Understanding Numerical Data Types in Python
Before diving into Python programming, it's crucial to understand numeric data types, as they are fundamental to many operations.
Python provides two primary numeric data types: integers (int) and floating-point numbers (float). These types are built-in, meaning Python can handle them directly without any additional setup. An integer is a numeric data type representing whole numbers without any decimal points, such as 1, 2, or 456566. A float is a numeric data type representing decimal numbers, like pi (3.14159265359) or Euler's number (2.71828).
Integer represents whole numbers you commonly encounter in your daily life, such as 1, 2, 45, or 456566.
On the other hand, floating numbers include values like pi (3.14159265359) and Euler's number (2.71828).
# Example of an integer
integer_number = 5
# Example of a floating number
float_number_pi = 3.14159265359
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Before diving into Python programming, it's crucial to understand numeric data types, as they are fundamental to many operations.
Python provides two primary numeric data types: integers (int) and floating-point numbers (float). These types are built-in, meaning Python can handle them directly without any additional setup. An integer is a numeric data type representing whole numbers without any decimal points, such as 1, 2, or 456566. A float is a numeric data type representing decimal numbers, like pi (3.14159265359) or Euler's number (2.71828).
Integer represents whole numbers you commonly encounter in your daily life, such as 1, 2, 45, or 456566.
On the other hand, floating numbers include values like pi (3.14159265359) and Euler's number (2.71828).
# Example of an integer
integer_number = 5
# Example of a floating number
float_number_pi = 3.14159265359
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