Song Tempo vs Energy

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

np.random.seed(42)

# Music features
tempo = np.concatenate([
    np.random.normal(80, 15, 1500),   # Slow songs
    np.random.normal(120, 20, 3000),  # Pop/rock
    np.random.normal(160, 15, 1500)   # Electronic/dance
])
energy = 0.2 + tempo/200 * 0.5 + np.random.beta(2, 2, len(tempo)) * 0.3
energy = np.clip(energy, 0, 1)

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

# Custom colormap: pink to yellow_lime
colors = ['#020B14', '#2d0d2d', '#F527B0', '#D3F527']
cmap = LinearSegmentedColormap.from_list('pink_lime', colors, N=256)

h = ax.hist2d(tempo, energy, bins=45, cmap=cmap, cmin=1)
cbar = plt.colorbar(h[3], ax=ax, pad=0.02)
cbar.set_label('Tracks', 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('Tempo (BPM)', fontsize=11, color='white', fontweight='500')
ax.set_ylabel('Energy', fontsize=11, color='white', fontweight='500')
ax.set_title('Song Tempo vs Energy', 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()