How to convert Nnumpy array to a dictionary in Python?

Question

Hi guys how would I go on converting numpy arrays as such:

[[  8.82847075  -5.70925653]
 [  1.07032615  -1.77975378]
 [-10.41163742  -0.33042086]
 [  0.23799394   5.5978591 ]
 [  7.7386861   -4.16523845]]

To what I desire in Python 3.10. That includes having the keys and values rounded to the nearest integer:

{'9':-6, '1':-2, '-10':0, '0':6, '8':-4}

EuxhenH · Accepted Answer · 2021-11-01 23:10:15Z

1

The following should work

a = np.round(a)
d = dict(zip(a[:, 0].astype(str), a[:, 1]))

Note: Equal keys will merge.

answered Nov 1, 2021 at 23:10

EuxhenH

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2 Comments

Ruben Gutierrez Over a year ago

What do you mean by "Equal keys will merge"? Isn't that a characteristic of dictionaries where all the keys have to be unique or am I getting this wrong?

EuxhenH Over a year ago

Yes! I mean, if a key appears twice, then the latter one will replace the former. For example, if a=[[1, 2], [1, 3]], then d={'1':3}.

Onyambu · Accepted Answer · 2021-11-01 23:09:22Z

1

dict(zip(*d.round().astype(int).T))
Out: {9: -6, 1: -2, -10: 0, 0: 6, 8: -4}

The data

d = np.array([[  8.82847075,  -5.70925653],
       [  1.07032615,  -1.77975378],
       [-10.41163742,  -0.33042086],
       [  0.23799394,   5.5978591 ],
       [  7.7386861 ,  -4.16523845]])

answered Nov 1, 2021 at 23:09

Onyambu

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Comments

Anthony Aniobi · Accepted Answer · 2021-12-08 23:58:09Z

0

You can convert array to dictionary without any external library. this method uses list comprehension:

assuming input array is in_array and the output dictionary is out_dict

out_dict = {int(x[0]):int(x[1]) for x in in_array}

edited Dec 8, 2021 at 23:58

answered Nov 1, 2021 at 23:03

Anthony Aniobi

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