# numpy.arange() function with example in python | 2019

numpy.arange() : If you want generate a sequence of numbers, arange() function is very helpful. It has regular range of numbers and with specific interval range numbers. Depends on usecase, you will use this function. It return evenly spaced values within a given interval.

Syntax: numpy.arange([start, ]stop, [step, ]dtype=None)

Values are generated within the half-open interval [start, stop) (in other words, the interval including start but excluding stop). For integer arguments the function is equivalent to the Python built-in range function, but returns an ndarray rather than a list.

When using a non-integer step, such as 0.1, the results will often not be consistent. It is better to use numpy.linspace for these cases.

Parameters:
start : number, optional
Start of interval. The interval includes this value. The default start value is 0.

stop : number
End of interval. The interval does not include this value, except in some cases where step is not an integer and floating point round-off affects the length of out.

step : number, optional
Spacing between values. For any output out, this is the distance between two adjacent values, out[i+1] – out[i]. The default step size is 1. If step is specified as a position argument, start must also be given.

dtype : dtype
The type of the output array. If dtype is not given, infer the data type from the other input arguments.

Returns:
arange : ndarray
Array of evenly spaced values.

For floating point arguments, the length of the result is ceil((stop – start)/step). Because of floating point overflow, this rule may result in the last element of out being greater than stop.

### #numpy.arange() example program

` ` ``` import numpy as np print(np.arange(5)) print(np.arange(5.0)) print(np.arange(4, 12)) print(np.arange(10, 20, 2)) ``` ` ` ` `

Output:

```[0 1 2 3 4]
[ 0.  1.  2.  3.  4.]
[ 4  5  6  7  8  9 10 11]
[10 12 14 16 18]``` 