Leveraging Jupyter notebooks

Jupyter notebooks are arguably the most-used tool in Python scientific computing and data science projects. In this section, we will briefly discuss the basics of Jupyter notebooks as well as the reasons why they are a great tool for data analysis purposes. Then, we will consider the way PyCharm supports the usage of these notebooks.

We will be working with the jupyter_notebooks project in the chapter source. Don’t forget you’ll need to install the requirements within the requirements.txt file in a virtual environment in order to use the sample project. If you need a refresher on how to do this, refer back to Chapter 3.

Even though we will be writing code in Jupyter notebooks, it is beneficial to first consider a bare-bones program in a traditional Python script so that we can fully appreciate the advantages of using a notebook later on. Let’s look at the main.py file and see how we can work with it. We can see that this file...