Calendar Heatmap
Deep Work Minutes Calendar
Daily deep work sessions tracked in neon purple gradient for productivity.
Output
Python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.patches as mpatches
np.random.seed(132)
days = 365
deep_work = np.random.exponential(90, days)
deep_work = np.clip(deep_work, 0, 240)
for i in range(days):
if i % 7 >= 5:
deep_work[i] = deep_work[i] * 0.3
weeks = 53
data = np.zeros((7, weeks))
for i, val in enumerate(deep_work):
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=240)
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('Deep Work - Focused 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', '1-75', '76-160', '161+'])]
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(deep_work) / 60
ax.annotate(f'{total:.0f} hours of deep work', 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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