Calendar Heatmap

Savings Deposits Calendar

Daily savings deposits tracked in neon lime gradient for financial tracking.

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

np.random.seed(127)

days = 365
savings = np.zeros(days)
deposit_days = np.random.choice(days, size=100, replace=False)
for d in deposit_days:
    savings[d] = np.random.uniform(10, 200)

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

# CLAUDE.md Neon Lime palette
colors_neon = ['#ffffff', '#eefce0', '#b8f978', '#6CF527']
cmap = LinearSegmentedColormap.from_list('neon_lime', 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=200)

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('Savings Deposits - Amount 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', '$1-65', '$66-130', '$131+'])]
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='Amount',
          title_fontsize=9)

total = np.sum(savings)
ax.annotate(f'${total:,.0f} saved', xy=(0.98, 1.1), xycoords='axes fraction',
            fontsize=11, color='#6CF527', ha='right', fontweight='bold')

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

Matplotlib

Category

Time Series

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