How do I change id values in a numpy array to a string numpy array with a dictionary

Question

I'm working on a script that converts ids of school names to actual school names structured in a numpy array.

For example

[[1,2,3],[3,6,7]]

becomes

[[school-a,school-b,school-c],[school-c,school-f,school-g]

The school and ids sit together in a python dictionary.

I've tried doing this:

for x in np.nditer(finalarray, op_flags=['readwrite']):
    x[...] = school_ids.get(int(x))
    print(school_ids.get(int(x)))
print(finalarray)

but that gave the error:

ValueError: invalid literal for int() with base 10: 'school-a'

it's important that the structure of the numpy array stays the same, because I also thought of just iterating every item, but then the structure is lost.

Answer 1

Using the solution from this post :

x = np.array([[1,1,3], [2,2,2]])
d = {1: 'a', 2:'b', 3:'c'}
np.vectorize(d.get)(x)
>> array([['a', 'a', 'c'],
   ['b', 'b', 'b']], dtype=object)

Answer 2

suppose I have a dict :

dictt = {
    0: 'school-a',
    1: 'school-b',
    2: 'school-c',
    3: 'school-d',
    4: 'school-e',
    5: 'school-f',
    6: 'school-g',
    7: 'school-h',
    8: 'school-i'
}

_ids = np.array([[1,2,3],[3,6,7]])
school_ids = np.array(list(dictt.values()))
print school_ids[_ids-1]

got:

[['school-a' 'school-b' 'school-c']
 ['school-c' 'school-f' 'school-g']]