Welcome to the intro-level DS class, where we will learn about python basics and how to use python for exploratory data analysis. Hope you'll enjoy the class and learn something from it.
If you can, try to go throug the following reading and set up your local environment before class:
- Anaconda set up
- Git introduction
- Set up you forked repo for commit and push + Homework submisstion instructions
You can run python in different settings, for example, you can use jupyter notebook for interactive exploration, use interpreter in command line by typing python in terminal (you'll see >>> prompt appear), or run python script in command line by python <your_script>.py. We will be using notebooks for the class as it's easy to follow with markdown and easy to interact with.
0. Environment set up (material in section 0)
1. Assign values to variables and simple arithmetics
2. `Print` and simple string manimulation
3. Value comparison and conditions using `if-elif-else`
4. Collections: list, tuple, set, and dictionary
* Git - Commiting, Pushing, and Pull Request
Homework_01(Exercise0,3,4) is due next class. Please refer to homework submission instructions for how to open pull request for submission.
5. Iteration: loops and comprehensions
* HW01 review [delayed]
https://github.com/tdpetrou/Minimally-Sufficient-Pandas
https://github.com/cmawer/pycon-2017-eda-tutorial/blob/master/EDA-cheat-sheet.md