Python Variables and Data Types

Variables are the foundation of every program. They give meaningful names to the data your code works with — think of them as labeled containers that hold values in memory.

Python Variables and Data Types

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Key Takeaways

• A variable is a name that references a value stored in memory
• Python is dynamically typed — you don't declare types explicitly
• The type() function reveals the data type of any value
• Python ships with a rich set of built-in types covering text, numbers, collections, and more

Creating Variables

In Python, you create a variable simply by assigning a value with =:

# Variables are created on assignment — no type declaration needed
name = "Ada Lovelace"
age = 36
pi = 3.14159
is_programmer = True

Python figures out the type automatically. This is called dynamic typing.

Variable Naming Rules

Not every name is valid. Python enforces these rules:

1. Names can contain letters, digits, and underscores
2. Names cannot start with a digit — 1score is invalid, score1 is fine
3. No spaces — use underscores instead (my_variable, not my variable)
4. Names cannot be Python keywords like if, class, return, or True
5. Names are case-sensitive — Score, score, and SCORE are three different variables

# Valid names
user_name = "Alice"
total_score_2 = 98
_private_flag = True

# Invalid names (these would cause SyntaxError)
# 2nd_place = "Bob"    — starts with a digit
# my variable = 10     — contains a space
# class = "Math"       — 'class' is a reserved keyword

🖼️ Visual Suggestion: A quick-reference table of Python's reserved keywords.

Checking Types with type()

The built-in type() function tells you exactly what kind of data a variable holds:

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

y = "hello"
print(type(y))  # <class 'str'>

z = 3.14
print(type(z))  # <class 'float'>

Try it yourself — change the values below, then press Run to execute real Python in your browser:

name = "Ada Lovelace"
age = 36
pi = 3.14159
is_programmer = True

for value in (name, age, pi, is_programmer):
    print(value, "->", type(value))

Python's Built-in Data Types

Python provides a surprisingly rich collection of types out of the box. Here's the complete landscape:

Text and Boolean

Numeric Types

Collection Types

Other Notable Types

• range — represents an immutable sequence of numbers, commonly used in loops
• bytes / bytearray — raw binary data (immutable and mutable, respectively)
• memoryview — memory-efficient access to binary data without copying

Comprehensive Code Example

# Text
greeting = "Hello, Python!"
print(type(greeting))       # <class 'str'>

# Numbers
count = 100
temperature = 36.6
imaginary = 4 + 5j
print(type(count))          # <class 'int'>
print(type(temperature))    # <class 'float'>
print(type(imaginary))      # <class 'complex'>

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

# Collections
fruits = ["apple", "banana", "cherry"]       # list (mutable, ordered)
coordinates = (10.0, 20.0)                   # tuple (immutable, ordered)
unique_ids = {101, 102, 103}                 # set (mutable, unordered, unique)
profile = {"name": "Ada", "age": 36}         # dict (mutable, key-value pairs)

# Range and bytes
numbers = range(1, 11)       # represents 1 through 10
raw_data = b"hello"          # immutable bytes literal
print(type(numbers))         # <class 'range'>
print(type(raw_data))        # <class 'bytes'>

🖼️ Visual Suggestion: A diagram grouping Python data types into categories — numeric, sequence, mapping, set, and binary.

Dynamic Typing in Action

Because Python is dynamically typed, a variable can be reassigned to a completely different type:

value = 10          # int
value = "ten"       # now it's a str — no error
value = [10, 20]    # now it's a list

This flexibility is powerful but demands discipline. Use clear variable names so the intended type is always obvious.

Up next: we'll dive deeper into Python's most versatile data type — strings and their powerful built-in methods.