Salary vs Experience

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

np.random.seed(42)

# Career data
experience = np.clip(np.random.exponential(5, 5000), 0, 35)
salary = 40000 + experience * 5000 + np.random.normal(0, 15000, 5000)
salary = np.clip(salary, 30000, 250000)

fig, ax = plt.subplots(figsize=(10, 8), facecolor='#020B14')
ax.set_facecolor('#020B14')

# Custom colormap: purple to yellow
colors = ['#020B14', '#1a0d2e', '#4927F5', '#F5B027', '#F5D327']
cmap = LinearSegmentedColormap.from_list('career', colors, N=256)

h = ax.hist2d(experience, salary/1000, bins=40, cmap=cmap, cmin=1)
cbar = plt.colorbar(h[3], ax=ax, pad=0.02)
cbar.set_label('Employees', color='white', fontsize=11)
cbar.ax.yaxis.set_tick_params(color='white')
plt.setp(plt.getp(cbar.ax.axes, 'yticklabels'), color='white')

ax.set_xlabel('Years of Experience', fontsize=11, color='white', fontweight='500')
ax.set_ylabel('Salary ($K)', fontsize=11, color='white', fontweight='500')
ax.set_title('Salary vs Experience', fontsize=14, color='white', fontweight='bold', pad=15)

ax.tick_params(colors='white', labelsize=9)
for spine in ax.spines.values():
    spine.set_color('#333333')

plt.tight_layout()
plt.show()