How to create a 2d numpy ndarray using two list comprehensions

Question

I tried to create a 2D numpy ndarray using the following code:

temp = np.array([[np.mean(w2v[word]) for word in docs if word in w2v] for docs in X[:5]])

temp has a shape of (5,) instead of expected (5,x).

Also temps's data structure is like: array([list([.....],...)])

It seems that the inner list is not converted to ndarray.

Most likely the inner lists differ in length. It can make a 2d array from that, so it just makes a 1d containing their pointers. In effect an array equivalent of the original list. — hpaulj
– hpaulj, Commented Nov 18, 2018 at 7:31

Dinari · Accepted Answer · 2018-11-18 07:32:24Z

1

Your missing np.array in there, it should be:

temp = np.array([np.array([np.mean(w2v[word]) for word in docs if word in w2v] for docs in X[:5])])

Running example:

bob
Out[70]: [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

tmp = np.array([np.array([x for x in Y]) for Y in bob])

tmp
Out[72]: 
array([[1, 2, 3],
       [4, 5, 6],
       [7, 8, 9]])

answered Nov 18, 2018 at 7:32

Dinari

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1 Comment

Dinari Over a year ago

Note that as @hpaulj commented, np can't really handle not squared 2d matrices, in which case you will have an array of np arrays.

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