September 2024
Intermediate to advanced
416 pages
13h 8m
German
Content preview from Praktisches Python Data Wrangling und Datenqualität
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Anhang C. Daten finden
Im Allgemeinen gibt es auf vier "Quellen" für Daten, auf die du zurückgreifen kannst, wenn du versuchst, eine Frage über die Welt zu beantworten. Ich setze "Quellen" in Anführungszeichen, weil es sich dabei wirklich um Quellen handelt und nicht um bestimmte Websites, Datenbanken oder sogar Organisationen. Stattdessen handelt es sich um die Mechanismen, die Journalisten, Forscher und andere Fachleute nutzen, um Daten über die Welt zu sammeln, um ihre Fragen zu beantworten.
Datenarchive und APIs
Der Zugang zu "offenen Daten" ist zunehmend ein Merkmal vieler staatlicher und wissenschaftlicher Organisationen geworden, um die Transparenz, Rechenschaftspflicht und - vor allem in der Wissenschaft - die Reproduzierbarkeit zu verbessern. Das bedeutet, dass viele Behörden, gemeinnützige Organisationen und wissenschaftliche Zeitschriften Webseiten unterhalten, auf denen du strukturierte Daten zu ihrer Arbeit finden kannst. Eine einfache Websuche nach "nyc open data" oder "baltimore open data" bringt dich zum Beispiel zu den "Open Data"-Portalen dieser Städte; eine ähnliche Suche nach "johannesburg open data" bringt dich zunächst zur Website des South African Cities Open Data Almanac (SCODA), aber ein paar Links weiter findest du weitere Datensätze von einer Organisation namens "DataFirst" sowie das South African Data Portal unter http://opendataforafrica.org. Auf all diesen Seiten findest du Daten - aber wie in Kapitel 3 beschrieben, kann die Qualität dieser Daten ...
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