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).
Project details
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Outlyzer-0.0.4.tar.gz
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