ETFs/Funds data quality + cross-asset invariant test + automated README stats

Per maintainer feedback on the initial version, this PR drops the
`country` column addition for ETFs/Funds — the country semantics for
those asset classes (investment scope, not listing-exchange country)
need a richer signal than `exchange -> country` can give. What
remains is still substantial:

## 1. Data-quality fixes on `etfs.csv` (surfaced by the new invariant)

- **14 non-ETF rows removed**: `^REIT` plus 13 US-equity duplicates
  that already existed correctly in `equities.csv` (`BHF`, `BHFAN`,
  `BHFAO`, `BHFAP`, `DTB`, `DTE`, `DTP`, `HTGC`, `PBC`, `PSEC`, `RGA`,
  `RZA`, `TPVG`).
- **56 cross-asset symbol collisions removed** — all 56 were corporate
  bonds / senior notes / equity share-class rows misclassified as ETFs
  (Brighthouse, Corvus Gold, Great Ajax Corp. notes, Argo notes,
  CMS Energy junior subordinated notes, Conifer Holdings senior notes,
  Qwest Corp notes, DTE Energy variants, `ASGI` = Aberdeen Global
  Infrastructure Income Fund, etc.).
- **29 ETF rows with corrupted `exchange` values fixed** — issuer name
  written into the exchange column instead of a real exchange code
  (`Xtrackers`, `Fundlogic`, `Purpose Investments`, `CI Investments`,
  `Horizons ETFs Management`, `Harvest Portfolios Group`,
  `IA Clarington Investments`, `National Bank Investments`,
  `Caldwell Investment Management`, `Developed Markets`,
  `Emerging Markets`, `High Yield Bonds`). Re-derived from ticker
  suffix.
- **`FSST` completed** (Fidelity Sustainable U.S. Equity ETF) — row
  previously had every field NaN. Filled name, currency, summary,
  category_group, category, family, exchange (`PCX`), isin.

## 2. New cross-asset invariant test

`tests/test_invariants.py::test_no_symbol_collisions_across_asset_classes`
asserts that a given `symbol` belongs to at most one of `equities.csv`,
`etfs.csv`, `funds.csv`. This is the test that surfaced the 56 + 14 = 70
cleanup rows above; it would have caught all of them before they
landed on `main`.

## 3. Automated README statistics

`.github/workflows/database_update.yml` gains a new
`Update-README-Statistics` job that runs after the existing
`Add-New-Ticker` / `Update-Compression-Files` / `Update-Categorization-Files`
jobs. It recomputes the statistics tables from the on-disk CSVs and
rewrites `README.md` in-place, committing the result. The
`Check-GICS-Categorisation` job now also depends on it.

README is now split into three tables that reflect the actual schema
of each asset class rather than the previous combined-table layout
whose `Countries` column for ETFs/Funds had no backing data:

```
Table A — Equities only (has country, sector, industry)
| Product  | Quantity | Sectors | Industries | Countries | Exchanges |
| Equities | 160.113  | 11      | 62         | 113       | 84        |

Table B — ETFs / Funds (no country: no schema for it)
| Product | Quantity | Families | Categories | Exchanges |
| ETFs    | 36.485   | 320      | 51         | 51        |
| Funds   | 57.853   | 1.540    | 74         | 33        |

Table C — Currencies / Cryptos / Indices / Money Markets
| Product           | Quantity | Category              |
| Currencies        | 2.556    | 175 Currencies        |
| Cryptocurrencies  | 3.367    | 351 Cryptocurrencies  |
| Indices           | 91.178   | 63 Exchanges          |
| Money Markets     | 1.367    | 2 Exchanges           |
```

The B-table columns are renamed from the previous "Sectors / Industries"
(which were really family/category counts) to be honest about what the
numbers represent.

## What this PR explicitly does NOT do

- **No `country` column on `etfs.csv` / `funds.csv`.** Per
  @JerBouma's feedback, "country" for ETFs/Funds should reflect the
  investment scope (e.g. iShares MSCI World ETF listed on NYSE has
  global scope, not "United States"), not the listing exchange. The
  obvious deterministic source (exchange -> country) doesn't fit that
  semantics. Deferred to a focused discussion / future PR if the
  community decides on a definition.
- **No country fill on missing equities.** 80k equity rows still have
  empty `country`; filling them from listing exchange would be wrong
  for the same reason ASML on Nasdaq stays "Netherlands". Needs an
  actual issuer-domicile source.

## Test plan

- [ ] `pytest tests/` — 50 tests pass (was 49 before; the new
      `test_no_symbol_collisions_across_asset_classes` is the +1)
- [ ] `test_no_symbol_collisions_across_asset_classes` passes
- [ ] `black --check tests/ financedatabase/` clean
- [ ] CI `Update-README-Statistics` job rewrites README correctly on
      next data update
- [ ] Spot-check: `BHF`, `DTE`, `RGA`, etc. exist in `equities.csv`
      only (not in `etfs.csv` anymore)
- [ ] Spot-check: `FSST` has all fields populated

Related: #140 (test infra), #143 (introduced the `exchange -> market`
invariant pattern), #144 (proposes splitting CSVs by exchange).

Author: dokson

.github/workflows/database_update.yml

@@ -426,8 +426,119 @@ jobs:
           if: steps.run.outputs.status != '0'
           run: exit "${{ steps.run.outputs.status }}"
 
+  Update-README-Statistics:
+    needs: [Add-New-Ticker, Update-Compression-Files, Update-Categorization-Files]
+    runs-on: ubuntu-latest
+    steps:
+      - name: checkout repo content
+        uses: actions/checkout@v3
+      - name: pull changes
+        run: git pull https://${{secrets.PAT}}@github.com/JerBouma/FinanceDatabase.git main
+      - name: setup python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.13'
+      - run: pip install pandas
+      - name: Refresh the statistics tables in README.md
+        uses: jannekem/run-python-script-action@v1
+        with:
+          script: |
+            import re
+            from pathlib import Path
+            import pandas as pd
+
+            def _n(x: int) -> str:
+                """Format an integer with a thousand-separator dot (e.g. 160.113)."""
+                return f"{x:,}".replace(",", ".")
+
+            # Table A: Equities — Quantity, Sectors, Industries, Countries, Exchanges
+            eq = pd.read_csv("database/equities.csv", dtype=str)
+            table_a_row = (
+                "Equities",
+                _n(len(eq)),
+                _n(eq["sector"].nunique()),
+                _n(eq["industry"].nunique()),
+                _n(eq["country"].nunique()),
+                _n(eq["exchange"].nunique()),
+            )
+
+            # Table B: ETFs / Funds — Quantity, Families, Categories, Exchanges
+            # (no Countries column: ETF/Fund 'country' is semantically the investment
+            # scope, not a HQ — not derivable from listing exchange alone.)
+            table_b_rows = []
+            for asset in ("ETFs", "Funds"):
+                df = pd.read_csv(f"database/{asset.lower()}.csv", dtype=str)
+                table_b_rows.append((
+                    asset,
+                    _n(len(df)),
+                    _n(df["family"].nunique()),
+                    _n(df["category"].nunique()),
+                    _n(df["exchange"].nunique()),
+                ))
+
+            # Table C: Currencies / Cryptocurrencies / Indices / Money Markets
+            table_c_rows = []
+            for asset, fname, col, label in [
+                ("Currencies",       "currencies.csv",   "quote_currency", "Currencies"),
+                ("Cryptocurrencies", "cryptos.csv",      "cryptocurrency", "Cryptocurrencies"),
+                ("Indices",          "indices.csv",      "exchange",       "Exchanges"),
+                ("Money Markets",    "moneymarkets.csv", "exchange",       "Exchanges"),
+            ]:
+                df = pd.read_csv(f"database/{fname}", dtype=str)
+                table_c_rows.append((asset, _n(len(df)), f"{_n(df[col].nunique())} {label}"))
+
+            def _fmt_table_a(row):
+                h = "| Product           | Quantity   | Sectors    | Industries    | Countries | Exchanges |\n"
+                h += "| ----------------- | ---------- | ---------- | ------------- | --------- | --------- |"
+                a, q, s, i, c, e = row
+                b = f"| {a:<17} | {q:<10} | {s:<10} | {i:<13} | {c:<9} | {e:<9} |"
+                return h + "\n" + b
+
+            def _fmt_table_b(rows):
+                h = "| Product           | Quantity   | Families   | Categories    | Exchanges |\n"
+                h += "| ----------------- | ---------- | ---------- | ------------- | --------- |"
+                b = "\n".join(
+                    f"| {a:<17} | {q:<10} | {f:<10} | {c:<13} | {e:<9} |"
+                    for (a, q, f, c, e) in rows
+                )
+                return h + "\n" + b
+
+            def _fmt_table_c(rows):
+                h = "| Product           | Quantity  | Category              |\n"
+                h += "| ----------------- | --------- | --------------------- |"
+                b = "\n".join(
+                    f"| {a:<17} | {q:<9} | {c:<21} |"
+                    for (a, q, c) in rows
+                )
+                return h + "\n" + b
+
+            readme = Path("README.md")
+            text = readme.read_text(encoding="utf-8")
+            # Replace the existing combined "Equities/ETFs/Funds" table with two tables (A + B).
+            text = re.sub(
+                r"\| Product\s+\| Quantity\s+\| Sectors[^\n]*\| Industries[^\n]*\n\|[^\n]*\n(?:\|[^\n]*\n){3}",
+                _fmt_table_a(table_a_row) + "\n\n" + _fmt_table_b(table_b_rows) + "\n",
+                text,
+                count=1,
+            )
+            text = re.sub(
+                r"\| Product\s+\| Quantity\s+\| Category[^\n]*\n\|[^\n]*\n(?:\|[^\n]*\n){4}",
+                _fmt_table_c(table_c_rows) + "\n",
+                text,
+                count=1,
+            )
+            readme.write_text(text, encoding="utf-8")
+            print("README.md statistics tables refreshed.")
+      - name: Commit README update
+        run: |
+          git config --global user.name 'GitHub Action'
+          git config --global user.email 'action@github.com'
+          git add README.md
+          git diff-index --quiet HEAD || git commit -m "Update README statistics"
+          git push
+
   Check-GICS-Categorisation:
-    needs:  [Add-New-Ticker, Update-Compression-Files, Update-Categorization-Files]
+    needs:  [Add-New-Ticker, Update-Compression-Files, Update-Categorization-Files, Update-README-Statistics]
     runs-on: ubuntu-latest
     steps:
       - name: checkout repo content

README.md

@@ -23,16 +23,19 @@ Some key statistics of the database:
 
 | Product           | Quantity   | Sectors    | Industries    | Countries | Exchanges |
 | ----------------- | ---------- | ---------- | ------------- | --------- | --------- |
-| Equities          | 158.429    | 12         | 63            | 111       | 83        | 
-| ETFs              | 36.786     | 295        | 22            | 111       | 53        |
-| Funds             | 57.881     | 1541       | 52            | 111       | 34        |
+| Equities          | 160.113    | 11         | 62            | 113       | 84        |
+
+| Product           | Quantity   | Families   | Categories    | Exchanges |
+| ----------------- | ---------- | ---------- | ------------- | --------- |
+| ETFs              | 36.485     | 320        | 51            | 51        |
+| Funds             | 57.853     | 1.540      | 74            | 33        |
 
 | Product           | Quantity  | Category              |
 | ----------------- | --------- | --------------------- |
 | Currencies        | 2.556     | 175 Currencies        |
-| Cryptocurrencies  | 3.367     | 352 Cryptocurrencies  |
-| Indices           | 91.183    | 64 Exchanges          |
-| Money Markets     | 1.367     | 3 Exchanges           |
+| Cryptocurrencies  | 3.367     | 351 Cryptocurrencies  |
+| Indices           | 91.178    | 63 Exchanges          |
+| Money Markets     | 1.367     | 2 Exchanges           |
 
 The Finance Database is used within or referenced by: