NumPy assigns different string dytpes when mixing types in np.array() because:

It promotes all elements to a common type (string, in this case).The resulting d type is determined by the length of the longest string representation of any element.The order of elements affects how NumPy infers the common type and can lead to differing results <u4,<u5,<u32 etc.