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arXiv · 2310.14427

CMDA: a tool for Continuous Monitoring Data Analysis

Pejman Farhadi Ghalati·Andreas Schuppert
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Abstract

Over the last few years, with the growth of time-series collecting and storing, there has been a great demand for tools and software for temporal data engineering and modeling. This paper presents a generic workflow for time series data research, including temporal data importing, preprocessing, and feature extraction. This framework is developed and built as a robust and easy-to-use Python package, called CMDA, with a modular structure that offers tools to prepare raw data, allowing both scientists and non-experts to analyze various temporal data structures.

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Pejman Farhadi Ghalati, Andreas Schuppert. 2023-10-22. CMDA: a tool for Continuous Monitoring Data Analysis. https://arxiv.org/abs/2310.14427

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