Python Basics: Variables and Data Types in Depth 🌟

🔑 Understanding Variable Assignment

In Python, variables act as labels to store values, making your code organized and reusable. Assigning values is straightforward:

a = 3  # Variable 'a' now holds the value 3

Now, whenever you reference a, Python knows it represents 3. For example:

b = 4
print(a + b)  # Output: 7

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🧠 Variable Types and Reassigning Values

Python variables are dynamically typed, meaning the type is determined by the value you assign. For instance:

a = 3
print(type(a))  # Output: <class 'int'>

You can even reassign a different type to the same variable:

a = "Shivank"
print(type(a))  # Output: <class 'str'>

This flexibility is powerful but requires careful tracking of variable usage to avoid unexpected behavior.

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📋 Data Types Overview

Here’s a recap of common Python data types that variables can hold:

1️⃣ Integers:

Whole numbers without decimals:

age = 25
print(type(age))  # Output: <class 'int'>

2️⃣ Floats:

Numbers with decimals:

pi = 3.14159
print(type(pi))  # Output: <class 'float'>

3️⃣ Strings:

Text enclosed in single or double quotes:

name = "Shivank"
print(type(name))  # Output: <class 'str'>

4️⃣ Booleans:

True or False values:

is_active = True
print(type(is_active))  # Output: <class 'bool'>

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🔤 Strings: Assigning and Combining

Strings are versatile and easy to assign:

greeting = "Hello"
print(greeting)  # Output: Hello

To combine strings, use the + operator:

first_name = "Shivank"
last_name = "Agarwal"
full_name = first_name + " " + last_name
print(full_name)  # Output: Shivank Agarwal

Tip: Be consistent with quotes. Mixing single and double quotes like greeting = 'Hello" will throw an error.

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📝 The Importance of Meaningful Variable Names

Readable code is maintainable code. Instead of using generic names like x or y, use descriptive variable names:

person_name = "Shivank"
person_age = 25

This practice helps others (and future you!) understand the purpose of each variable at a glance.

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🔄 Overwriting Variables

Python allows overwriting variables, even with different data types:

a = 3
print(a)  # Output: 3

a = "Python"
print(a)  # Output: Python

Caution: Overwriting variables unintentionally can lead to confusion, especially in larger projects.

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➕ Performing Operations on Variables

Python’s flexibility extends to variable operations. For numbers:

x = 10
y = 20
result = x + y
print(result)  # Output: 30

For strings:

word1 = "Data"
word2 = "Science"
phrase = word1 + " " + word2
print(phrase)  # Output: Data Science

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🔍 Debugging with the type() Function

To avoid confusion, you can check the type of a variable using the type() function:

x = 42
print(type(x))  # Output: <class 'int'>

x = "Hello"
print(type(x))  # Output: <class 'str'>

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🛠️ Practical Example

Here’s a combined example to reinforce these concepts:

# Assigning values
name = "Alex"
age = 30
is_coding = True

# Performing operations
message = name + " is " + str(age) + " years old."
print(message)  # Output: Alex is 30 years old.

# Checking types
print(type(age))        # Output: <class 'int'>
print(type(is_coding))  # Output: <class 'bool'>

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🚀 Key Takeaways

• Variables in Python hold values and make code manageable.

• Python automatically infers a variable’s data type, but type() helps you confirm it.

• Use descriptive names for clarity and maintainability.

• Python allows reassigning variables, even with different types.

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Next Steps 🔮

In the next section, we’ll dive into control structures like loops and conditionals, unlocking Python’s full potential for building dynamic and interactive programs. Stay tuned! 😊