Perform EDA and diagnose data quality
Company: Citadel
Role: Data Scientist
Category: Data Manipulation (SQL/Python)
Difficulty: Medium
Interview Round: Technical Screen
Given a tabular dataset loaded into a pandas DataFrame, write code to perform exploratory data analysis end-to-end: inspect and report column data types, measure feature scales (min, max, mean, std) and identify potential outliers, check and summarize missing values (counts and percentages), compute basic summary statistics, and plot a correlation heatmap to highlight strongly related features. Conclude with a short written summary of quality issues and next steps to address them.
Quick Answer: This question evaluates proficiency in exploratory data analysis and data quality assessment using pandas and related tools, covering inspection of data types, summary statistics, missing-value diagnostics, outlier detection, and feature correlation.