timedatamodel

A lightweight Pythonic data model for time series data, interoperable with NumPy, Pandas and Polars.

Features

• TimeSeries — univariate time series with metadata (name, unit, frequency, timezone, …); the underlying DataFrame is optional, so the same class also serves as a metadata-only descriptor for catalog/registration use

• Four data shapes — SIMPLE, VERSIONED, CORRECTED, AUDIT — model everything from standard point-in-time data to full audit trails

• Full interoperability with pandas, NumPy, Polars, and PyArrow via from_* / to_* methods

• Enum-based Frequency (ISO 8601 durations) and DataType annotations

• Optional pint unit support and unit-string validation

Getting Started

• Installation
• Overview
• Basic Usage

Examples

• Examples

API Reference

• API Reference