Weighted first and last names from SCB, the SSA and the Census under a sex table, personnummer, samordningsnummer, SSN and ITIN in their valid ranges, and date, time and datetime over date()

data-import/names-se.py

@@ -0,0 +1,52 @@
+#!/usr/bin/env python3
+"""Rebuild data/sv_SE/first-name.tsv and last-name.tsv from SCB's whole-population name counts (CC0, "Källa: SCB").
+
+    data-import/names-se.py [--source URL_OR_FILE] [--first N] [--last N] [--cache DIR] [--out DIR]
+
+A tilltalsnamn goes under each sex that carries it, so a name both sexes carry has two rows.
+"""
+import argparse
+import re
+from pathlib import Path
+
+import tsv
+
+SOURCE = "https://www.scb.se/contentassets/9fe7dbb460994c72b835163dbc491ef9/namn-med-minst-tva-barare-31-december-2022.xlsx"
+OUT = Path(__file__).resolve().parent.parent / "data" / "sv_SE"
+CACHE = Path(__file__).resolve().parent / "cache"
+SHEETS = {"f": "Tilltalsnamn kvinnor", "m": "Tilltalsnamn män"}
+SURNAMES = "Efternamn"
+NAME = re.compile(r"^[^\W\d_]{2,}([ '-][^\W\d_]{2,})*$")
+PARTICLES = {"af", "av", "de", "den", "der", "di", "du", "la", "le", "van", "von"}
+
+
+def cased(name):
+    """SCB's uppercase name as it is written: each part capitalised, a particle before another part lowercased."""
+    parts = name.lower().split(" ")
+    return " ".join(w if w in PARTICLES and len(parts) > 1 else w.title() for w in parts)
+
+
+def counted(rows, top):
+    """The top names of a sheet by bearers, initials and single letters dropped."""
+    names = [(cells[0], int(cells[1])) for cells in rows if len(cells) >= 2 and cells[1].isdigit() and NAME.match(cells[0])]
+    return sorted(names, key=lambda n: (-n[1], n[0]))[:top]
+
+
+def main():
+    p = argparse.ArgumentParser(description=__doc__.splitlines()[0])
+    p.add_argument("--cache", default=str(CACHE))
+    p.add_argument("--first", type=int, default=2000, help="names per sex")
+    p.add_argument("--last", type=int, default=5000)
+    p.add_argument("--out", default=str(OUT))
+    p.add_argument("--source", default=SOURCE)
+    a = p.parse_args()
+    data = tsv.fetch(a.source, a.cache, "scb-namn-2022.xlsx", magic=b"PK")
+    first = [{"name": cased(n), "sex": sex, "count": c} for sex, sheet in SHEETS.items() for n, c in counted(tsv.xlsx_rows(data, sheet), a.first)]
+    last = [{"name": cased(n), "count": c} for n, c in counted(tsv.xlsx_rows(data, SURNAMES), a.last)]
+    out = Path(a.out)
+    tsv.write(out / "first-name.tsv", ["name", "sex", "count"], sorted(first, key=lambda r: (r["name"], r["sex"])))
+    tsv.write(out / "last-name.tsv", ["name", "count"], sorted(last, key=lambda r: r["name"]))
+
+
+if __name__ == "__main__":
+    main()