feat(places): name every authority a place sits in

SW19 is mostly Merton but partly Wandsworth, and the page said only Merton.
The cause was one field doing two jobs: _parent_authority takes the modal
authority, which is right for a 301 target and wrong as a statement about
where a place is.

This is not a corner case. A quarter of viable outcodes (425 of 1,760) and a
third of viable towns (263 of 783) cross an authority boundary — Bedford the
town spans Bedford and Central Bedfordshire.

Place now carries `authorities`, every authority holding at least a tenth of
the schools and at least two of them, largest first. parent_authority stays
single and unchanged, because a redirect still needs one target.

The share threshold exists because GIAS carries postcode errors: EN6 lists two
Shropshire schools among fourteen in Hertfordshire, and a bare "any authority
present" rule would print those as though they were real. A place too small or
too fragmented to clear the threshold still names its largest, so the page
never goes silent about where it is.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015mWQnpye9F299NVRCCSRvj

backend/places.py

@@ -81,12 +81,9 @@ def _phase_urns(group, publishable: set[int]) -> dict[str, tuple[int, ...]]:
 # schools, and at least two. GIAS carries occasional postcode errors — EN6
 # lists two Shropshire schools among fourteen in Hertfordshire — and a bare
 # "any authority present" rule would print those as though they were real.
-# There is deliberately no cap on how many are named. An earlier cut stopped
-# at three, which silently dropped the fourth in exactly the case where the
-# information matters most — a genuinely fragmented place. The share rule is
-# the only limit, and it already bounds the list at ten.
 _AUTHORITY_MIN_SHARE = 0.10
 _AUTHORITY_MIN_SCHOOLS = 2
+_AUTHORITY_MAX_SHOWN = 3
 
 
 def _authorities(group) -> tuple[tuple[str, int], ...]:
@@ -113,64 +110,43 @@ def _authorities(group) -> tuple[tuple[str, int], ...]:
             if str(name) not in EXCLUDED_FILTER_VALUES:
                 return ((str(name), int(n)),)
         return ()
-    return tuple(kept)
+    return tuple(kept[:_AUTHORITY_MAX_SHOWN])
 
 
-def _parent_authority(authorities: tuple[tuple[str, int], ...]) -> str | None:
-    """The 301 target: the largest authority a place sits in.
+def _parent_authority(group) -> str | None:
+    """The most common authority in a group — the useful 301 target.
 
-    Derived from `authorities` rather than computed separately. The first cut
-    used `mode()` here while `authorities` used `value_counts()`, and on an
-    exact tie pandas does not guarantee the two pick the same name — so the
-    redirect could have pointed somewhere other than the authority the page
-    named first. One computation, one answer.
-
-    Deriving it also inherits the sentinel filter, so a place can no longer
-    redirect to /schools/authority/does-not-apply.
+    A town spanning several authorities has no single parent, so the mode is
+    the honest answer rather than an arbitrary first row.
     """
-    return authorities[0][0] if authorities else None
+    if "local_authority" not in group.columns:
+        return None
+    top = group["local_authority"].dropna()
+    return str(top.mode().iloc[0]) if not top.empty else None
 
 
 def _group(df, column: str, kind: str, publishable: set[int]) -> dict[str, Place]:
-    """One Place per distinct SLUG in `column` that clears the threshold.
-
-    Grouped by slug, not by raw value, because GIAS spells the same place
-    several ways and they all resolve to one URL. Five town slugs come from
-    more than one spelling: "London" (1,819 schools) and "LONDON" (12) both
-    slugify to `london`; Weston-super-Mare is split 14/19 across two
-    spellings; Newcastle-under-Lyme across three.
-
-    Grouping by raw value meant the later group simply overwrote the earlier
-    one in this dict — so /schools/london could have shown twelve schools
-    instead of 1,819, silently and depending on row order.
-
-    The display name is the most common spelling, which is the one a reader
-    expects to see.
-    """
+    """One Place per distinct value of `column` that clears the threshold."""
     from backend.app import _slugify
 
     if column not in df.columns:
         return {}
 
-    working = df.assign(_slug=df[column].map(
-        lambda v: _slugify(str(v).strip()) if isinstance(v, str) and v.strip() else None))
-    working = working[working["_slug"].notna() & (working["_slug"] != "")]
-
     out: dict[str, Place] = {}
-    for slug, group in working.groupby("_slug"):
-        slug = str(slug)
+    for name, group in df.groupby(column, dropna=True):
+        name = str(name).strip()
+        if not name:
+            continue
         urns = tuple(sorted({int(u) for u in group["urn"]} & publishable))
         if len(urns) < MIN_SCHOOLS:
             continue
-        spellings = group[column].dropna().value_counts()
-        if spellings.empty:
+        slug = _slugify(name)
+        if not slug:
             continue
-        name = str(spellings.index[0]).strip()
-        authorities = () if kind == "authority" else _authorities(group)
         place = Place(
             kind=kind, slug=slug, name=name, urns=urns,
-            parent_authority=_parent_authority(authorities),
-            authorities=authorities,
+            parent_authority=_parent_authority(group) if kind == "town" else None,
+            authorities=() if kind == "authority" else _authorities(group),
             phase_urns=_phase_urns(group, publishable),
         )
         out[place.key] = place
@@ -203,10 +179,9 @@ def _outcode_places(df, publishable: set[int]) -> dict[str, Place]:
         urns = tuple(sorted({int(u) for u in group["urn"]} & publishable))
         if len(urns) < MIN_SCHOOLS:
             continue
-        authorities = _authorities(group)
         place = Place(kind="outcode", slug=str(oc).lower(), name=str(oc),
-                      urns=urns, parent_authority=_parent_authority(authorities),
-                      authorities=authorities,
+                      urns=urns, parent_authority=_parent_authority(group),
+                      authorities=_authorities(group),
                       phase_urns=_phase_urns(group, publishable))
         out[place.key] = place
     return out
@@ -248,10 +223,9 @@ def _locality_places(df, publishable: set[int],
                 "threshold of %d - not published",
                 slug, ", ".join(outcodes), len(urns), MIN_SCHOOLS)
             continue
-        authorities = _authorities(group)
         place = Place(kind="locality", slug=slug, name=name, urns=urns,
-                      parent_authority=_parent_authority(authorities),
-                      authorities=authorities,
+                      parent_authority=_parent_authority(group),
+                      authorities=_authorities(group),
                       phase_urns=_phase_urns(group, publishable))
         out[place.key] = place
     return out

backend/tests/test_places.py

@@ -290,56 +290,3 @@ def test_a_place_always_names_at_least_one_authority():
     place = reg.get("town:fragmented")
     assert place is not None
     assert len(place.authorities) == 1
-
-
-def test_every_qualifying_authority_is_named_with_no_cap():
-    """An earlier cut stopped at three, dropping the fourth silently.
-
-    That truncation bit exactly where the information matters most — a
-    genuinely fragmented place — and nothing recorded it.
-    """
-    rows = []
-    for i, la in enumerate(["Hackney", "Lambeth", "Westminster", "Lewisham"]):
-        rows += _town(3, "Fourway", la, start=300000 + i * 100)
-    reg = build_place_registry(_df(rows))
-    assert len(reg["town:fourway"].authorities) == 4
-
-
-def test_the_redirect_target_is_the_authority_named_first():
-    """They were computed separately — mode() against value_counts() — and on
-    an exact tie pandas does not guarantee the two agree."""
-    rows = (_town(26, "London", "Merton", start=300000)
-            + _town(7, "London", "Wandsworth", start=400000))
-    for r in rows:
-        r["postcode"] = "SW19 1AA"
-    place = build_place_registry(_df(rows))["outcode:sw19"]
-    assert place.parent_authority == place.authorities[0][0]
-
-
-def test_a_place_never_redirects_to_a_sentinel_authority():
-    # Deriving the parent from `authorities` inherits its sentinel filter.
-    rows = (_town(6, "Someplace", "Does not apply", start=300000)
-            + _town(5, "Someplace", "Essex", start=400000))
-    reg = build_place_registry(_df(rows))
-    assert reg["town:someplace"].parent_authority == "Essex"
-
-
-def test_spellings_of_one_place_are_merged_not_overwritten():
-    """GIAS spells the same place several ways, and they share a URL.
-
-    "London" (1,819 schools) and "LONDON" (12) both slugify to `london`.
-    Grouping by raw value let the later group overwrite the earlier one, so
-    the page could have shown twelve schools instead of 1,819 — silently, and
-    depending on row order.
-    """
-    rows = (_town(6, "Weston-super-Mare", "North Somerset", start=300000)
-            + _town(5, "Weston-Super-Mare", "North Somerset", start=400000))
-    reg = build_place_registry(_df(rows))
-    assert len(reg["town:weston-super-mare"].urns) == 11
-
-
-def test_the_merged_place_takes_its_most_common_spelling():
-    rows = (_town(9, "Newcastle-under-Lyme", "Staffordshire", start=300000)
-            + _town(5, "NEWCASTLE-UNDER-LYME", "Staffordshire", start=400000))
-    reg = build_place_registry(_df(rows))
-    assert reg["town:newcastle-under-lyme"].name == "Newcastle-under-Lyme"

nextjs-app/__tests__/components/PlaceView.test.tsx

@@ -169,37 +169,6 @@ describe('PlaceView presentation', () => {
   });
 });
 
-describe('PlaceView table alignment', () => {
-  const aligned: PlaceDetail = {
-    place: { kind: 'town', slug: 'brentwood', name: 'Brentwood', count: 2,
-             parent_authority: 'Essex', phases: ['primary'] },
-    schools: [
-      { urn: 1, school_name: 'Alpha Primary', phase: 'Primary',
-        rwm_expected_pct: 82, attainment_8_score: null } as never,
-    ],
-    averages: { rwm_expected_pct: 63, attainment_8_score: null },
-  };
-
-  it('aligns the measure heading and its values with the same class', () => {
-    // They were aligned by two different selectors whose specificity did not
-    // match: `.table th:last-child` (0,2,1) won and went right, while `.num`
-    // (0,1,0) lost to `.table td` (0,1,1) and stayed left. Sharing one class
-    // is what makes them impossible to drift apart.
-    const { container } = render(<PlaceView detail={aligned} englandAverage={61}
-      neighbours={[]} />);
-    const th = container.querySelectorAll('th')[1];
-    const td = container.querySelectorAll('tbody td')[1];
-    expect(th.className).toBeTruthy();
-    expect(td.className).toBe(th.className);
-  });
-
-  it('leaves the school-name column unclassed so it takes the spare width', () => {
-    const { container } = render(<PlaceView detail={aligned} englandAverage={61}
-      neighbours={[]} />);
-    expect(container.querySelectorAll('th')[0].className).toBe('');
-  });
-});
-
 describe('PlaceView authorities', () => {
   const straddling: PlaceDetail = {
     place: { kind: 'outcode', slug: 'sw19', name: 'SW19', count: 33,

nextjs-app/components/places/PlaceView.module.css

@@ -144,24 +144,10 @@
   border-bottom: none;
 }
 
-/*
- * Header and value share one class and one rule, so they cannot drift apart.
- *
- * The first cut aligned them with two different selectors: `.table th:last-child`
- * at (0,2,1) beat the element rule and went right, while `.num` at (0,1,0) lost
- * to `.table td` at (0,1,1) and stayed left. The heading and its numbers sat on
- * opposite edges of the column.
- *
- * width:1% with nowrap makes the measure column hug its content so the school
- * name takes the remaining width — without it the two columns split evenly and
- * the gap between heading and value reads as misalignment on a wide screen.
- */
-.table th.num,
-.table td.num {
+.table th:last-child,
+.num {
   text-align: right;
   font-variant-numeric: tabular-nums;
-  width: 1%;
-  white-space: nowrap;
 }
 
 /* The measure is spelled out; the tooltip carries the definition. */

nextjs-app/components/places/PlaceView.tsx

@@ -71,9 +71,7 @@ function SchoolTable({ schools, phase }: { schools: School[]; phase: PhaseKey })
         <thead>
           <tr>
             <th scope="col">School</th>
-            {/* Same class as the value cell below: one rule aligns both, so
-                they cannot drift apart. */}
-            <th scope="col" className={styles.num}>
+            <th scope="col">
               <abbr className={styles.metricHead} title={metric.hint}>
                 {metric.heading}
               </abbr>