September 2024
Intermediate to advanced
568 pages
14h 25m
German
Content preview from Datenvisualisierung mit Python und JavaScript, 2.
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Kapitel 12. Die Bereitstellung der Daten
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In Kapitel 6 wurde gezeigt, wie du mit einem Web Scraper deine Daten aus dem Internet holen kannst. Wir haben Scrapy verwendet, um einen Datensatz von Nobelpreisträgern zu holen, und in den Kapiteln 9 und 11 haben wir den Nobelpreis-Datensatz mit Pandas bereinigt und erforscht.
In diesem Kapitel lernst du am Beispiel unseres Nobelpreis-Datensatzes, wie du Daten statisch oder dynamisch von einem Python-Server an JavaScript auf dem Client-Browser übermitteln kannst. Diese Daten sind im JSON-Format gespeichert und bestehen aus einer Liste von Nobelpreisträger-Objekten, wie in Beispiel 12-1 gezeigt.
Beispiel 12-1. Unsere Nobelpreis-JSON-Daten, gescraped und dann bereinigt
[{"category":"Physiology or Medicine","country":"Argentina","date_of_birth":"1927-10-08T00:00:00.000Z","date_of_death":"2002-03-24T00:00:00.000Z","gender":"male","link":"http:\/\/en.wikipedia.org\/wiki\/C%C3%A9sar_Milstein","name":"C\u00e9sar Milstein","place_of_birth":"Bah\u00eda Blanca , Argentina","place_of_death":"Cambridge , England","text":"C\u00e9sar Milstein , Physiology or Medicine, 1984","year":1984,"award_age":57,"born_in":"","bio_image":"full/6bf65058d573e07b72231407842018afc98fd3ea.jpg","mini_bio":"<p><b>César Milstein</b>, <a href='http://en.w..."}['...']]
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