Calendar Heatmap

Cooking Meals Calendar

Daily home-cooked meals tracked in neon yellow gradient for healthy eating.

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

np.random.seed(130)

days = 365
meals = np.random.poisson(2, days)
meals = np.clip(meals, 0, 4)

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

# CLAUDE.md Neon Yellow palette
colors_neon = ['#ffffff', '#f8fce0', '#e5f978', '#D3F527']
cmap = LinearSegmentedColormap.from_list('neon_yellow', 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=4)

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('Home Cooking - Meals 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='Meals',
          title_fontsize=9)

total = int(np.sum(meals))
ax.annotate(f'{total} meals cooked', xy=(0.98, 1.1), xycoords='axes fraction',
            fontsize=11, color='#D3F527', ha='right', fontweight='bold')

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

Matplotlib

Category

Time Series

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