Calendar Heatmap
Social Media Engagement Calendar
Daily social media engagement metrics showing viral content days.
Output
Python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.patches as mpatches
np.random.seed(333)
days = 365
engagement = np.random.exponential(500, days)
engagement = np.clip(engagement, 0, 5000)
eng_levels = np.digitize(engagement, bins=[0, 200, 500, 1000, 2000, 3500]) - 1
weeks = 53
data = np.zeros((7, weeks))
for i, val in enumerate(eng_levels):
week = i // 7
day = i % 7
if week < weeks:
data[day, week] = val
# Pink/magenta for social
colors = ['#0a0a0f', '#500724', '#9d174d', '#db2777', '#f472b6', '#fbcfe8']
cmap = LinearSegmentedColormap.from_list('social', 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('Social Media Engagement - Daily Interactions', 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, ['<200', '200-500', '500-1K', '1K-2K', '2K-3.5K', '3.5K+'])]
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(engagement))
viral = int(np.sum(engagement >= 2000))
ax.annotate(f'Total: {total:,} interactions | {viral} viral days', xy=(0.98, 1.1), xycoords='axes fraction',
fontsize=11, color='#f472b6', ha='right', fontweight='bold')
plt.tight_layout()
plt.subplots_adjust(bottom=0.25)
plt.show()
Library
Matplotlib
Category
Time Series
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