How do I approach Data Manipulation (SQL/Python) interview questions?

Data Manipulation (SQL/Python) questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master data manipulation (sql/python) interviews.

What difficulty level is this interview question?

This is a Medium difficulty Data Manipulation (SQL/Python) question, commonly asked during Technical Screen rounds at Aeonea.

What role is this question designed for?

This question is commonly asked for Software Engineer candidates at Aeonea during technical interviews.

Fill missing values with means | Aeonea Interview Question

Fill missing values with means

Last updated: Mar 29, 2026

Quick Overview

This question evaluates proficiency in missing-data imputation and pandas DataFrame manipulation, testing skills in column-wise aggregation, group-wise operations, and edge-case handling within the Data Manipulation (SQL/Python) domain.

Aeonea

Sep 6, 2025, 12:00 AM

Software Engineer

Technical Screen

Data Manipulation (SQL/Python)

You are given a pandas DataFrame df with missing values in multiple numeric columns. Write a concise pandas expression to replace NaNs in each numeric column with that column's mean while leaving non-numeric columns unchanged. Also explain how you would: (a) perform the operation in-place, (b) compute and apply per-group means based on a key column (e.g., 'group'), and (c) skip columns whose values are all NaN.

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