Distance vs Taxi Fare

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

np.random.seed(412)
BG_COLOR = '#ffffff'
TEXT_COLOR = '#1f2937'

n = 80
distance = np.random.uniform(0.5, 20, n)
fare = 3.5 + 2.2 * distance + np.random.normal(0, 3, n)

df = pd.DataFrame({'Distance (miles)': distance, 'Fare ($)': fare})

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

sns.regplot(
    data=df,
    x='Distance (miles)',
    y='Fare ($)',
    scatter_kws={'color': '#F5B027', 'alpha': 0.6, 's': 55, 'edgecolor': 'white', 'linewidths': 0.5},
    line_kws={'color': '#4927F5', 'linewidth': 2.5},
    ci=95,
    ax=ax
)

for collection in ax.collections[1:]:
    collection.set_facecolor('#4927F5')
    collection.set_alpha(0.15)

corr = np.corrcoef(distance, fare)[0, 1]
ax.text(0.05, 0.95, 'r = %.3f' % corr, transform=ax.transAxes, fontsize=12,
        color='#4927F5', fontweight='bold', va='top',
        bbox=dict(boxstyle='round,pad=0.3', facecolor='#f8fafc', edgecolor='#e5e7eb'))

slope = np.polyfit(distance, fare, 1)[0]
ax.text(0.05, 0.85, '$%.2f/mile' % slope, transform=ax.transAxes, fontsize=11,
        color='#F5B027', va='top')

ax.set_xlabel('Distance (miles)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Fare ($)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Taxi Distance vs Fare', 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()