Skip to main content

A library to detect and remove outliers using IQR.

Project description

IQR Outlier Detection Library

This Python package helps in detecting and removing outliers from a dataset using the Interquartile Range (IQR) method.

Features

  • Detects outliers using IQR.
  • Removes outliers from a dataset.
  • Works with Pandas DataFrames and Series.

Installation

pip install iqr-outlier

Import the package:

from iqr_outlier.detection import detect_outliers # Returns list with outliers
from iqr_outlier.removal import remove_outliers # Return a pandas series with outliers removed
import pandas as pd

Example

# Sample dataset
data = pd.Series([10, 12, 14, 15, 18, 20, 22, 24, 30, 100])

# Detect outliers
outliers = detect_outliers(data)
print("Outliers:", outliers.tolist())

# Remove outliers
cleaned_data = remove_outliers(data)
print("Cleaned Data:", cleaned_data.tolist())

Project Structure

iqr_outliers/
│-- iqr_outlier/
│   │-- __init__.py
│   │-- detection.py
│   │-- removal.py
│-- setup.py
│-- test.py
│-- README.md

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

iqr_outlier-0.1.4.tar.gz (1.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

iqr_outlier-0.1.4-py3-none-any.whl (1.7 kB view details)

Uploaded Python 3

File details

Details for the file iqr_outlier-0.1.4.tar.gz.

File metadata

  • Download URL: iqr_outlier-0.1.4.tar.gz
  • Upload date:
  • Size: 1.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.1

File hashes

Hashes for iqr_outlier-0.1.4.tar.gz
Algorithm Hash digest
SHA256 f8f948504532d04fb048c92706e5efc9134ee6fd9229b4fcc8e65e28867977ee
MD5 e5f42051cbdb4999bd35170b9842af0b
BLAKE2b-256 2f7f3cac21e65a64d7be11f46afd7ae9649641ea41ffb6f807612a45b19bc87f

See more details on using hashes here.

File details

Details for the file iqr_outlier-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: iqr_outlier-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 1.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.1

File hashes

Hashes for iqr_outlier-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 e5af6b104abe5a7d50d95cb42a0ae88572c00ed368a4350477e0a818cb02c318
MD5 e3d2e2ccfe12c5a06e85cf00df04aeca
BLAKE2b-256 960f882351fef3cd13dc02d754af7d62d3f168cdc76855995c16f4a0a4760990

See more details on using hashes here.

Supported by

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