Flatten numpy array

Question

Is there a simple way in NumPy to flatten type object array?

I know .flatten() method flattens non-object type arrays constructed from same size arrays:

I1 a = np.array([[1],[2],[3]])

I2 a.flatten()
O2 array([1, 2, 3])

however, I can't get dtype=object array flattened:

I4 b
O4 array([[1], [2, 3], [3]], dtype=object)

I5 b.flatten()
O5 array([[1], [2, 3], [3]], dtype=object)

Thanks.

The example is already as flat as it can be (b.shape = (3,))! What exactly do you mean by flatten? — Henry Gomersall
– Henry Gomersall, Commented Jul 6, 2012 at 17:54

nye17 · Accepted Answer · 2012-07-06 18:03:59Z

64

if you want [1,2,3,3], try this then

np.hstack(b)

answered Jul 6, 2012 at 18:03

nye17

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8 Comments

Oriol Nieto Over a year ago

Nice. I was about to post this (which does the exact same thing): [x for bb in b for x in bb]

nye17 Over a year ago

@urinieto actually the list comprehension-based method you posted is faster, although it's kinda nicer to have it settled in numpy's way.

Gökhan Sever Over a year ago

how about for an array of 20k element?

mgilson Over a year ago

@nye17 -- But at the end of the day, it's often nice to have a numpy array instead of a list.

nye17 Over a year ago

@GökhanSever 20k wouldn't be a problem for modern computers, if you are really thresholded by speed in this kind of computation, I would say that you shouldn't have had an inhomogenous data array to begin with.

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jedrix · Accepted Answer · 2022-01-14 23:29:18Z

0

In case when your array does not contain more than one nested array, np.hstack(arr) function won't work!

Workaround:

arr = np.array([[0]])
if arr.any():
    arr = np.hstack(arr)
else:
    arr = arr.flatten()

answered Jan 14, 2022 at 23:29

jedrix

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