V. Gónzalez-Pérez, P. Keil, Yachao Li, A. Zülke, R. Burrel, D. Csala, H. Hoster
{"title":"A Python Package to Preprocess the Data Produced by Novonix High-Precision Battery-Testers","authors":"V. Gónzalez-Pérez, P. Keil, Yachao Li, A. Zülke, R. Burrel, D. Csala, H. Hoster","doi":"10.5334/jors.281","DOIUrl":null,"url":null,"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.","PeriodicalId":37323,"journal":{"name":"Journal of Open Research Software","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Open Research Software","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5334/jors.281","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
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.