Calendar Heatmap
Music Practice Calendar
Daily music practice minutes tracked in neon purple gradient for musicians.
Output
Python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.patches as mpatches
np.random.seed(126)
days = 365
practice = np.random.exponential(30, days)
practice = np.clip(practice, 0, 120)
practice[np.random.choice(days, size=60, replace=False)] = 0
weeks = 53
data = np.zeros((7, weeks))
for i, val in enumerate(practice):
week = i // 7
day = i % 7
if week < weeks:
data[day, week] = val
# CLAUDE.md Neon Purple palette
colors_neon = ['#ffffff', '#e5e0fc', '#9a78f9', '#4927F5']
cmap = LinearSegmentedColormap.from_list('neon_purple', colors_neon, 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=120)
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('Music Practice - Minutes Per Day', fontsize=16, color='#1f2937', 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_neon, ['0', '1-30', '31-75', '76+'])]
ax.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(0, -0.15), ncol=4,
fontsize=8, facecolor='#f9fafb', edgecolor='#d1d5db', labelcolor='#374151', title='Minutes',
title_fontsize=9)
total = np.sum(practice) / 60
ax.annotate(f'{total:.0f} hours practiced', xy=(0.98, 1.1), xycoords='axes fraction',
fontsize=11, color='#4927F5', ha='right', fontweight='bold')
plt.tight_layout()
plt.subplots_adjust(bottom=0.25)
plt.show()
Library
Matplotlib
Category
Time Series
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