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NumPy Arrays, dtypes and Scalars, what does print(a.dtype) print after a = np.array([1, 2.5, True])?

Block 1, Arrays, dtypes and Scalars, question 1 of the NumPy sample

import numpy as np
a = np.array([1, 2.5, True])
print(a.dtype)

What does this print?

  1. A. int64
  2. B. float64
  3. C. bool
  4. D. object
Show the answer and why each option is right or wrong

Answer, B. float64

A. int64
Assumes the two non float values outvote the single float and the dtype settles on int64.
B. float64
Correct. With bool, int and float all present, NumPy still promotes to the widest of the three, float64.
C. bool
Assumes the presence of a boolean anywhere forces the narrower bool dtype regardless of the other values.
D. object
Assumes a three way mix of value kinds is too ambiguous for a numeric dtype and falls back to object.

The promotion rule does not count votes, it only asks which dtype among those present can hold every value without loss. With int, float and bool together, float64 is that dtype, exactly as it would be with only two of the three kinds present.

The answer above is what NumPy 2.4.4 printed when the snippet was run, not what someone expected it to do.

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