Reading material

  • Milestone: Learning Python and the Colab environment

    • David Beazley’s Practical Python Programming course is a great starting point if you are familiar with another programming language. Review sections 0, 1, 2, and 3.

    • Bill Lubanovic’s book is a great resource as you aquaint yourself with Python. Use your luc.edu address to login and access any content at O’Reilly at no cost, including Lubanovic’s book.

    • Google offers a basic tutorial on its Colab environment. Colab is a hosting environment for interactive Python notebooks. (If you don’t like Google, you can use any other Python environment you wish, including Anacoda Navigator, Spyder, or even your Linux shell. You’ll find, however, that Colab is very good when you try to access data from your Google Drive.)

    • Markdown (.md) is a markup language for basic document formatting. There are several tutorials about MarkDown. Matt Cone’s site is one of the best. (Note: you don’t need to download any special editors to write MarkDown. You can type it directly into the text cell of a Colab notebook).

    • In a Colab notebook, MarkDown can also render LaTeX expressions. LaTeX is another markup language, designed especially for mathematical typesetting. For a LaTeX tutorial look no further than Overleaf. (Note: you don’t need to create an Overleaf account to practice LaTeX code. You can type it directly into the next cell of a Colab notebook).

  • Milestone: pandas, matplotlib, and visualization techniques

    • Pandas for Everyone: Python Data Analysis is a good introductory book. The book is available at no cost, via the O’Reilly library. You will need to sign in with your LUC email address and go through the single sign-on (SSO) process. Part I of the book corresponds to this milestone in the course.

    • Also from O’Reilly, you may want to watch all, or at least some, of the tutorial videos in Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python. At the very least watch chapters 4 and 3. If you have time, watch chapter 2 as well.

    • The pandas project offers a good introduction to the environment as well.

    • The matplotlib project offers a good introduction to plots and visualization. At the very least, review the pyplot tutorial, and the lifecycle of a plot.