feat(chart): tech sector debt issuance with 4x spike

src/charts/tech_debt.py

@@ -0,0 +1,60 @@
+"""Tech Debt Issuance Chart"""
+import sys
+from pathlib import Path
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent))
+
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import numpy as np
+from src.utils.styling import get_theme, EXPORT_DPI, BUBBLE_ZONE, GRAY_DARK, WARNING_ZONE
+
+
+def plot_tech_debt() -> str:
+    plt.rcParams.update(get_theme())
+    fig, ax = plt.subplots(figsize=(12, 7))
+
+    years = [2020, 2021, 2022, 2023, 2024, 2025, 2026]
+    debt = [25, 30, 28, 25, 30, 121, 125]  # 2026 = mid-range projection
+    five_year_avg = float(np.mean(debt[:5]))  # ~27.6
+
+    colors = [GRAY_DARK] * 5 + [BUBBLE_ZONE, WARNING_ZONE]
+    hatch = ["", "", "", "", "", "", "//"]  # 2026 hatched
+
+    bars = ax.bar(years, debt, color=colors, edgecolor="white", width=0.6, hatch=hatch)
+
+    # 5-year average line
+    ax.axhline(y=five_year_avg, color="#333", linestyle="--", linewidth=2, alpha=0.7)
+    ax.text(2020.5, five_year_avg + 3, f"5-Year Avg: ${five_year_avg:.1f}B",
+            fontsize=10, fontweight="bold", color="#333")
+
+    # "4x spike" annotation
+    ax.annotate("4\u00d7 the\n5-yr average", xy=(2025, 121), xytext=(2023.5, 80),
+                arrowprops=dict(arrowstyle="->", color=BUBBLE_ZONE, lw=2),
+                fontsize=12, fontweight="bold", color=BUBBLE_ZONE, ha="center")
+
+    # Value labels on bars
+    for bar, val in zip(bars, debt):
+        ax.text(bar.get_x() + bar.get_width() / 2, val + 2, f"${val}B",
+                ha="center", fontsize=9, fontweight="bold")
+
+    ax.set_title("Big Tech Debt Issuance \u2014 The 2025 AI Funding Spike",
+                 fontsize=16, fontweight="bold")
+    ax.set_xlabel("Year", fontsize=12)
+    ax.set_ylabel("Corporate Debt Issuance (Billions USD)", fontsize=12)
+    ax.grid(True, alpha=0.3, axis="y")
+    ax.set_ylim(0, 150)
+
+    fig.savefig("output/charts/06_tech_debt.png", dpi=EXPORT_DPI,
+                facecolor=fig.get_facecolor(), edgecolor="none")
+    plt.close(fig)
+    return "output/charts/06_tech_debt.png"
+
+
+def main():
+    path = plot_tech_debt()
+    print(f"Chart saved: {path}")
+
+
+if __name__ == "__main__":
+    main()