feat(places): say what each school is, not only how it scored

The location tables carried one column: a percentage. A parent
shortlisting from a town page is asking a different question first —
does it take my child's age, is it a faith school, does it have a
nursery — and the page could not answer any of it.

Primary tables gain Ages, Religious character, Nursery and
Constituency; secondary tables the same minus Nursery, which is a
question about a different intake. An all-through school renders in
both groups, so its nursery shows under primary alone.

The measure moves to the second column rather than the last. Six
columns overflow a phone and .tableWrap turns that into a horizontal
swipe; with the measure last, the one number the page exists for is
the one scrolled off the screen.

Cell rules are the ones the school page already uses, so the two
surfaces cannot disagree about the same school: "Does not apply",
"None" and "Not applicable" all read as no religious character, and
the en-dash age normalisation moves into formatAgeSpan, which
formatAgeRange now delegates to.

Backend: nursery_provision and parliamentary_constituency were not in
the place response. Both are optional GIAS mart columns that
data_loader degrades to NULL, and the `in rows.columns` guard keeps a
mart the pipeline has not rebuilt working.

Also fixes a live bug on the same line: SCHOOL_COLUMNS already ends
with latitude and longitude, and the endpoint concatenated them again,
so pandas dropped one of every duplicated pair and warned "columns are
not unique" on each request. Ordered de-duplication removes the
warning and the silent drop.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01FuPUioHpxtaiDNagQvjxyM

backend/tests/test_places_api.py

@@ -137,3 +137,49 @@ def test_an_authority_without_a_page_is_named_but_carries_no_slug(straddling_cli
     by_name = {a["name"]: a for a in body["place"]["authorities"]}
     assert by_name["Essex"]["slug"] == "essex"
     assert by_name["Isles Of Scilly"]["slug"] is None
+
+
+def _attributed_df() -> pd.DataFrame:
+    """The same town, with the four attributes the place table now shows."""
+    df = _schools_df()
+    df["age_range"] = "4-11"
+    df["religious_denomination"] = "Church of England"
+    df["nursery_provision"] = True
+    df["parliamentary_constituency"] = "Brentwood and Ongar"
+    return df
+
+
+@pytest.fixture()
+def attributed_client(monkeypatch):
+    from backend import app as app_module
+
+    monkeypatch.setattr(app_module, "load_school_data", _attributed_df)
+    monkeypatch.setattr(app_module, "load_latest_school_data", _attributed_df)
+    monkeypatch.setattr(app_module, "_place_registry", None)
+    return TestClient(app_module.app, raise_server_exceptions=False)
+
+
+def test_place_detail_carries_the_attributes_the_table_shows(attributed_client):
+    """age_range and religious_denomination ride in on SCHOOL_COLUMNS.
+
+    nursery_provision and parliamentary_constituency do not, and the place
+    table needs all four — a column the response cannot fill is a column of
+    dashes on ~3,900 pages.
+    """
+    body = attributed_client.get("/api/places/town/brentwood").json()
+    school = body["schools"][0]
+    assert school["age_range"] == "4-11"
+    assert school["religious_denomination"] == "Church of England"
+    assert school["nursery_provision"] is True
+    assert school["parliamentary_constituency"] == "Brentwood and Ongar"
+
+
+def test_place_detail_survives_a_mart_without_the_optional_columns(client):
+    """The base fixture has neither column, as an unrebuilt mart does not.
+
+    data_loader degrades those to NULL rather than failing the load, so the
+    endpoint must not assume they are present.
+    """
+    res = client.get("/api/places/town/brentwood")
+    assert res.status_code == 200
+    assert "nursery_provision" not in res.json()["schools"][0]