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dc.contributor.authorStadler, Konstantin
dc.date.accessioned2018-07-27T09:38:21Z
dc.date.available2018-07-27T09:38:21Z
dc.date.created2018-01-03T13:52:27Z
dc.date.issued2017
dc.identifier.citationThe Journal of Open Source Software. 2017, 2 (16), 332-332.nb_NO
dc.identifier.issn2475-9066
dc.identifier.urihttp://hdl.handle.net/11250/2506671
dc.description.abstractGathering the data basis for regional to global models and scenarios in many scientific fields regularly requires the parsing of multiple data sources. In particular for data related to economic (national accounts, trade statistics, etc.) and environmental (climate, ecosystem descriptions, etc.) variables, these data are mostly categorised per country. There is, however, no single standard of how to name or specify individual countries. As a consequence, parsing routines need to be adopted for each used data source.nb_NO
dc.language.isoengnb_NO
dc.publisherJournal of Open Source Softwarenb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleThe country converter coco - a Python package for converting country names between different classification schemesnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.source.pagenumber332-332nb_NO
dc.source.volume2nb_NO
dc.source.journalThe Journal of Open Source Softwarenb_NO
dc.source.issue16nb_NO
dc.identifier.doi10.21105/joss.00332
dc.identifier.cristin1534913
dc.description.localcode© 2017 Authors of JOSS papers retain copyright. This work is licensed under a Creative Commons Attribution 4.0 International License.nb_NO
cristin.unitcode194,64,25,0
cristin.unitnameInstitutt for energi- og prosessteknikk
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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