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Python Cheat Sheet PDF

Download our essential introduction to Python cheat sheet covering variables, control flow, functions, data structures, OOP, and dates.

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← All cheat sheets

Python Cheat Sheet PDF

Download our essential introduction to Python cheat sheet covering variables, control flow, functions, data structures, OOP, and dates.

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Table of Contents

Basics

Syntax for

How to use

Explained

Comments

# print(1 +  2)
print(5  * 10)
# This program will only print 50

We call the sequence of characters that follows the # a code comment; any code that follows # will not be executed

Arithmetical Operations

1 + 2  # output: 3

Addition

4 - 5  # output: -1

Subtraction

30 * 2  # output: 60

Multiplication

20 / 3  # output: 6.666666666666667

Division

4 ** 3  # output: 64

Exponentiation

(4 * 18) ** 2 / 10  # output: 518.4

Use parentheses to control the order of operations

Initializing Variables

cost = 20
total_cost = 20 + 2 ** 5
currency = 'USD'
1_app = 'Facebook'  # this will cause an error

Variable names can only contain letters, numbers, and underscores―they cannot begin with a number

Updating Variables

x = 30
print(x)  # output: 30
x = 50
print(x)  # output: 50

To update a variable, use the = assignment operator to set a new value

Operation Shortcuts

x += 2  # Addition
x -= 2  # Subtraction
x *= 2  # Multiplication
x /= 2  # Division
x **= 2  # Exponentiation

Augmented assignment operators: used to update a variable in place without repeating the variable name; for example, instead of writing: x = x + 2 , you can use:
x += 2

Data Types

x = [1 ,2 ,3]
y = 4
print(type(x))  # list
print(type(y))  # integer
print(type('4'))  # string

Use the type() command to determine the data type of a value or variable

int('4')  # casting a string to an integer
str(4)  # casting an integer to a string
float('4.3')  # casting a string to a float
str(4.3)  # casting a float to a string

Converting between data types is also referred to as casting

Data Structures

Syntax for

How to use

Explained

Lists

a_list = [1, 2]
a_list.append(3)
print(a_list)  # output: [1, 2, 3]

Creating a list and appending a value to it

row_1 = ['Facebook', 0.0, 'USD', 2974676]
row_2 = ['Instagram', 4.5, 'USD', 2161558]

Creating a list of data points; lists can store multiple data types at the same time

Indexing

print(row_1[0])  # output: 'Facebook' 
print(row_2[0])  # output: 'Instagram' 
print(row_1[1])  # output: 0.0
print(row_2[1])  # output: 4.5
print(row_1[3])  # output: 2974676
print(row_2[3])  # output: 2161558

Retrieving an element from a list using each item’s index number; note that list indexing begins at 0

Negative Indexing

print(row_1[-1])  # output: 2974676
print(row_2[-1])  # output: 2161558
print(row_1[-3])  # output: 0.0
print(row_2[-3])  # output: 4.5
print(row_1[-4])  # output: 'Facebook' 
print(row_2[-4])  # output: 'Instagram'

Negative list indexing works by counting backwards from the last element, beginning with -1

num_ratings = [row_1[-1], row_2[-1]]
print(name_and_ratings)  # output: [2974676, 2161558]

Retrieving multiple list elements to create a new list

List Slicing

row_3 = ['Clash of Clans', 0.0, 'USD', 2130805, 4.5]

print(row_3[:2])  # output: ['Clash of Clans', 0.0]
print(row_3[1:4])  # output: [0.0, 'USD', 2130805]
print(row_3[3:])  # outputs [2130805, 4.5]

List slicing includes the start index but excludes the end index; when the start is omitted, the slice begins at the start of the list; when the end is omitted, it continues to the end of the list

List of Lists

from csv import reader
opened_file = open('AppleStore.csv')
read_file = reader(opened_file)
apps_data = list(read_file)

Opening a dataset file and using it to create a list of lists

row_1 = ['Facebook', 'USD', 2974676, 3.5]
row_2 = ['Instagram', 'USD', 2161558, 8.2]
row_3 = ['Clash', 0.0, 'USD', 2130805, 4.5]
row_4 = ['Fruit', 1.99, 'USD', 698516, 9.1]

lists = [row_1, row_2, row_3, row_4]

Creating a list of lists by initializing a new list whose elements are themselves lists

Indexing

first_row_first_element = lists[0][0]  # output: 'Facebook'
second_row_third_element = lists[1][2]  # output: 2161558
third_row_last_element = lists[-2][4]  # output: 4.5
last_row_last_element = lists[-1][-1]  # output: 9.1

Retrieving an element from a list of lists by first selecting the row, then the element within that row

Slicing List of Lists

first_two_rows = lists[:2] 
last_two_rows = lists[-2:]
all_but_first_row = lists[1:]
second_row_partial = lists[1][:3] 
# output: ['Instagram', 'USD', 2161558]
last_row_partial = lists[-1][1:3] 
# output: [1.99, 'USD']

Slicing lists of lists allows extracting full rows or specific elements from a single row; positive indices select from the start, and negative indices select from the end

Dictionaries

# First way:
dictionary = {'key_1': 1, 'key_2': 2}
# Second way:
dictionary = {}
dictionary['key_1'] = 1
dictionary['key_2'] = 2

Creating a dictionary by defining key:value pairs at time of initialization (first way) or by creating an empty dictionary and setting the value for each key (second way)

dictionary = {'key_1': 100, 'key_2': 200}
dictionary['key_1']  # returns 100
dictionary['key_2']  # returns 200

Retrieve individual dictionary values by specifying the key; keys can be strings, numbers, or tuples, but not lists or sets 

dictionary = {'key_1': 100 , 'key_2': 200}
'key_1' in dictionary  # returns True
'key_5' in dictionary  # returns False
100 in dictionary  # returns False

Use the in operator to check for dictionary key membership

dictionary = {'key_1': 100 , 'key_2': 200}
dictionary['key_1'] += 600
dictionary['key_2'] = 400
print(dictionary)  # output: {'key_1': 700 , 'key_2': 400}

Update dictionary values by specifying the key and assigning a new value

Frequency Tables

frequency_table = {}
for row in a_data_set:
    a_data_point = row[5]
    if a_data_point in frequency_table:
        frequency_table[a_data_point] += 1
    else:
        frequency_table[a_data_point] = 1

Builds a frequency table by counting occurrences of values in the 6th column (row[5]) of a_data_set, incrementing the count if the value exists, or adding it if not

Defined Intervals

data_sizes = {'0 - 10 MB': 0, 
		      '10 - 50 MB': 0, 
		      '50 - 100 MB': 0,
		      '100 - 500 MB': 0,
		      '500 MB +': 0}
for row in app_data[1:]:
	data_size = float (row[2])
	if data_size < 10000000:
		data_sizes['0 - 10 MB'] += 1
	elif 10000000 < data_size <= 50000000:
		data_sizes['10 - 50 MB'] += 1
	elif 50000000 < data_size <= 100000000:
		data_sizes['50 - 100 MB'] += 1
	elif 10000000 < data_size <= 500000000:
		data_sizes['100 - 500 MB'] += 1
	elif data_size > 500000000:
		data_sizes['500 MB +'] += 1

Categorizes app sizes from apps_data into predefined ranges (e.g., '0 - 10 MB') and increments the corresponding count based on each app's size inside the data_sizes dictionary

Functions

Syntax for

How to use

Explained

Basic Functions

def square(number): 
	return number**2

print(square(5))  # output: 25

Create a function with a single parameter: number

def add(x, y):
	return x + y

print(add(3, 14))  # output: 17

Create a function with more than one parameter x and y

def freq_table(list_of_lists, index):
    frequency_table = {}
    for row in list_of_lists:
        value = row[index]
        if value in frequency_table:
            frequency_table[value] += 1
        else:
            frequency_table[value] = 1
    return frequency_table

This function creates a frequency table for any given column index of the provided list_of_lists

Arguments

def subtract(a, b):
	return a - b

print(subtract(a=10, b=7))  # output: 3
print(subtract(b=7, a=10))  # output: 3
print(subtract(10, 7))  # output: 3

Use named arguments and positional arguments

Helper Functions

def find_sum(lst):
	a_sum = 0
	for element in lst:
		a_sum += float(element)
	return a_sum

def find_length(lst):
	length = 0
	for element in lst:
		length += 1
	return length

def mean(lst):
	return find_sum(lst) / find_length(lst)

print(mean([1, 2, 4, 6, 2])  # output: 3

Define helper functions to find the sum and length of a list; the mean function reuses these to calculate the average by dividing the sum by the length

Multiple Arguments

def price(item, cost):
	return "The " + item + " costs $" + str(cost) + "."

print(price("chair", 40.99))  # output: 'The chair costs $40.99.'

Define a function that accepts multiple arguments and returns a formatted string combining both inputs

def price(item, cost):
	print("The " + item + " costs $" + str(cost) + ".")

price("chair", 40.99)  # output: 'The chair costs $40.99.'

Similar to the previous function, but uses print() to display the string immediately rather than returning it for further use

Default Arguments

def add_value(x, constant=3.14):
	return x + constant

print(add_value(6, 3))  # output: 9
print(add_value(6))  # output: 9.14

Define a function with a default argument; if no second argument is provided, the default value is used in the calculation

Multiple Return Statements

def sum_or_difference(a, b, return_sum=True):
	if return_sum:
		return a + b
	else:
		return a - b

print(sum_or_difference(10, 7))  # output: 17
print(sum_or_difference(10, 7, False))  # output: 3

This function uses multiple return statements to either return the sum or the difference of two values, depending on the return_sum argument, which defaults to True

def sum_or_difference(a, b, return_sum=True):
	if return_sum:
		return a + b
	return a - b

print(sum_or_difference(10, 7))  # output: 17
print(sum_or_difference(10, 7, False))  # output: 3

This function is similar to the previous one but omits the else clause, returning the difference directly when return_sum is False, simplifying the logic

Returning Multiple
Values

def sum_and_difference(a, b):
	a_sum = a + b
	a_difference = a - b 
	return a_sum, a_difference

sum_1, diff_1 = sum_and_difference(15, 10)

This function returns multiple values (sum and difference) at once by separating them with commas, allowing them to be unpacked into separate variables when called

Strings

Syntax for

How to use

Explained

Formatting

continents = "France is in {} and China is in {}".format("Europe", "Asia")
print(continents)  # output: France is in Europe and China is in Asia

Insert values by order into placeholders for simple string formatting

squares = "{0} times {0} equals {1}".format(3, 9)
print(squares)  # output: 3 times 3 equals 9

Use indexed placeholders to repeat or position values

population = "{name}'s population is {pop} million".format(name="Brazil", pop=209)
print(population)  # output: Brazil's population is 209 million

Assign values to named placeholders using variable names

two_decimal_places = "I own {:.2f}% of the company".format(32.5548651132)
print(two_decimal_places)  # I own 32.55% of the company

Format a float to two decimal places for precise output

india_pop = "The approximate population of {} is {:,}".format("India", 1324000000)
print(india_pop)  # output: The approximate population of India is 1,324,000,000

Insert a number with commas as a thousand separator by position

balance_string = "Your bank balance is ${:,.2f}".format(12345.678)
print(balance_string)  # output: Your bank balance is $12,345.68

Format a number with commas and two decimal places for currency formatting

String Cleaning

green_ball = "red ball".replace("red", "green")
print(green_ball)  # output: green ball

Replace parts of a string by specifying the old and new values

friend_removed = "hello there friend!".replace(" friend", "")
print(friend_removed)  # output: hello there!

Remove a specified substring from a string by replacing it with an empty string

bad_chars = ["'", ",", ".", "!"]
string = "We'll remove apostrophes, commas, periods, and exclamation marks!"

for char in bad_chars:
    string = string.replace(char, "")

print(string)  # output: Well remove apostrophes commas periods and exclamation marks

Use a loop to remove multiple specified characters from a string by replacing them with an empty string

print("hello, my friend".title())  # output: Hello, My Friend

Capitalize the first letter of each word in the string

split_on_dash = "1980-12-08".split("-")
print(split_on_dash)  # output: ['1980', '12', '08']

Split a string into a list of substrings based on the specified delimiter

first_four_chars = "This is a long string."[:4]
print(first_four_chars)  # output: This

Slice the string to return the first four characters; missing indices default to the start or end of the string

superman = "Clark" + " " + "Kent"
print(superman)  # output: Clark Kent

Concatenate strings using the + operator to join them with a space

Control Flow

Syntax for

How to use

Explained

For Loops

row_1 = ['Facebook', 0.0, 'USD', 2974676]
for element in row_1:
	print(element)

With each iteration, this loop will print an element from row_1, in order

rating_sum = 0 
for row in apps_data[1:]:
	rating = float(row[7]) 
	rating_sum = rating_sum + rating

Convert a column of strings (row[7]) in a list of lists (apps_data) to a float and keep a running sum of ratings

apps_names = []
for row in apps_data[1:]:
	name = row[1]  
	apps_names.append(name)

Append values with each iteration of a for loop

Conditional Statements

price = 0
print(price == 0)  # output: True
print(price == 2)  # output: False

Use comparison operators to check if a value equals another, returning True or False

print('Games' == 'Music')  # output: False
print('Games' != 'Music')  # output: True
print([1,2,3] == [1,2,3])  # output: True
print([1,2,3] == [1,2,3,4])  # output: False

Compare strings and lists using == for equality and != for inequality, returning True or False

If Statements

if True:
	print('This will always be printed.')

The condition True always executes the code inside the if block

if True:
	print(1)
if 1 == 1:
	print(2)
	print(3)

Both conditions evaluate to True, so all print statements are executed

if True:
	print('First Output')
if False:
	print('Second Output')
if True:
	print('Third Output')

Only the blocks with True conditions are executed, so the second print statement is skipped

Else Statements

if False:
	print(1)
else:
	print('The condition above was false.')

The code in the else clause is always executed when the if statement is False

if "car" in "carpet":
	print("The substring was found.")
else:
	print("The substring was not found.")

The in operator checks if a substring exists in a string, executing the corresponding if or else block

Elif Statements

if 3 == 1:
	print('3 does not equal 1.')
elif 3 < 1:
	print('3 is not less than 1.')
else:
	print('Both conditions above are false.')

The elif statement allows for multiple conditions to be tested; if the if condition is False, the elif condition is checked, and if both are False, the else block is executed

Multiple Conditions

if 3 > 1 and 'data' == 'data':
	print('Both conditions are true!')
if 10 < 20 or 4 >= 5:
	print('At least one condition is true.')

Use and to require both conditions to be True and or to require at least one condition to be True

if (20 > 3 and 2 != 1) or 'Games' == 'Game':
	print('At least one condition is true.')

Use parentheses to group conditions and control the order of evaluation in complex logical expressions

Object-Oriented Programming Basics

Syntax for

How to use

Explained

Defining Classes

class MyClass:
	pass

Define an empty class

Instantiating Class Objects

class MyClass:
	pass

mc_1 = MyClass()

Instantiate an object from the class by calling the class name followed by parentheses

Setting Class Attributes

class MyClass:
	def __init__(self, param_1):
		self.attribute = param_1

mc_2 = MyClass("arg_1")
# mc_2.attribute is set to "arg_1"

Use the __init__ method to initialize an object's attributes during instantiation by passing arguments

Defining Class Methods

class MyClass:
	def __init__(self, param_1):
		self.attribute = param_1
	def add_20(self):
		self.attribute += 20

mc_3 = MyClass(10)  # mc_3.attribute is 10 
mc_3.add_20()  # mc_3.attribute is now 30

Define a method within the class to modify an attribute; add_20 increases the value of attribute by 20 when called

Dates and Time

Syntax for

How to use

Explained

Importing Datetime Examples

import datetime
current_time = datetime.datetime.now()

Import the module, requiring the full path to access functions or classes

import datetime as dt
current_time = dt.datetime.now()

Import the module with alias dt for shorter references, a common practice

from datetime import datetime
current_time = datetime.now()

Import only the datetime class, enabling direct access without the module name prefix

from datetime import datetime, date
current_time = datetime.now()
current_date = date.today()

Import multiple classes from the module, allowing direct use of their respective methods

from datetime import *
current_time = datetime.now()
current_date = date.today()
min_year = MINYEAR
max_year = MAXYEAR

Import all classes and functions from the module, making every definition and all constants accessible without using a prefix; this is not advised for this module

Creating Datetime Objects

import datetime as dt
eg_1 = dt.datetime(1985, 3, 13, 14, 30, 45)

Create a datetime object with both date (March 13, 1985) and time (14:30:45) components

from datetime import datetime as dt
eg_2 = dt.strptime("15/08/1990 08:45:30", 
                   "%d/%m/%Y %H:%M:%S")

Convert a formatted string into a datetime object; the "p" stands for parsing

eg_2_str = eg_2.strftime("%B %d, %Y at %I:%M %p")
print(eg_2_str)  # output: "August 15, 1990 at 08:45 AM"

Convert a datetime object into a formatted string; the "f" stands for formatting

eg_3 = dt.time(hour=5, minute=23, second=45, microsecond=123456)
print(eg_3)  # output: 05:23:45.123456

Create a time object that includes microseconds

eg_4 = dt.timedelta(weeks=3)
future_date = eg_1 + eg_4
print(future_date)  # output: 1985-04-03 14:30:45

Add a timedelta object representing 3 weeks to a datetime object to calculate a future date

Accessing Datetime Attributes

eg_1.year  # returns 1985
eg_1.month  # returns 3
eg_2.day  # returns 15
eg_2.hour  # returns 8
eg_3.minute  # returns 23
eg_3.microsecond  # returns 123456

Access specific components directly from datetime and time objects using their built-in attributes

eg_2_time = eg_2.time()
print(eg_2_time)  # output: 08:45:30

Extract the time component from a datetime object that contains both date and time using the .time() method

Mike Levy

Written by

Mike Levy

Mike is a life-long learner who is passionate about mathematics, coding, and teaching. When he's not sitting at the keyboard, he can be found in his garden or at a natural hot spring.

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