Metadata-Version: 2.4
Name: dynamicts
Version: 0.1.4
Summary: A library for time series analysis and preprocessing
Home-page: https://github.com/Chinar-Quantum-AI-Ltd/DynamicTS
Author: Chinar-Quantum-AI-Ltd
Author-email: engineering@chinarqai.com
License: MIT
Project-URL: Issue Tracker, https://github.com/Chinar-Quantum-AI-Ltd/DynamicTS/issues
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Requires-Dist: ensure>=1.0.2
Requires-Dist: pandas>=2.0.2
Requires-Dist: numpy>=1.24.4
Requires-Dist: matplotlib>=3.7.5
Requires-Dist: statsmodels>=0.14.1
Provides-Extra: testing
Requires-Dist: pytest>=7.1.3; extra == "testing"
Requires-Dist: mypy>=0.971; extra == "testing"
Requires-Dist: flake8>=5.0.4; extra == "testing"
Requires-Dist: tox>=3.25.1; extra == "testing"
Requires-Dist: black>=22.8.0; extra == "testing"
Dynamic: author
Dynamic: author-email
Dynamic: description
Dynamic: home-page
Dynamic: project-url
Dynamic: summary

# DynamicTS

A Python library for time series analysis and preprocessing.

## Modules
- statistical_measures.py: Rolling stats, moving averages, missing detection, visuals
- stationarity.py: ADF test, rolling stat visuals
- smoothing.py: Simple exponential smoothing, plotting
- correlation.py: ACF, PACF, lag matrix
- summary.py: Summary and combined plots

## Requirements
- pandas
- numpy
- matplotlib
- statsmodels

## Usage
Import the modules and use the functions as needed for your time series analysis workflow.
