Calendar Heatmap

Social Calls Calendar

Daily social calls tracked in neon pink gradient for relationship tracking.

Output
Social Calls Calendar
Python
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
import matplotlib.patches as mpatches

np.random.seed(137)

days = 365
calls = np.random.poisson(1.5, days)
calls = np.clip(calls, 0, 6)

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

# CLAUDE.md Neon Pink palette
colors_neon = ['#ffffff', '#fce0f3', '#f97dc4', '#F527B0']
cmap = LinearSegmentedColormap.from_list('neon_pink', 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=6)

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('Social Calls - Calls 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', '2-3', '4+'])]
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='Calls',
          title_fontsize=9)

total = int(np.sum(calls))
ax.annotate(f'{total} calls made', xy=(0.98, 1.1), xycoords='axes fraction',
            fontsize=11, color='#F527B0', ha='right', fontweight='bold')

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

Matplotlib

Category

Time Series

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