Metadata-Version: 2.4
Name: eventimpact
Version: 0.1.0
Summary: Bayesian impact analysis for bounded events on time-series metrics.
Author-email: Tom Muga <tonmuga@gmail.com>
License-Expression: MIT
Keywords: bayesian,promotion,impact,time-series,analytics
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.26.4
Requires-Dist: scipy>=1.11.4
Requires-Dist: matplotlib>=3.6.3
Dynamic: license-file

# EventImpact Python Library

A lightweight, production‑grade Python toolkit to quantify the impact of any bounded event
(e.g. limited‑time promotion, marketing campaign, feature release) on a time‑series metric.

---

## 📥 Installation

```bash
pip install eventimpact
```

## Interpretation
- The higher the **p_positive**, the more the evidence of a stronger effect.
- The **Immediate Effect** represents the immediate jump that occured in response to the event.
- The **Slope Effect** represents the after effect after the immediate jump. Did the effect sustain or was it weaker? 

