Age vs Blood Pressure

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

np.random.seed(417)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'

n = 90
age = np.random.uniform(25, 75, n)
bp = 100 + 0.5 * age + np.random.normal(0, 10, n)

df = pd.DataFrame({'Age (years)': age, 'Systolic BP (mmHg)': bp})

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

sns.regplot(
    data=df,
    x='Age (years)',
    y='Systolic BP (mmHg)',
    scatter_kws={'color': '#F5276C', 'alpha': 0.6, 's': 55, 'edgecolor': 'white', 'linewidths': 0.5},
    line_kws={'color': '#276CF5', 'linewidth': 2.5},
    ci=95,
    ax=ax
)

for collection in ax.collections[1:]:
    collection.set_facecolor('#276CF5')
    collection.set_alpha(0.15)

ax.axhline(120, color='#22c55e', linestyle='--', alpha=0.5, linewidth=1)
ax.text(73, 122, 'Normal', color='#22c55e', fontsize=9, ha='right')
ax.axhline(140, color='#ef4444', linestyle='--', alpha=0.5, linewidth=1)
ax.text(73, 142, 'High', color='#ef4444', fontsize=9, ha='right')

corr = np.corrcoef(age, bp)[0, 1]
ax.text(0.05, 0.95, 'r = %.3f' % corr, transform=ax.transAxes, fontsize=12,
        color='#276CF5', fontweight='bold', va='top',
        bbox=dict(boxstyle='round,pad=0.3', facecolor='#f8fafc', edgecolor='#e5e7eb'))

ax.set_xlabel('Age (years)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Systolic BP (mmHg)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Age vs Blood Pressure', 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()