Calendar Heatmap

Reading Habit Tracker

Daily reading minutes calendar showing consistency and reading streaks.

Output
Reading Habit Tracker
Python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.patches as mpatches

np.random.seed(654)

# Generate reading minutes
days = 365
reading = np.random.choice([0, 0, 15, 30, 45, 60, 90], size=days, p=[0.2, 0.1, 0.2, 0.2, 0.15, 0.1, 0.05])

read_levels = np.digitize(reading, bins=[0, 1, 15, 30, 45, 60]) - 1

weeks = 53
data = np.zeros((7, weeks))
for i, val in enumerate(read_levels):
    week = i // 7
    day = i % 7
    if week < weeks:
        data[day, week] = val

# Warm amber/orange gradient
colors = ['#ffffff', '#fef3c7', '#fcd34d', '#f59e0b', '#d97706', '#92400e']
cmap = LinearSegmentedColormap.from_list('reading', colors, N=256)

fig, ax = plt.subplots(figsize=(16, 4), facecolor='#ffffff')
ax.set_facecolor('#ffffff')

im = ax.imshow(data, cmap=cmap, aspect='auto', vmin=0, vmax=5)

ax.set_yticks(range(7))
ax.set_yticklabels(['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun'], fontsize=9, color='#374151')
ax.set_xticks(range(0, 52, 4))
ax.set_xticklabels(['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec', ''], 
                   fontsize=9, color='#374151')

ax.set_title('Daily Reading Time - Book Tracker', fontsize=16, color='#111827', fontweight='bold', pad=15)

for i in range(8):
    ax.axhline(y=i-0.5, color='#e5e7eb', linewidth=0.5)
for i in range(weeks+1):
    ax.axvline(x=i-0.5, color='#e5e7eb', linewidth=0.5)

ax.tick_params(colors='#374151', length=0)
for spine in ax.spines.values():
    spine.set_visible(False)

legend_elements = [mpatches.Patch(facecolor=c, label=l, edgecolor='#d1d5db') 
                   for c, l in zip(colors, ['None', '<15m', '15-30m', '30-45m', '45-60m', '60m+'])]
ax.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(0, -0.15), ncol=6, 
          fontsize=8, facecolor='white', edgecolor='#d1d5db', labelcolor='#374151')

read_days = int(np.sum(reading > 0))
total_hours = int(np.sum(reading)) // 60
ax.annotate(f'{read_days} reading days | {total_hours} hours total', xy=(0.98, 1.1), xycoords='axes fraction',
            fontsize=10, color='#d97706', ha='right', fontweight='bold')

plt.tight_layout()
plt.subplots_adjust(bottom=0.25)
plt.show()
Library

Matplotlib

Category

Time Series

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