As part of the Python for Data Science video series I wanted to provide some basic Python programming resources for those who may be new to Python. The list of links below is designed to get new Python programmers off to a quick start and it focuses on things that are most relevant to data analysis. (E.g., there’s nothing in here about writing custom classes.)
If you have suggestions for other links, feel free to mention them in the comments below.
General overviews:
- Python for Beginners – https://www.python.org/about/gettingstarted/
- Beginner’s Guide – https://wiki.python.org/moin/BeginnersGuide/Programmers
- Learn Python in 10 Minutes – https://www.stavros.io/tutorials/python/
Installing packages:
- You’ll usually use pip and PyPi, so start here: https://packaging.python.org/tutorials/installing-packages/#installing-from-pypi
- When you need something more, i.e., installing from source or installing from Github read the rest: https://packaging.python.org/tutorials/installing-packages/
Importing packages:
Data types:
- E.g., booleans, numerics, strings, lists, sets, and dictionaries – https://en.wikibooks.org/wiki/Python_Programming/Data_Types
Control flow:
- E.g., for loops, if/elif/else, continue, break, next – https://docs.python.org/3/tutorial/controlflow.html
Defining functions:
- E.g., fizz_buzz() – http://anh.cs.luc.edu/python/hands-on/3.1/handsonHtml/functions.html