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Data Tome\n\n[![Latest Release](https://img.shields.io/github/v/release/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome/releases)\n[![PlatformIO Registry](https://badges.registry.platformio.org/packages/alexandrehiroyuki/library/DataTome.svg)](https://registry.platformio.org/libraries/alexandrehiroyuki/DataTome)\n[![Latest Release Date](https://img.shields.io/github/release-date/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome/releases)\n[![Last Commit Date](https://img.shields.io/github/last-commit/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome/commits/master)\n\n[![GitHub Stars](https://img.shields.io/github/stars/AlexandreHiroyuki/DataTome?style=flat\u0026color=yellow)](https://github.com/AlexandreHiroyuki/DataTome/stargazers)\n[![Contributors](https://img.shields.io/github/contributors-anon/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome/graphs/contributors)\n[![Top Language](https://img.shields.io/github/languages/top/AlexandreHiroyuki/DataTome)](https://github.com/AlexandreHiroyuki/DataTome)\n\n\u003cp align=\"center\"\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/AlexandreHiroyuki/DataTome/main/docs/icon.png\" width=\"128\" height=\"128\" /\u003e\n\u003c/p\u003e\n\n## Description\n\nData Tome is a C++ library for data analysis and data filtering on embedded devices (IoT). Focus on the developer's experience and performance.\n\n- Simple Moving Average (SMA). \n- Exponential Moving Average (EMA).\n- Cumulative Average (CA).\n- Simple Moving Median (implemented on DataTomeAnalysis).\n- Variance, Standard Deviation, and more.\n\n## Getting Started\n\n- This library is listed in the official [Arduino Library Manager](https://www.arduino.cc/reference/en/libraries/datatome/).\n- _**—Recommended Platform—**_ Use the [PlatformIO Registry](https://registry.platformio.org/libraries/alexandrehiroyuki/DataTome) to install the library!\n- You can see the source code at the [GitHub Repository](https://github.com/AlexandreHiroyuki/DataTome).\n- To avoid duplicating data for smaller samples of the same data, _[check the Partials feature](https://alexandrehiroyuki.github.io/DataTomeDocs/docs/category/partials)_!\n\n## Documentation\n\nThis library calculates statistical functions using a time-series sample implemented with a circular array that improves the performance.\n\n- Online Docs: _[Click here to see the full documentation](https://alexandrehiroyuki.github.io/DataTomeDocs/)_\n\n- Docs GitHub Repository: _[The documentation is coded with docusaurus, and you can visit the repository](https://github.com/AlexandreHiroyuki/DataTomeDocs)_\n\n## Contributing\n\n[Read here how to contribute](https://github.com/AlexandreHiroyuki/DataTome/blob/master/CONTRIBUTING.md).\n\nIt describes how to report issues, code conventions, testing, and how to publish a package on the PlatformIO Registry.\n\n## Developed by\n\n**Alexandre Hiroyuki** – [GitHub](https://github.com/AlexandreHiroyuki) – [LinkedIn](https://www.linkedin.com/in/alexandre-hiroyuki-yamauchi/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falexandrehiroyuki%2Fdatatome","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falexandrehiroyuki%2Fdatatome","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falexandrehiroyuki%2Fdatatome/lists"}