Enhance Jupyter Notebook’s productivity with these Tips & Tricks. | Shalu Anand

Enhance Jupyter Notebook’s productivity with these Tips & Tricks.

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One of the significant ways by which data scientists and engineers at Netflix interact with their data is through Jupyter notebooks. Notebooks leverage the use of collaborative, extensible, scalable, and reproducible data science. For many of us, Jupyter Notebooks is the de facto platform when it comes to quick prototyping and exploratory analysis.

However, there’s more to this than meets the eye. A lot of Jupyter functionalities sometimes lie under the hood and are not adequately explored.

Let's try and explore Jupyter Notebooks’ features which can enhance our productivity while working with them.

➡️Executing Shell Commands

The notebook is the new shell

The shell is a way to interact textually with the computer. The most popular Unix shell is Bash(Bourne Again SHell ). Bash is the default shell on most modern implementations of Unix and in most packages that provide Unix-like tools for Windows.

Now, when we work with any Python interpreter, we need to regularly switch between the shell and the IDLE, in case we need to use the command line tools. However, the Jupyter Notebook gives us the ease to execute shell commands from within the notebook by placing an extra !

before the commands. Any command that works at the command line can be used in IPython by prefixing it with the ! character.

➡️Jupyter Themes

Theme-ify your Jupyter Notebooks!

If you are a person who gets bored while staring at the white background of the Jupyter notebook, themes are just for you. The themes also enhance the presentation of the code.

➡️Notebook Extensions

Extend the possibilities

Notebook extensions let you move beyond the general vanilla way of using the Jupyter Notebooks. Notebook extensions are JavaScript modules that you can load on most of the views in your Notebook’s frontend. These extensions modify the user experience and interface.

➡️Jupyter Widgets

Make notebooks interactive

Widgets are eventful python objects that have a representation in the browser, often as a control like a slider, textbox, etc. Widgets can be used to build interactive GUIs for notebooks.

➡️Qgrid

Make Data frames intuitive

Qgrid is also a Jupyter notebook widget but mainly focused on data frames. It uses SlickGrid to render pandas DataFrames within a Jupyter notebook. This allows you to explore your DataFrames with intuitive scrolling, sorting, and filtering controls, as well as edit your DataFrames by double-clicking cells.

➡️Slideshow

Code is great when communicated.

Notebooks are an effective tool for teaching and writing explainable codes. However, when we want to present our work either we display our entire notebook(with all the codes)

or we take the help of PowerPoint. Not anymore. Jupyter Notebooks can be easily converted to slides and we can easily choose what to show and what to hide from the notebooks.

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