Python Cheat Sheet

Python is a programming language that is interpreted object-oriented and high-level. It has semantics making it ideal for Rapid Application Development and, as a scripting or glue language to connect components. Python’s built-in data structures and dynamic typing make it highly appealing. Its syntax is simple and easy to learn emphasizing readability and reducing program maintenance costs.

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Python Basics Cheat Sheet

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Python Operators

Operators in Python perform operations on values and variables using standard symbols for logic and math.

Arithmetic Operators in Python

Python arithmetic operators are used to perform mathematical operations on numeric values.

Operators Function Example
Addition(+) Adds two or more values 10 + 3 = 13
Subtraction(-) Subtract two or more values 10 – 3 = 7
Multiplication(*) Multiply two or more values 10 * 3 = 30
Division(/) Divides two or more values 10 / 3 = 3.333…
Modulus(%) Finds the remainder 10 % 3 = 1
Exponentiation(**) Used to raise the number to the power of a number 10 ** 3 = 1000
Floor division(//) Gives the floor value 10 // 3 = 3

Comparison Operators in Python

Python comparison operators are used to compare the values of two operands and return True or False based on whether the condition is met.

Operators Function Example
Equal to (==) Check whether the values are equal  x == y
Not Equal to(!=) Check whether the values are not equal  x != y
Less Than Check whether the values are less than the other value x < y
Greater Than Check whether the values are greater than the other value x > y
Less than or equal to Check whether the values are less than or equal to the other value x <= y
Greater than or equal to Check whether the values are greater than or equal to the other value x >= y

Assignment Operators in Python

The assignment operator in Python is used to assign values to variables.

Operators Function Example
Equal to(=) Assign a value to the variable x = 3  
Addition Assignment Operator (+=)  Subtracts the value and then assign it to the variable x += 3 (x = x + 3)
Subtraction Assignment Operator (-=)  Subtract the value and then assign it to the variable x -= 3 (x = x – 3)
Multiplication Assignment Operator (*=) Multiply the value and then assign it to the variable x *= 3 (x = x * 3)
Division Assignment Operator (/=) Divide the value and then assign it to the variable x /= 3 (x = x / 3)
Modulus Assignment Operator (%=)  Find the remainder and then assign it to the variable x %= 3 (x = x % 3)

Logical Operators in Python

Python logical operators help us to perform logic operations on nodes, groups, or numbers.

Operators Function Example
and Checks for one or more conditions together x=True, y=False

x and y  returns False

or Checks for only one condition x=True, y=False

x or y  returns True

not Reverse the output of the boolean value not x returns False

Identity Operators in Python

Python identity operators are used to compare the memory location of two objects.

x = [“apple”, “banana”]

y = [“apple”, “banana”]

Operators Function Example
is Checks if the value is available, if present returns True x is y  returns True
Is not Check if the value is not present, if not then return True x is not y  returns False

Membership Operators in Python

Python membership operators are used to test whether a value or variable exists in a sequence (string, list, tuples, sets, dictionary) or not. 

x = [“apple”, “banana”]

Operators Function Example
in Check if the substring is available, if yes then return True “banana” in x
not in Checks if the substring is not  available, if yes then returns True else False “orange” not in x

Bitwise Operators in Python

Bitwise operators in Python are used to perform bitwise operations on integers.

x = 10   # Binary: 1010

y = 4    # Binary: 0100

Operators Function Example
Bitwise AND(&) Performs bitwise and operation on the values x & y  returns 0
Bitwise OR(|) Performs bitwise or operation on the values x | y  returns 14
Bitwise XOR(^) Performs bitwise xor operation on the values x ^ y returns 14
Bitwise NOT(~) Performs bitwise not operation on the values x ~ y returns -11
Left Shift(<<) Performs left shift on the given value x << 1 returns 20
Right Shift(>>) Performs right shift on the given value x >> 1 returns 1

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Data Types in Python

Data types denote the classification of data items, indicating the operations feasible on individual data.

Integer Data Type

An integer in Python is a whole number, positive or negative, without decimals, of unlimited length.

x = 10    

y = 20   

print(type(x))  # Output: int

Float Data Type

The float data type in Python is used to represent real numbers with both an integer and fractional component.

x = 4.2

y = 10.5

print(type(x))   # Output: float

Boolean Data Type

The Boolean data type in Python is one of the built-in data types. It represents one of two values: True or False.

x = True                

y = False

print(type(x))         # Output: bool

Complex Data Type

The complex data type in Python consists of two values, the first one is the real part and the second one is the imaginary part of the complex number.

x = 2 + 3i           

print(type(x))     # Output: complex

String data type

A string is a sequence of characters enclosed in single quotes or double quotes.

1. Define a string

my_string = "Hello, World!"

my_string = ‘Hello, World!’

2. Indexing in a string

The process of accessing the element in a sequence using their position in the sequence is called Indexing

print(my_string[0])   # Output: H

print(my_string[7])   # Output: W

print(my_string[-1])  # Output: !

3. Length of a string

Len function returns the length of an object

print(len(my_string)) # Output: 13

4. String Concatenation

Joining more than one string together

string1 = "Hello"

string2 = "Intellipaat"

result = string1 + ", " + string2 + "!"

print(result)  # Output: Hello, Intellipaat!

5. String Methods

Method Function Example
replace() Replace the desired word with a new word. my_str = “Hello Intellipaat”)

my_str.replace(“Hello”, “Hi”)

# Output: “Hi Intellipaat”

split() Splits the words into items of a list where each word is one item. x = my_str.split()

# Output: [“Hi”, “Intellipaat”]

join() Joins the words based on a delimiter ” “.join(x)

# Output: “Hi Intellipaat”

lower() Converts all the text into lowercase name = “INTELLIPAAT”

x = name.lower()

# Output: “intellipaat”

upper() Converts all the text into an uppercase name = “intellipaat”

x = name.lower()

# Output: “iINTELLIPAAT”

strip() Removes the extra whitespace from the front name = ”     INTELLIPAAT”

x = name.lower()

# Output: “INTELLIPAAT”

find() Searches for a substring in the main string txt = “Hello, welcome to my Intellipaat.”

x = txt.find(“welcome”)

# Output: 7

6. String Slicing

Slicing is the extraction of a part of a string, list, or tuple

s = "Python"

print(s[2:5])   # Output: tho

print(s[:4])    # Output: Pyth

print(s[3:])

7. Escape Characters

An escape character is a backslash \ followed by the character you want to insert in the string.

print("This is a \"quote\" inside a string.")  # Output: This is a "quote" inside a string.

print("This is a \nnew line.")   # Output: This is a #  new line.

8. String Formatting

# Old Style Formatting 

name = "Alice"

age = 30

# Using placeholders %s (string) and %d (integer) within the string, 

# followed by the % operator and a tuple containing the values to substitute.

print("Name: %s, Age: %d" % (name, age))

# str.format() Method

name = "Rohit"

age = 25

# Using `{}` as a placeholder within the string, followed by the `.format()` method

# and passing the values to substitute as arguments to the method.

print("Name: {}, Age: {}".format(name, age))

# Formatted String Literals (f-strings) (Python 3.6+)

name = "Ashish"

age = 35

# Using f-string notation with `{}` placeholders directly within the string, 

# and using the variables directly within the curly braces.

print(f"Name: {name}, Age: {age}")

# `Template Strings`

from string import Template

name = "David"

age = 40

# Creating a Template object with placeholders as $variable, 

# and using the `substitute()` method to replace placeholders with values.

template = Template("Name: $name, Age: $age")

print(template.substitute(name=name, age=age))

Lists in Python

A list is a data structure in Python that is a mutable, or changeable, ordered sequence of elements.

1. Define a List

my_list = [1, 2, 3, 4, 5]

2. Accessing Elements in a List

print(my_list[0])   # Output: 1

print(my_list[2])   # Output: 3

print(my_list[-1])  # Output: 5

3. Length of a List

Len function returns the length of an object

print(len(my_list)) # Output: 5

4. List Slicing

Slicing is the extraction of a part of a string, list, or tuple

my_list = [1, 2, 3, 4, 5]

print(my_list[1:3])   # Output: [2, 3]

print(my_list[:3])    # Output: [1, 2, 3]

print(my_list[3:])    # Output: [4, 5]

5. List Methods

my_list = [1,2,3,4,5]
Method Function Example
append() Inserts an element at the end of the list. my_list = [1,2,3,4,5]

my_list.append(6)

# Output: [1,2,3,4,5,6]

insert() Insert an element at a particular index in the list. my_list.insert(2,10)

# Output: [1,2,10,3,4,5,6]

pop() Removes the last element in the list my_list.pop()

# Output: [1,2,10,3,4,5]

sort() Sorts the list in ascending or descending order. my_list.sort() 

# Output: [1,2,3,4,5,10]

reverse() Reverses the order of the elements of the list my_list.reverse()

# Output: [10,5,4,3,2,1]

6. Checking the Membership operator in the list 

Allows you to check the presence or absence of a substring within a given string

print(4 in my_list)   # Output: True

print(6 in my_list)   # Output: False

7. List Comprehensions

Writing the operation performed on the data within a line or few

squares = [x**2 for x in range(5)]

print(squares)        # Output: [0, 1, 4, 9, 16]

8. Nested Lists

List inside a list is called Nested List

matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

print(matrix[1][2])   # Output: 6

9. Copying Lists

Creating a copy of the original list so that the changes do not occur in the original

original_list = [1, 2, 3]

copied_list = original_list.copy()

Dictionary

A dictionary in Python is a collection of key-value pairs. Each key is associated with a value, and you can access the value by using the key.

1. Creating a dictionary

my_dict = {"key1": "value1", "key2": "value2", "key3": "value3"}

2. Accessing values in a dictionary

print(my_dict["key1"])   # Output: value1

print(my_dict["key2"])   # Output: value2

3. Length of a dictionary

print(len(my_dict))      # Output: 3

4. Dictionary Methods

Adding or updating key-value pairs

dict1["key4"] = "value4"     # Add new key-value pair

print(dict1)                 # Output: {'key1': 'value1', 'key2': 'value2', 'key3': 'value3', 'key4': 'value4'}

dict1["key1"] = "new_value"  # Update existing value

print(dict1)                 # Output: {'key1': 'new_value', 'key2': 'value2', 'key3': 'value3', 'key4': 'value4'}

Removing key-value pairs

del dict1["key3"]            # Delete a key-value pair

print(dict1)                 # Output: {'key1': 'new_value', 'key2': 'value2', 'key4': 'value4'}

dict1.pop("key2")            # Remove and return the value associated with the key

print(dict1)                 # Output: {'key1': 'new_value', 'key4': 'value4'}

Clearing a dictionary

dict1.clear()                # Remove all items in the dictionary

print(dict1)                 # Output: {}

5. Dictionary Iteration

Iterating over keys

for key in my_dict:

    print(key)   # Output: key1

                      #         key4

Iterating over values

for value in my_dict.values():

    print(value) # Output: new_value

                       #         value4

Iterating over key-value pairs

for key, value in my_dict.items():

    print(key, value)  # Output: key1 new_value

                               #         key4 value4

6. Dictionary Comprehensions

squares = {x: x**2 for x in range(5)}

print(squares)   # Output: {0: 0, 1: 1, 2: 4, 3: 9, 4: 16}

7. Nested Dictionaries

nested_dict = {"key1": {"nested_key1": "nested_value1"}, "key2": {"nested_key2": "nested_value2"}}

print(nested_dict["key1"]["nested_key1"])   # Output: nested_value1

Tuple in Python

In Python, a tuple is an unchangeable ordered collection of elements, defined with parentheses and separated by commas.

1. Creating a Tuple:

my_tuple = (1, 2, 3, 4, 5)

2. Accessing Elements in tuple:

first_element = my_tuple[0]   # Accessing the first element

last_element = my_tuple[-1]   # Accessing the last element

3. Length of a Tuple:

length = len(my_tuple)   # Returns the number of elements in the tuple

4. Iterating Over a Tuple:

for item in my_tuple:

     print(item)

5. Tuple Concatenation:

tuple1 = (1, 2, 3)

tuple2 = (4, 5, 6)

concatenated_tuple = tuple1 + tuple2   # Results in (1, 2, 3, 4, 5, 6)

6. Tuple Repetition:

repeated_tuple = (1, 2) * 3   # Results in (1, 2, 1, 2, 1, 2)

7. Checking if an Element Exists in a tuple:

if 3 in my_tuple:

    print("3 is present in the tuple")

8. Tuple Methods:

count = my_tuple.count(3)   # Returns the number of occurrences of the element 3 in the tuple

9. Finding the Index of an Element in tuple:

index = my_tuple.index(3)   # Returns the index of the first occurrence of the element 3 in the tuple

10. Immutability:

# Attempting to modify a tuple will result in an error

# my_tuple[0] = 10  # This will raise an error

11. Unpacking Tuples:

x, y, z = my_tuple   # Unpacking into variables

first, *middle, last = my_tuple   # Unpacking with asterisk operator

Sets in Python

In Python, a set is a mutable unordered collection of unique elements, defined using curly braces {} and separated by commas.

1. Creating a Set

my_set = {1, 2, 3, 4, 5}        # Set with normal elements

my_set = {[1,2,3,4,5]}          # Set with a list as an element

2. Adding an element in Set

my_set.add(4)       # This will add 4 to the set at a random place 

# Output: {1,2,3,4}

3. Checking the length of the Set

len(my_set)         # len will return the total length of the set  

# Output: 5

4. Set Methods

Method Explanation Example
add() Adds an element to the set my_set.add(10)
pop() Removes an element from the set my_set.pop()
remove() Removes a specific element from the set my_set.remove(10)
update() Add multiple elements to the set my_set.update([7,8,9])
clear() Removes all the elements of the set my_set.clear()
union Gives only the unique elements from the sets my_set.union(my_set1)
intersection Gives the common elements from the sets my_set.intersection(my_set1)

5. Set Comprehensions

x = {0,1,2,3,4}

squares = {x**2 for x in range(5)}   # Performs the operation on the set elements

# Output: {0, 1, 4, 9, 16}

6. Frozen Set

Immutable sets are called Frozen Sets. Once created elements cannot be added or removed. It can be used as a key in the dictionary.

Creating the Frozenset

frozen_set = frozenset([1, 2, 3, 4, 5])

Operations on frozen sets

print(1 in frozen_set)

# Output: True

print(len(frozen_set))

# Output: 5

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Flow Control Statements in Python

Flow control statements in Python are used to control the flow of execution of a program. They allow you to make decisions about which code to execute and when to execute it.

Conditional Statements in Python

In Python, a conditional statement allows for decision-making based on certain conditions.

If Statement

x = 10 

if x > 5:

# Checks for the condition to be True or False

print("x is greater than 5")

# If True then this line of code gets executed

# Output: x is greater than 5

If-else statement

x = 4

if x > 5:    # Checks for the condition

print("x is greater than 5")   # Runs if the condition is True

else:

print("x is less than or equal to 5") # Runs if the condition is False

 # Output: x is less than or equal to 5

If-elif-else statement

x = 3
if x > 5:   # Checks for the first condition

    print("x is greater than 5")   # Runs if the first condition is True

elif x == 5:  # Checks for the second condition when the first condition becomes False

    print("x is equal to 5")  # Runs if the condition is True

else:          

    print("x is less than 5")   # Runs if both the condition becomes False

# Output: x is less than 5

Nested if Statements

If inside an if statement is called nested if

x = 10
if x > 5:   # Check for the condition that goes inside the block
if x ; 15:   # Again checks for the condition, if True moves inside the if block
print("x is between 5 and 15")  # Runs if the condition is True

else:

print("x is greater than or equal to 15")  # Runs if the condition is False
else:
print("x is less than or equal to 5")  # Runs if the condition is False

# Output: x is between 5 and 15

Have a look at our blog on Python modules and frameworks to learn more!

Functions

A function is a block of code that only runs when it is called. We can pass data (or parameters) into a function, and after executing the function, it will return the data as a result.

def new_function():
print(“Hello World”)
new_function()

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Lambda Function

A lambda function is a small anonymous function. It can take any number of arguments but can only have one expression.

lambda a,b: a+b
lambda a,b: a*b

Generic Operations

In Python, we have a huge list of Python built-in functions. Some of them are mentioned as follows:

  • range(5): 0,1,2,3,4
  • S=input(“Enter:”)
  • Len(a): Gives item count in a
  • min(a): Gives minimum value in a
  • max(a): Gives maximum value in a
  • sum(a): Adds up items of an iterable and returns sum
  • sorted(a): Sorted list copy of a
  • importing modules: import random

File Operations:

In Python, we have several functions for creating, reading, updating, and deleting files. The ‘open()’ function takes two parameters that are filename and mode.

There are four different methods (or modes) for opening a file, which are mentioned below:

There are four different modes for opening a file:

  • “r” (Read): This is the default mode. It opens a file for reading, and if the file does not exist, it raises an error.
  • “a” (Append): This mode opens a file for appending data. If the file does not exist, it creates a new file.
  • “w” (Write): This mode opens a file for writing data. If the file does not exist, it creates a new file. If the file already exists, it truncates the file and overwrites its contents.
  • “x” (Create): This mode creates a new file. If the file already exists, it raises an error.

To open a file, you can use the ‘open()’ function and assign the returned file object to a variable.

For example:

f = open("File Name", "opening mode")

Here, “File Name” should be replaced with the actual name of the file you want to open, and “opening mode” should be replaced with the desired mode, such as “r” for read, “w” for write, “a” for append, or “r+” for both read and write operations.

Try and Except Blocks

The try block allows us to test a block of code for errors. The except block allows us to handle the error. Refer to the example mentioned below:

try:

[Statement body block]
raise Exception()
except Exception as e:
[Error processing block]

Oops Concepts

Python is an object-oriented programming language. In Python, almost everything is an object with its own properties and methods. Here, a class is like an object constructor or “blueprint” for creating objects.

  • Inheritance: A process of using details from a new class without modifying the existing class.
  • Polymorphism: A concept of using common operations in different ways for different data inputs.
  • Encapsulation: Hiding the private details of a class from other objects.

An Example of a Class/Object

Class: class Pen:
pass
object:obj=Pen()

Comments

Single line comments in Python start with the hash character, ‘#,’ and multiline comments should be used with “““triple quotes”””

# Single Line Comment
"""
Multi-line comment
"""

Download a Printable Python Cheat Sheet PDF

With this, we come to the end of the Python Basics Cheat Sheet. To get in-depth knowledge, try Data Science with Python, which comes with 24*7 support to guide you throughout your learning period. Intellipaat’s Python Course will let you master the concepts of the widely-used and powerful programming language, Python. You will gain hands-on experience working with various Python packages like SciPy, NumPy, Python MatPlotLib, Lambda functions, and more. You will work on hands-on projects in the domain of Python and apply it to the various domains of big data, data science, and machine learning.

A lot of questions can be raised about this topic.
Check out the list of Python Coding Interview Questions created by the experts.

 

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FAQs

What is a cheat sheet in Python?

A Python cheat sheet is a quick reference guide summarizing key syntax, commands, and concepts. It helps developers recall information easily while coding, serving as a handy tool for efficiency.

How to learn Python for beginners?

The best way for beginners to learn Python is to start with the fundamentals like variables, data types, conditionals, and loops. Practice with interactive tutorials and small projects.

What is a cheat sheet in programming?

A programming cheat sheet condenses essential programming elements like syntax, functions, and commands into a concise, accessible format. It assists programmers in recalling important data quickly during development tasks.

How do you make a cheat sheet?

Crafting a cheat sheet involves organizing key information logically, using bullet points, tables, or diagrams. Condense concepts into easily digestible sections, ensuring clarity and relevance for quick reference.

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