Create a matrix from a list of list of tuples using a list comprehension
I have a list of lists of tuples list1
list1 = [[('a',0.01),('b',0.23),('c',1e-7)],
[('a',0.91),('b',0.067),('c',0.38)]]
and I want to create a numpy matrix where each row will be the second value of the tuple in list1
. Thus, the matrix, let's call it A
, has the form
A = [[0.01,0.23,1e-7],[0.91,0.067,0.38]] A.shape >>> (2,3)
So far, I've managed to achieve this in a slow and inefficient way.
A = []
for i in range(len(list1)):
A.append(np.array([v for k,v in list1[i]]))
A = np.array(A)
How can I do this using a list comprehension?
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1 answer
To do this, you need nested lists:
np.array([[tup[1] for tup in lst] for lst in list1])
Out:
array([[ 1.00000000e-02, 2.30000000e-01, 1.00000000e-07],
[ 9.10000000e-01, 6.70000000e-02, 3.80000000e-01]])
The best solution would be:
np.array(list1)[:,:,1].astype('float')
Out:
array([[ 1.00000000e-02, 2.30000000e-01, 1.00000000e-07],
[ 9.10000000e-01, 6.70000000e-02, 3.80000000e-01]])
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