Scientific Data: A 50 Steps Guide using Python
(Sprache: Englisch)
This guide provides a solid understanding of how to understand experimental data within a natural scientific context while ensuring sustainable use of findings and processing as seen through a programmer's eye. The concise problem - solution - discussion...
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This guide provides a solid understanding of how to understand experimental data within a natural scientific context while ensuring sustainable use of findings and processing as seen through a programmer's eye. The concise problem - solution - discussion structure used throughout supported by Python code snippets emphasizes the book's focus on practitioners.
Autoren-Porträt von Matthias Hofmann
Matthias Hofmann holds a Ph.D. in Physical Chemistry from the University of Regensburg. At Albert Invent, Matthias continues to contribute to innovative methods in natural science research and accelerating R&D through a data-driven approach.He is the author of "Data Management for Natural Scientists - A Practical Guide to Data Extraction and Storage Using Python".
Bibliographische Angaben
- Autor: Matthias Hofmann
- 2024, 250 Seiten, 85 farbige Abbildungen, Englisch
- Verlag: Walter de Gruyter
- ISBN-10: 3111334570
- ISBN-13: 9783111334578
- Erscheinungsdatum: 23.09.2024
Sprache:
Englisch
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