Credit Score Income

import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap

np.random.seed(888)
income = np.random.lognormal(10.5, 0.6, 6000)
credit = 500 + 100 * np.log(income/10000) + np.random.normal(0, 50, 6000)
credit = np.clip(credit, 300, 850)

fig, ax = plt.subplots(figsize=(10, 8), facecolor='#fffbeb')
ax.set_facecolor('#fef3c7')

colors = ['#fef3c7', '#fde68a', '#fcd34d', '#fbbf24', '#f59e0b', '#d97706', '#b45309', '#92400e']
cmap = LinearSegmentedColormap.from_list('gold', colors, N=256)

hb = ax.hexbin(income/1000, credit, gridsize=28, cmap=cmap, mincnt=1, edgecolors='white', linewidths=0.3)

cbar = plt.colorbar(hb, ax=ax, pad=0.02, shrink=0.8)
cbar.outline.set_edgecolor('#fde68a')
cbar.ax.tick_params(colors='#b45309', labelsize=9)
cbar.set_label('Applicants', color='#b45309', fontsize=10)

ax.set_xlabel('Annual Income ($K)', color='#b45309', fontsize=11)
ax.set_ylabel('Credit Score', color='#b45309', fontsize=11)
ax.tick_params(colors='#b45309', labelsize=10)
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['left'].set_color('#fde68a')
ax.spines['bottom'].set_color('#fde68a')

plt.tight_layout()