For two arrays a and b,
a = np.array([[1],[2],[3],[4]])
b = np.array(['a', 'b', 'c', 'd'])
I want to generate the following array
c = np.array([[1, 'a'], [2, 'b'], [3, 'c'], [4, 'd']])
Is there a way to do this efficiently ?
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3 Answers
You need:
import numpy as np
a = np.array([[1],[2],[3],[4]])
b = np.array(['a', 'b', 'c', 'd'])
print(np.array(list(zip(np.concatenate(a), b))))
Output:
[[1, 'a'], [2, 'b'], [3, 'c'], [4, 'd']]
Alternate Solution
print(np.stack((np.concatenate(a), b), axis=1))
1 Comment
eugene
oh.. then would ` list(zip(np.concatenate(a), b)` be better? np.array(zip(np.concatenate(a), b)) returns weird object..
Solution
>>> import numpy as np
>>> a = np.array([[1],[2],[3],[4]])
>>> b = np.array(['a', 'b', 'c', 'd'])
# You have strange array so result is strange
>>> np.array([[a[i],b[i]] for i in range(a.shape[0])])
array([[array([1]), 'a'],
[array([2]), 'b'],
[array([3]), 'c'],
[array([4]), 'd']], dtype=object)
# You want this
>>> np.array([[a[i][0],b[i]] for i in range(a.shape[0])])
array([['1', 'a'],
['2', 'b'],
['3', 'c'],
['4', 'd']], dtype='<U11')
>>>
Note:
You may want to reshape your 'a' array.
>>> a.shape
(4, 1)
>>> a
array([[1],
[2],
[3],
[4]])
Reshape like this for easier use, for next time...
>>> a.reshape(4)
array([1, 2, 3, 4])
Comments
You can do:
c = np.vstack((a.flatten(), b)).T
