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, 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 the topics are ordered in a way that you can read it like a tutorial (i.e., each topic depends only on material preceding it).
The guide was written using Python 3.
PYTHON Python script
- Imports
- Data Types
- Math
- Comparisons and Boolean Operations
- Conditional Statements
- Lists
- Tuples
- Strings
- Dictionaries
- Sets
- Defining Functions
- Anonymous (Lambda) Functions
- For Loops and While Loops
- Comprehensions
- Map and Filter
- Collections
- Classes and Objects
MODULES Modules script
- NUMPY
- SCIPY
- PANDAS
- RE (Regular Expressions)
- SQLITE
Natural Language Processing (NLP) NLP script
- Library imports
- Book corpora
- Wordnet
- NLTK functions
- Tokenization
- Stemming
- Lemmatization
- POS taggin
- Chunking
- Frequency distribution1
- Latent semantic analysis (LSA)
- Sentiment analysis
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.
Thank you!
forked from: https://github.com/justmarkham/python-reference
By Kevin Markham ([email protected])
http://www.dataschool.io