outlier-detective

What problem does it solve?

This Skill helps identify and manage unusual or anomalous data points within datasets, which is crucial for data quality, fraud detection, and accurate analysis.

Core Features & Use Cases

• Statistical Methods: Detect outliers using Z-score, IQR, and Modified Z-score.
• ML Methods: Employ Isolation Forest and LOF for more complex anomaly detection.
• Visualization: Generate box plots and distribution plots to visually inspect outliers.
• Use Case: Clean a sales dataset by removing or flagging transactions with unusually high or low values before performing trend analysis.

Quick Start

Use the outlier-detective skill to find outliers in the 'revenue' column of your 'sales_data.csv' file using the IQR method.