Productivity Score Calendar

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.patches as mpatches

np.random.seed(444)

days = 365
# Lower on weekends
productivity = np.zeros(days)
for i in range(days):
    dow = i % 7
    if dow < 5:
        productivity[i] = np.random.choice([3, 5, 6, 7, 8, 9, 10], p=[0.05, 0.1, 0.15, 0.25, 0.25, 0.15, 0.05])
    else:
        productivity[i] = np.random.choice([0, 2, 4, 5, 6], p=[0.3, 0.25, 0.25, 0.15, 0.05])

prod_levels = np.digitize(productivity, bins=[0, 2, 4, 6, 8, 9]) - 1

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

colors = ['#0a0a0f', '#1e3a5f', '#2563eb', '#3b82f6', '#60a5fa', '#93c5fd']
cmap = LinearSegmentedColormap.from_list('productivity', colors, N=256)

fig, ax = plt.subplots(figsize=(16, 4), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

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='#e2e8f0')
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='#e2e8f0')

ax.set_title('Daily Productivity Score (1-10)', fontsize=16, color='white', fontweight='bold', pad=15)

for i in range(8):
    ax.axhline(y=i-0.5, color='#1e293b', linewidth=0.5)
for i in range(weeks+1):
    ax.axvline(x=i-0.5, color='#1e293b', linewidth=0.5)

ax.tick_params(colors='#e2e8f0', length=0)
for spine in ax.spines.values():
    spine.set_visible(False)

legend_elements = [mpatches.Patch(facecolor=c, label=l, edgecolor='#334155') 
                   for c, l in zip(colors, ['1-2', '3-4', '5-6', '7-8', '9', '10'])]
ax.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(0, -0.15), ncol=6, 
          fontsize=8, facecolor='#1e293b', edgecolor='#334155', labelcolor='white')

avg = np.mean(productivity)
high_days = int(np.sum(productivity >= 8))
ax.annotate(f'Avg Score: {avg:.1f}/10 | {high_days} high productivity days', xy=(0.98, 1.1), xycoords='axes fraction',
            fontsize=11, color='#60a5fa', ha='right', fontweight='bold')

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