Python numpy.arange()

Introduction

numpy.arrange() is a highly versatile python numpy function that is used to return evenly spaced values within a given interval.

The function is an implementation of a range function that is utilized within the numpy environment. Therefore, it can be used to create numeric ranges for integer, float, and complex data types.

Syntax

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

• start: The starting value of the sequence. If not specified, the default value is 0
• stop: The end value of the sequence. This argument must always be specified.
• step: The spacing between values in the sequence. If not specified, the default value is 1.
• dtype: The output data type. If not specified, the default data type is float.

Note that the start and step parameters are optional, but if you want to use the step parameter, you also need to specify the start parameter.

Examples

Integer Range

import numpy as np
np.arange(5)

Output:

array([0, 1, 2, 3, 4])

Float Range

import numpy as np
np.arange(1, 5, 0.5)

Output:

array([ 1. ,  1.5,  2. ,  2.5,  3. ,  3.5,  4. ,  4.5])

Specifying Data Type

import numpy as np
np.arange(1, 5, dtype=np.complex)

Output:

array([ 1.+0.j,  2.+0.j,  3.+0.j,  4.+0.j])

Conclusion

The numpy.arange() function is a powerful and flexible tool for creating numeric ranges. Its ability to handle different data types and its support for both integer and float ranges make it a valuable tool for data analysis and scientific computing.