Sleep Hours vs Productivity Score

import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd

np.random.seed(408)
BG_COLOR = '#0a0a0f'
TEXT_COLOR = 'white'

n = 70
sleep = np.random.uniform(4, 10, n)
productivity = 30 + 8 * sleep + np.random.normal(0, 8, n)
productivity = np.clip(productivity, 0, 100)

df = pd.DataFrame({'Sleep Hours': sleep, 'Productivity Score': productivity})

fig, ax = plt.subplots(figsize=(10, 6), facecolor=BG_COLOR)
ax.set_facecolor(BG_COLOR)

sns.regplot(
    data=df,
    x='Sleep Hours',
    y='Productivity Score',
    scatter_kws={'color': '#276CF5', 'alpha': 0.7, 's': 55, 'edgecolor': 'white', 'linewidths': 0.5},
    line_kws={'color': '#F5B027', 'linewidth': 2.5},
    ci=95,
    ax=ax
)

for collection in ax.collections[1:]:
    collection.set_facecolor('#F5B027')
    collection.set_alpha(0.15)

ax.axvspan(7, 9, alpha=0.1, color='#22c55e')
ax.text(8, 95, 'Optimal', color='#22c55e', fontsize=9, ha='center')

corr = np.corrcoef(sleep, productivity)[0, 1]
ax.text(0.05, 0.95, 'r = %.3f' % corr, transform=ax.transAxes, fontsize=12,
        color='#F5B027', fontweight='bold', va='top',
        bbox=dict(boxstyle='round,pad=0.3', facecolor='#1a1a2e', edgecolor='#333'))

ax.set_xlabel('Sleep Hours', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Productivity Score', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Sleep vs Productivity', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors='#888', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#333')

plt.tight_layout()
plt.show()