Module 3: Data Types

Float Data Type

INTERACTIVE CHEAT SHEET

The Concept

In Python, a float (floating-point number) is a number that contains a decimal point or uses scientific notation. It represents real numbers and is typically used when you need more precision than a whole number can provide. Floats in Python are usually implemented as double precision, giving them about 15 decimal places of accuracy.

Key Points

Floats represent real numbers: 3.14, -1.0, 0.0.
They contain a decimal point or scientific "e" notation.
Floats have limited precision (~15 decimal places of accuracy).
You can check a value's type using type(value), which returns <class 'float'>.

Python · Memory model

How Python stores a float in memory

A CPython float wraps a C double. The object header tracks metadata; the payload holds 8 bytes of floating-point bits.

Choose a float example

x = 1.0·32 bytes total · 24 metadata

Object layout (bytes)

Object header: type, ref count, and other metadata

8 data bytes: sign, exponent, and mantissa of the float

Simple value: x = 1.0

A float like 1.0 is stored as a fixed-size object: metadata for the object plus 8 bytes of IEEE 754 data.

Floats are immutable objects, just like ints and strings.
Different variables can reference the same float if they hold the same value.
The exact header layout is CPython-specific, but the mental model — header + data bytes — stays the same.

Core Concept Mastery • Python Visual Series Module

🔥Module 1: Python Setup & Basics

Module 2: Variables & Memory

Module 3: Data Types

Module 4: Operators

Module 5: Conditional Statements

Module 6: Control Statements

Module 7: Lists, Tuples, Sets & Dictionaries

Module 8: Functions

Module 9: Classes & Objects

Float Data Type

The Concept

Key Points

How Python stores a float in memory

Simple value: x = 1.0

Float Data Type

The Concept

Key Points

How Python stores a float in memory

Simple value: x = 1.0