# NumPy around()

The `around()` function rounds the elements of an array to the nearest whole number.

### Example

``````import numpy as np

# create an array with decimal values
array1 = np.array([1.234, 2.678, 3.543, 4.876, 5.192])

# round the elements using around()
result = np.around(array1)

print(result)

# Output : [1. 3. 4. 5. 5.]``````

## around() Syntax

The syntax of `around()` is:

``numpy.round(array, decimals=0, out=None)``

## around() Arguments

The `around()` function takes one argument:

• `array` - the input array whose elements are to be rounded
• `decimal` (optional) - number up to which the elements of `array` is rounded
• `out` (optional) - the output array where the result will be stored.

## around() Return Value

The `around()` function returns a new array with the rounded values.

## Example 1: Round Array Elements to Nearest Integer

``````import numpy as np

# create a 2D array with decimal values
array1 = np.array([[1.2, 2.7, 3.5],
[4.8, 5.1, 6.3],
[7.2, 8.5, 9.9]])

# round the elements to the nearest integer using np.around()
result = np.around(array1)

print("Rounded array:")
print(result)``````

Output

```Rounded array:
[[ 1.  3.  4.]
[ 5.  5.  6.]
[ 7.  8. 10.]]```

In the above example, the `np.around()` function rounds the elements of the array to the nearest integer.

However, even after rounding, the data type of the array remains as `float64`. That is the reason for the presence of a decimal point in the output.

If you prefer to have the output as integers without the decimal points, you can convert the data type of the rounded array to `int` using `astype()` as:

``rounded_array = np.around(array1).astype(int)``

Then the output will be,

```[[ 1  3  4]
[ 5  5  6]
[ 7  8 10]]```

## Example 2: Round Elements to Given Number of Decimal Places

``````import numpy as np

# create an array
array1 = np.array([1.23456789, 2.3456789, 3.456789])

# round the elements to 2 decimal places
rounded_array = np.around(array1, decimals=2)

print(rounded_array)``````

Output

`[1.23 2.35 3.46]`

Each element in array1 is rounded to 2 decimal places as specified by the decimal argument in the `np.around()` function.

## Example 3: Use out to Store the Result in Desired Location

``````import numpy as np

# create an array
array1 = np.array([1.2, 2.7, 3.5])

# create an empty array with the same shape as array1
rounded_array = np.zeros_like(array1)

# round the elements of array1 and store the result in rounded_array
np.around(array1, out=rounded_array)

print(rounded_array)``````

Output

`[1. 3. 4.]`

Here, after specifying `out=rounded_array`, the rounded_array contains the rounded values of each element in array1.