# numpy.arange() in Python | np.arange() in Python

Numpy `arange()` function is used to generate evenly spaced numeric values within the provided interval. It is one of the ways to generate Numpy array.

## Syntax of Numpy arange()

`np.arange(start, stop, step, dtype=None)`

`start` parameter is optional and is used to specify the start of interval. Its default value is 0. It is included in the interval.

`stop` parameter is used to specify the end of interval. It is not included in the interval.

`step` parameter is optional and is used to specify the step size of the interval. Its default value is 1.

`dtype` parameter is optional and controls the data type of the resultant Numpy array.

Note: In mathematical terms, numbers generated by `np.arange()` function belongs to this interval: [start, stop). `np.arange()` function generates 1-dimensional Numpy array but with the help of `np.ndarray.reshape()` function you can change it to n-dimensional Numpy array.

## Python program to generate Numpy array using np.arange() function

```import numpy as np

x = np.arange(1, 10)
print('Numpy array x:', x)
y = np.arange(5, 21, 3).reshape(3, 2)
print('Numpy array y:\n', y)```

Output of the above program

```Numpy array x: [1 2 3 4 5 6 7 8 9]
Numpy array y:
[[ 5  8]
[11 14]
[17 20]]```

The code `np.arange(1, 10)` generated 1-D Numpy array having values from 1 to 10 but 10 is not included.

The code `np.arange(5, 21, 3).reshape(3, 2)` generated Numpy array having values from 5 to 21 with a step size of 3 and then converted that 1-D array to 2-D array having 3 rows and 2 columns using `reshape()` function.