23 lines
952 B
Python
23 lines
952 B
Python
import pandas as pd
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import numpy as np
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data = pd.read_csv('owid-covid-data.csv')
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df = data[['iso_code', 'date', 'total_cases']]
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df['date']=pd.to_datetime(df['date'], format='%Y-%m-%d')
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df.info()
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iso = df.iso_code.unique()
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df2 = pd.DataFrame(columns=['iso_code', 'date', 'total_cases'])
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df3 = pd.DataFrame(columns=['iso_code', 'date', 'total_cases'])
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for country in iso:
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country_v = df.loc[df['iso_code'] == country]
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months = country_v.set_index('date').groupby(pd.Grouper(freq='M')).max()
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i=0
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for index, month in months.iterrows():
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#df2.append(month)
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if i==months.shape[0]-1:
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df3 = df3.append({'iso_code': month['iso_code'], 'date': month.name, 'total_cases': month['total_cases']}, ignore_index=True)
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df2 = df2.append({'iso_code': month['iso_code'], 'date': month.name, 'total_cases': month['total_cases']}, ignore_index=True)
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i += 1
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df2.to_csv('month-covid.csv', sep=',')
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df3.to_csv('max-covid.csv', sep=',')
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