Lecture 2#
Topic#
In this lecture we cover more python basics, numpy and pandas.
Lecture Slides#
Exercises#
Suggested Homework#
Re-do or finish the exercise notebook a few days after class to practice the basics
Go through chapter 2 and 3 of the Python Data Science Handbook and type all the code examples into a jupyter notebook.
Watch the concise introduction to pandas (see below)
Additional materials#
Python Data Science Handbook#
The excellent Python Data Science Handbook by Jake VanderPlas has a free online version. The lecture slides on numpy and pandas are based on Chapter 2 and 3 of that book. However, the book is more complete.
Concise Intro to pandas#
This video is a very short introduction to pandas that covers topics that will be useful in this class:
Video Series on Pandas#
The following video series is completely optional and goes much deeper than what we need. The video titles in the playlist are very informative. I would not suggest to watch all of this from start to finiss but to watch a video if you are struggling with a specific topic in your finl project.
Numpy tutorial from the scipy conference#
This is a detailed tutorial on numpy. It goes beyond what we need in the class but is a good starting point if you want to learn more.
Blogpost on tracebacks#
I highly recommend to read this blogpost.