I want to create an array with numbers going from 0 to 10 in its 1st sub-array, from 11 to 20 in its 2nd and so on...
I can create the sub arrays with
for i in range(10):
print np.arange(10*i, 10*(i+1))
which gives me
[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 36 37 38 39]
[40 41 42 43 44 45 46 47 48 49]
[50 51 52 53 54 55 56 57 58 59]
[60 61 62 63 64 65 66 67 68 69]
[70 71 72 73 74 75 76 77 78 79]
[80 81 82 83 84 85 86 87 88 89]
[90 91 92 93 94 95 96 97 98 99]
but I can't fit it inside an array... Tried -
a = np.array((10,10))
for i in range(10):
a[i] = np.arange(10*i, 10*(i+1))
Which gave ValueError: setting an array element with a sequence.
How can I fix this?
Edit:
All the answers here provide a working way to achieve what I want, which is the main thing I wanted, but I also want to understand why the error appears, since the np.arange()
, from what I understand, returns an ndarray
To add multiple rows to an 2D Numpy array, combine the rows in a same shape numpy array and then append it, # Append multiple rows i.e 2 rows to the 2D Numpy array. empty_array = np. append(empty_array, np.
To expand the shape of an array, use the numpy. expand_dims() method. Insert a new axis that will appear at the axis position in the expanded array shape. The function returns the View of the input array with the number of dimensions increased.
I guess the easiest way to do this is to reshape an arange
from 0
to 100
:
>>> np.arange(100).reshape(10, -1)
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, 36, 37, 38, 39],
[40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
[50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
[60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
[70, 71, 72, 73, 74, 75, 76, 77, 78, 79],
[80, 81, 82, 83, 84, 85, 86, 87, 88, 89],
[90, 91, 92, 93, 94, 95, 96, 97, 98, 99]])
Here the .reshape(..)
call will thus transform the matrix such that it is a 2D-array, with 10 "rows" and a number of columns such that the total amount of cells is 100.
In case you do not want to construct a 2D-array, but a Python list
of 1D arrays, we can use list comprehension:
[np.arange(i, i+10) for i in range(0, 100, 10)]
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