Height vs Weight Correlation

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

np.random.seed(411)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'

n = 100
height = np.random.normal(170, 10, n)
weight = 0.8 * height - 70 + np.random.normal(0, 8, n)

df = pd.DataFrame({'Height (cm)': height, 'Weight (kg)': weight})

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

sns.regplot(
    data=df,
    x='Height (cm)',
    y='Weight (kg)',
    scatter_kws={'color': '#4927F5', 'alpha': 0.6, 's': 55, 'edgecolor': 'white', 'linewidths': 0.5},
    line_kws={'color': '#F5276C', 'linewidth': 2.5},
    ci=95,
    ax=ax
)

for collection in ax.collections[1:]:
    collection.set_facecolor('#F5276C')
    collection.set_alpha(0.15)

corr = np.corrcoef(height, weight)[0, 1]
ax.text(0.05, 0.95, 'r = %.3f' % corr, transform=ax.transAxes, fontsize=12,
        color='#F5276C', fontweight='bold', va='top',
        bbox=dict(boxstyle='round,pad=0.3', facecolor='#f8fafc', edgecolor='#e5e7eb'))

ax.set_xlabel('Height (cm)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Weight (kg)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Height vs Weight Relationship', 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()