Skip to main content

Outlier detection

Project description

Outlyzer -A Python package to detect outliers in a dataset

Outlyzer is a Python library that provides various methods for detecting outliers in a dataset. It includes implementation of Z-score, IQR, and Mahalanobis distance methods for identifying outliers, as well as visualization-based methods using scatter plots, box plots, and other types of visualizations.

Installation

You can install Outlyzer using pip:

pip install outlyzer

Usage:

- Import the desired method from the library, e.g.:
    from Outlyzer.zscore import detect_outliers_zscore        
    from Outlyzer.iqr import detect_outliers_iqr

- Pass your dataset or data series to the respective function, e.g.:
    outliers_zscore = detect_outliers_zscore(data)
    outliers_iqr = detect_outliers_iqr(data)

The functions will return a boolean array indicating whether each data point is an outlier (True) or not (False).

Star History Chart

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

Outlyzer-0.0.4.tar.gz (8.0 kB view hashes)

Uploaded Source

Built Distribution

Outlyzer-0.0.4-py3-none-any.whl (9.6 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page