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# --- |
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# version: 3.6.6 |
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# --- |
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# %% {"tags": ["parameters"]} |
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# Our default parameters |
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# This cell has a "parameters" tag, means that it defines the parameters for use in the notebook |
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run_date = "2018-04-28" |
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source_id = 'sensor1' |
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# %% |
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import pandas as pd |
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import numpy as np |
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import papermill as pm |
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import matplotlib.pyplot as plt |
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import matplotlib.dates as mdates |
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from datetime import datetime, timedelta |
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import time |
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import os |
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plt.ioff() |
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# %% |
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run_datetime = datetime.strptime(run_date, '%Y-%m-%d') |
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ts = pd.date_range("00:00", "23:59", freq="5min") |
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td = ts - timedelta((datetime.now() - run_datetime).days) |
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data = pd.DataFrame(np.random.randn(len(td)), columns=['mydata']) |
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data = data.rolling(70, min_periods=1, center=True).mean() # Smooth it so it looks purdy |
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data['date'] = td |
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data['hour'] = data['date'].apply(lambda x: datetime.strftime(x, "%H")) |
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# %% |
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print(data['date'].describe()) |
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data.describe() |
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# %% |
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data = data.sort_values('date').set_index('date', drop=True) |
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data.head(5) |
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# %% |
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fig, ax = plt.subplots() |
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ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M:%S')) |
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plt.gcf().autofmt_xdate() |
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ax.plot(data.index, data['mydata'], c='k', alpha=.5) |
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ax.set(title="Activity for the day of {}".format(run_date)) |
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pm.display('activity_day_fig', fig) |
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# %% |
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month_partition = run_datetime.strftime("%Y-%m") |
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output_file = "../data/output/step1/" + month_partition + "/" + run_date + '-' + source_id + '.csv' |
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print(output_file) |
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# %% |
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os.makedirs(os.path.dirname(output_file), exist_ok=True) |
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data.to_csv(output_file) |
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Aiscalate /
aiscalator
