Computer programs need to track numberic data every single day. You may want to track balances in bank accounts, scientific numbers, or just counters. Python gives us a wide variety of numeric processing types. Here are some of the more common ones:
Integers are whole numbers that are either positive or negatives. Unlike langues such as Java or C++ (or Python 2.x) Python does not distinguish between regular and long integers. Here are some examples of declaring integers
positiveNumber = 123456 negativeNumber = -111
Floating Point Numbers
Floating point numbers are numbers that have decimal points or numbers in scientific notations. They can be positive or negative.
dollar = 3.15 pi = 3.14159 sci = 8.2e10
Octal, hex, binary
Here are examples of numbers in octal, hexadecimal, and binary numbers.
oct = 0o237 hex = Ox9F binary = Ob10011111
Decimals and Fractions
Python provides us with Decimal and Fraction data types which maintainer percision with decimal points. A loss of percision may not get noticed in trival programs, but when working with big datasets, the loss of percision can introduce major bugs in the program.
d = Decimal('1.59') f = Fraction(1, 3) # Numerator / denominator
Booleans hold true and false values.
b = True f = False
For more information
You can learn more by visiting the python documentation.