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Analysis of the impact of economic and social factors on the spread of covid during the first and second wave of the epidemic in Europe
Per il calcolo della % dei missing values per ogni regione, viene usato questo codice:
plt.hist(data_manager.df.isna().sum(axis=1)/len(data_manager.df))
Dato che data_manager
e' un dataframe con una riga per ogni regione e una colonna per ogni feature, e' corretto fare df.isna().sum(axis=1) per sapere, per ogni regione, quante features sono mancanti. Pero', il risultato andrebbe poi normalizzato per il numero totale di features disponibili (len(data_manager.df.columns)), e non per il numero totale di regioni (len(data_manager.df)).
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