In Python, the `float`

data type is used to represent decimal numbers or numbers with a fractional component.

Here are some examples of floats:

```
3.14
-0.001
2.71828
0.0
```

You can perform various operations on floats, just like with integers.

For example:

```
a = 3.14
b = 2.71
# Addition
sum_result = a + b # result will be 5.85
# Subtraction
difference = a - b # result will be 0.43
# Multiplication
product = a * b # result will be 8.5094
# Division
quotient = a / b # result will be 1.1589850746...
```

Floats can also represent very large or very small numbers using scientific notation.

For example:

```
big_number = 1.23e100 # 1.23 times 10 to the power of 100
small_number = 1.23e-5 # 1.23 times 10 to the power of -5
```

Keep in mind that due to the way floating-point numbers are represented in binary, there can be some precision issues when performing certain operations. This is a common source of errors in numerical computations. For critical applications that require precise calculations, you may need to use specialized libraries like `decimal`

or `numpy`

that provide more control over precision. To learn more, click here.