March 2025
Intermediate to advanced
504 pages
12h 5m
Italian
Content preview from Python Polars: la guida definitiva
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Capitolo 14. Unire e concatenare
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Spesso i dati provengono da più fonti che dovrai collegare e combinare in modo significativo. Esistono diversi modi per combinare i DataFrames, che esamineremo in questo capitolo.
Curiosamente, questo è il punto in cui Polars ha iniziato a lavorare: dovendo combinare due file CSV in Rust, Ritchie Vink ha iniziato il suo viaggio che ha portato al punto in cui siamo ora. Questo dà un senso speciale alle operazioni di questo capitolo.
In questo capitolo imparerai:
-
Puoi utilizzare
df.join()per combinare i DataFrames in base ai valori presenti nei DataFrames e alle strategie qui descritte. -
df.join_asof()è un join speciale che unisce i DataFrame in base al valore più vicino nell'altro DataFrame. -
Come combinare i DataFrames utilizzando
pl.concat(),df.vstack(),df.hstack()edf.extend() -
Come combinare le Serie con
series.append() -
Le differenze tra tutti questi metodi e quando utilizzarli
Le istruzioni per ottenere i file di cui potresti aver bisogno sono riportate nel Capitolo 2. Partiamo dal presupposto che i file si trovino nella sottodirectory dei dati.
Unirsi
Per combinare diversi DataFrames all'indirizzo , Polars offre il metodo df.join() che accetta gli argomenti elencati nella Tabella 14-1.
| Argomento | Descrizione |
|---|---|
|
Il DataFrame con cui unirsi. ... |
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