Split a trip into its two economies, so travel stops being a 60% slab

travel dominated every trip page and said nothing. The tempting fix is a finer
travel taxonomy, which needs a hand-maintained merchant list — the trap #19
already describes — and it is also the wrong diagnosis.

travel is the only category that spans both phases of a trip. Every other one is
100% on-the-ground: on Europe 2026, dining, transport, entertainment, groceries
and shopping are all exactly $0.00 before departure. The chart was not bad, it
was two economies stacked into one, and travel was the only thing visible in the
union.

So split on start_date and use the axis that carries information in each phase.
Booked ahead ($22,050.51, 57%) is all flights and stays, so merchant is the axis
— Agoda $4,490, Air India $3,454, Luxury Escapes $3,284. On the ground
($16,946.94) travel falls to $8,241 among dining $4,452 and transport $2,938, and
category is finally worth charting.

The hero is the ratio, not a lone total, with the on-ground daily rate beside it
— the only figure comparable between trips, since totals are not: Europe
$677.88/day against Auckland $83.39. A trip with near-zero committed spend says
so, because Sonu + Sunny's $184.84 is a filing artefact (both legs' bookings sit
on the first trip), not a cheap trip.

Two dataviz rules this page was breaking. Category bars now use one copper hue
with the name as a direct label: the per-bar rainbow double-encoded identity the
label already carries, and the trip subset fails CVD validation on this surface
(other vs shopping at delta-E 5.0 protan, below the floor of 6). And the hero
figure drops the serif and tabular-nums, which read as decoration at that size.
The phase bar is two ordinal steps of one hue, validated with --ordinal against
the card surface, with a 2px gap so the boundary is an edge.

278 passing, build clean. Data verified against the database directly; I could
not render the page in a browser to eyeball the layout.

src/lib/queries.ts

@@ -927,6 +927,33 @@ export interface TripAnalytics {
   category_breakdown: { category: string; amount: number; count: number }[];
   daily_spend: { date: string; amount: number }[];
   top_merchants: { merchant: string; amount: number; count: number }[];
+  /**
+   * A trip has two economies, and mixing them is what made `travel` look like an
+   * uninformative 60% slab: it is the ONLY category that spans both. Measured on
+   * Europe 2026, every other category is 100% on-the-ground — dining, transport,
+   * entertainment, groceries and shopping are all exactly $0.00 before departure.
+   *
+   * So the fix is not a finer travel taxonomy (which would need a hand-maintained
+   * merchant list, the trap ticket #19 already describes). It is to split by phase
+   * and use the axis that carries information in each: merchant before departure,
+   * where everything is a flight or a booking, and category after it, where travel
+   * drops to a normal-sized slice among peers.
+   *
+   * `committed` is dated before `start_date`; everything else is `on_ground`. A trip
+   * with no start_date has no knowable split, so it all reads as on-ground.
+   */
+  phases: {
+    committed: number;
+    committed_count: number;
+    on_ground: number;
+    on_ground_count: number;
+  };
+  /** Pre-departure spend by merchant — the bookings that make up the commitment. */
+  committed_merchants: { merchant: string; amount: number; count: number }[];
+  /** On-the-ground spend by category, where category is finally worth charting. */
+  on_ground_categories: { category: string; amount: number; count: number }[];
+  /** On-ground spend per day of the trip window. The comparable rate between trips. */
+  on_ground_daily: number;
   tag_breakdown: { tag_id: number; name: string; color: string; amount: number; count: number }[];
   participant_splits: {
     participant_id: number;
@@ -1064,7 +1091,10 @@ export async function getTripAnalytics(tripId: number, viewerId: number): Promis
   //
   // COUNT(*) deliberately still counts refund rows: a refund is a transaction
   // that occurred on the trip, even though it subtracts from the total.
-  const [categoryRows, dailyRows, merchantRows, tagRows, splitRows] = await Promise.all([
+  const [
+    categoryRows, dailyRows, merchantRows, tagRows, splitRows,
+    phaseRows, committedMerchantRows, onGroundCategoryRows,
+  ] = await Promise.all([
     queryRaw<{ category: string; amount: number; count: number }>(`
       SELECT
         COALESCE(o.category_override, t.category, 'other') AS category,
@@ -1242,6 +1272,58 @@ export async function getTripAnalytics(tripId: number, viewerId: number): Promis
          OR paid_to_me.pid IS NOT NULL OR paid_by_me.pid IS NOT NULL
       ORDER BY 3 DESC
     `, [tripId, viewerId]),
+
+    // ── The phase split, and the right axis on each side of it ──
+    //
+    // $3 is the trip's start_date. NULL makes every comparison NULL, so a trip with
+    // no dates collapses to all-on-ground rather than erroring or silently
+    // reporting everything as committed.
+    queryRaw<{ committed: number; committed_count: number; on_ground: number; on_ground_count: number }>(`
+      SELECT
+        COALESCE(SUM(CASE WHEN t.transaction_date < $2::date THEN ${SPEND_SIGNED} END), 0)::float AS committed,
+        COUNT(*) FILTER (WHERE t.transaction_date < $2::date)::int AS committed_count,
+        COALESCE(SUM(CASE WHEN t.transaction_date >= $2::date OR $2 IS NULL THEN ${SPEND_SIGNED} END), 0)::float AS on_ground,
+        COUNT(*) FILTER (WHERE t.transaction_date >= $2::date OR $2 IS NULL)::int AS on_ground_count
+      FROM transaction_overrides o
+      JOIN transactions t ON t.id = o.transaction_id
+      WHERE o.trip_id = $1
+        AND ${NET_SPEND_ROWS}
+        AND ${EXCLUDE_RECONCILED_SOURCE}
+        AND COALESCE(o.category_override, t.category, 'other') NOT IN ('transfers', 'investment')
+    `, [tripId, trip.start_date]),
+
+    queryRaw<{ merchant: string; amount: number; count: number }>(`
+      SELECT
+        COALESCE(o.merchant_normalized, t.merchant_normalized, t.merchant_name, t.description) AS merchant,
+        SUM(${SPEND_SIGNED})::float AS amount,
+        COUNT(*)::int AS count
+      FROM transaction_overrides o
+      JOIN transactions t ON t.id = o.transaction_id
+      WHERE o.trip_id = $1
+        AND t.transaction_date < $2::date
+        AND ${NET_SPEND_ROWS}
+        AND ${EXCLUDE_RECONCILED_SOURCE}
+        AND COALESCE(o.category_override, t.category, 'other') NOT IN ('transfers', 'investment')
+      GROUP BY 1
+      ORDER BY 2 DESC
+      LIMIT 12
+    `, [tripId, trip.start_date]),
+
+    queryRaw<{ category: string; amount: number; count: number }>(`
+      SELECT
+        COALESCE(o.category_override, t.category, 'other') AS category,
+        SUM(${SPEND_SIGNED})::float AS amount,
+        COUNT(*)::int AS count
+      FROM transaction_overrides o
+      JOIN transactions t ON t.id = o.transaction_id
+      WHERE o.trip_id = $1
+        AND (t.transaction_date >= $2::date OR $2 IS NULL)
+        AND ${NET_SPEND_ROWS}
+        AND ${EXCLUDE_RECONCILED_SOURCE}
+        AND COALESCE(o.category_override, t.category, 'other') NOT IN ('transfers', 'investment')
+      GROUP BY 1
+      ORDER BY 2 DESC
+    `, [tripId, trip.start_date]),
   ]);
 
   const num_days = (trip.start_date && trip.end_date)
@@ -1260,6 +1342,12 @@ export async function getTripAnalytics(tripId: number, viewerId: number): Promis
     tag_breakdown: tagRows,
     participant_splits: splitRows,
     viewer_is_owner: trip.owner_id === viewerId,
+    phases: phaseRows[0] ?? { committed: 0, committed_count: 0, on_ground: 0, on_ground_count: 0 },
+    committed_merchants: committedMerchantRows,
+    on_ground_categories: onGroundCategoryRows,
+    // Per day of the trip window, not per day of the whole span — the commitment
+    // was made over months and dividing it by trip length would be meaningless.
+    on_ground_daily: (phaseRows[0]?.on_ground ?? 0) / num_days,
   };
 }