Variables Data Types and Operators¶

Variables¶

Python uses variables to store information that can be used later in a program. Think of a variable as a name tag attached to an object in memory — not the box itself, but the label stuck onto it.

🧱 Creating Variables¶

A variable is created when you assign a value to a name using the = sign.

name = "Chandravesh"
age = 31
revenue = 45000.75
is_active = True

You can later use these variables anywhere in your program:

print("Name:", name)
print("Age:", age)
print("Revenue:", revenue)
print("Active:", is_active)

🎯 What Really Happens in Memory¶

When you write:

x = 10

Python creates an object (10) in memory, and x is just a reference (a label) that points to that object.

If you do this:

y = x

Now both x and y point to the same object in memory.

x = 10
y = x

print(id(x))
print(id(y))

✅ The id() function shows that both have the same ID, meaning they point to the same memory location.

Now, if you change the object:

x = 20
print(y)

❗ y still points to the old object (10), because you changed what x points to, not the object itself.

💡 Analogy¶

Think of x and y as name tags stuck to a coffee mug. Both can point to the same mug ☕, but if x changes its tag to a new mug, y still remains attached to the old one.

Variables¶

A variable is created when you assign a value to a name using the = sign.

name = "Chandravesh"
age = 30
revenue = 45000.75
is_active = True

You can later use these variables anywhere in your program.

print("Name:", name)
print("Age:", age)
print("Revenue:", revenue)

✅ Naming Rules

• Must start with a letter or underscore (_)

• Can contain letters, numbers, and underscores

• Case-sensitive (name ≠ Name)

• Avoid using keywords like for, if, class, etc.

🧮 Data Types¶

Every value in Python has a type.

You can check a variable’s type with the built-in type() function.

x = 42
y = "Analytics"
print(type(x))  # <class 'int'>
print(type(y))  # <class 'str'>

⚙️ Operators in Python¶

Operators perform operations on variables and values.

Arithmetic Operators¶

Comparison Operators¶

Logical Operators¶

🔁 Type Conversion¶

You can change one data type to another using:

x = "100"
y = int(x)     # converts string to integer
z = float(x)   # converts string to float
print(type(y), type(z))

Why Naming Conventions Exist¶

Good naming makes code easier to read, debug, and share. Python follows certain rules and best practices:

• Variable names cannot be Python keywords (like class, if, for).

• They must start with a letter or underscore (_), not a number.

• They are case-sensitive (Name ≠ name).

These conventions help both humans and computers understand the code clearly!

class = "Business"
print(class)

class_name = "Business"
print(class_name)

🧠 Quick Practice Questions¶

• What is the difference between a variable and an object in Python?

• What will this code print and why?

  a = [1, 2, 3]
  b = a
  b.append(4)
  print(a)

• Predict the output:

  x = 5
  y = x
  x = 7
  print(y)

• Create variables to store:

• Your name, age, monthly income, and whether you are a student. Then print them in one line using:

print(name, age, income, is_student)

• Write a Python program that:

1. Takes two numbers a and b.

2. Prints their sum, difference, and product.

Example:

a = 10
b = 3
## your code here

• Predict the output without running the code:

x = 5
y = 10
print(x > 2 and y < 5)
print(x == 5 or y == 5)
print(not (x == y))

• Which of the following are valid variable names? a) 2price  b) _price  c) class  d) price2

• Predict the output:

  value = 5
  Value = 10
  print(value + Value)

• Identify the data types:

  a = 10
  b = "Python"
  c = 3.14
  d = True

• Find a reserved keyword using keyword.kwlist and try using it as a variable. What error do you get? Replace it with a meaningful name.

• Write a short Python snippet that calculates profit margin using variables with clear business-style names (cost_price, selling_price, profit_margin).

Exercises¶

Exercise 1¶

Write filter_and_square(nums) that returns squares of even integers from nums (ignore non-integers).

Exercise 2¶

Implement safe_divide_list(nums, denom) that divides each numeric n in nums by denom, skipping non-numeric entries and avoiding ZeroDivisionError.

Exercise 3¶

Create flatten_unique(list_of_lists) that flattens a nested list and returns unique values in sorted order.