Merging 2 numpy arrays into a dictionary-CodePudding

I have 2 numpy darrays and want to create a dictionary from them. For example {(7.9,3.8,6.4,2): 2}

import numpy as np

little_X_test= np.array([[7.9, 3.8, 6.4, 2],
 [5.2, 4.1, 1.5, 0.1],
 [6.9, 3.1, 5.1, 2.3]])
little_y_test= np.array([2, 0, 2])

d = {}
for A, B in zip(little_X_test, little_y_test):
    d[A] = B

Error message

TypeError: unhashable type: 'numpy.ndarray'

CodePudding user response：

Numpy arrays, lists, and other mutable object are non hashable.

If you convert to tuple this works as the object is immutable.

NB. You don't have to use a loop, use the dict constructor directly

import numpy as np

little_X_test= np.array([[7.9, 3.8, 6.4, 2],
                         [5.2, 4.1, 1.5, 0.1],
                         [6.9, 3.1, 5.1, 2.3]])
little_y_test= np.array([2, 0, 2])

d = dict(zip(map(tuple, little_X_test), little_y_test))

output:

>>> d
{(7.9, 3.8, 6.4, 2.0): 2,
 (5.2, 4.1, 1.5, 0.1): 0,
 (6.9, 3.1, 5.1, 2.3): 2}