author: Yisong Chen

Maintained as a lightweight toolkit for quick outlier analysis workflows.

Outlier Detection Tool

Detect outliers in 2D (x, y) datasets using Cook's distance.

Install (editable / dev)

python3 -m pip install -e .[dev]

Quickstart

from outlier_detection_tool import detect_outliers, summarize_outliers

df = detect_outliers("data/data.csv", threshold=0.5)
print(summarize_outliers(df))

CLI

outlier-detect --input data/data.csv --threshold 0.5 --output output_with_outliers.csv

Development

python -m venv .venv
. .venv/bin/activate
pip install -e '.[dev]'
pytest -q