September 2024
Intermediate to advanced
568 pages
14h 25m
German
Content preview from Datenvisualisierung mit Python und JavaScript, 2.
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Kapitel 11. Daten mit Pandas erforschen
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Im vorigen Kapitel haben wir den Nobelpreis-Datensatz bereinigt, den wir in Kapitel 6 aus der Wikipedia geholt haben. Jetzt ist es an der Zeit, unseren neuen Datensatz zu erkunden und nach interessanten Mustern, Geschichten und allem anderen zu suchen, was die Grundlage für eine interessante Visualisierung sein könnte.
Versuchen wir zunächst, den Kopf frei zu bekommen und uns die vorliegenden Daten genau anzuschauen, um eine grobe Vorstellung von den vorgeschlagenen Visualisierungen zu bekommen. Beispiel 11-1 zeigt die Form des Nobel-Datensatzes mit kategorialen, zeitlichen und geografischen Daten.
Beispiel 11-1. Unser bereinigter Nobelpreis-Datensatz
[{'category':'Physiology or Medicine','date_of_birth':'8 October 1927','date_of_death':'24 March 2002','gender':'male','link':'http://en.wikipedia.org/wiki/C%C3%A9sar_Milstein','name':'César Milstein''country':'Argentina','place_of_birth':'Bahía Blanca, Argentina','place_of_death':'Cambridge , England','year':1984,'born_in':NaN},...]
Die Daten in Beispiel 11-1 lassen auf eine Reihe von Geschichten vermuten, die wir untersuchen wollen:
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Geschlechterunterschiede bei den Preisträgern
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Nationale Trends (z. B. welches Land hat die meisten Preise in Wirtschaftswissenschaften)
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Details zu den einzelnen Gewinnern, wie z.B. ihr Durchschnittsalter ...
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