Python: Two similar methods in Numpy to create array with initial content

Numpy library provides several methods to create array with initial content. Two of them are to generate a sequence of values between start and end numbers: arange and linspace . What are difference between those two methods?

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arange

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

By given start and end numbers, it generates a sequence from start number to end number (not included) without interval (interval = 1) between numbers.

You can also specify interval:

>>> np.arange(0, 10, 3)
array([0, 3, 6, 9])

The interval could be float:

>>> np.arange(0, 10, 1.2)
array([0. , 1.2, 2.4, 3.6, 4.8, 6. , 7.2, 8.4, 9.6])

To generate 2-dimensional array, you need to combine arange with reshap :

>>> np.arange(0, 10, 1.2).reshape(3,3)
array([[0. , 1.2, 2.4],
       [3.6, 4.8, 6. ],
       [7.2, 8.4, 9.6]])

You have to make sure the size after reshape is correct, otherwise, it will fail:

>>> np.arange(0, 10, 1.2).reshape(3,4)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: cannot reshape array of size 9 into shape (3,4)

linspace

You can use linspace to generate an array with 50 elements by default, from start number to end number:

>>> np.linspace(0, 10)
array([ 0.        ,  0.20408163,  0.40816327,  0.6122449 ,  0.81632653,
        1.02040816,  1.2244898 ,  1.42857143,  1.63265306,  1.83673469,
        2.04081633,  2.24489796,  2.44897959,  2.65306122,  2.85714286,
        3.06122449,  3.26530612,  3.46938776,  3.67346939,  3.87755102,
        4.08163265,  4.28571429,  4.48979592,  4.69387755,  4.89795918,
        5.10204082,  5.30612245,  5.51020408,  5.71428571,  5.91836735,
        6.12244898,  6.32653061,  6.53061224,  6.73469388,  6.93877551,
        7.14285714,  7.34693878,  7.55102041,  7.75510204,  7.95918367,
        8.16326531,  8.36734694,  8.57142857,  8.7755102 ,  8.97959184,
        9.18367347,  9.3877551 ,  9.59183673,  9.79591837, 10.        ])

The 3rd argument number is to tell how many elements will be generated from start number to end number, which is different from 3rd argument of arange method:

>>> np.linspace(0, 10, 3)
array([ 0.,  5., 10.])

And as you see, the type of element is float by default. If you want to change, then passing dtype argument:

>>> np.linspace(0, 10, 3, dtype=int)
array([ 0,  5, 10])

Similarly, you can also combine with rshape to generate 2 dimensional array:

>>> np.linspace(0, 10, 6, dtype=int).reshape(2,3)
array([[ 0,  2,  4],
       [ 6,  8, 10]])

Yes, that’s the simple introduction of two similar methods in numpy library to generate arrays with initial content between start and end number.

Thanks for reading and happy coding!