1

If I do

import numpy as np

l = np.array([1, 2, 3, 'A', 'B'], dtype=str)
print(l + l)

I get the error "numpy.core._exceptions.UFuncTypeError: ufunc 'add' did not contain a loop with signature matching types (dtype('<U3'), dtype('<U3')) -> dtype('<U3')"

I don't understand why something like this would happen, l surely has the same dtype as itself. If I also create a new array and try to add them both, this error will still occur, even after converting both dtypes to str.

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  • 1
    What do you expect to happen? Commented Jul 8, 2021 at 23:31
  • It's telling you it doesn't support the unicode dtype for that operation. Commented Jul 9, 2021 at 0:02
  • 1
    The error isn't complaining about different dtypes. It's a question of what does + mean when dealing with strings. Python strings defines it as join. + for numeric dtypes is addition. The numpy developers chose not to define it for string dtypes. For the most part, numpy does not have any fast compiled code for strings; the np.char functions all use Python's own string methods. Commented Jul 9, 2021 at 1:45

1 Answer 1

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4

Since you specified str type, I assume that the + operation you want is string concatenation. NumPy does not inherently map + to its broadcast operations in this context. Instead, use the documented operation char.add:

import numpy as np

l = np.array([1, 2, 3, 'A', 'B'], dtype=str)

print(l)
print(l[0] + l[1])
print(np.char.add(l, l))

Output:

['1' '2' '3' 'A' 'B']
12
['11' '22' '33' 'AA' 'BB']
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