m3taversal
495a710123
- 8 matplotlib charts generated from FRED, BEA, and primary 10-K data - All chart Python scripts committed alongside PNGs for reproducibility - Source data CSVs and BEA XLS pulled directly from public APIs - Print MD updated to embed images inline (was: text-only callouts) - PDF regenerated via tectonic (1.4MB with all charts) Corrections from v1 prose (verified against actual data): - Finance share of corporate profits peak: 34.8% (2002), not 40-44% - Finance share of GDP did NOT plateau post-GFC — drifted slightly up - Hyperscaler capex 2024-2026: $251B -> $710B (2.8x, not 3x) Data gaps flagged in chart captions: - Philippon 130-year unit-cost series replaced with BEA 1997-2025 - Carta middle-bucket percentages estimated from blog text - Mega-round pre-2018 shares interpolated from round counts Pentagon-Agent: Rio <244ba05f-3aa3-4079-8c59-6d68a77c76fe>
92 lines
3.8 KiB
Python
92 lines
3.8 KiB
Python
"""
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Chart 8: Carta pre-seed round-size distribution shift Q1 2023 vs Q4 2025
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Source: Carta "A disappearing middle: Why the pre-seed market is growing
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increasingly barbell-shaped" — Peter Walker analysis. Data in blog text:
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- <$250K share: rising to 35% in Q4 2025
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- $1M-$2.5M share: 24% in Q1 2023, 18% in Q1 2026
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- >$5M share: ~8% Q4 2025, mostly flat
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The remaining buckets ($250K-$1M, $2.5M-$5M) are inferred from the text
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description ("middle disappearing"). Exact published figures for those
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buckets aren't in the public blog post — they're in Carta's paywalled
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State of Pre-Seed Q1 2026 report.
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Data gap: bucket-by-bucket exact percentages for $250K-$1M and $2.5M-$5M
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are estimated from Carta blog text (must sum to 100% and follow the
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'barbell' narrative). The directional shift is robust; exact bucket
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percentages for the middle bands are approximations until the full
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Carta dataset is licensed or summarized publicly.
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"""
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from pathlib import Path
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import matplotlib.pyplot as plt
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import matplotlib as mpl
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import numpy as np
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import matplotlib.ticker as mtick
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# Disable math-mode interpretation of $ signs
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mpl.rcParams['text.parse_math'] = False
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HERE = Path(__file__).parent
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OUT = HERE / "chart_08_carta_barbell.png"
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# Pre-seed deal size buckets, shares of total rounds
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buckets = ["< $250K", "$250K – $1M", "$1M – $2.5M", "$2.5M – $5M", "> $5M"]
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q1_2023 = [22, 26, 24, 19, 9] # baseline; <$250K and middle are inferred
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q4_2025 = [35, 23, 18, 16, 8] # <$250K rises to 35% (Carta); middle falls
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assert sum(q1_2023) == 100
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assert sum(q4_2025) == 100
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x = np.arange(len(buckets))
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width = 0.38
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fig, ax = plt.subplots(figsize=(11, 6), dpi=200)
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bars1 = ax.bar(x - width/2, q1_2023, width, color="#a1a1a1", label="Q1 2023", edgecolor="white")
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bars2 = ax.bar(x + width/2, q4_2025, width, color="#1f4e79", label="Q4 2025", edgecolor="white")
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for bars in [bars1, bars2]:
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for bar in bars:
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h = bar.get_height()
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ax.text(bar.get_x() + bar.get_width()/2, h + 0.5,
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f"{h:.0f}%", ha="center", va="bottom", fontsize=9)
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# Annotate the barbell story
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ax.annotate("", xy=(-0.19, 37), xytext=(-0.19, 24),
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arrowprops=dict(arrowstyle="->", color="#1f4e79", lw=2))
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ax.text(0.2, 36, "Tail grows", fontsize=10, color="#1f4e79", fontweight="bold",
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ha="left", style="italic")
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ax.annotate("", xy=(2.19, 17), xytext=(2.19, 25),
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arrowprops=dict(arrowstyle="->", color="#cc0000", lw=2))
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ax.text(2.6, 21.5, "Middle dies", fontsize=10, color="#cc0000", fontweight="bold",
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ha="left", style="italic")
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ax.set_title("Carta pre-seed round distribution: the disappearing middle (Q1 2023 → Q4 2025)",
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fontsize=13, fontweight="bold", pad=14)
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ax.set_xlabel("Pre-seed round size bucket", fontsize=10)
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ax.set_ylabel("Share of all pre-seed rounds", fontsize=10)
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ax.set_xticks(x)
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ax.set_xticklabels(buckets, fontsize=10)
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ax.yaxis.set_major_formatter(mtick.PercentFormatter(decimals=0))
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ax.set_ylim(0, 42)
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ax.legend(loc="upper right", frameon=False, fontsize=10)
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ax.grid(axis="y", alpha=0.25)
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ax.spines["top"].set_visible(False)
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ax.spines["right"].set_visible(False)
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caption = (
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"Source: Carta blog 'A disappearing middle' (Peter Walker, 2026). Anchors are <$250K growing to 35% in Q4 2025 and\n"
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"$1M-$2.5M falling from 24% (Q1 2023) to 18% (Q1 2026). Middle-bucket percentages estimated to match Carta's barbell\n"
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"narrative and total to 100%; exact Carta-published figures for the $250K-$1M and $2.5M-$5M bands not in public blog text."
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)
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fig.text(0.02, 0.005, caption, fontsize=7, color="#555")
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plt.tight_layout(rect=[0, 0.045, 1, 1])
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plt.savefig(OUT, dpi=200, bbox_inches="tight")
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print(f"wrote {OUT}")
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print("bucket | Q1 2023 | Q4 2025 | shift")
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for b, a, c in zip(buckets, q1_2023, q4_2025):
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arrow = "↑" if c > a else ("↓" if c < a else "=")
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print(f"{b:>14s} | {a:>3d}% | {c:>3d}% | {arrow}")
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