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up vote 5 down vote favorite

I want to convert this list in a numpy array:

var=[array([ 33.85967782]), array([ 34.07298272]), array([ 35.06835424])]

The result should be the following:

[[ 33.85967782]
 [ 34.07298272]
 [ 35.06835424]]

but, if I type var = np.array(var), the result is the following:

[array([ 33.85967782]) array([ 34.07298272]) array([ 35.06835424])]

I have the numpy library: import numpy as np

can you help me, please?

Thanks!

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2 Answers 2

up vote 5 down vote accepted

np.vstack is the canonical way to do this operation:

>>> var=[np.array([ 33.85967782]), np.array([ 34.07298272]), np.array([ 35.06835424])]

>>> np.vstack(var)
array([[ 33.85967782],
       [ 34.07298272],
       [ 35.06835424]])

If you want a array of shape (n,1), but you have arrays with multiple elements you can do the following:

>>> var=[np.array([ 33.85967782]), np.array([ 35.06835424, 39.21316439])]
>>> np.concatenate(var).reshape(-1,1)
array([[ 33.85967782],
       [ 35.06835424],
       [ 39.21316439]])
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Traceback (most recent call last): File "/home/worm1988/Desktop/Tesi/appoggio.py", line 78, in <module> var = numpy.vstack(var) File "/usr/lib/python2.7/dist-packages/numpy/core/shape_base.py", line 226, in vstack return _nx.concatenate(map(atleast_2d,tup),0) ValueError: all the input array dimensions except for the concatenation axis must match exactly –  Elvio Mar 20 at 14:33
1  
+1 I checked the docs, Looks good to me –  Aaron Hall Mar 20 at 14:49
1  
@Elvio All elements of a numpy array must have the same shape, this is simply saying that all elements do not have the same shape. The data that you are working with appears to be different then what is shown, can you please update your post with relevant data. –  Ophion Mar 20 at 14:53
    
@Ophion can you try with this data, please? gist.github.com/worm1988/9af484900aac7db3a5f1 –  Elvio Mar 20 at 15:05
2  
@Elvio The very last array has two elements while all other arrays only have one element. Splitting the last array into two fixes the problem, works fine with np.vstack. Please see Another option in my post. –  Ophion Mar 20 at 15:07
up vote 3 down vote

I don't know why your approach isn't working, but this worked for me:

>>> import numpy as np
>>> from numpy import array
>>> var=[array([ 33.85967782]), array([ 34.07298272]), array([ 35.06835424])]
>>> np.array(var)
array([[ 33.85967782],
       [ 34.07298272],
       [ 35.06835424]])

This also worked (fresh interpreter):

>>> import numpy as np
>>> var = [np.array([ 33.85967782]), np.array([ 34.07298272]), np.array([ 35.06835424])]
>>> np.array(var)
array([[ 33.85967782],
       [ 34.07298272],
       [ 35.06835424]])
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