outlipy 0.1.0a1

A Python library for outlier detection and handling.

OutliPy

OutliPy is a lightweight, object-oriented Python library built on top of Pandas and NumPy for detecting and handling outliers in tabular data.

Key Features

1. Pandas Accessor: Use the fluent df.outli. API for detection and handling.

2. Robust Validation: Intelligent column validation and clear, custom error messages (e.g., missing columns, zero-variance data).

3. Outlier Detection: Users can easily switch between methods or customize detection sensitivity. Automatically detect outliers using multiple statistical methods such as

   • Interquartile Range (IQR)
   • Z-score
   • Percentile thresholds
   • Modified Absolute Deviation

4. Outlier Handling: Choose how to deal with detected outliers:

   • Remove outliers from your dataset
   • Cap or replace them with defined limits or mean/median values
   • grouped handling

Where to find it? and Installation

The Github Repository is found here: https://github.com/kbbn-debugger/OutliPy

Installation

pip install outlipy

Dependencies

Pandas - The main structure of this library.

Numpy - Heavily relies on computation.

License

BSD 3

Documentation

[Under construction]