Python Variables and Data Types: A Practical Introduction

Imagine you're shipping a package. You fill out a label that asks for the weight. You write "heavy" instead of a number. The shipping system crashes — it can't calculate a price from the word "heavy."

That's exactly the kind of problem data types solve in programming. Types tell Python whether something is a number, a piece of text, a true/false answer, or nothing at all. Getting this right is the difference between code that works and code that explodes.

In the previous tutorial, you learned how to create variables and work with strings and numbers. Now we're going deeper. You'll meet every core data type in Python, learn how to check and convert between them, and avoid the most common type-related bugs.

A data type is a label that tells Python what kind of value something is. It determines what operations you can perform on that value.

Think of it like containers in a kitchen. A measuring cup holds liquids. A scale weighs solids. You wouldn't pour flour into a measuring cup and expect an accurate weight. Each container is designed for a specific kind of thing.

Python has five core data types you'll use every day:

The type() function is your best friend when working with data types. It tells you exactly what kind of value you're dealing with. When your code isn't working, checking types is usually the fastest way to find the problem.

Python has two types of numbers: integers (int) for whole numbers and floats (float) for decimals. Most of the time, you don't need to think about the difference. But sometimes it really matters.

Use integers when something is always a whole number — like counting people, tracking scores, or indexing a list. Use floats when you need precision — like measuring temperature, calculating percentages, or working with money.

Big numbers are hard to read. Is 1000000 one million or ten million? Python lets you use underscores as visual separators. Python completely ignores the underscores — they're just for your eyes.

Here's something that surprises almost everyone the first time they see it. Try running this code:

You expected 0.3, but you got 0.30000000000000004. This isn't a Python bug. Every programming language has this problem.

Computers store numbers in binary (1s and 0s). Some decimal numbers, like 0.1, can't be represented perfectly in binary — just like 1/3 can't be written perfectly as a decimal (0.333333... goes on forever).

One more important detail: regular division (/) always produces a float, even when both numbers are integers and the result is a whole number.

A boolean is the simplest data type in Python. It can only be one of two values: True or False. That's it.

Booleans are like light switches — on or off, yes or no. They're the foundation of every decision your code makes. Every if statement, every while loop, every comparison boils down to a boolean.

Every value in Python can be treated as a boolean. Some values count as True (called "truthy") and some count as False (called "falsy"). You can check any value by passing it to bool().

None is Python's way of saying "nothing here." It's not zero. It's not an empty string. It's the complete absence of a value.

Think of a form with a "middle name" field. If someone leaves it blank, that's different from writing the number 0 or an empty string "". They just don't have a middle name. That blank field is None.

Always use is None or is not None to check for None. Don't use ==. This is a Python convention backed by a real technical reason.

You'll see None used as a default value in functions all the time. It's a clean way to say "this argument is optional."

Python gives you two tools for checking types: type() and isinstance(). They look similar but serve different purposes.

type() tells you the exact type of a value. It's great for debugging — when something isn't working, checking the type often reveals the problem immediately.

isinstance() checks if a value is of a certain type (or one of several types). It's the preferred way to check types in real code because it works with inheritance and is more readable.

Here's a fun fact: booleans are actually a subclass of integers in Python. True is secretly 1 and False is secretly 0.

Sometimes you have a value in one type but need it in another. A user types their age into a form — it arrives as the string "25", but you need the integer 25 to do math. Python gives you built-in functions to convert between types.

Not every conversion works. Python will crash with a ValueError if you try to convert something that doesn't make sense.

Converting to bool() follows the truthy/falsy rules we covered earlier:

Python has some convenient shortcuts for working with variables that most other languages don't have. These aren't just clever tricks — professional developers use them every day.

You can assign values to multiple variables on a single line. This is especially nice when you have a group of related values.

In most languages, swapping two variables requires a temporary variable. Python has a cleaner way.

The line a, b = b, a works because Python evaluates the entire right side first (b, a becomes 2, 1), and then assigns those values to the left side. No temporary variable needed.

Time to put your knowledge to the test! These exercises cover everything from this tutorial. They go from easiest to hardest.

Remember: struggling is learning. Try each exercise before peeking at hints. Read error messages carefully — they usually tell you exactly what went wrong.

In the next tutorial — [Numbers and Math](/python/numbers-and-math) — you'll dive deeper into Python's number system. You'll learn about the math module, rounding strategies, number formatting, and how to build programs that crunch numbers like a pro.