How Can I Precisely Limit Floating-Point Numbers to Two Decimal Places in Python?

Limiting Floats to Two Decimal Points: Floating-Point Imprecision and Alternative Solutions

Encountering discrepancies between expected and displayed floating-point values is a common issue faced by developers. In Python, the code provided aims to round the value of 'a' to 13.95 but produces a slightly different result due to the limitations of floating-point representation.

Floating-point numbers are used to represent real numbers in a binary computer system. However, not all numbers can be represented with full precision, leading to rounding errors. In the case of 'a', the rounded value is the same as the original value because the computer stores it as a binary fraction that cannot exactly represent 13.95.

Python's double precision floating-point type uses 53 bits of precision, while regular floats have 24 bits. This means that the precision of floating-point numbers is limited to 16 decimal digits for double precision and 8 decimal digits for regular floats.

To address this issue, several approaches can be considered:

Display Formatting

To display 'a' with only two decimal places, use string formatting techniques such as:

print("%.2f" % a)  # Output: 13.95
print("{:.2f}".format(a))  # Output: 13.95

Decimal Type

If exact precision is required, consider using the decimal type from the decimal module:

import decimal
decimal.Decimal('13.95')  # Output: Decimal('13.95')

Integer Representation

For currency values where accuracy is required only up to two decimal places, use integers to store values in cents and divide by 100 to convert to dollars:

value_in_cents = 1395  # Store value as an integer
value_in_dollars = value_in_cents / 100  # Output: 13.95

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