Metadata-Version: 2.4
Name: pandas-outliers
Version: 1.0.1
Summary: A simple library that adds .outliers() method to pandas DataFrame for easy outlier detection.
Home-page: https://pypi.org/project/pandas-outliers/
Author: Kiran Hamza
Author-email: 
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: scipy
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# 🧠 pandas-outliers

`pandas-outliers` is a simple and powerful Python library that extends the functionality of **Pandas DataFrames** by adding an easy one-line method to detect outliers in your data.

---

## 🚀 Features
✅ Detect outliers in any numeric column with **just one line**  
✅ Works with **IQR (Interquartile Range)**, **Z-score**, and **Isolation Forest** methods  
✅ 100% compatible with Pandas DataFrames  
✅ Lightweight, beginner-friendly, and fast  

---

## 💡 Installation
You can install it using pip:
```bash
pip install pandas-outliers

import pandas as pd
import pandas_outliers

# Sample data
data = pd.DataFrame({
    "age": [22, 23, 25, 45, 23, 24, 120],
    "salary": [25000, 27000, 26000, 28000, 1000000, 29000, 27500]
})

# Detect outliers in one line 👇
outliers = data.outliers()

print(outliers)

output
   age   salary
6   120  1000000


⚙️ Methods Supported

IQR (default) – detects values outside 1.5×IQR range

Z-score – detects data points beyond a given threshold

Isolation Forest – detects anomalies using machine learning

🧑‍💻 Author

Kiran Hamza
📍 Python & Data Science Enthusiast
💌 [Your Email or GitHub Profile Here]

🪪 License

This project is licensed under the MIT License — see the LICENSE
 file for details.

⭐ Tip: If you like this library, please star the repo or share it with your data science friends!


---

## 📜 2️⃣ LICENSE (MIT License — copy this into a file named `LICENSE`)
```text
MIT License

Copyright (c) 2025 Kiran Hamza

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights  
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell      
copies of the Software, and to permit persons to whom the Software is          
furnished to do so, subject to the following conditions:                       

The above copyright notice and this permission notice shall be included in     
all copies or substantial portions of the Software.                            

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR     
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,       
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE    
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER         
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,  
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE  
SOFTWARE.
