pandas sums as pd #Reading CSV file with record of electrical surpluses = pd.read_csv ((('registro_excesos.csv') #Convert the column of dates to date format of pandas excesses['date'] = pd.to_datetime (((excesos['date']) #Group by month and hour, and get the sum of electrical surpluses_per_hour = excesos.groupby[(excesos['date'].dt.month, excesos['fecha'].dt.hour]) ['excesos'].sum) #Find the time with the greatest electrical surplus for monthly hours =excesses_per_hour.max.level =excesos_per_group.by (((xmax.id=0).
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