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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]) |