industryts 0.0.4

Python library that provides functions to manipulate time series collected from industrial contexts

Industry Time Series Library

Time Series Manipulation for Industry Data

This repository hosts the industry-ts: Industry Time Series Library --- a Python library that provides functions to manipulate time series collected from industrial contexts.

This project aims to address the necessity for open-source tools developed for solving problems with data collected from industrial process.

The modules introduced provide a variety of functions that are particularly tailored to industry data, directed to working with its most common issues, such as discontinuities in process measurements and faulty sensors.

Table of Contents

• Industry Time Series Library
  • Time Series Manipulation for Industry Data
  • Table of Contents
  • Main Features
  • How to use it
  • Documentation

Main Features

• Data Generation: Generate synthetic data from well defined stochastic processes for testing and benchmarking purposes.
• Modelling: Fit time series models to data.
• Preprocessing: Preprocess time series with filtering, feature engineering and other techniques.

How to use it

The package is available in PyPI, and can be installed with pip:

pip install industryts

Alternatively, to use the library, you can clone the repository and install it with pip:

git clone https://github.com/Industry-Time-Series/industry-ts.git
cd industry-ts
git checkout packaging
pip install .

Documentation

The official documentation is hosted on https://industry-time-series.github.io/industry-ts/