customize the appearance of text in Markdown, adjust font size within Pandas data frames, fine-tune cell dimensions, modify cursor colors, toggle the visibility of the toolbar, and more. Furthermore, you can enhance the aesthetics of your visualizations generated with Matplotlib by configuring plotting styles through jtplot.style(). You also have the capability to manipulate figure properties, including grids, spines, and more.
Installing Jupyter Themes Before you can apply any of the available themes, it is imperative to install them from your preferred package manager, either pip or Conda.
Using pip:
pip install jupyterthemes
With Conda:
conda install -c conda-forge jupyterthemes
Upon executing the conda command in the Anaconda Prompt, you will be presented with a list of packages slated for installation. Note that your list may slightly differ if you already possess some of the requisite packages.
Once the installation of packages is successfully completed, you can proceed to change the theme either directly from the Anaconda Prompt or by launching Jupyter Notebook and applying the desired theme.
Currently, there exists a selection of nine themes, which can be accessed with the following command:
jt -l
You will be presented with a roster of themes, including chesterish, grade3, gruvboxd, gruvboxl, manokai, oceans16, onedork, solarizedd, and solarizedl.
For added convenience, you can employ the aforementioned command with an exclamation mark at the outset within the notebook to query the list, like so: !jt -l.
Subsequently, you may choose from the list and implement your chosen theme by executing the following command within the Anaconda Prompt:
jt -t <name of the theme>
For instance: jt -t chesterish
Now, commence Jupyter Notebook from the Anaconda Prompt with the subsequent command:
jupyter notebook
Below is an illustration of Jupyter Notebook adorned with the chesterish theme.
By default, the theme conceals both the toolbar and the notebook’s appellation. However, you can toggle their visibility using this command: jt -t grade3 -T -N to display both the toolbar and the notebook’s name.
Furthermore, you have the option to invert the theme within the notebook itself:
!jt -r
It’s important to note that refreshing your notebook is essential to witness these alterations taking effect.
You also have the liberty to experiment with various customizations, such as:
- Altering the font:
!jt -t solarizedd -f fira -fs 115 - Adjusting cell width:
!jt -t chesterish -cellw 90% -linech 170 - Modifying cursor width and color:
!jt -t oceans16 -cursc r -cursw 5
Elevating Your Visualizations with Themes The jupyterthemes library offers you the means to create visually compelling presentations through its jtplot submodule. Import this module and utilize its style() method to enhance the properties of your figures.
# Import the module from jupyterthemes import jtplot
Here are some examples of how the style() method can be employed to enhance the aesthetics of your visualizations.
Outlook Jupyter themes constitute a potent tool for refining the aesthetics of your notebook, allowing you to harness the full potential of the available themes. Notably, one of their standout features is the ability to modify the appearance of plots generated through Matplotlib. With the jupyterthemes library, you can elevate the quality of your visualizations to new heights.
For more information and resources, visit the jupyterthemes’ GitHub repository.