Created
November 1, 2018 20:42
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gadgedbridge simple data exploration
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| import sqlite3 | |
| import matplotlib.pyplot as plt | |
| import datetime | |
| import numpy as np | |
| conn = sqlite3.connect('Gadgetbridge') | |
| c = conn.cursor() | |
| a=c.execute("select strftime('%Y.%m.%d', datetime(timestamp, 'unixepoch')) as d,sum(STEPS) from MI_BAND_ACTIVITY_SAMPLE group by d").fetchall() | |
| b={x[0]:x[1] for x in a} | |
| fig, ax = plt.subplots() | |
| plt.bar( | |
| np.arange(len(b)), | |
| list(b.values()), | |
| 0.3, | |
| tick_label=list(b.keys()), | |
| label="steps", | |
| color="#ff7f0e", | |
| ) | |
| plt.legend() | |
| plt.tight_layout() | |
| plt.xticks(rotation=60) | |
| plt.show() | |
| c.close() |
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that results in:
One can also group by say week:
a=c.execute("select strftime('%W', datetime(timestamp, 'unixepoch')) as d,sum(STEPS) from MI_BAND_ACTIVITY_SAMPLE group by d").fetchall()