Back to Data Types, firstly by looking at Numbers!

In Python, numbers are primarily represented by two data types: `int`

for integers (whole numbers) and `float`

for floating-point numbers (numbers with decimal points).

This distinction helps in organizing data more precisely and is a basic concept that beginners need to understand.

### Integers (`int`

)

In Python, an integer is any whole number, positive or negative, without a decimal point. This includes numbers like 5, -3, or 2048.

All numbers in Python are written just as they are:

```
5 # An example of an integer
-3 # Another example of an integer
2048 # And another example of an integer
```

### Floating-Point Numbers (`float`

)

Floating-point numbers, or floats, are numbers that have a decimal point. They can be used to represent fractions, decimals, or precise measurements. Positive numbers, negative numbers, and zero can all be represented with a float.

Here's how you write floats in Python:

```
3.14 # An example of a decimal
-0.001 # Another example of a decimal
0.0 # Yet another example of a decimal
```

Python also supports scientific notation with floats, which is handy for expressing very large or very small numbers:

```
5.972e24 # Earth's mass in kilograms
-1.602e-19 # Charge of an electron in coulombs
```

## Why Python's Number Types Matter

Understanding the distinction between integers and floats in Python is crucial for precision in calculations, especially in scientific and financial applications where the distinction can affect results. Knowing when to use each type will help you manage data more effectively and avoid common programming errors.