# What is Python round() Function?

Python `round()`

is a built-in function that you can utilize to `round`

a given number according to your specified precision. When you use this function, you’re able to control how many `decimal`

places the number should be `rounded`

to. This is helpful for achieving the desired level of accuracy in your calculations or for presenting data in a more understandable format.

To get a better understanding, imagine you’re a chef at a popular restaurant, and you need to calculate ingredient measurements. The `round()`

function becomes your culinary assistant, allowing you to `round`

quantities to the desired `decimal`

places. Its purpose is to provide accurate and presentable representations of numbers in your code.

With a foundational grasp of the Python `round()`

function, let’s progress and delve into its syntax and parameters. Understanding these facets holds significant importance when it comes to applying this function in practical scenarios. So, let’s delve into these aspects to facilitate practical comprehension through examples.

## Python round() Syntax and Parameters

The syntax of the `round()`

function is pleasantly uncomplicated. Let’s examine this more closely:

rounded_number = round(your_number, precision)

As you employ the capabilities of the `round()`

function, it’s important to note that it necessitates `two`

parameters: the numerical value you intend to round, known as `number`

, and the optional `precision`

parameter. This precision parameter determines the count of decimal positions for `rounding`

. And if you not to specify it, then the `round()`

function will automatically round to the nearest `whole`

number.

Now that you have a good grasp of the syntax and parameters of Python `round()`

, let’s delve into its return values to gain insight into how this function operates in real-world examples.

## Python round() Return Value

The return value of the Python `round()`

function is the result of `rounding`

the input number based on the defined precision, involving `decimal`

places. The manner in which you utilize the function determines the resulting `rounded`

numerical output, which can then be utilized for various purposes such as computations, comparisons, or displaying data. For instance:

Here, we have an example where we initialize a variable named `original_number`

with the value `7.2365`

. This is the value we intend to `round`

. Using the `round()`

function, we create another variable called `rounded_result`

by rounding the `original_number`

to `2`

decimal places. Finally, we utilize the `print()`

function to display the value of `rounded_result`

.

Rounded Number: 7.24

In summary, the return value of the `round()`

function is the `rounded`

numeric value that reflects the effect of rounding the input number according to the specified precision or default rounding behavior.

As previously mentioned, the `round()`

function serves the purpose of `rounding`

numbers. Now, let’s explore practical instances that will provide you with a concrete understanding of how this function operates in real-world scenarios.

### I. Functionality of round() for Number Rounding

The functionality of the `round()`

function in Python revolves around the process of round off the numbers. When you provide a number to the `round()`

function, it adjusts the number according to the precision. If the precision is not provided, the function defaults to round off to the nearest `integer`

. Here’s a breakdown of how the functionality works:

#### A. Round() With Precision (Decimal Places)

You can use the `round()`

function with precision to ensure that a given number is `rounded`

to a specific number of `decimal`

places. This capability is especially valuable when you need to manage the level of accuracy or the specific details in your numeric data.

This empowers you to define the extent to which your numbers are approximated while maintaining control over how much detail is retained in your computations or presentations. Consider below illustration:

In this example, we start by assigning the value `3.14159`

to a variable called `number`

. This is the original number that we want to `round`

. Next, we utilize the `round()`

function to round the number to `three`

decimal places. This results in a rounded value, which we store in a variable named `rounded_number`

. Finally, we use the `print()`

function to display the rounded result along with a message.

This above example illustrates how you can easily `round`

any integer to the particular precision and then showcased the outcome with a clear message.

#### B. Round() Without Precision

Python `round()`

function is also be used without `precision`

. When you use the `round()`

function without specifying the precision or the number of `decimal`

places, you’re directing the function to round the given number to the nearest integer.

In simpler terms, this means the function will adjust the number to the closest `whole`

number without considering any `decimal`

fractions. Here’s what happens when you use the `round()`

function without precision.

For this example, we encountered an example where we started by assigning the value `7.6`

to a variable called `num`

. This particular value is what we intend to `round`

. Subsequently, we used the `round()`

function to round the num to the nearest `integer`

. The rounded outcome was stored in another variable named `rounded_num`

. Lastly, to display the result, we employed the `print()`

function.

This shows how you rounded the initial number, `7.6`

, to the closest whole number, which turned out to be `8`

. Afterward, you displayed it with an appropriate message.

### II. Python round() with Negative Integers

The `round()`

function in Python behaves slightly differently with `negative`

integers as compared to positive ones. When you are rounding `negative`

numbers, the behavior is based on the concept of round half to `even`

, also known as `banker's`

rounding. Here’s how it works:

- If the fractional part of the number is exactly
`0.5`

,`round()`

will round to the nearest even integer. - If the fractional part is less than
`0.5`

, it will round down to the nearest integer. - If the fractional part is greater than
`0.5`

, it will round up to the nearest integer.

Let’s see this behavior in action with negative integers:

In this example, we encountered an example where we began by initializing a variable named `negative_number`

with the value `-3.5`

. This represents a negative number that we want to `round`

. Following that, we used the `round()`

function to round the `negative_number`

to the nearest integer. The result of this rounding operation was stored in a new variable called `rounded_negative_number`

.

To observe the outcomes, we employed the `print()`

function to display both the original `negative_number`

and the `rounded_negative_number`

. This allowed us to compare the initial negative number with its rounded counterpart.

Rounded negative number: -4

Keep in mind that the behavior of `round()`

can lead to some unexpected results, especially when dealing with negative numbers and ties (`numbers that end in 0.5`

).

### III. Rounding to Two Decimal Places with round()

Rounding to two decimal places with Python `round()`

means you’re modifying a provided number to keep just the initial `two`

digits after the decimal point. If needed, the `third`

digit is rounded. For instance, let’s take a look at the following example:

Here, we came across a piece of code where we began by creating a list named `item_prices`

that holds various prices, such as `12.99`

, `8.7532`

, `5.5223`

, and `20.0`

. These represent the costs of different items we have. Next, we computed the total cost by using the `sum()`

function on the `item_prices`

list, resulting in the `total_cost`

variable.

Following that, we employed the `round()`

function to round the `total_cost`

to two decimal places, and the rounded value was stored in the `rounded_total`

variable. To showcase the results, we used the `print()`

function to display both the original `total_cost`

and the `rounded_total`

.

47.27

The output of the code would reveal the `unrounded`

total cost and the `rounded`

total cost, allowing you to observe how the rounding operation affects the calculated `sum`

.

### IV. Python round() up to Nearest 10

Imagine you’re a treasure hunter, and you’ve stumbled upon a collection of gems with varying values. You can harness the power of the `round()`

function to round these gem values to the nearest multiple of `10`

. Consider the below illustration:

For this example, we’ve crafted a function named `round_to_nearest_10()`

that serves the purpose of rounding numbers to the closest multiple of `10`

. Inside this function, we calculate the `remainder`

of a number when divided by `10`

. If the remainder is less than `5`

, we round down to the nearest multiple of `10`

by subtracting the `remainder`

from the `number`

. On the other hand, if the remainder is `5`

or greater, we round up to the next multiple of `10`

by adding the difference between `10`

and the `remainder`

to the number.

To apply this function, we have a tuple called `numbers_to_round`

, containing several original numbers that we intend to `round`

. We then create another tuple called `rounded_numbers`

, using a technique known as a list comprehension. This enables us to run each number in the `numbers_to_round`

tuple through the `round_to_nearest_10()`

function, producing a `tuple`

of the rounded results.

Finally, we use the `print()`

function to display both the original numbers and the corresponding numbers after they have been rounded to the nearest multiple of `10`

. This provides a clear view of how our rounding operation has affected the initial numbers.

Rounded to nearest 10: (10, 30, 40, 60)

Finally, by observing the output of the code, you gain insight into the transformation of the original numbers as they are `rounded`

to their nearest multiples of `10`

.

### V. Python round() with Conditional Statement

Using Python `round()`

with `conditional statements`

allows you to control how rounding is applied based on specific conditions. Conditional statements enable you to customize the `rounding`

behavior according to your requirements. Here’s how you can utilize `round()`

with conditional statements:

In this example, we started by setting an `original_value`

of `3.7`

. Then, we used our `custom_round()`

function on this value, which calculated that the decimal part is `0.7`

(`since 3.7 - 3 = 0.7`

). Given that the decimal part is greater than or equal to `0.5`

, the function rounds the number up by adding `1`

to the integer part.

To visualize the results, we utilized the `print()`

function. It showcased both the original `original_value`

as well as the `rounded_value`

after our custom rounding operation.

Custom rounded value: 4

As you can see , this above example showcase the process through which you can easily manipulate the `rounding`

process based on conditions to derive a `rounded`

value different from the original number.

## Python round() Advanced Examples

In the following section, we will examine several advanced examples of Python `round()`

function, highlighting its flexibility and wide range of applications.

### I. Python round() with Math Library

The Python `round()`

in combination with the `math`

library allows you to apply more advanced `rounding`

techniques and utilize additional mathematical functions. The `math`

library provides a range of mathematical operations and functions that can be beneficial when working with numerical data. Here’s how you can utilize the `round()`

function with the `math`

library. For instance:

Here, we came across a code where we imported the `math`

library to access advanced mathematical functions. Our next step involved defining a function called `advanced_rounding()`

. This function is meant to take a single value as input.

Within the function, we utilized the `math.floor()`

function to `round`

down the provided value to the nearest `integer`

. In a similar fashion, we employed the `math.ceil()`

function to round the value up to the nearest integer. The `rounded-down`

and `rounded-up`

outcomes were stored in variables named `rounded_down`

and `rounded_up`

.

To display the results, we used the `print()`

function. This allowed us to showcase the original value given to the function, along with the `rounded-down`

and `rounded-up`

results. To showcase how our `advanced_rounding()`

function works, we took the value `3.7`

as an example and applied the function to it. The resulting output exhibited the initial value, the value rounded down, and the value rounded up.

Rounded down: 3

Rounded up: 4

This encapsulation within a function allows you to reuse the advanced rounding logic for different values without repeating the code.

### II. Python round() with NumPy

In Python, you can access a potent array and matrix processing prowess along with an array of mathematical functions through the `NumPy`

library. Among these functions is `NumPy's`

own version of the `round()`

function, named `numpy.round()`

. This function closely resembles the built-in `round()`

function, yet it delivers additional choices and potentials, especially when you’re working with `arrays`

or `matrices`

. For example.

For this example, we’re using the `NumPy`

library in this code. First, we import it as ‘`np`

‘. Then, we’ve crafted a class called ‘`ArrayRounding`

‘. The purpose is to facilitate rounding operations on arrays. In its constructor (`init`

), we’re taking an ‘`array`

‘ as input and storing it as an instance variable. Inside the class, there’s a method `round_array()`

. When this method is invoked, it rounds the array’s elements using the `numpy.round()`

function. The result is stored in ‘`rounded_array`

‘, which is returned.

We then create an `input_array`

containing some float values. We make an instance of `ArrayRounding`

, passing the ‘input_array’. With this instance, we call the `round_array()`

method to get the rounded values. Finally, we print out both the original and rounded arrays to compare the results.

Rounded array: [3. 3. 1.]

Through the encapsulation of functionality within a `class`

, you enable the reusability of array rounding logic across various arrays, all the while upholding a well-organized and structured code layout.

### III. Python round() With Decimal Module

Python `round()`

, when used in conjunction with the `decimal module`

, allows you to perform `decimal`

arithmetic with precise control over `rounding`

behavior. The decimal module provides the `Decimal`

data type, which is alternative to the built-in floating-point numbers (`float`

) for applications that require exact decimal representation and `rounding`

. Here’s an example of how the `round()`

function from the `decimal`

module works.

In this example, we’re utilizing an example that employs the `decimal`

module, specifically the `Decimal`

class and the `ROUND_HALF_EVEN`

constant. Our shared objective is to create a class named `DecimalRounding`

. Within this class, we’ve constructed an `__init__`

method. When an instance of `DecimalRounding`

is created, it requires a number to be provided. This number is stored as an attribute of the instance.

The class also encompasses a method named `round_number()`

. This method, upon invocation, takes the stored number and utilizes the `quantize()`

method, which rounds it to `two`

decimal places. The rounding operation is performed according to the `banker's`

rounding method, guided by the `ROUND_HALF_EVEN`

constant. The resulting rounded number is then returned.

Stepping outside the class, we’re initiating a number with the value `101.14159`

. Next, we establish an instance of `DecimalRounding`

, assigning the previously defined number as input. By invoking the `round_number()`

method through this instance, we obtain the rounded `result`

. The last step involves printing both the original number and the calculated rounded value for our collective observation.

Rounded number: 101.14

As evident from the example above, employing this method allows you to seamlessly integrate the Python `round()`

function with the decimal module, leading to improved outcomes.

### IV. Handling Exceptions and Errors with round()

When using the `round()`

function in Python, there are situations where `exceptions`

and `errors`

might occur. Handling `exceptions`

and `errors`

is an important practice in programming to ensure that your code behaves gracefully and doesn’t crash unexpectedly. For instance, if you attempt to round a `non-numeric`

value, the `round()`

function will raise a `TypeError`

. Let’s glimpse at handling this situation.

Here, we defined a function called `perform_rounding()`

. Inside this function, we attempted to execute the `round()`

function on the string `Hello, World!`

. Since the `round()`

function is typically used with numeric values, trying to apply it to a string results in a `TypeError`

.

To handle this potential `error`

, we enclosed the `round()`

function call within a try block. If a `TypeError`

occurs during the attempted rounding operation, the code inside the `except`

block is executed. In this case, we printed out an `error`

message indicating that an `error`

has occurred, along with a message that provides more details about the specific `error`

.

Finally, we invoked the `perform_rounding()`

function, causing the code within it to run. As expected, this led to a `TypeError`

being raised due to trying to round a `string`

, and our `error`

handling mechanism printed out a relevant `error`

message to inform us about the issue.

By using this amazing approach, you are able to encapsulate the provided code within a function, which not only simplifies its execution but also provides a structured and organized way to handle potential errors and exceptions.

Now that you’ve comprehensively grasped the Python `round()`

function, its uses, and its convenience and flexibility across various scenarios, you’ve established a strong foundation. To enrich your comprehension, let’s explore certain theoretical concepts that will greatly benefit you on your path through Python programming.

## Practical Usage of round()

Here are some practical ways you can use Python `round()`

in your programming journey:

### I. Financial Calculations

Use `round()`

to round currency values when performing financial calculations. Ensure that monetary amounts are presented in a clear and consistent manner.

### II. Scientific Data Presentation

`Round`

your scientific measurements or calculations to enhance their presentation quality. You can specify the desired precision level to align with the significance of the data, ensuring that your results are accurately represented.

### III. User Interface and Display

`Round`

the results that you display to users within software applications. This approach helps create a cleaner and more readable interface, particularly when presenting information on dashboards or in reports.

## Exploring Unique Use Cases of round()

The `round()`

function in Python can be applied in various unique and creative ways beyond its common uses. Here are some interesting and unique use cases for the `round()`

function:

### I. Game Mechanics and Animations

Use `round()`

to control the position of objects in a game, creating smoother animations by rounding coordinates to pixel values.

### II. Musical Applications

Apply the `round()`

function to your advantage in music software to handle tempo changes effectively. Round beat durations to the nearest rhythm unit, allowing you to manage and maintain a consistent musical tempo.

### III. Text Generation and Word Lengths

Round word lengths generated by a text generator to fit within certain character limits, ensuring consistent formatting.

`Congratulations!`

You’ve learned Python `round()`

function. It’s more than just a simple tool – it’s your `precision`

partner, helping you round numbers with finesse and accuracy. By using this function, you’ve unlocked the power to control the level of `precision`

in your calculations or data presentations.

In this fantastic guide, you’ve acquired a deep understanding of the capabilities and potential of the Python `round()`

function. You’ve explored its functionalities with both `integers`

and `floating-point`

numbers, delved into its behavior with `negative`

integers, and even examined how it interacts with sequences like `lists`

and `tuples`

. Additionally, you’ve ventured into its applications with modules like `math`

, `decimal`

, and `numpy`

, discovering how to gracefully handle exceptions and `errors`

along the way.

So, whether you’re crafting the perfect recipe, fine-tuning a software dashboard, or setting the tempo for a musical masterpiece, the Python `round()`

function is your ally in precision and clarity. Use its flexibility and convenience, explore its capabilities, and let your creativity flourish as you round your way to success!