https://github.com/tommygrammar/eventimpact
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..
https://github.com/tommygrammar/eventimpact
Last synced: 8 days ago
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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..
- Host: GitHub
- URL: https://github.com/tommygrammar/eventimpact
- Owner: tommygrammar
- License: mit
- Created: 2025-05-11T16:12:25.000Z (12 days ago)
- Default Branch: blackgrammar-projects
- Last Pushed: 2025-05-11T16:16:22.000Z (12 days ago)
- Last Synced: 2025-05-11T17:26:37.044Z (12 days ago)
- Language: Python
- Size: 5.86 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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
```
Find it on pypi as:
```link
https://pypi.org/project/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?