List Of Python Cheat Sheets
Last updated
Last updated
****https://gist.github.com/bgoonz/dd7fd80df384fba134b42f256298bdb4#file-python-cheatsheet-py
Table of Contents
So let’s dive into the best Python cheat sheets recommended by us.
This is the best single cheat sheet. It uses every inch of the page to deliver value and covers everything you need to know to go from beginner to intermediate. Topics covered include container types, conversions, modules, maths, conditionals and formatting to name a few. A highly recommended 2-page sheet!
Some might think this cheat sheet is a bit lengthy. At 26 pages, it is the most comprehensive cheat sheets out there. It explains variables, data structures, exceptions, and classes – to name just a few. If you want the most thorough cheat sheet, pick this one.
Some of the most popular things to do with Python are Data Science and Machine Learning. In this cheat sheet, you will learn the basics of Python and the most important scientific library: NumPy (Numerical Python). You’ll learn the basics plus the most important NumPy functions. If you are using Python for Data Science, download this cheat sheet.
This Python data science cheat sheet from DataCamp is all about getting data into your code. Think about it: importing data is one of the most important tasks when working with data. Increasing your skills in this area will make you a better data scientist—and a better coder overall!
This cheat sheet is for more advanced learners. It covers class, string and list methods as well as system calls from the sys module. Once you’re comfortable defining basic classes and command line interfaces (CLIs), get this cheat sheet. It will take you to another level.
Want to learn Python well, but don’t have much time? Then this course is for you. It contains 5 carefully designed PDF cheat sheets. Each cheat sheet takes you one step further into the rabbit hole. You will learn practical Python concepts from the hand-picked examples and code snippets. The topics include basic keywords, simple and complex data types, crucial string and list methods, and powerful Python one-liners. If you lead a busy life and do not want to compromise on quality, this is the cheat sheet course for you!
The wonderful team at Dataquest have put together this comprehensive beginners cheat sheet. It covers all the basic data types, looping and reading files. It’s beautifully designed and is the first of a series.
This intermediate-level cheat sheet is a follow-up of the other Dataquest cheat sheet. It contains intermediate dtype methods, looping and handling errors.
NumPy is at the heart of data science. Advanced libraries like scikit-learn, Tensorflow, Pandas, and Matplotlib all built on NumPy arrays. You need to understand NumPy before you can thrive in data science and machine learning. The topics of this cheat sheet are creating arrays, combining arrays, scalar math, vector math and statistics.
This is only one great NumPy cheat sheet—if you want to get more, check out our article on the 10 best NumPy cheat sheets!
Want to master the visualization library Bokeh? This cheat sheet is for you! It contains all the basic Bokeh commands to get your beautiful visualizations going fast!
Pandas is everywhere. If you want to master “the Excel library for Python coders”, why not start with this cheat sheet? It’ll get you started fast and introduces the most important Pandas functions to you.
You can find a best-of article about the 7 best Pandas Cheat Sheets here.
Regex to the rescue! Regular expressions are wildly important for anyone who handles large amounts of text programmatically (ask Google). This cheat sheet introduces the most important Regex commands for quick reference. Download & master these regular expressions!
This cheat sheet is the most concise Python cheat sheet in the world. It contains keywords, basic data structures, and complex data structures—all in a single 1-page PDF file. If you’re lazy, this cheat sheet is a must!
If you love cheat sheets, here are some interesting references for you (lots of more PDF downloads):
