Website Traffic Calendar

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

np.random.seed(666)

days = 365
traffic = np.random.lognormal(8, 0.5, days).astype(int)
traffic = np.clip(traffic, 500, 15000)

traffic_levels = np.digitize(traffic, bins=[0, 1500, 3000, 5000, 8000, 12000]) - 1

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

colors = ['#0a0a0f', '#164e63', '#0891b2', '#22d3ee', '#67e8f9', '#a5f3fc']
cmap = LinearSegmentedColormap.from_list('traffic', 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('Website Traffic - Daily Unique Visitors', 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, ['<1.5K', '1.5-3K', '3-5K', '5-8K', '8-12K', '12K+'])]
ax.legend(handles=legend_elements, loc='upper left', bbox_to_anchor=(0, -0.15), ncol=6, 
          fontsize=8, facecolor='#1e293b', edgecolor='#334155', labelcolor='white')

total = int(np.sum(traffic))
avg = int(np.mean(traffic))
ax.annotate(f'Total: {total:,} visitors | Avg: {avg:,}/day', xy=(0.98, 1.1), xycoords='axes fraction',
            fontsize=11, color='#22d3ee', ha='right', fontweight='bold')

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