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46 lines
1.5 KiB
46 lines
1.5 KiB
import telegram_send
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from sqlalchemy import create_engine, text
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import pandas as pd
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import datetime as dt
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import matplotlib.pyplot as plt
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# Get the relevant data
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engine = create_engine('sqlite:///history/data.sqlite')
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query = 'SELECT * FROM messages'
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data = pd.read_sql_query(sql=text(query), con=engine.connect())
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data = data[data['content']=='Coffee']
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grand_total = len(data)
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data['datetime'] = pd.to_datetime(data['date'])
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# Calculate weekdays and hours
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data['weekday'] = data['datetime'].dt.dayofweek
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data['hour'] = data['datetime'].dt.hour
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data['day'] = data['datetime'].dt.day
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lastmonth = (dt.datetime.now().month - 1) % 12
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monthly = data[data['datetime'].dt.month == lastmonth].copy()
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# Make plots
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monthly['weekday'].plot.hist(bins=7)
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plt.savefig('files/monthly_weekdays.png')
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plt.close()
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monthly['hour'].plot.hist(bins=24)
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plt.savefig('files/monthly_hour.png')
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plt.close()
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data['weekday'].plot.hist(bins=7)
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plt.savefig('files/all_weekdays.png')
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plt.close()
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data['hour'].plot.hist(bins=24)
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plt.savefig('files/all_hour.png')
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plt.close()
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# Calculate on which day the most coffee was made
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monthly['count'] = 1
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aggregated = monthly.groupby(['day']).count()['count']
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message1 = 'Last month, coffee was made {amount} times.'.format(amount=len(monthly)) + ' Most coffee was made on day {day} of the month, with a total amount of {amount} times.'.format(day=aggregated.idxmax(),amount=aggregated.max()) + ' From the start of this chat, a grand total amount of {amount} times coffee was made.'.format(amount=grand_total)
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telegram_send.send(messages=[message1])
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