{"title":"Python for Atmosphere and Ocean Scientists","authors":"Damien B. Irving","doi":"10.21105/JOSE.00037","DOIUrl":null,"url":null,"abstract":"Python is rapidly emerging as the programming language of choice for data analysis in the atmosphere and ocean sciences. By consulting online tutorials and help pages, most researchers in this community are able to pick up the basic syntax and programming constructs (e.g., loops, lists and conditionals). This self-taught knowledge is sufficient to get work done, but it often involves spending hours to do things that should take minutes, reinventing a lot of wheels, and a nagging uncertainty at the end of it all regarding the reliability and reproducibility of the results. To help address these issues, the Python for Atmosphere and Ocean Scientists educational materials cover a suite of programming and data management best practices that are not so easy to glean from a quick Google search.","PeriodicalId":75094,"journal":{"name":"The Journal of open source education","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of open source education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21105/JOSE.00037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Python is rapidly emerging as the programming language of choice for data analysis in the atmosphere and ocean sciences. By consulting online tutorials and help pages, most researchers in this community are able to pick up the basic syntax and programming constructs (e.g., loops, lists and conditionals). This self-taught knowledge is sufficient to get work done, but it often involves spending hours to do things that should take minutes, reinventing a lot of wheels, and a nagging uncertainty at the end of it all regarding the reliability and reproducibility of the results. To help address these issues, the Python for Atmosphere and Ocean Scientists educational materials cover a suite of programming and data management best practices that are not so easy to glean from a quick Google search.
Python正迅速成为大气和海洋科学中数据分析的首选编程语言。通过查阅在线教程和帮助页面,该社区的大多数研究人员都能够掌握基本的语法和编程结构(例如循环、列表和条件)。这些自学成才的知识足以完成工作,但它通常需要花费数小时来做一些需要几分钟时间的事情,重新发明很多轮子,以及最后关于结果的可靠性和可重复性的令人不安的不确定性。为了帮助解决这些问题,Python for Atmosphere and Ocean Scientists的教材涵盖了一套编程和数据管理的最佳实践,这些实践不太容易从谷歌快速搜索中收集到。