numpy.arange() function creates an array of evenly spaced values within a given interval. It is similar to Python's built-in range() function but returns a NumPy array instead of a list.

Let's understand with a simple example:

import numpy as np 

#create an array 
arr= np.arange(5 , 10)
print(arr)

[5 6 7 8 9]

Syntax of numpy.arange():

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

Parameters of numpy():

• start (optional): The starting value of the sequence. Default is 0.
• stop (required): The endpoint of the sequence, exclusive.
• step (optional): The spacing between consecutive values. Default is 1.
• dtype (optional): The desired data type of the output array.

Return Type:

• Array of evenly spaced values.

Specify Start and Stop

Generate a sequence of integers starting from 5 to 14.

import numpy as np

# Creating a sequence of numbers from 0 to 9
sequence = np.arange(10)
print("Basic Sequence:", sequence)

Basic Sequence: [0 1 2 3 4 5 6 7 8 9]

Floating-Point Step Size

Generate a sequence of floating-point numbers.

import numpy as np 

# Creating a sequence of floating-point numbers from 0 to 1 
# with a step size of 0.2 using np.arange()
sequence = np.arange(0, 1, 0.2)
print("Floating-Point Sequence:", sequence)

Floating-Point Sequence: [0.  0.2 0.4 0.6 0.8]

Combining with Conditional Filtering

Generate a sequence and filter specific values.

import numpy as np 

# Creating a sequence of numbers from 0 to 20 
sequence = np.arange(0, 20, 3)

# Filtering the sequence to include only values greater than 10
filtered = sequence[sequence > 10]
print("Filtered Sequence:", filtered)

Filtered Sequence: [12 15 18]