PYTHON

np arange

np.arange([start], stop, [step])

>>> np.arange(10) # stop
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> np.arange(2, 10)
array([2, 3, 4, 5, 6, 7, 8, 9])
>>> np.arange(2, 10, 2)
array([2, 4, 6, 8])

np.arange in python

>>> np.arange(3)
array([0, 1, 2])
>>> np.arange(3.0)
array([ 0.,  1.,  2.])
>>> np.arange(3,7)
array([3, 4, 5, 6])
>>> np.arange(3,7,2)
array([3, 5])

np arange

# Standard range() in python needs whole numbers for step size
print(np.arange(0, 1, 0.1))
array([0., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])

numpy arange

arange() NumPy arange() is one of the array creation routines based on numerical
ranges.
It creates an instance of ndarray with evenly spaced values and returns the 
reference to it.

python array use numpy arange

import numpy as np
e = np.arange(0, 1, 0.3)
print(e)

numpy arange number of elements

>>> import numpy as np
>>> np.linspace(start=0, stop=7.5, num=4)
array([ 0. ,  2.5,  5. ,  7.5])
>>> list(_)
[0.0, 2.5, 5.0, 7.5]