Summary
This chapter introduces Python’s core numeric types—integers and floating-point numbers—explaining their representations, differences (including truthiness and precision), scientific notation, and readability enhancements such as underscores.

General domain of usage
Scientific computing

Numbers are everywhere in Python. You'll use two core numeric types most of the time: **integers** (`int`) for whole numbers and **floating-point numbers** (`float`) for decimals (including scientific notation like `1e-3`).


## Integer and Float Essentials

* **Integers (`int`)**: whole numbers such as `-2`, `0`, `7`, `456566`. Python supports arbitrarily large integers;
* **Floats (`float`)**: decimal values such as `2.5`, `3.14159`, `2.71828`, or scientific notation like `6.02e23`;
* **Truthiness**: `0` and `0.0` are `False`, any other `int/float` is `True` in boolean contexts.

## Scientific Notation

Scientific notation is a compact way to write very large or very small numbers using powers of ten. In Python, a number written with `e` means “multiply by 10 raised to a power”: for example, `1e-3` means $$1 × 10⁻³$$ (0.001), and `6.02e23` means $$6.02 × 10²³$$. Numbers written in this form are always treated as `float`.


# Basic numeric literals
n_int = 42
n_float = 3.14
n_sci = 1e-3   # 0.001

print(n_int, n_float, n_sci)

## Writing Large Numbers Readably

Humans often write `1,000,000` or `1 000 000`. Python doesn't allow commas or spaces inside numeric literals, use **underscores** for readability.

million = 1_000_000
print(million == 1000000)   # True

Floats are stored as binary fractions, tiny rounding differences are normal (e.g., `0.1 + 0.2` may not be exactly `0.3`). You'll handle rounding and formatting later.

Note

Which literal is valid in Python code for one million?

Pick the true statement about `int` and `float`.

A focused, beginner-friendly course on working with numbers in Python. Learn about integers, floats, arithmetic operations, type conversion, and how to avoid common pitfalls when handling numerical data.

Understanding Numeric Types

Integer and Float Essentials

Scientific Notation

Writing Large Numbers Readably

1. What is the type of `1e2`?

2. Which literal is valid in Python code for one million?

3. Pick the true statement about `int` and `float`.