Most of the numeric types in Python are pretty typical and will probably sound familiar if you’ve used almost any other programming language in the past. In this article, I will introduce you to all the numeric data types in Python.

## Numeric Data Types in Python

The Numeric data types can be used to track your bank balance, distance to March, the number of visitors to your website, and just about any other numerical quantity.

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In Python, numbers are not a single type of object, but a category of similar types. Python supports the usual number types (for example, integers and floating points), as well as literals to create numbers and expressions to process them.

Also, Python provides more advanced numerical programming support and objects for more advanced work. A comprehensive inventory of numeric data types and data structures in Python includes:

- Integer and floating-point
- Complex numbers
- Decimals
- Fractions
- Sets
- Booleans
- Built-in functions and modules: round, math, random
- External Libraries

Among its basic types, Python provides integers, which are positive and negative, and floating-point numbers, which are numbers with a fractional part. Python also allows us to write integers using hexadecimal, octal, and binary literals; offers a complex number type and allows integers to have unlimited precision, they can grow to have as many digits as your memory space allows.

The table below shows how all the above mentioned numerical data types look like while written in a program:

Numeric Data Types | Interpretation in Python |
---|---|

Integers | 12, -2, 66666 |

Floating-point | 1.22, 3.14e-10 |

Octal, hex, and binary literals | 0o177, 0x9ff, 0b101010 |

Complex numbers | 3+4j, 3.0+4.0j |

Sets | set(‘spam’), {1, 2, 3, 4} |

Decimal | Decimal(‘1.0’) |

Fraction | Fraction(1, 3) |

Boolean types | bool(X), True, False |

I hope you liked this article on the types of Numerical Data Types in Python programming language. Feel free to ask your valuable questions in the comments section below.