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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

Jupyter Notebook 99.97% Python 0.03% Shell 0.01%

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covid-eu-analysis's Issues

Calcolo % missing values per ogni regione

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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