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Sleep.py
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import io | |
import pandas as pd | |
import numpy as np | |
import matplotlib.pyplot as plt | |
# Define the input CSV string | |
csv_string = """timestamp,duration | |
2022-02-20 23:00:00,420 | |
2022-02-21 00:30:00,300 | |
2022-02-21 07:15:00,360 | |
2022-02-22 01:00:00,420 | |
2022-02-22 06:30:00,240 | |
2022-02-23 00:45:00,360 | |
2022-02-23 06:30:00,420 | |
""" | |
# Load the sleep data | |
sleep_data = pd.read_csv(io.StringIO(csv_string)) | |
# Preprocess the data | |
sleep_data['date'] = pd.to_datetime(sleep_data['timestamp']).dt.date | |
sleep_data['start_time'] = pd.to_datetime(sleep_data['timestamp']).dt.time | |
sleep_data['end_time'] = pd.to_datetime(sleep_data['timestamp'] + pd.to_timedelta(sleep_data['duration'], unit='m')).dt.time | |
# Aggregate the data | |
daily_sleep = sleep_data.groupby('date').agg( | |
total_sleep=('duration', 'sum'), | |
start_time=('start_time', 'min'), | |
end_time=('end_time', 'max') | |
) | |
# Calculate the polar coordinates | |
theta = np.linspace(0, 2 * np.pi, len(daily_sleep), endpoint=False) | |
r = daily_sleep['total_sleep'] / 60 | |
# Plot the chart | |
fig = plt.figure(figsize=(8, 8)) | |
ax = fig.add_subplot(111, projection='polar') | |
ax.plot(theta, r, color='black', linewidth=3) | |
ax.fill(theta, r, facecolor='black', alpha=0.1) | |
ax.set_theta_zero_location('N') | |
ax.set_theta_direction(-1) | |
ax.set_rlim(0, 8) | |
ax.set_rlabel_position(105) | |
ax.set_xticklabels(['12am', '', '', '', '', '', '6am', '', '', '', '', '', '12pm', '', '', '', '', '', '6pm', '', '', '', '', '']) | |
ax.set_title('Sleep Pattern', fontsize=18, pad=20) | |
# Add vinyl disk-like styling | |
ax.spines['polar'].set_visible(False) | |
ax.grid(linestyle='--', alpha=0.8) | |
ax.text(0.5, 1.05, 'Sleep Vinyl', transform=ax.transAxes, fontsize=24, ha='center') | |
ax.text(0.5, 1.01, 'Amount of sleep (hours)', transform=ax.transAxes, fontsize=16, ha='center') | |
ax.annotate('', xy=(np.pi, 8), xytext=(0, 8), | |
arrowprops=dict(facecolor='black', arrowstyle='<|-', lw=1.5, alpha=0.8)) | |
plt.show() |
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