View as a Python script or a Jupyter notebook
This is the reference guide to Python that I wish had existed when I was learning the language.
Here's what I want in a reference guide:
- High-quality examples that show the simplest possible usage of a given feature
- Explanatory comments, and descriptive variable names that eliminate the need for some comments
- Presented as a single script (or notebook), so that I can keep it open and search it when needed
- Code that can be run from top to bottom, with the relevant objects defined nearby
This is not written as a full-fledged Python tutorial, though I ordered the topics such that you can read it like a tutorial (i.e., each topic depends only on material preceding it).
The guide was written using Python 2 but is fully compatible with Python 3. Relevant differences between Python 2 and 3 are noted throughout the guide.
Click to jump to the relevant section of the script or the notebook:
- Imports (script, notebook)
- Data Types (script, notebook)
- Math (script, notebook)
- Comparisons and Boolean Operations (script, notebook)
- Conditional Statements (script, notebook)
- Lists (script, notebook)
- Tuples (script, notebook)
- Strings (script, notebook)
- Dictionaries (script, notebook)
- Sets (script, notebook)
- Defining Functions (script, notebook)
- Anonymous (Lambda) Functions (script, notebook)
- For Loops and While Loops (script, notebook)
- Comprehensions (script, notebook)
- Map and Filter (script, notebook)
If you like the general format of this guide, but need more explanation of each topic, I highly recommend reading the Appendix of Python for Data Analysis. It presents the essentials of the Python language in a clear and focused manner.
If you are looking for a resource that will help you to learn Python from scratch, this is my list of recommended resources.
If there's a topic or example you'd like me to add to this guide, or you notice a mistake, please create a GitHub issue or leave a blog comment.
Thank you!