Are there cheat sheets to learn python?

Python is versatile, flexible, and a simple to debug programming language with extensive libraries and frameworks. Python is easy to learn and ideal for first time programmers. 

We’ve compiled a list of the best cheat sheets you can use to learn Python programming to clear doubts and make your Python journey as seamless as possible.

THE BELAMY

gto76

gto76 is a comprehensive Python cheat sheet available on GitHub. The author [Jure Šorn] has included syntax for every Python concept, from basic to advanced. It covers lists, range, enumerates, tuple, dictionaries, generator, and iterator; data types, libraries such as Numpy, Games, Data, Image, Audio, Logging, Scraping, etc., threading, introspection, metaprogramming, and operators.

Programmingwithmosh.com

Mosh Hamedani has some serious street-cred in the programming world, thanks to his free Python tutorials on YouTube. He created this Python cheat sheet to cover core Python concepts like strings, variables, receiving inputs, operators, arithmetic operations, if statements, loops, tuples, functions, exceptions, dictionaries, classes, modules, and inheritance standard libraries, Pypi, and more.

ALSO READ

Perso.limsi.fr

Perso.limsi.fr is a single page cheat sheet explaining Python concepts. It covers Python 3 topics from beginner to intermediate, including basic concepts, modules, conversions, container types, conditionals, and more.

WebsiteSetup

WebsiteSetup covers fundamental and intermediate Python concepts including data types, string creation, math operators, defining functions, lists, tuples, conditional statements, dictionaries, loops, dealing with exceptions, and troubleshooting errors. It is also available in PDF format.

Pythoncheatsheet.org

Pythoncheatsheet.org is a comprehensive Python cheat sheet covering various topics, including Python fundamentals, functions, flow control, exception handling, data structures, lists, sets, loops, debugging, YAML, JSON, configuration files, data classes, context manager, virtual environments, and more.

DataCamp

DataCamp is extremely beneficial for Python beginners interested in data science. It covers data types, strings, variables, lists, Python scientific computing packages, Numpy arrays, libraries and more.

Cheatography

Cheatography is a two-page Python cheat sheet for quick reference. It covers Python sys variables, sys.argv, special methods, file methods, list methods, string methods, Python os variables, DateTime methods, and Python indexes and slices.

Ehmatthes.github.io

ehmatthes.github.io covers syntax rules as well as important concepts. The sheet discusses lists, dictionaries, loops, if and while statements, functions, classes, code testing, exceptions, and files, as well as Pygame, Plotly, Django, and Matplotlib.

Python for Data Science

Python for Data Science is a one-page Python cheat sheet to learn the fundamentals of this programming language, especially geared towards data science. It covers data types and conversions, variables and calculations, strings and operations methods, lists and operations and methods, libraries, and Numpy arrays.

Real Python

Real Python uses syntax and examples to explain basic Python concepts. It covers primitives such as numbers, strings, and Booleans and collections such as lists and dictionaries, control statements, loops, and functions.

Are you finding difficulty remembering all the syntax that you need to work with Python?
Guys, don’t worry if you are a beginner and have no idea about how Python works, this Python for Data Science cheat sheet will give you a quick reference of the basics that you must know to get started.
While at Intellipaat, we support our learners with a handy reference, that is the reason we have created this Cheat sheet. Take a deep dive to learn Python by our online tutorial.

Download a Printable PDF of this Cheat Sheet

This cheat sheet is designed for the one who has already started learning about Python but needs a handy reference sheet.

Watch Python Interview Questions tutorial:

Python Basic:

Python is a high-level dynamic programming language that is very easy to learn. It comes with powerful typing and the codes are written in a very ‘natural’ style, that’s the reason, it is easy to read and understand. Python programming language can run on any platform, from Windows to Linux to Macintosh, Solaris, etc.

Basic rules to write Python syntax:

Rule #1: Python is white-space dependent; code blocks are indented using spaces.
Rule #2: Python language is case sensitive. It matters for variables, functions and any keyword in general.

Data Types

In Python, every value has a datatype. in Python programming, everything is an object, data types are classes and variables are instances that mean the object of these classes.
There are various data types in Python. Some of the important types are listed below.

• • Numbers: a=2[Integer], b=2.0[Float], c=1+2j[Complex]

• • List: a=[1,2,3,’Word’]

• • Tuple: a= [1,2,4]

• • String: a=“New String”

• • Sets: a= {2,3,4,5}

• • Dictionary: x= {‘a’: [1,2],‘b’: [4,6]

Operators

In python, Operators are only the constructs that can manipulate the value of operands. For example, in the expression 5 + 10 = 15. Here, 5 and 10 are operands and + is operator.

• • Numeric Operator [Say, a holds 5, b holds 10]
    • • a + b = 15
    • • a – b = -5
    • • a * b = 50
    • • b/a = 2
    • • b % a = 0
    • • a**b =510
    • • 0//2.0 = 3.0, -11//3 = -4

• • Comparison Operator
    • • [a == b]: not true
    • • [a!= b]: true
    • • [a > b]: not true.
    • • [a > b]: not true
    • • [a >= b]: not true
    • • [a =700: print[“Buy.”] else: print[“Don’t buy.”]
        • • For loop [Iterative Loop Statement]:

        a=“New Text” count=0 for i in a: if i==‘e’: count=count+1 print[count]

        • • While loop [Conditional Loop Statement]:

        a=0 i=1 while i