Ad Impressions vs Click-Through Rate

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

np.random.seed(410)
BG_COLOR = '#0a0a0f'
TEXT_COLOR = 'white'

n = 75
impressions = np.random.uniform(10, 500, n)
ctr = 4 - 0.005 * impressions + np.random.normal(0, 0.5, n)
ctr = np.clip(ctr, 0.5, 5)

df = pd.DataFrame({'Impressions (K)': impressions, 'CTR (%)': ctr})

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

sns.regplot(
    data=df,
    x='Impressions (K)',
    y='CTR (%)',
    scatter_kws={'color': '#F527B0', 'alpha': 0.7, 's': 55, 'edgecolor': 'white', 'linewidths': 0.5},
    line_kws={'color': '#27D3F5', 'linewidth': 2.5, 'linestyle': '-'},
    ci=95,
    ax=ax
)

for collection in ax.collections[1:]:
    collection.set_facecolor('#27D3F5')
    collection.set_alpha(0.15)

ax.axhline(2.0, color='#F5B027', linestyle='--', alpha=0.5, linewidth=1)
ax.text(480, 2.1, 'Industry Avg', color='#F5B027', fontsize=9, ha='right')

corr = np.corrcoef(impressions, ctr)[0, 1]
ax.text(0.05, 0.05, 'r = %.3f' % corr, transform=ax.transAxes, fontsize=12,
        color='#27D3F5', fontweight='bold', va='bottom',
        bbox=dict(boxstyle='round,pad=0.3', facecolor='#1a1a2e', edgecolor='#333'))

ax.set_xlabel('Ad Impressions (K)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_ylabel('Click-Through Rate (%)', fontsize=12, color=TEXT_COLOR, fontweight='500')
ax.set_title('Ad Impressions vs CTR', fontsize=14, color=TEXT_COLOR, fontweight='bold', pad=15)

ax.tick_params(colors='#888', labelsize=10)
for spine in ax.spines.values():
    spine.set_color('#333')

plt.tight_layout()
plt.show()