Python round() Function Explained with Practical Examples

Python round() Function Explained

The round() built‑in is a staple for numerical work in Python. It returns a value rounded to a specified number of decimal places, defaulting to the nearest integer when no precision is provided.

Syntax

round(number, ndigits=None)

• number – The numeric value to round.
• ndigits – Optional; the number of decimal places to keep. If omitted, the result is an integer.

Return Value

When ndigits is omitted, round() returns an int. If ndigits is supplied, the result is a float rounded to that precision.

Rounding Rules

• If the digit following the target place is 5 or greater, the value is rounded up.
• If it is less than 5, the value is truncated at the specified precision.

Why Rounding Matters: A Real‑World Example

In financial markets, rounding can influence millions of dollars in trading. For instance, the Vancouver Stock Exchange in 1982 truncated trade prices to three decimal places, leading to a cumulative monthly loss of about 25 points. Rounding instead of truncating yields far tighter results.

# Example: Truncating vs. Rounding
import random

def truncate(num):
    return int(num * 1000) / 1000

arr = [random.uniform(0.01, 0.05) for _ in range(1_000_000)]

# Truncation
sum_truncate = 0
for val in arr:
    sum_truncate = truncate(sum_truncate + val)

# Rounding
sum_round = 0
for val in arr:
    sum_round = round(sum_round + val, 3)

print("Truncated sum:", sum_truncate)
print("Rounded sum:", sum_round)

The truncated total can deviate by hundreds of units, whereas rounding keeps the deviation to a fraction of a unit.

Common Use Cases

Rounding Floating‑Point Numbers

# Basic rounding
print(round(10.60))        # 11
print(round(10.40))        # 10
print(round(10.3456, 2))   # 10.35
print(round(10.3445, 2))   # 10.34

Rounding Integers

print(round(15))  # 15

Rounding Negative Numbers

print(round(-2.8))   # -3
print(round(-1.5))   # -2

Rounding Numpy Arrays

import numpy as np
arr = [-0.341111, 1.455098989, 4.232323, -0.3432326, 7.626632, 5.122323]
print(np.round(arr, 2))  # [-0.34  1.46  4.23 -0.34  7.63  5.12]

Using the Decimal Module for Precision

The decimal module offers finer control over rounding modes.

import decimal
num = decimal.Decimal('15.456')
print(num.quantize(decimal.Decimal('0.00'), rounding=decimal.ROUND_HALF_UP))  # 15.46

Key Takeaways

• Use round(number, ndigits) for standard rounding.
• Omitting ndigits returns an integer; providing it returns a float.
• For critical financial or scientific calculations, consider decimal for deterministic rounding.