Numpy.arange() method returns an array with evenly spaced elements as per the interval. The interval mentioned is half-opened, i.e., [Start, Stop).
Syntax
numpy.arange(start, stop, step, dtype)
Parameters
- start (optional, number): Start of an interval. The default start value is 0.
- stop: number. End of the interval.
- step (number, optional): The step can’t be zero. Otherwise, you’ll get a ZeroDivisionError.
- dtype: The type of an output array. If the dtype is not given, infer the data type from the other input arguments.
Return Value
It returns an array.
Example 1: Basic usage of np.arange()
import numpy as np
print(np.arange(4), "\n")
Output
[0 1 2 3]
Example 2: Specifying start and stop
import numpy as np
arr = np.arange(18, 22)
print(arr)
Output
[18 19 20 21]
Example 3: Specifying step size
import numpy as np
arr = np.arange(17, 22, 2)
print(arr)
Output
[17 19 21]
Example 4: Passing ‘float’ arguments
import numpy as np
arr = np.arange(2, 11.1, 3)
print(arr)
Output
[ 2. 5. 8. 11.]
Example 5: Creating a multi-dimensional array
import numpy as np
print(np.arange(4).reshape(2, 2), "\n")
Output
[[0 1]
[2 3]]
That’s it.
Related posts
Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.