I can generate an array like this :
arr = np.array(range(0,36))
arr
#Output
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33,
34, 35])
My question is how can I generate nxn array like:
array([[ 0, 1, 2, 3, 4, 5],
[6, 7, 8, 9, 10, 11],
[12, 13, 14, 15, 16, 17],
[18, 19, 20, 21, 22, 23],
[24, 25, 26, 27, 28, 29],
[30, 31, 32, 33, 34, 35]])
The way you've written that output doesn't look right, bit if you mean a 6x6 array then:
>>> arr = np.array(range(0,36)).reshape((6,6))
>>> arr
array([[ 0, 1, 2, 3, 4, 5],
[ 6, 7, 8, 9, 10, 11],
[12, 13, 14, 15, 16, 17],
[18, 19, 20, 21, 22, 23],
[24, 25, 26, 27, 28, 29],
[30, 31, 32, 33, 34, 35]])
Note there's an outside set of square brackets here compared to your desired output...
A slightly more compact (.reshape can take multiple args) and possible quicker way (np.arange thx @jadsq):
np.array(np.arange(36)).reshape(6,6)
