1. Python Cheat Sheet For Beginners
2. Python Crash Course Cheat Sheet
3. Beginners Python Cheat Sheet
4. Basic Python Cheat Sheet

Beginner’s Python Cheat Sheet - Dictionaries Focuses on dictionaries: how to build and modify a dictionary, access the information in a dictionary, and loop through dictionaries in a variety of ways. Includes sections on nesting lists and dictionaries, using dictionary comprehensions, and more.

• 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!
• Javabeginnerstutorial provides Tutorial for beginners to learn the basic concepts of Java and realated technologies. You will learn the fundamentals. Topics also contain cheatsheet for a quick review of what you have learned in a given topic.
• Python for Beginners –Cheat Sheet Data types and Collections i nt eger 10 fl o a t 3.14 b o o l ea n True/False s t ri ng ‘abcde’ l i s t 1, 2, 3, 4, 5.
• Python Cheat Sheet: Python is a multi-paradigm general-purpose, object-oriented programming languageIt is a cross-platform programming language.

• Python is a multi-paradigm general-purpose, object-oriented programming language
• It is a cross-platform programming language so code python file written in one system can be run same on different systems.
• Easy to learn.
• Simple Syntax and akin to pseudocode.
• Automatic Garbage Collection.
• It is an open-source programming language.

Applications of Python

Python is a very versatile language and it is used in many IT fields such as:

• Web Development (back-end)
• Desktop Applications
• Data Science.
• Machine Learning
• Artificial Intelligence.

Major Characteristic of Python

• Very Simple Programming language.
• Python has the most libraries.
• Support Object-Oriented programming
• Ideal Programming language for a beginner.
• Robust and Secure
• Highly Scalable
• Use Interpreter
• Dynamic Programming language.
• Multi-threading.

Python IDE’s

There are many IDE’s on the internet for Python the two most recommended ones are:

• PyCharm (By Jetbrains)
• Atom (Powered by GitHub)

Standard Data Types in Python:

Python has two types of Data types:

• Base Type.
• Container Type.

Base Type

Container Type Data Types

Python Operators

Python has some standard operators which include arithmetic operators too.

Python Comparison Operator

There are some operators in python which are used to compare two objects or values and return a Boolean value True and False:

Logical Operators

Python has three logical Operators:

• and
• or
• not

Python Identifiers

Identifies are the name given to an object, identifiers can be also known as a variable name. There are some rules associated with an identifier or variable name. Using identifies we can give a name to variables, functions, modules, classes.

Identifiers rule:

• The first letter of an identifier could be a lowercase or upper case Alphabet or _ (underscore symbol), and it could be followed by any alphabet, digit (0,9) and _.
• There should be no special symbol in identifier except _.
• Do not use reserved keywords as an identifier.

Variable Assignment

We use equal to “=” symbol to assign an object to an identifier.

The identifier name should be on the left side and value on the right side of the assignment operator.

Example:

x =20

Python I/O

Example:

By default input() accept value as string.

Type Conversion

Using there are many reserved keywords in python which are used to convert the data type of a variable.

Indexing Calling in Python

In python String, List and tuple objects support indexing calling.

Example:

Boolean Logic in Python

In python, we often encounter with Boolean values when we deal with comparison operator conditional statements.

Types of Boolean

In python there are two types of Booleans:

• True
• False

Modules Name and Import

Python Math Module

Math is the most important and widely used standard module of python, it provides many methods related to mathematics.

Conditional Statement

Python Conditional statement consists of 3 keywords if, elif and else.

Example:

Loops

There are two loops statements present in python:

• for loop
• while loop

Example:

Break

It is a statement used inside the loop statement, and it is used to terminate the loop flow and exist from the loop immediately.

Example:

Continue

Continue is the opposite of break, it is also used in loop statements and directly jump to the next iteration.

Example:

Function

To create a user-defined function in python we use the def keyword and to exit from a function we return a value using the return keyword.

Example:

Python List

A list is a collection of different data types, and it stores all elements in a contagious memory location.

Create a list

To create a list we use square brackets [ ].

Example:

Indexing

List support indexing, with the help of indexing we can access the specific element of the list.

Example:

List Slicing

With list slicing, we can access a sequence of elements present in the list.

Example:

List Unpacking

Loop through a List:

Adding Elements in the list:

Removing Elements from a list

If condition with a list

List Comprehension

lst_2 = [i for i in lst ]

Condition inside list comprehension

Zip function to combine two lists

Map and Filter on a list

List Operations

Python Tuples

Tuples in python similar to a list, the only difference is tuples are immutable.

Create a tuple:

Convert a list into a tuple

Indexing In tuple

Python Arrays

Python does not have inbuilt support for arrays but it has standard libraries to for array data structure. Array is a very useful tool to perform mathematical concepts.

Create an Array:

Python Sets

Python set is similar to the mathematic sets, a python set does not hold duplicates items and we can perform the basic set operation on set data types.

Create a Set:

Basic Set operation

Dictionary

Dictionary is a collection of key: value pair and the key could only be an immutable data type.

Create a dictionary:

Python Cheat Sheet For Beginners

Convert a list into a dictionary:

Accessing Dictionary Elements

We use the key to access the corresponding value.

Looping Through a dictionary:

Generator Comprehension

Like a list comprehension, we have generator comprehension in generator comprehension we use parenthesis () instead of sq. brackets [].

Example:

Exception Handling:

In exception handling we deal with runtime error there are many keywords associated with exception handling:

Example:

Python Class

Class provides the Object-Oriented programming concepts to python.

Create a class

Create a constructor for a class:

The constructor is the special method of class which executes automatically during the object creation of the class.

Magic Methods of class

Class Private members:

Conventionally to declare an attribute private we, write it name starting with __ double underscore.

Example:

Inheritance:

An inheritance we can use the methods and property of another class:

Example:

Multiple Inheritance:

Basic Generic Operations on Containers

People Also Read:

Data Science is rapidly becoming a vital discipline for all types of businesses. An ability to extract insight and meaning from a large pile of data is a skill set worth its weight in gold. Due to its versatility and ease of use, Python has become the programming language of choice for data scientists.

In this Python cheat sheet, we will walk you through a couple of examples using two of the most used data types: the list and the Pandas DataFrame. The list is self-explanatory; it’s a collection of values set in a one-dimensional array. A Pandas DataFrame is just like a tabular spreadsheet, it has data laid out in columns and rows.

Let’s take a look at a few neat things we can do with lists and DataFrames in Python!
Get the pdf here.

Python Cheat Sheet

Lists

Creating Lists

Create an empty list and use a for loop to append new values.

#add two to each value
my_list = []
for x in range(1,11):
my_list.append(x+2)

We can also do this in one step using list comprehensions:

my_list = [x + 2 for x in range(1,11)]

Creating Lists with Conditionals

As above, we will create a list, but now we will only add 2 to the value if it is even.

#add two, but only if x is even
my_list = []
for x in range(1,11):
if x % 2 0:
my_list.append(x+2)
else:
my_list.append(x)

Python Crash Course Cheat Sheet

Using a list comp:

my_list = [x+2 if x % 2 0 else x
for x in range(1,11)]

Selecting Elements and Basic Stats

Beginners Python Cheat Sheet

Select elements by index.

#get the first/last element
first_ele = my_list[0]
last_ele = my_list[-1]

Some basic stats on lists:

#get max/min/mean value
biggest_val = max(my_list)
smallest_val = min(my_list)avg_val = sum(my_list) / len(my_list)

DataFrames

Basic Python Cheat Sheet

Reading in Data to a DataFrame

We first need to import the pandas module.

import pandas as pd

Then we can read in data from csv or xlsx files:

df_from_csv = pd.read_csv(‘path/to/my_file.csv’,
sep=’,’,
nrows=10)
xlsx = pd.ExcelFile(‘path/to/excel_file.xlsx’)
df_from_xlsx = pd.read_excel(xlsx, ‘Sheet1’)

Slicing DataFrames

We can slice our DataFrame using conditionals.

df_filter = df[df[‘population’] > 1000000]
df_france = df[df[‘country’] ‘France’]

Sorting values by a column:

df.sort_values(by=’population’,
ascending=False)

Filling Missing Values

Let’s fill in any missing values with that column’s average value.

df[‘population’] = df[‘population’].fillna(
value=df[‘population’].mean()
)

Applying Functions to Columns

Apply a custom function to every value in one of the DataFrame’s columns.

def fix_zipcode(x):
”’
make sure that zipcodes all have leading zeros
”’
return str(x).zfill(5)
df[‘clean_zip’] = df[‘zip code’].apply(fix_zipcode)