Metadata-Version: 2.4
Name: quantiletools
Version: 0.1.0
Summary: Custom quantile calculation tools using Hyndman & Fan (1996) methods.
Home-page: https://github.com/yourusername/quantiletools
Author: Subbiah
Author-email: subbiahbayes@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python
Dynamic: summary

# quantiletools

`quantiletools` is a Python package that implements the 9 quantile types defined in Hyndman & Fan (1996), with pure Python logic and no dependency on NumPy's `np.quantile()` methods.

---

## 🚀 Features

- Implements Types 1–9 from Hyndman & Fan (1996)
- No reliance on `np.quantile(method=...)`
- Dataset-level and group-level quantile summaries
- Fully vectorized for performance

---

## 📦 Installation

If downloaded locally:

```bash
pip install .

## 📚 Example Usage

```python
# Import from package 
from quantiletools import quantiles_for_vars, quantiles_by_group

# Example DataFrame
import pandas as pd
import numpy as np

df = pd.DataFrame({
    "X1": np.random.randn(10),
    "X2": np.random.randn(10),
    "Group": np.random.choice(["A", "B"], size=10)
})

# Compute quantiles
quantiles_for_vars(df, ["X1", "X2"], probs=[0.1, 0.5, 0.9], qtype=[1, 7])

