How do I get the key from dictionary of numpy.array() in python

Question

I have a dictionary that has numpy.array() as a values:

dictionary = {0: array([11,  0,  2,  0]), 1: array([  2,   0,   1, 100]), 1: array([  5,   10,   1, 100])}

I want to get key of specific value, e.g: [11, 0, 2, 0]. So, I wrote this code:

print(list(a_dictionary.keys())[list(a_dictionary.values()).index([11,  0,  2,  0])])

But it gives me an error: ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

How to handle this? Is there any other way to get a key of specific list value in dictionary?

python_user · Accepted Answer · 2020-10-22 14:30:03Z

1

You can use np.array_equal to check if two numpy arrays are equal. The following code will set key_needed to the key in dictionary if the elements match, if there is no value with that numpy array key_needed will be None.

If there are multiple keys that have the same numpy array this will return only the first occurrence.

import numpy as np

d={0: np.array([11,  0,  2,  0]), 1: np.array([  2,   0,   1, 100]), 1: np.array([  5,   10,   1, 100])}

value_to_search=[11, 0, 2, 0]

value_to_search=np.array(value_to_search)

key_needed=None

for key in d:
    if np.array_equal(d[key],value_to_search):
        key_needed=key
        break

print(key_needed) # 0

answered Oct 22, 2020 at 14:30

python_user

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1 Comment

python_user Over a year ago

np :), if you want a one liner version where the array values can be in multiple keys you can try this key_needed=[k for k,v in d.items() if np.array_equal(v,value_to_search)]. An empty list [] if no values are present and a list that has the keys if the keys are duplicate.

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