outlier-detection-and-quality-assessment

What problem does it solve?

This Skill helps data analysts and engineers detect anomalies and evaluate data distribution quality, improving data integrity for downstream analysis.

Core Features & Use Cases

• Anomaly Detection: Uses IQR method to identify outliers in numerical datasets.
• Data Distribution Analysis: Conducts skewness and kurtosis evaluations to understand data shape.
• Use Case: Detect abnormal sales figures in a large dataset to flag potential errors or fraud, ensuring accurate reporting.
• Visualization: Generates boxplots to visually identify data spread and outliers, supporting data cleaning efforts.
• Quality Assessment: Provides insights into data distribution characteristics to inform preprocessing steps.

Quick Start

Load your Excel dataset, run the script, and visualize outliers with a single command to identify problematic data points instantly.