Using a for loop with Python lists allows you to iterate through

each element in the list, one at a time.

This is a fundamental way to work with lists in Python,

making it easier to process or manipulate the elements.

1. Iterating Over List Items

You can use a for loop to access and perform operations on each item in the list.

Example:

fruits = ['apple', 'banana', 'cherry']
for fruit in fruits:
    print(fruit)

Output:

apple
banana
cherry

2. Using the range() Function

Sometimes, you want to iterate using the index of the items. You can use the range() function along with the len() function to achieve this.

Example:

fruits = ['apple', 'banana', 'cherry']
for i in range(len(fruits)):
    print(f"Index {i}: {fruits[i]}")

Output:

Index 0: apple
Index 1: banana
Index 2: cherry

3. Performing Operations on List Items

We can perform calculations, modifications, or any other operations on the elements.

Example:

numbers = [1, 2, 3, 4, 5]
squared_numbers = []
for num in numbers:
    squared_numbers.append(num ** 2)
print(squared_numbers)

Output:

[1, 4, 9, 16, 25]

4. Nested for Loops with Lists

When working with nested lists (lists within lists), use nested for loops.

Example:

matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
for row in matrix:
    for item in row:
        print(item, end=' ')

Output:

1 2 3 4 5 6 7 8 9

Overview

Use a for loop to iterate over each element in a list.

Access elements by index using range() .

max() Function in Python

The max() function in Python is used to find the maximum value in a sequence or among multiple values. It works with various data types, including numbers, strings, and more.

Return Value

The function returns:

• The largest item in the iterable.

• The largest of the provided arguments.

Examples

1. Maximum in a List

numbers = [10, 20, 30, 40, 50]
print(max(numbers))

Output

50

2. Maximum Among Multiple Values

print(max(3, 7, 2, 9))

Output

9

for loops and the range ( ) function in Python

For Loops in Python

A for loop in Python is used to iterate over a sequence

(like a list, tuple, string, or range) and execute a block of code

for each item in the sequence.

• variable: Takes the value of each item in the sequence, one by one.

• sequence: The data structure or iterable you want to loop over.

Example:

Looping Through a List

fruits = ['apple', 'banana', 'cherry']
for fruit in fruits:
    print(fruit)

Output:

apple
banana
cherry

The range() Function

The range() function generates a sequence of numbers, commonly used with for loops. It doesn't create a list but provides a range object that is iterable.

• start: The starting number (inclusive). The default is 0.

• stop: The ending number (exclusive). This is required.

• step: The increment (default is 1).

Examples of range()

1. Simple Range

    for i in range(5):  
        print(i)
   

   Output:

    0
    1
    2
    3
    4
   

2. Range with Start and Stop

    for i in range(2, 6):
        print(i)
   

   Output:

    2
    3
    4
    5
   

3. Range with Step

    for i in range(0, 10, 2): 
        print(i)
   

   Output:

    0
    2
    4
    6
    8
   

4. Range in Reverse

    for i in range(10, 0, -2):  
        print(i)
   

   Output:

    10
    8
    6
    4
    2
   

Key Points

1. For Loop: Iterates through each item in a sequence.

2. Range Function: Generates a sequence of numbers, which can be

   customized using start, stop, and step values.

3. Combination: Use range() with for loops for precise control over iteration.

   What’s the next milestone?

   On Day 6 of the 100 Days of Python, I will learn about Python functions and Karel.

The random module in Python is used to generate

random numbers or make random selections.

It is widely used for games, testing, and other

applications where randomization is needed.

Common Functions in the random Module

1.random()

Generates a random floating-point number between 0.0 (inclusive) and 1.0 (exclusive).

Example:

   import random
   print(random.random())

Output

0.483475829

2. randint(a, b)

Generates a random integer between a and b (both inclusive).

Example:

print(random.randint(1, 10))

Output

Random number between 1 and 10

3.uniform(a, b)

Generates a random floating-point number between a and b.

Example

print(random.uniform(1.5, 5.5))

Output

Random float between 1.5 and 5.5

Use Cases

. Games: Randomizing player turns or shuffling cards.

. Testing: Generating test data.

Important Note

The numbers generated by the random module are pseudo-random, meaning they are determined by an algorithm and are not truly random.

Understanding Offsets and Appending Items to the Lists

Understanding Offset (Index) in Lists

In Python, a list is an ordered collection of items, and each item has a position called an index or offset. The index starts at 0 for the first item in the list and increments by 1 for each item.

Key Points:

1. Indexing starts at 0:

   • First item: Index 0

   • Second item: Index 1

   • Last item: Index -1 (negative indexing)

2. Accessing items using an offset:

   • You can retrieve an item by specifying its index within square brackets ([]).

   • Example:

       fruits = ['apple', 'banana', 'cherry']
       print(fruits[0])  #Output: apple
       print(fruits[1])  #Output: banana
       print(fruits[-1]) #Output: cherry (last item)
     

3. Out of range:

Accessing an index that doesn’t exist in the list raises an IndexError.

Example:

    (fruits[5])  # Raises IndexError

Appending Items to Lists

In Python, appending items to a list means adding new elements to the end of an existing list. Python lists are dynamic, so you can easily modify their size by adding items.

How to Append Items to Lists

1. Using the append() Method

   The append() method adds a single item to the end of a list.

   It does not create a new list; it modifies the original list in place.

Example:

    numbers = [1, 2, 3]
    numbers.append(4)  # Adds 4 to the end of the list
    print(numbers)  # Output: [1, 2, 3, 4]

2. Appending a List as an Item

   • You can append an entire list as a single item. In this case, the appended list becomes a nested list.

Example:

    numbers = [1, 2, 3]
    numbers.append([4, 5])  # Adds a nested list
    print(numbers)  # Output: [1, 2, 3, [4, 5]]

3. Appending Items from Another Iterable

   Use the extend() method if you want to append multiple items from another iterable (like a list) to the current list.

   This adds the items individually, not as a nested list.

Example:

    fruits = ['apple', 'banana']
    fruits.extend(['cherry', 'orange'])  # Adds multiple items
    print(fruits)  # Output: ['apple', 'banana', 'cherry', 'orange']

1. Key Differences: append() vs extend()

   | Operation | Effect | Example | Result | | --- | --- | --- | --- | | append(item) | Adds item as a single element | list.append([4, 5]) | [1, 2, 3, [4, 5]] | | extend(iterable) | Adds each element from iterable | list.extend([4, 5]) | [1, 2, 3, 4, 5] |

When to Use append()

• When adding one item at a time.

• When you want to add a nested list.

When to Use extend()

• When adding multiple items from another iterable.

• When you want to merge lists.

By understanding these methods, you can effectively grow and manipulate Python lists to suit your program's needs.

IndexErrors and Working with Nested Lists

IndexErrors in Python

An IndexError occurs in Python when you try to access an element of a sequence

(such as a list, tuple, or string) using an index that is out of range.

This means the index is either greater than the last index of the sequence or

3. less than the negative of the sequence's length.

   ---

   What Causes IndexErrors?

   1. Accessing an Index Greater Than the Sequence Length:

      • If you try to access an index that is beyond the valid range, Python raises an IndexError.

        my_list = [1, 2, 3]
        print(my_list[3])  # IndexError: list index out of range

2. Using Negative Indices That Exceed the Range:

   • Negative indices count from the end of a sequence. If the negative index exceeds the sequence's length, an IndexError occurs.

        my_list = [1, 2, 3]
        print(my_list[-4])  # IndexError: list index out of range

3. Accessing an Empty Sequence:

   • An empty sequence (like an empty list) has no valid sequence.

        empty_list = []
        print(empty_list[0])  # IndexError: list index out of range

How to Avoid IndexErrors

Check the Length of the Sequence Before Accessing: Use the len() function to ensure the index is within the valid range.

1.  my_list = [1, 2, 3]
    index = 3
    if index < len(my_list):
        print(my_list[index])
    else:
        print("Index out of range!")
   

Examples of IndexErrors

Example 1: Accessing an Invalid Index

    fruits = ["apple", "banana", "cherry"]
    print(fruits[5])  # IndexError: list index out of range

Example 2: Negative Index Exceeding Range

    numbers = [10, 20, 30]
    print(numbers[-4])  # IndexError: list index out of range

Example 3: Empty List

    empty_list = []
    print(empty_list[0])  # IndexError: list index out of range

Key Takeaways

• Always ensure indices are within the sequence's valid range.

• Handle user inputs, dynamic indices, or uncertain data carefully to avoid unexpected errors.

• Use tools like len() and loops to work safely with sequences.

• Where My Learning Takes Me Next

  On Day 3 of the 100 Days of Python, I will learn about Python Loops.

if / else Statement :

If Statement: Checks a condition. If the condition is True,

the code inside the if block runs.

Else Statement: Runs if the if condition is False

Critical Points

The condition in the if the statement must be evaluated to True or False.

Indentation is crucial in Python; the code inside if or else must be indented.

Condition Check

Conditionals in Python to check a condition and tell the computer what to do in each case.

Example

if <this condition is true>:

<then execute this line of code>

What if the condition is false?

The else keyword is used to define a block of code that will execute if the condition checked in the if statement is false.

if cow can fly:

else:
    print("This is real life")

Comparator Operators

\> Greater than

< Less than

\>= Greater than or equal to

<= Less than or equal to

\== Equal to

!= Not equal to

Key Points

Conditional operators are used for comparisons.

They are often combined with if-else statements for decision-making.

They always return True or False.

List of Conditional Operators

Modulo Operator (%) in Python

The modulo operator (%) returns the remainder when one number is divided by another.

It’s commonly used in programming for tasks like finding even/odd numbers.

Example

result = a % b

a: Dividend (number being divided)

b: Divisor (number dividing)

result: Remainder after division

If a is divisible by b, the result is 0.
Example: 10 % 5 gives 0.

Nested if statement and elif statement

A nested if statement is an if statement inside another if statement.

It allows for checking a condition only if a previous condition is True.

This structure is useful when decisions are dependent on

Example

You can put if/else statements inside other if/else statements. This is known as nesting. e.g.

if maths_score >= 90:
    if english_score >= 90:
        print("You're good at everything")
    else:
        print("You're good at maths")
if english_score >= 90:
    print("You're good at english)

Output

You are good at everything

In this case, only when a student has over 90 in maths and English, get

You are good at everything.

Key point:

You can also haveif statements that don't have a paired else statement.

Elif Statement in Python

The elif statement (short for "else if") allows you to check multiple conditions.

If one condition is True, the corresponding block of code runs, and the

remaining conditions are skipped.

Example

marks = 85

if marks >= 90:
    print("Grade: A")
elif marks >= 80:
    print("Grade: B")
elif marks >= 70:
    print("Grade: C")
else:
    print("Grade: F")

Output

Grade: B

Key Differences:

Nested if: Used when one condition depends on another condition being True.

Elif: Used to check multiple independent conditions.

Combining Both:

You can use both nested if and elif in the same code.

age = 25
has_ticket = True

if age >= 18:
    if has_ticket:
        print("You can enter the event.")
    else:
        print("You need a ticket.")
elif age >= 13:
    print("You can enter with an adult.")
else:
    print("You are too young to enter.")

Output

You can enter the event.

Multiple if Statements

A nested if statement is an ifstatement placed inside another if or else block.

It allows for checking multiple conditions

age = 25
has_ticket = True
is_vip = False

if age >= 18:
    print("You are old enough to enter.")

if has_ticket:
    print("You have a ticket.")

if is_vip:
    print("You have VIP access.")

Output

You are old enough to enter.
You have a ticket.

Key Points About Multiple if Statements:

Each ifstatement is evaluated independently.
If multiple conditions are True, all their corresponding blocks will execute.

Order Matters:
Since all if statements are evaluated, and the order of conditions can impact the flow of the program.

Different from if-elif:

In if-elif, only one block of code runs when a condition is True.

In multiple if statements, more than one block can run.

When to Use Multiple if Statements:

When you check multiple conditions Independent.

When multiple conditions can be true simultaneously.

Logical Operators

Logical operators in Python are used to combine or modify

conditional statements. They return a Boolean value

(True or False)based on the logic of the conditions provided.

Types of Logical Operators

1. and (Logical AND)

Combines two conditions.

Returns True only if both conditions are True.

If either condition is False, it returns False.

2. or (Logical OR)

Combines two conditions.

Returns True if at least one condition is True.

Returns False only if both conditions are False.

3. not (Logical NOT)

Reverses the logical state of a condition.

If the condition is True, not makes it False, and vice versa.

When to Use Logical Operators

Use and when all conditions need to be True.

Use or when at least one condition needs to be True.

Use not to reverse the logic of a condition.

Truth Table for Logical Operators

Key Highlights

if/else Statements: Control the program's flow by executing code blocks based on conditions.

Comparator Operators: Enable comparisons like ==, !=, <, and >.

Nested if and elif: Handle dependent and independent conditions effectively.

Logical Operators: Combine conditions using and, or, and not.

What's next in my journey?

On Day 3 of the 100 Days of Python, I will learn about

Randomisation and Python lists.

Python has four basic primitive data types.

. Integers: These are whole numbers

Example: 1 5 -10 etc

. Strings: These are used for texts enclosed in Quotes

Example:

name = "Muniba"

. Floating Point Numbers (Floats): These are numbers with a decimal point.

Example: 4.13, 3.158, -0.6 etc

.Booleans: These are used for logical decisions.

Example: True or False

These can only have two possible values.

Type Error, Type Checking, and Type Correction

Type Error :

A type error is a programming error that

occurs when you put the value of the wrong data type.

Because some operations are only made for specific data types.

Len( ) Function: It returns the number of characters in a string

Example

1. Scenario causing a TypeError

len(12345)

Output

TypeError

Len() function does not like working with integers we end up with a TypeError and it breaks our code and gives us TypeError.

2. This is the correct application of len( ) function

print(len("hello"))

Output

5

An Additional Case

We have some sort of fancy machine that is going to take potatoes into fries.

it is probably going to have to peel the potato, wash the potato, cut it up, fry it,

and finally return it in the form of fries.

Now let’s say we decided to give it a rock instead of a potato and we just pass it through the function

then we are going to get an error

Type Checking:

Type checking is the checking of Data types whether it is

integer, floating, strings, and booleans.

print(type("abc"))
print(type(123))
print(type(3.14))
print(type(True))

Output

<class ‘str’>

<class ‘int’>

<class ‘float’>

<class ‘bool’>

These are the major Primitive Data Types.

Type Conversion

Type conversion in Python is the process of converting one data type to another.

It is helpful when you need to perform operations between different data types.

You can convert data into different data types using special functions.

Example

float()

int()

str()

Mathematical Operations in Python

Python provides a wide range of mathematical operations that are used by programmers.

Order of Operations (PEMDAS)

• Python follows the standard mathematical order of operations:

  1. Parentheses ()

  2. Exponents **

  3. Multiplication/Division * /

  4. Addition/Subtraction + -

Numbers Manipulations And F Strings in Python

Number Manipulation

Number manipulation is used to modify, and transform numbers. It is done by flooring.

Flooring a Number

You can floor a number or remove all decimal places using int( )

functions that convert a floating number with decimal places into an integer.

Example

int(3.7483) becomes 3

Rounding a Number

If you want to round a decimal number to the nearest whole number using the mathematical way

where anything over .5 rounds up and anything below rounds down.

Then you can use the Python round() function.

round

(3.738492)

Output

4

round

(3.14159)

Output

3

Assignment Operators

Assignment operators such as the addition assignment operator +=

will add the number on the right to the original value of the variable

on the left and assign the new value to the variable.

+=

-=

*=

`/=`

f-Strings

In Python, we can use f-strings to insert a variable or an expression into a string.

age = 12

print(f"I am {age} years old")

Output

I am 12 years old

Final project

The final project of today is to make a Tip Calculator.

Tip Calculator

We are going to build a Tip Calculator.

print("Welcome to the tip calculator!")
bill = float(input("What was the total bill? $"))
tip = int(input("What percentage tip would you like to give? 10 12 15 "))
people = int(input("How many people to split the bill? "))
tip_as_percent = tip / 100
total_tip_amount = bill * tip_as_percent
bill_per_percent = totall_bill / people
final_amount = round(bill_per_person, 2)
print(f"Each person should pay: ${finalamount}")

Output

Welcome to the tip calculator!

What was the total bill? $153.45

What percentage tip would you like to give? 10 12 15 15

How many people to split the bill? 5

Each person should pay: $35.29

What will I Learn Next?

On Day 3 of the 100 Days of Python, I will learn about Control Flow and Logical Operators.

Printing to the Console in Python

print() function is used to display the Information to the user

For Example. Texts, Numbers, and output or the result of any calculations.

It is also used to debug code and make a program interactive by showing messages.

Example

print("Today I learned!")

Output

Today I Learned!

Text is always inside the strings(““)otherwise the syntax error is shown on the screen.

The reason for putting up strings inside the parentheses is to tell the computer that it is not the code it is just text.

String Manipulation

String manipulation in Python refers to performing various operations on strings, such as altering their contents, extracting parts of them, or checking certain properties.

Python makes string manipulation easy with a variety of functions.

Example

1. \n character separates one line into two separate lines.

Print("Hello Muniba!\nHello Muniba!")

Output

Hello Muniba!

Hello Muniba!

2. Spacing

print ("Hello" + " " +"Muniba!")

Output

Hello Muniba!

Code Intelligence

Code intelligence in Python refers to the advanced tools, techniques, and features available to help developers write, understand, and maintain Python code more efficiently.

It involves features like auto-completion, error detection, intelligent suggestions, and navigation, which can help developers code faster and with fewer mistakes.

1. Code Navigation

Code navigation allows you to easily navigate to specific parts of your code. It includes features such as go to definition, find references and peek definition. This is useful for large codebases or when working with external libraries.

Example: If you click on a function name in your Python code, the IDE can take you to its definition, even if it’s in a different file or module.

2. Auto-Completion and Code Suggestions

Auto-completion or code suggestions help developers by predicting and completing the code they are typing. Python-specific features such as methods or classes from libraries are suggested as you type, saving time and preventing errors.

3. Error Detection

Code intelligence tools in Python can identify syntax errors while you are coding.

They alert you to issues in the code such as missing parentheses, incorrect function calls, or undefined variables, before running the code.

Example: If you forget to close a bracket in a function call or assign a variable that isn't defined, code intelligence will highlight the error in real time.

The Python Input Function

In Python, the input()function is used to take input from the user something like a name or any other piece of information.

It allows you to interact with the program by prompting the user to enter some data, and then the program processes that data and shows the next result of that data.

How it works:

1. The input()function displays the prompt to the user (if provided).

2. The program waits for the user to enter some data through the keyboard.

3. Once the user enters the data and press Enter, the input() function returns the input as a string.

Example

name = input("Enter your name: ")

print("Hello " + name + "!")

Output

Enter your name: Muniba

Hello Muniba!

Python Variables

In Python, variables are used to store data values that can be used later in the program.

They act as "containers" for holding data, such as numbers, strings, or more complex data types like lists, dictionaries, and objects.

Variable Namings Rules :

A variable name must start with a letter (a-z, A-Z) or an underscore ( _ ), followed by letters,

numbers (0-9), or an underscore. It cannot be a keyword (reserved word in Python)

like if, for, class, etc

Final project

At the end of the day, we will make a Band name generator Like I want to create or

someone else wants to create their Band name so let’s take a look at the final project of today

Band Name Generator

print("Welcome to Band Name Generator")

city = input("Which city did you grow up in?")

pet= input("What is the name of your pet?")

print("Your Band name could be: "+ city + " " +pet)

Output

Welcome to Band Name Generator

Which city did you grow up in? Haripur

What is the name of your pet? Cat

Your band name could be: Haripur Cat

The Problems I Faced Today

Variable naming in Python follows certain rules,

such as avoiding reserved keywords,

starting with letters or underscores, and using only letters, numbers, and underscores.

By practicing these rules repeatedly, you can improve your ability to name variables correctly and consistently.

Most Important Things I learned

Indentation is very important in Python.

If the code is not correctly indented it will show you an Indentation Error.

I will Work on it More

I will practice more on the variable naming and the input()function.

Because it was a bit difficult for me.

What will I Learn Next?

I will learn data types and how to manipulate strings in Day 2 of 100 Days.

What the Course Includes

This course is packed with so much to learn! Some of the things I’ll be working on are:

• Python programming basics and advanced concepts.

• Creating websites with Flask.

• Working with data using Pandas and NumPy.

• Learning about Machine Learning with Scikit-Learn.

• Front-end basics like HTML, CSS, and Bootstrap.

• Using Git and GitHub for version control.

• Deploying projects with Heroku and GitHub Pages.

Each day focuses on a project, so by the end of the course, I’ll have built 100 small Python projects! That’s so exciting because I’ll not only learn the theory but also create something cool every day.

Why I Picked This Course

I’ll be starting my B.S. in Artificial Intelligence soon, and Python is super important for AI. I wanted a course that’s beginner-friendly but also helps me build a strong foundation for the future. This one stood out because it’s fun, practical, and covers a lot of useful topics.

What You’ll Find on This Blog

I’ll be writing about my experience with this course, sharing what I learned, what I struggled with, and how I overcame challenges. I’ll post updates regularly, so if you’re just starting out or thinking about learning Python, I hope my blog will help and inspire you.

I can’t wait to see where this journey takes me. Stay tuned for updates!