Summary

Congratulations, we have now set up an environment that's ready to work with data. We started by installing Python and the Jupyter Notebook app by using the conda package installer called Anaconda. Next, we launched the Jupyter app and discussed how to navigate all of the features of both the dashboard and a notebook. We created a working directory that can be used as a template for all data analysis projects.

We ran our first Python code by creating a hello_world notebook and walk through the core features available in Jupyter. Finally, we verified and explored different Python packages (NumPy, pandas, sklearn, Matplotlib, and SciPy) and their purposes in data analysis. You should now be comfortable and ready to run additional Python code commands in Jupyter Notebook.

In the next chapter, we will expand your data literacy skills with some hands-on lessons. We will discuss the foundational library of NumPy, which is used for the analysis of data structures called arrays.