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A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers. / Gonzalez-Perez, V.; Keil, P.; Li, Y. et al.
In: Journal of Open Research Software, Vol. 8, 04.03.2020, p. 1-5.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Gonzalez-Perez, V, Keil, P, Li, Y, Zülke, A, Burrel, R, Csala, D & Hoster, H 2020, 'A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers', Journal of Open Research Software, vol. 8, pp. 1-5. https://doi.org/10.5334/jors.281

APA

Gonzalez-Perez, V., Keil, P., Li, Y., Zülke, A., Burrel, R., Csala, D., & Hoster, H. (2020). A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers. Journal of Open Research Software, 8, 1-5. https://doi.org/10.5334/jors.281

Vancouver

Gonzalez-Perez V, Keil P, Li Y, Zülke A, Burrel R, Csala D et al. A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers. Journal of Open Research Software. 2020 Mar 4;8:1-5. doi: 10.5334/jors.281

Author

Gonzalez-Perez, V. ; Keil, P. ; Li, Y. et al. / A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers. In: Journal of Open Research Software. 2020 ; Vol. 8. pp. 1-5.

Bibtex

@article{8a897258681c41b28481f9d7f7d6ba40,
title = "A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers",
abstract = "We present preparenovonix, a Python package that handles common issues encountered in data fles generated with a range of software versions from the Novonix battery-testers. This package can also add extra information that makes easier coulombic counting and relating a measurement to the experimental protocol. The package provides a master function that can run at once the cleaning and adding derived information, with fexibility to choose only some features. There is a separate function to simply read a column by its given name. The usage of all the functions is documented in the code including examples. The code presented here can be installed either as a python package or from a GitHub repository.",
keywords = "Batteries, Battery-testers, Clean data, Data, Novonix, Python",
author = "V. Gonzalez-Perez and P. Keil and Y. Li and A. Z{\"u}lke and R. Burrel and D. Csala and H. Hoster",
year = "2020",
month = mar,
day = "4",
doi = "10.5334/jors.281",
language = "English",
volume = "8",
pages = "1--5",
journal = "Journal of Open Research Software",
issn = "2049-9647",
publisher = "Ubiquity Press Ltd.",

}

RIS

TY - JOUR

T1 - A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers

AU - Gonzalez-Perez, V.

AU - Keil, P.

AU - Li, Y.

AU - Zülke, A.

AU - Burrel, R.

AU - Csala, D.

AU - Hoster, H.

PY - 2020/3/4

Y1 - 2020/3/4

N2 - We present preparenovonix, a Python package that handles common issues encountered in data fles generated with a range of software versions from the Novonix battery-testers. This package can also add extra information that makes easier coulombic counting and relating a measurement to the experimental protocol. The package provides a master function that can run at once the cleaning and adding derived information, with fexibility to choose only some features. There is a separate function to simply read a column by its given name. The usage of all the functions is documented in the code including examples. The code presented here can be installed either as a python package or from a GitHub repository.

AB - We present preparenovonix, a Python package that handles common issues encountered in data fles generated with a range of software versions from the Novonix battery-testers. This package can also add extra information that makes easier coulombic counting and relating a measurement to the experimental protocol. The package provides a master function that can run at once the cleaning and adding derived information, with fexibility to choose only some features. There is a separate function to simply read a column by its given name. The usage of all the functions is documented in the code including examples. The code presented here can be installed either as a python package or from a GitHub repository.

KW - Batteries

KW - Battery-testers

KW - Clean data

KW - Data

KW - Novonix

KW - Python

U2 - 10.5334/jors.281

DO - 10.5334/jors.281

M3 - Journal article

VL - 8

SP - 1

EP - 5

JO - Journal of Open Research Software

JF - Journal of Open Research Software

SN - 2049-9647

ER -