Training Hours vs Race Time

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

np.random.seed(414)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'

n = 65
training = np.random.uniform(5, 50, n)
race_time = 60 - 0.6 * training + np.random.normal(0, 5, n)

df = pd.DataFrame({'Training Hours/Week': training, 'Race Time (min)': race_time})

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

sns.regplot(
    data=df,
    x='Training Hours/Week',
    y='Race Time (min)',
    scatter_kws={'color': '#6CF527', 'alpha': 0.6, 's': 55, 'edgecolor': 'white', 'linewidths': 0.5},
    line_kws={'color': '#F54927', 'linewidth': 2.5},
    ci=95,
    ax=ax
)

for collection in ax.collections[1:]:
    collection.set_facecolor('#F54927')
    collection.set_alpha(0.15)

corr = np.corrcoef(training, race_time)[0, 1]
ax.text(0.95, 0.95, 'r = %.3f' % corr, transform=ax.transAxes, fontsize=12,
        color='#F54927', fontweight='bold', va='top', ha='right',
        bbox=dict(boxstyle='round,pad=0.3', facecolor='#f8fafc', edgecolor='#e5e7eb'))

ax.set_xlabel('Training Hours/Week', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('10K Race Time (min)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Training vs Race Performance', 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()