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Presentation . 2022
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Other literature type . 2022
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Einstieg in die Programmierung, mit, insbesondere, Python

descriptionPublicationkeyboard_double_arrow_right Presentation , Other literature type 24 Jun 2022 German Publisher:Zenodo
Authors: Wallace, David; Schieberle, Andreas;

doi: 10.5281/zenodo.6984248 , 10.5281/zenodo.6984247

Einstieg in die Programmierung, mit, insbesondere, Python

Abstract

Die HeFDI-Forschungsdatentage ermöglichen es Forschenden, Lehrenden und allen weiteren Interessierten, Themen und Angebote des Forschungsdatenmanagements (FDM) kennenzulernen und zu erproben. Zudem stellen verschiedene hessische Infrastruktur-Einrichtungen und Zentren ihre Dienste und Angebote vor. Die Forschungsdatentage sind ein Angebot der Landesinitiative HeFDI - Hessische Forschungsdateninfrastrukturen, welche vom Hessischen Ministerium für Wissenschaft und Kunst (HMWK) finanziert wird.

Das Warum und Wie eines Einstiegs ins Programmieren wird hier generell besprochen. Es gibt eine Vielfalt an Anwendungsmöglichkeiten und Technologien, um ins Programmieren einzusteigen. In dieser Session wird aber ein Beispiel der tabellierten Datenauswertung in Python - mithilfe eines interaktiven Interpreters - vorgetragen.

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Keywords

integrated development environment, Datenmodell, Lernstrategie, Interpreter, FDM, data collection, data aggregation, IDE, Integrierte Entwicklungsumgebung, Forschungsdatenmanagement, programming language, programming, documentation, data model, Automatisierung, data transformation, Tabelle, RDM, Dokumentation, informatics, Datentransformation, Datenerhebung, data validation, Programmiersprache, Werkzeug, FAIR data, FAIR principles, table (data arrengement), tool, learning strategy, Programmierung, Datenvalidierung, Datenaggregation, Daten, Datenverarbeitung, FAIR-Prinzipien, Informatik, data, automatisation, research data management, FAIRe Daten, data processing, Software, Python

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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