November 2023
Intermediate to advanced
576 pages
13h 30m
German
Content preview from Handbuch Data Science mit PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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KAPITEL 9
Vergleiche, Maskierungen und boolesche Logik
In diesem Kapitel kommt die Verwendung boolescher Maskierungen zum Untersuchen und Bearbeiten von Werten in NumPy-Arrays zur Sprache. Maskierungen sind von Interesse, wenn man die in einem Array enthaltenen Werte anhand eines bestimmten Kriteriums entnehmen, modifizieren, zählen oder auf andere Weise bearbeiten möchten. Sie könnten beispielsweise alle Werte zählen wollen, die einen bestimmten Grenzwert überschreiten, oder möchten die Ausreißer entfernen, die einen gewissen Schwellenwert überschreiten. In NumPy sind boolesche Maskierungen häufig die effizienteste Methode, Aufgaben dieser Art zu erledigen.
Beispiel: Regentage zählen
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.