Cheatsheet

Useful commands and tips

Variables and Types

Variables

Definition: Containers for storing information.
Example: x = 10

Data Types

Integers (int): Whole numbers (e.g., count of dates).
Floats (float): Decimal numbers (e.g., compatibility score).
Booleans (bool): True/False values (e.g., availability).
Strings (str): Text values (e.g., names).

  name = "Alexander"  # String variable
  flags = 0           # Integer variable
  butterflies = True  # Boolean variable

Type Conversion

Checking: Use type() to check the type of a variable.
Conversion:
- int(): Converts to integer.
- float(): Converts to float.
- str(): Converts to string.
- bool(): Converts to boolean.

String Formatting

Concatenation: Combine strings using +.
Formatting: Use f"..." for formatted strings.

name = "Alexander"
print(f"Hello, {name}!")

Hello, Alexander!

Comparisons

Comparison Operators

Symbol	Meaning	Example
==	Equal to	score == 100
!=	Not equal to	degree != “Computer Science”
<	Less than	salary < 80000
>	Greater than	experience > 5
<=	Less than or equal to	age <= 65
>=	Greater than or equal to	test_score >= 80

Logical Operators

Symbol	Meaning	Example
and	Both conditions must be true	score > 80 and experience > 5
or	At least one condition must be true	score > 80 or experience > 5
not	Condition must be false	not (score > 80)

Decision-Making

if Statements

Structure:

if condition:
    # code to execute if condition is True

Example:

flat_rating = 8
if flat_rating >= 7:
    print("This is a good apartment!")

This is a good apartment!

if-else Statements

Structure:

if condition:
    # code to execute if condition is True
else:
    # code to execute if condition is False

Example:

flat_rating = 4
if flat_rating >= 7:
    print("Apply for this flat!")
else:
    print("Keep searching!")

Keep searching!

if-elif-else Statements

Structure:

if condition:
    # code to execute if condition is True
elif condition:
    # code to execute if condition is False
else:
    # code to execute if condition is False

Example:

flat_rating = 8
if flat_rating >= 9:
    print("Amazing flat - apply immediately!")
elif flat_rating >= 7:
    print("Good flat - consider applying")
else:
    print("Keep looking")

Good flat - consider applying

Complex Conditions

Nested if Statements: Use if statements inside other if statements.
Logical Operators: Combine conditions using and, or, not.
Structure:

if (condition1) and (condition2):
    # code if both conditions are True
elif (condition1) or (condition2):
    # code if at least one condition is True
else:
    # code if none of the conditions are True

Example:

flat_rating = 9
price = 900
if (flat_rating >= 9) and (price < 1000):
    print("Amazing flat - apply immediately!")

Amazing flat - apply immediately!

Lists and Tuples

Lists

Definition: Ordered, mutable collections of items.
Creation: Use square brackets [].

ratings = [4.5, 3.8, 4.2]
restaurants = ["Magic Place", "Sushi Bar", "Coffee Shop"]

Accessing Elements

Indexing: Use [index] to access elements.

print(restaurants[0])  # Access the first element

Magic Place

Negative Indexing: Use [-1] to access the last element.

print(restaurants[-1])  # Access the last element

Coffee Shop

Slicing: Use [start:end] to access a range of elements.

print(restaurants[0:2])  # Access the first two elements

['Magic Place', 'Sushi Bar']

Adding Elements

Appending: Use append() to add an element to the end of the list.

restaurants.append("Pasta Place")

Inserting: Use insert() to add an element at a specific index.

restaurants.insert(0, "Pasta Magic")

Removing Elements

Removing: Use remove() to remove an element by value.

restaurants.remove("Pasta Place")

Removing by Index: Use pop() to remove an element by index.

restaurants.pop(0)

'Pasta Magic'

Nested Lists

Definition: Lists containing other lists or tuples.
Accessing: Use nested indexing.

restaurant_data = [
    ["Pasta Place", 4.5, 3],
    ["Sushi Bar", 4.2, 1]
]
print(restaurants[0][1])  # Access the second element of the first list

Tuples

Definition: Ordered, immutable collections of items.
Creation: Use parentheses ().
Immutability: Once created, cannot be changed.
Memory Efficiency: Use less memory than lists.
Use Cases: Ideal for fixed data (e.g., restaurant location).

ratings = (4.5, 3.8, 4.2)
restaurant_info = ("Pasta Place", "Italian", 2020)

Loops

for Loops

Definition: Iterate over a sequence of items.
Structure:

for item in sequence:
    # code to execute for each item

Example:

treatments = ["Standard Drug", "New Drug A", "New Drug B"]
for treatment in treatments:
    print(f"Evaluating efficacy of {treatment}")

Evaluating efficacy of Standard Drug
Evaluating efficacy of New Drug A
Evaluating efficacy of New Drug B

Range in for Loops

Definition: Generate a sequence of numbers.
Structure:

range(start, stop, step)

Example:

for phase in range(5):  # 0 to 4
    print(f"Starting Phase {phase + 1}")

Starting Phase 1
Starting Phase 2
Starting Phase 3
Starting Phase 4
Starting Phase 5

for phase in range(1, 5):  # 1 to 4
    print(f"Starting Phase {phase}")

Starting Phase 1
Starting Phase 2
Starting Phase 3
Starting Phase 4

for phase in range(1, 5, 2):  # 1 to 4, step 2
    print(f"Starting Phase {phase}")

Starting Phase 1
Starting Phase 3

break and continue

break: Exit the loop.
continue: Skip the current iteration and continue with the next.

efficacy_scores = [45, 60, 75, 85, 90]
for score in efficacy_scores:
    if score < 50:
        continue
        print(f"Treatment efficacy: {score}%")
    if score >= 85:
        break

Tuple unpacking

Definition: Assign elements of a tuple to variables.
Structure:
Example:

restaurant_info = ("Pasta Place", "Italian", 2020)
name, cuisine, year = restaurant_info
print(name)
print(cuisine)
print(year)

Pasta Place
Italian
2020

while Loops

Definition: Execute code repeatedly as long as a condition is true.
Structure:

while condition:
    # code to execute while condition is True

Example:

phase = 1
while phase <= 5:
    print(f"Starting Phase {phase}")
    phase += 1

Starting Phase 1
Starting Phase 2
Starting Phase 3
Starting Phase 4
Starting Phase 5

Functions

Basic Function

Definition: Use the def keyword.
Structure:

def function_name(parameters):
    # code to execute (function body)
    return value  # Optional

Example:

def greet_visitor(name):
    return f"Welcome to the library, {name}!"

greet_visitor("Student")

'Welcome to the library, Student!'

Return Value

Definition: The value returned by a function.
Example:

def multiply_by_two(number):
    return number * 2

result = multiply_by_two(5)
print(result)

Note: If a function does not return a value, it implicitly returns None.

Default Parameters

Definition: Provide default values for function parameters.
Structure:

def greet_visitor(name="People"):
    return f"Welcome to the library, {name}!"

print(greet_visitor()) # Calls the function with the default parameter
print(greet_visitor("Tobias")) # Calls the function with a custom parameter

Multiple Parameters

Definition: Functions can have multiple parameters.
Structure:

def greet_visitor(name, age):
    return f"Welcome to the library, {name}! You are {age} years old."

print(greet_visitor("Tobias", 30))

String Methods

Definition: Methods are functions that are called on strings.
Structure:

string.method()

Common String Methods:
- .strip() - Removes whitespace from start and end
- .title() - Capitalizes first letter of each word
- .lower() - Converts to lowercase
- .upper() - Converts to uppercase
Example:

title = "the hitchhikers guide"
print(title.title())

The Hitchhikers Guide

title = "   the hitchhikers guide    "
print(title.strip())

the hitchhikers guide

Packages

Standard Libraries

Definition: Libraries that are part of the Python standard library.
Access: Import them using import.

import math
import random

For long package names, you can use the as keyword to create an alias.

import random as rd

To call a function from an imported package, use the package name as a prefix.

random_number = rd.random()
print(random_number)

0.39766127791648553

Installing Packages

Definition: Install packages using pip.

pip install package_name

If you are using Miniconda, you can use conda instead.

conda install package_name