Why Does NumPy Fill Return Integers After Casting? Quick Fix Explained

Introduction

Hello, I'm Pipi. Recently a member in a Python group asked about a data‑analysis problem involving NumPy array filling.

Problem

The user forced a type conversion and used numpy.fill, but the resulting array remained integer, whereas they expected array([2.5, 2.5, 2.5, 2.5]).

Solution

The issue is that the variable a was not reassigned after conversion, so its dtype stayed as int. Reassigning a (e.g., a = a.astype(float)) allows the subsequent fill to produce a float array, or you can directly call a.fill(2.5) on a float‑typed array.

Conclusion

This short guide demonstrates how to correctly handle type casting and filling in NumPy, helping readers avoid a subtle pitfall. It also offers practical advice for asking technical questions, such as providing sanitized demo data and clear error screenshots.