In this Python tutorial, we will learn **how to round Numpy array in Python**. Also, we will cover these topics.

- Python NumPy round up
- Python NumPy round to integer
- Python NumPy round down
- Python NumPy round array
- Python NumPy round to significant digits
- Python NumPy round function
- Python numpy round half up
- Python numpy round to nearest 5
- Python numpy round to nearest 10
- Python np.round not working
- Python Numpy round to 2 decimal places
- Python NumPy round all values
- Python NumPy arange round
- Python round NumPy float array
- Python numpy array circular shift
- Python numpy.ndarray doesn’t define_round_method
- Python numpy circular buffer

**Table of Contents**show

## Python NumPy round

- In this section, we will discuss
**how to rounds the numbers in a NumPy array in Python**. - To do this task we are going to use function
**numpy.round()**. In Python, this function works mathematically and performs a rounding-off operation, and also signifies the number of decimal places that we want to round off. - This function will check the condition if the floating values are not given then it will round off the values up to 1. For example, if the values reach
**0.26783**then by default it will return**1**as a result.

**Syntax:**

Here is the Syntax of **numpy.round()** function

```
numpy.round_
(
a,
decimals=0,
)
```

- It consists of the few parameters
**a:**This parameter specifies which values we want to be rounded off( input array).**decimals:**This parameter signifies a number of decimal places that will be used to round off.

**Example:**

Let’s take an example and check how to use the** numpy round() **function in Python

**Source Code:**

```
import numpy as np
result=np.round(0.6789)
print("Rounded value:",result)
```

In the above code we have imported the NumPy library and then use the **numpy.round() function** and assign floating-point number(decimal). Once you will print ‘result’ then the output will display a rounded value that is 1.

Here is the Screenshot of the following given code

Read: Python reverse NumPy array

## Python NumPy round up

- In this Program, we will discuss
**how to round off the values in NumPy array in Python**. - By using the
**np.round()**method we can easily round off the array elements. In Python this method is a built-in function available in the NumPy module and this method if the floating values to be rounded are not given then by default it will consider as**0**. - In this example, we are going to understand how the numpy round method works in Python.

**Example:**

```
import numpy as np
new_arr = [3.67, 5.7, 1.2, 3.7, 8.6]
new_output = np.round_(new_arr)
print ("Rounded values:", new_output)
```

In the above example, we have declared a numpy array **‘new_arr’** as input for the round function. This function will check the condition if the value is **0.5** or above after the decimal point then this function will get the next number in the series.

Here is the execution of the following given code

Read: Python NumPy nan

## Python NumPy round to integer

- Let us see
**how to convert round values with integer in NumPy Python**. - To perform this particular task we are going to use the
**rint()**method. This method is used to round the array values to the nearest integer.

**Syntax:**

Here is the Syntax of **rint() **method

```
numpy.rint
(
x,
/,
out=None,
*,
where=True,
casting='same_kind',
order='K',
dtype=None,
subok=True
)
```

**Example:**

```
import numpy as np
new_val = [4.28, 2.87, 0.65, 0.34]
result = np.rint(new_val)
print(result)
```

In the above code we have imported a NumPy library and then use an np.rint() method and assigned an array **‘new_val’** in it.

Once you will print ‘result’ then the output will display new integer values.

Here is the output of the following given code

Read: Python NumPy Average

## Python NumPy round down

- In this section, we will discuss how to
**rounds the number in NumPy array**. - In this example, we are going to use the
**numpy.floor()**method. In Python, this function always returns the floor of the values of the numpy array elements. - This method will check the condition if
**i <=x**then the floor of the scaler x is the largest number**i**.

**Syntax:**

Here is the Syntax of numpy.floor() method

```
numpy.floor
(
x,
/,
out=None,
*,
where=True,
casting='same_kind',
order='K',
dtype=None
)
```

Let’s take an example and understand how floor function work in NumPy Python

**Example:**

```
import numpy as np
new_arr = np.array([-4.6, -3.4, -1.3, 1.2, 0.4, 0.6])
b= np.floor(new_arr)
print(b)
```

Read: Python NumPy absolute value

## Python NumPy round array

- In this Program, we will discuss
**how to get the rounded value in the NumPy array by using Python**. - To perform this particular task we are going to use the
**np.round()**method and it signifies the number of decimal places that we want to round off.

**Syntax:**

Here is the Syntax of numpy.round() method

```
numpy.round_
(
a,
decimals=0,
)
```

**Source Code:**

```
import numpy as np
new_array = np.array([3.5826945, 6.256485, 7.27384895])
z= np.round(new_array)
print(z)
```

In the above code, we have used the n**p.array()** method for creating an array and assigned decimal values to it. Once you will print **‘z’** then the output will display the exact positive integer number.

Here is the Screenshot of the following given code

Read: Python NumPy square

## Python NumPy round to significant digits

- In this section, we will discuss how to
**convert rounds with significant digits in Python**. - In Python, the rounding signifies replacing a number with an approximate value that is near to it. In this example, we are going to use the sigfig module for rounding the numbers to significant digits and in Python, the sigfig is used to the rounding number of digits in a value.
- In this module, we have specified the number of significant digits that is round and this function is basically used with floating-point numbers.

**Source Code:**

```
from sigfig import round
b= round(4576, sigfigs = 1)
print(b)
```

You can refer to the below Screenshot

As you can see in the Screenshot the output displays the accurate significant digit number.

Read: Python NumPy to list

## Python NumPy round function

- Let us see
**how to use the round() function in NumPy array in Python**. - In this example, we are going to use the
**np.round()**function for getting the exact number from the input. To do this task first we will import the numpy library and then declare**‘new_values’**and use the**np.round()**function in which we are going to pass decimal values as a parameter.

**Example:**

```
import numpy as np
new_values=np.round(0.5432)
print("Rounded value:",new_values)
```

Here is the implementation of the following given code

As you can see in the Screenshot the output displays the exact integer number.

Read: Python NumPy read CSV

## Python numpy round to nearest 5

- In this program, we will
**find the nearest value by using NumPy in Python**. - By using the
**np.round()**function we will easily get the nearest value that is**5**. To do this task we are going to assign the**‘4.8’**value in the**np.round()**function. Once you will print**‘b’**then the output will display the exact value.

**Source Code:**

```
import numpy as np
b= np.round(4.8)
print(b)
```

Here is the Screenshot of the following given code

### Round number to nearest 5

In this example, we will discuss **how to round numbers to the nearest 5 in Python**.

To do this task we are going to use the **round() **function and assign the** ‘new_arr’ **variable and divide the value by **5** and multiply with **5** again.

**Source Code:**

```
new_arr = int(input('Enter value:'))
new_output = round(new_arr/5)*5
print("Rounded value:",new_output)
```

Here is the implementation of the following given code

As you can see in the Screenshot we have entered the number ‘3547’ and its nearest number to 5 is **‘3545’**.

Read: Python NumPy log

## Python numpy round to nearest 10

- In this section, we will discuss
**how to round numbers to the nearest 10 by using NumPy Python**. - In this program, we will read a value from the user and then use the
**round()**function and assign the**‘new_arr’**variable and divide the value by**10**and multiply with 5 again.

**Example:**

```
new_arr = int(input('Enter value:'))
final = round(new_arr/10)*10
print("Rounded value:",final)
```

You can refer to the below Screenshot

As you can see in the Screenshot we have entered the number **‘3786’** and its nearest number to **5 **is **‘3790’**.

Read: Python NumPy max

## Python np.round not working

- In this section, we will discuss that
**np.round()**function will not work in Python. - we have already solved this problem in our below topic if someone wants to fix this problem you can use the ‘numpy.ndarray doesn’t define_round_method’ topic.
- As per the documentation in stackoverflow this function does not work when the value of decimals is less than
**5**the following link is given. - https://stackoverflow.com/questions/51349738/np-round-or-np-around-doesnt-work.

**Example:**

```
import numpy as np
new_values=np.around(5.543)
print("Rounded value:",new_values)
```

Here is the Screenshot of the following given code

Read: Python NumPy shape

## Python Numpy round to 2 decimal places

- Let us see
**how to get the rounded number in the NumPy array by using Python**. - By using the
**np.round()**function we can easily perform this particular task and assign**‘new_val’**to it. Once you will print**‘z’**then the output will display the exact integer number.

**Example:**

```
import numpy as np
new_val = np.array([23.58, 34.25, 67.27])
z= np.round(new_val)
print(z)
```

Here is the execution of the following given code

Read: Python NumPy Normalize

## Python NumPy round all values

- In this section, we will discuss
**how to round all the values in NumPy array by using Python**. - In this example first, we will create a list and assign decimal values to it. Now use for loop method with
**round()**function and iterate all the values. Once you will print**‘output’**then the result will display the exact integer values.

**Source Code:**

```
new_arr = ([6.345, 9.389, 8.789, 3.965])
output = [round(i) for i in new_arr]
print("rounded all values:",output)
```

You can refer to the below Screenshot

As you can see in the Screenshot the output displays a rounded value.

Read: Python NumPy 3d array

## Python NumPy arange round

- In this Program, we will discuss
**how to use the arange() function while extracting the rounded values in Python**. - By using the
**numpy.round()**method we can easily perform this particular task. In this example first we will declare a variable**‘new_array’**and assign**np.arange()**function to it. - Now use the
**np.round()**function and pass**‘new_array’**variable as an argument. Once you will print**‘z’**then the output will display a rounded value.

**Example:**

```
import numpy as np
new_array = np.arange(5.5, 11.75)
z= np.round(new_array)
print(z)
```

Here is the output of the following given code

As you can see in the Screenshot the output displays the exact integer numbers.

Read: Python NumPy Split

## Python round NumPy float array

- Let us see how to use the
**round()**function in a floating array by using Python. - In this example, we will create a simple array and assign decimal values to it and then declare a variable
**‘result’**and assign array**‘val_of_ele’**to it.

**Syntax:**

Here is the Syntax of numpy.round() function

```
numpy.round_
(
a,
decimals=0,
)
```

**Source Code:**

```
import numpy as np
val_of_ele = [7.344, 24.745, 89.2233, 18.734, 14.334]
result = np.round_(val_of_ele)
print ("Rounded Floating values:", result)
```

Here is the implementation of the following given code

As you can see in the Screenshot the output displays the integer values.

Read: Python NumPy Data types

## Python numpy array circular shift

- In this section, we will discuss
**how do we circular shift in NumPy array by using Python**. - To do this task we are going to use the
**numpy.roll()**method. In Python the**numpy.roll()**method is used to roll array values along with specified axis. If we have to use a positive integer for shifting the value towards the right while in the case of a negative integer it will shift the element towards the left. - In simple words, we can say that the element is being rolled from first to the last position and this method is available in the NumPy module package.

**Syntax:**

Here is the Syntax of numpy.roll() method

```
numpy.roll
(
a,
shift,
axis=None
)
```

**Example:**

```
import numpy as np
new_arr = np.array([4,7,8,9,3,8,11])
b=np.roll(new_arr,2)
print(b)
```

In the above code, we have used the **np.roll()** function for shifting the elements left to right.

Here is the Screenshot of the following given code

Read: Python NumPy repeat

## Python numpy.ndarray doesn’t define_round_method

- In this Program, we will discuss how the error problem
**‘numpy.ndarray doesn’t define_round_method**. - To do this task first we are going to import the numpy library and then use the round method to it and pass the
**np.array()**function as an argument.

**Source Code:**

```
import numpy as np
new_val = round(np.array([[4.6,7.9],[23,34],[1.8,3.45]]))
print(new_val)
```

Here is the execution of the following given code

As you can see in the Screenshot the output raises the error** ‘Numpy ndarray doesn’t define_round_method**

**Solution:**

In this example, we are going to change the round method to the **np.round()** method and assign decimal values in an array. Once you will print **‘new_val’** then the output will display the exact integer numbers.

**Example:**

```
import numpy as np
new_val = np.round(np.array([[4.6,7.9],[23,34],[1.8,3.45]]))
print(new_val)
```

You can refer to the below Screenshot

Read: Python Numpy unique

## Python numpy circular buffer

- In this program, we will discuss
**how to create an efficient circular buffer in NumPy Python**. - By using the collection module we can easily use the
**collection.deque()**method. In Python, this method is used for adding and removing values from either side that is on the left side or right side. - This method is like a stack and queue and it is available in a collection Python object.

**Example:**

```
import collections
import numpy as np
arr = collections.deque(maxlen=8)
for z in np.arange(18):
arr.append(z)
print(arr)
```

You can refer to the below Screenshot

You may like the following Python NumPy tutorials:

- Check if NumPy Array is Empty in Python
- Python NumPy shape with examples
- Python reverse NumPy array
- Python NumPy max with examples
- Python NumPy empty array
- Python NumPy nan

So, in this Python tutorial, we have learned **how to round Numpy array in Python**. Also, we have covered these topics.

- Python NumPy round up
- Python NumPy round to integer
- Python NumPy round down
- Python NumPy round array
- Python NumPy round to significant digits
- Python NumPy round function
- Python numpy round half up
- Python numpy round to nearest 5
- Python numpy round to nearest 10
- Python np.round not working
- Python Numpy round to 2 decimal places
- Python NumPy round all values
- Python NumPy arange round
- Python round NumPy float array
- Python numpy array circular shift
- Python numpy.ndarray doesn’t define_round_method
- Python numpy circular buffer

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