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