カントリーリスクプレミアムを可視化する

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import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from pathlib import Path

plt.style.use("scripts/k_dm.mplstyle")

data = pd.DataFrame(
    {
        "country": ["Japan", "United States", "Brazil", "India", "South Africa", "Turkey", "Mexico"],
        "risk_premium": [0.012, 0.018, 0.038, 0.031, 0.042, 0.055, 0.029],
        "region": ["Asia", "Americas", "Americas", "Asia", "Africa", "Europe", "Americas"],
    }
)

data = data.sort_values("risk_premium")
fig, ax = plt.subplots(figsize=(8, 4.8))
bars = ax.bar(data["country"], data["risk_premium"] * 100, color="#3b82f6")

average = data["risk_premium"].mean() * 100
ax.axhline(average, color="#ef4444", linestyle="--", linewidth=1.2, label=f"平均 {average:.1f}%")

for bar, value in zip(bars, data["risk_premium"]):
    ax.text(
        bar.get_x() + bar.get_width() / 2,
        value * 100 + 0.6,
        f"{value*100:.1f}%",
        ha="center",
        fontsize=10,
    )

ax.set_ylabel("リスクプレミアム（%）")
ax.set_title("主要国のリスクプレミアム比較（サンプルデータ）")
ax.set_ylim(0, 6.5)
ax.grid(axis="y", alpha=0.3)
ax.legend(loc="upper left")

output = Path("static/images/finance/visualize/country_risk_premium.svg")
output.parent.mkdir(parents=True, exist_ok=True)
fig.tight_layout()
fig.savefig(output)

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region_colors = {"Asia": "#3b82f6", "Americas": "#10b981", "Africa": "#f59e0b", "Europe": "#ef4444"}

data = data.sort_values("risk_premium")
colors = [region_colors[r] for r in data["region"]]

fig, ax = plt.subplots(figsize=(8, 4.8))
bars = ax.barh(data["country"], data["risk_premium"] * 100, color=colors)

for bar, value in zip(bars, data["risk_premium"]):
    ax.text(bar.get_width() + 0.1, bar.get_y() + bar.get_height() / 2,
            f"{value*100:.1f}%", va="center", fontsize=10)

ax.set_xlabel("リスクプレミアム（%）")
ax.set_title("国別リスクプレミアム（地域色分け）")
ax.grid(axis="x", alpha=0.3)

# 凡例
from matplotlib.patches import Patch
legend_elements = [Patch(facecolor=c, label=r) for r, c in region_colors.items()]
ax.legend(handles=legend_elements, loc="lower right")

fig.tight_layout()
plt.show()

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print(f"平均:   {data['risk_premium'].mean()*100:.2f}%")
print(f"中央値: {data['risk_premium'].median()*100:.2f}%")
print(f"標準偏差: {data['risk_premium'].std()*100:.2f}%")
print(f"最大-最小: {(data['risk_premium'].max() - data['risk_premium'].min())*100:.2f}%")