Screen Time vs Sleep Quality

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

np.random.seed(418)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'

n = 75
screen = np.random.uniform(1, 12, n)
sleep_quality = 95 - 5 * screen + np.random.normal(0, 8, n)
sleep_quality = np.clip(sleep_quality, 20, 100)

df = pd.DataFrame({'Screen Time (hrs)': screen, 'Sleep Quality': sleep_quality})

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

sns.regplot(
    data=df,
    x='Screen Time (hrs)',
    y='Sleep Quality',
    scatter_kws={'color': '#4927F5', 'alpha': 0.6, 's': 55, 'edgecolor': 'white', 'linewidths': 0.5},
    line_kws={'color': '#6CF527', 'linewidth': 2.5},
    ci=95,
    ax=ax
)

for collection in ax.collections[1:]:
    collection.set_facecolor('#6CF527')
    collection.set_alpha(0.15)

ax.axvline(2, color='#22c55e', linestyle='--', alpha=0.5, linewidth=1)
ax.text(2.2, 30, 'Recommended', color='#22c55e', fontsize=9, rotation=90)

corr = np.corrcoef(screen, sleep_quality)[0, 1]
ax.text(0.95, 0.95, 'r = %.3f' % corr, transform=ax.transAxes, fontsize=12,
        color='#6CF527', fontweight='bold', va='top', ha='right',
        bbox=dict(boxstyle='round,pad=0.3', facecolor='#f8fafc', edgecolor='#e5e7eb'))

ax.set_xlabel('Daily Screen Time (hours)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Sleep Quality Score', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Screen Time vs Sleep Quality', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors='#374151', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#e5e7eb')

plt.tight_layout()
plt.show()