Chapter: Variables and Data Types in Python

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1. Variables in Python

1.1 What Are Variables?

Variables are names used to store data values. Think of a variable as a container for data. You can assign, modify, and use variables throughout your program.

1.2 Variable Naming Rules

Here are the official rules for naming variables:

1. Variable names can only contain letters, numbers, and underscores (_).

2. They must not start with a number.

3. Variable names are case-sensitive (age and Age are different variables).

4. Reserved words (like if, else, while, etc.) cannot be used as variable names.

1.3 Good Practices for Naming Variables

• Use descriptive names (e.g., user_name instead of x).

• Use snake_case for variables (e.g., first_name).

• Keep names consistent.

1.4 Assigning Values to Variables

You can assign values to variables using the = operator:

x = 5      # Integer
name = "Alice"  # String
is_logged_in = True  # Boolean

Multiple Assignments

You can assign multiple variables in one line:

a, b, c = 1, 2, 3  # a=1, b=2, c=3
x = y = z = 0  # x, y, z all equal 0

Reassigning Variables

Variables in Python are dynamic, meaning their value and type can be reassigned.

x = 42
x = "Now I'm a string"

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2. Data Types in Python

Python has several built-in data types. These are broadly categorized into numeric, text, sequence, set, mapping, and boolean types.

2.1 Numeric Data Types

Integer (int)

• Whole numbers, positive or negative, with no decimal points.

• Unlimited precision (can store very large numbers).

Example:

age = 21
negative = -99
large_number = 12345678901234567890

Float (float)

• Numbers with decimal points or in exponential form.

Example:

pi = 3.14159
e = 2.718e3  # Scientific notation (equals 2718.0)

Complex (complex)

• Numbers with a real and imaginary part.

Example:

z = 3 + 4j  # 3 is the real part, 4j is the imaginary part

Numeric Type	Example	Notes
int	42, -3	No decimal places.
float	3.14, -2.71	Has decimals.
complex	3 + 4j	Imaginary numbers.

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2.2 Text Data Type

String (str)

• A sequence of characters enclosed in single, double, or triple quotes.

Examples:

greeting = "Hello, World!"
single_quote = 'Python is fun'
multi_line = """This is
a multiline
string."""

Tricks & Precautions:

• Strings are immutable. You can’t change their contents directly.

• Use escape sequences (, , etc.) to include special characters.

escaped = "He said, \"Python is awesome!\""

Common String Operations:

Operation	Example	Result
Concatenation	"Hello " + "World"	"Hello World"
Repetition	"A" * 5	"AAAAA"
Slicing	"Python"[0:3]	"Pyt"
Length	len("Hello")	5

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2.3 Boolean Data Type

Boolean (bool)

• Represents True or False.

Example:

is_active = True
has_errors = False

Booleans are often used in conditions:

if is_active:
    print("The user is active.")

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2.4 Sequence Data Types

List

• An ordered, mutable collection.

Example:

fruits = ["apple", "banana", "cherry"]

Key Methods:

Method	Example	Description
append()	fruits.append("grape")	Add an item to the end.
remove()	fruits.remove("banana")	Remove an item.
sort()	fruits.sort()	Sort items.

Tuple

• An ordered, immutable collection.

Example:

coordinates = (10, 20)

Range

• Represents a sequence of numbers.

Example:

nums = range(5)  # 0, 1, 2, 3, 4

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2.5 Mapping Data Type

Dictionary (dict)

• Stores key-value pairs.

Example:

user = {"name": "Alice", "age": 25}

Operation	Example	Result
Access Value	user["name"]	"Alice"
Add Key-Value	user["city"] = "Paris"	Adds new key-value.
Delete Key	del user["age"]	Removes "age".

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2.6 Set Data Type

Set

• An unordered, unique collection.

Example:

numbers = {1, 2, 3, 4, 4}  # Output: {1, 2, 3, 4}

Key Methods:

Method	Example	Description
add()	numbers.add(5)	Add an element.
remove()	numbers.remove(3)	Remove an element.

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2.7 NoneType

Represents a variable with no value.

nothing = None

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3. Type Conversion

Convert between data types using built-in functions:

• int(): Convert to integer.

• float(): Convert to float.

• str(): Convert to string.

Example:

x = "123"
y = int(x)  # Converts string to int

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4. Tricks and Precautions

1. Dynamic Typing: Be cautious with changing variable types, as it may lead to bugs.

   x = "5"
   x = x + 2  # Error: Can't add str and int

2. Immutable vs. Mutable:

   • Immutable: str, tuple.

   • Mutable: list, dict, set.

3. Copying Data:

   • Use copy() for mutable types to avoid unintended changes.

   original = [1, 2, 3]
   copy = original.copy()

4. Avoid Shadowing Built-ins: Don’t use names like list, str, or input as variable names.

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Summary Table: Data Types in Python

Category	Type	Examples	Notes
Numeric	int	1, -3, 42	Whole numbers.
	float	3.14, -0.01	Numbers with decimals.
	complex	3 + 4j	Real + imaginary parts.
Text	str	"hello", 'world'	Immutable sequences of chars.
Sequence	list	[1, 2, 3]	Mutable, ordered collection.
	tuple	(1, 2, 3)	Immutable collection.
	range	range(5)	Sequence of numbers.
Set	set	{1, 2, 3}	Unordered, unique collection.
Mapping	dict	{"key": "value"}	Key-value pairs.
Boolean	bool	True, False	Logical values.
NoneType	None	None	Represents no value.

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