May 2026
Intermediate
418 pages
10h 50m
Italian
Content preview from Python per Excel (Italian Edition), 2nd Edition
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Capitolo 4. Nozioni di base suNumPy
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Come ricorderai dal Capitolo 1, NumPy è il pacchetto fondamentale per il calcolo scientifico in Python, che fornisce supporto per i calcoli basati su array e l'algebra lineare. Poiché NumPy è una dipendenza chiave di pandas, in questo capitolo ne presenterò le basi: dopo aver spiegato cos'è un array NumPy, esamineremo la vettorizzazione e il broadcasting, due concetti importanti che ti consentono di scrivere codice matematico conciso e che ritroverai in pandas. Successivamente, vedremo perché NumPy offre funzioni speciali chiamate funzioni universali, prima di concludere questo capitolo imparando come ottenere e impostare i valori di un array e spiegando la differenza tra una vista e una copia di un array. Anche se in questo libro useremo raramente NumPy direttamente, conoscerne le basi renderà più facile imparare pandas nel prossimo capitolo.
Introduzione a NumPy
In questa sezione imparerai a conoscere gli array NumPy a una e due dimensioni e cosa si nasconde dietro i termini tecnici vettorializzazione, broadcasting e funzione universale.
Array NumPy
Per eseguire calcoli basati su array con liste annidate in , devi scrivere una sorta di ciclo. Ad esempio, puoi usare una comprensione di lista annidata per aggiungere un numero a ogni elemento di matrix:
In[1]:matrix=[[1,2,3],[4,5,6],[7,8,
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