The material presented here is a condensed introduction to Python and its data science related libraries such as NumPy, Pandas, and Matplotlib. The illustrative examples we use are associated with the financial markets.

We think it should also be useful to

• Anyone who wants a brief introduction to Python and the key components of its data science stack, and
• Python programmers who want a quick refresher on using Python for data analysis.

We do not expect any of our readers to have a formal background in computer science, although some familiarity with programming would be nice to have. The concepts and ideas here are covered with several examples to help connect theory to practice.