In this tutorial, we will cover `numpy.arange()`

function of the Numpy library which is used for array creation.

The NumPy `arange()`

function is one of the array creation routines **that is usually based on numerical ranges**. This method basically creates an instance of `ndarray`

with **evenly spaced values** and returns the reference to it.

- In this function, you can define the interval of the
**values that are contained in an array, the space between them, and their type**. - The values are usually generated using the
**half-opened interval**:**[Start, Stop)**. It usually means the interval includes the**start**but will exclude(not include) the**stop**. - There is an advantage of
`numpy.arange()`

over the normal built-in`range()`

function that with the help of`numpy.arange()`

we are allowed to generate sequences of numbers that are not integers.

### Syntax of `numpy.arange()`

Below we have the required syntax to use this function:

`numpy.arange(start, stop, step, dtype) `

**Note:** In the above syntax the first three parameters are used to determine the range of the values, while the fourth parameter is used to specify the type of the elements.

**Parameters:**

Let us now discuss the above-mentioned parameters of this function:

**start**This is an optional parameter used for indicating the start of the interval. The default value of this parameter is**0**. This value is included in the interval.**stop**This parameter is a number(integer or decimal) that is used to represent the value at which the interval ends excluding this value.**step**This is an optional parameter indicating the step size of the interval and it is a number by which the interval values change.**dtype**This option is used to indicate the data type of the numpy array items. The default value of this parameter is**None**.

**Returned Values:**

This method will return the array within the specified range.

Now it’s time to cover a few examples.

## Example 1: Creating a basic array

In the example given below, we are going to provide all the range arguments and will check the resulting output:

```
import numpy as np
a=np.arange(start=2, stop=12, step=2)
print("The Output is :",a)
```

Output:

The Output is : [ 2 4 6 8 10]

## Example 2:

In the example given below we will provide only two range arguments and then check the result:

```
import numpy as np
a=np.arange(start=2, stop=12)
print("The Output is :",a)
```

Output:

In the above code snippet as we have not passed the `step`

argument, thus it will take the default value of step i.e **1**. Thus the output is as follows:

The Output is : [ 2 3 4 5 6 7 8 9 10 11]

## Example 3: Using `arange()`

with single Argument

You need to provide **at least one argument** to the `arange()`

function. And it is recommended that the one argument you provide should be `stop`

(instead of `start`

) and then the method automatically takes the default value of `start`

and `step`

. Thus **start** will be taken as **0** and the **step** will be taken as **1**. In the example given below, we will provide only one **range argument **and then check the result. The code snippet is as follows:

```
import numpy as np
a=np.arange(12)
print("The Output is :",a)
```

Output:

The Output is : [ 0 1 2 3 4 5 6 7 8 9 10 11]

## Example 4: Providing Negative Arguments

In case we want to provide negative values for `start`

or both `start`

and `stop`

, and have a positive value for the `step`

argument, the arange()function will work normally with the negative values and will create an array with negative values. Let us now take a look at the code snippet given below:

```
import numpy as np
a=np.arange(-10, -1)
print("The output is:")
print(a)
```

Output:

The output is: [-10 -9 -8 -7 -6 -5 -4 -3 -2]