[Solved] Why does np.mean() return a float even when all array elements are integers? — Ans: Because mean is an average which can be fractional, so output is float | NumPy

NumPy - Aggregation Functions

Why does np.mean() return a float even when all array elements are integers?

ABecause mean is an average which can be fractional, so output is float

BBecause NumPy converts all integers to floats internally

CBecause <code>np.mean()</code> always returns a string

DBecause the array must contain floats to use <code>np.mean()</code>

Step-by-Step Solution

Solution:

Step 1: Understand what mean represents
Mean is the sum divided by count, which can produce fractional values.
Step 2: Explain data type of result
To represent fractional results, np.mean() returns a float even if input is integer.
Final Answer:
Because mean is an average which can be fractional, so output is float -> Option A
Quick Check:
Mean output is float to handle fractions [OK]

Quick Trick: Mean can be fractional, so output is float [OK]

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Why does np.mean() return a float even when all array elements are integers?