`round()`

The built-in round() function takes a numeric argument and returns it rounded to a specified number of decimal places. For the built-in numeric types, this rounding operation uses the round half-to-even strategy, which can yield results that may initially seem counterintuitive, such as rounding 2.5 to 2:

>>> round(2.5)
2

`round()` Signature

round(number, ndigits=None)

Arguments

Argument	Description	Default Value
`number`	The number to be rounded.	Required argument
`ndigits`	The number of decimal places to round to. If omitted, it rounds to an integer.	`None`

Return Value

Returns a number rounded to the specified number of decimal places.
Returns an integer if ndigits is omitted or None. Otherwise, the return value has the same type as number. For example, rounding a floating-point number returns a float, even when ndigits is zero or negative.
For any other object, round() delegates to that object’s __round__() method, so custom classes can support rounding by implementing it.

`round()` Examples

With a single argument to round to the nearest integer:

>>> round(1.5)
2

With two arguments to round to one decimal place:

>>> round(1.64, 1)
1.6

`round()` Common Use Cases

The most common use cases for the round() function include:

Rounding floating-point numbers for presentation purposes.
Rounding monetary values for display, though exact monetary arithmetic calls for the decimal module.
Reducing the precision of floating-point arithmetic results.

`round()` Real-World Example

Suppose you’re handling a list of product prices and want to round them to two decimal places for display on a web page:

>>> prices = [19.995, 20.005, 10.5, 5.678]
>>> rounded_prices = [round(price, 2) for price in prices]
>>> rounded_prices
[20.0, 20.0, 10.5, 5.68]

In this example, round() helps you format the prices to two decimal places, making them suitable for display in a financial context.

Tutorial

How to Round Numbers in Python

In this tutorial, you'll learn what kinds of mistakes you might make when rounding numbers and how you can best manage or avoid them. It's a great place to start for the early-intermediate Python developer interested in using Python for finance, data science, or scientific computing.

intermediate best-practices python

For additional information on related topics, take a look at the following resources: