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fix(hold-history): switch all metrics from container count to QTY sum

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Rename page title to "Hold 歷史績效". Change trend, reason pareto, and
duration derivation to use QTY-based counting so cards, trend chart, and
analytical charts are consistent with each other.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
egg
2026-03-02 08:56:26 +08:00
parent d8e91624d4
commit 803690646b
2 changed files with 15 additions and 14 deletions
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27
src/mes_dashboard/services/hold_dataset_cache.py
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@@ -376,26 +376,27 @@ def _derive_trend(df: pd.DataFrame) -> Dict[str, Any]:
day_data[key] = _empty_trend_metrics()
continue
# holdQty: distinct containers on hold as of this day
# holdQty: total QTY on hold as of this day
on_hold = (tdf["HOLD_DAY"] <= d) & (
tdf["RELEASE_DAY"].isna() | (tdf["RELEASE_DAY"] > d)
)
hold_qty = int(tdf.loc[on_hold, "CONTAINERID"].nunique())
hold_qty = _safe_int(tdf.loc[on_hold, "QTY"].sum())
# newHoldQty: new holds arriving this day (dedup)
# newHoldQty: QTY of new holds arriving this day (dedup)
new_mask = (tdf["HOLD_DAY"] == d) & (tdf["RN_HOLD_DAY"] == 1)
new_hold_qty = int(new_mask.sum())
new_hold_qty = _safe_int(tdf.loc[new_mask, "QTY"].sum())
# releaseQty: releases on this day
release_qty = int((tdf["RELEASE_DAY"] == d).sum())
# releaseQty: QTY released on this day
release_mask = tdf["RELEASE_DAY"] == d
release_qty = _safe_int(tdf.loc[release_mask, "QTY"].sum())
# futureHoldQty: future holds on this day
# futureHoldQty: QTY of future holds on this day
future_mask = (
(tdf["HOLD_DAY"] == d)
& (tdf["IS_FUTURE_HOLD"] == 1)
& (tdf["FUTURE_HOLD_FLAG"] == 1)
)
future_hold_qty = int(future_mask.sum())
future_hold_qty = _safe_int(tdf.loc[future_mask, "QTY"].sum())
day_data[key] = {
"holdQty": hold_qty,
@@ -428,15 +429,15 @@ def _derive_reason_pareto(df: pd.DataFrame) -> Dict[str, Any]:
.agg(count=("CONTAINERID", "count"), qty=("QTY", "sum"))
.reset_index()
)
grouped = grouped.sort_values("count", ascending=False)
total = grouped["count"].sum()
grouped = grouped.sort_values("qty", ascending=False)
total_qty = grouped["qty"].sum()
items: List[Dict[str, Any]] = []
cumulative = 0.0
for _, row in grouped.iterrows():
count = _safe_int(row["count"])
qty = _safe_int(row["qty"])
pct = round((count / total * 100) if total > 0 else 0, 2)
pct = round((qty / total_qty * 100) if total_qty > 0 else 0, 2)
cumulative += pct
items.append(
{
@@ -466,7 +467,7 @@ def _derive_duration(df: pd.DataFrame) -> Dict[str, Any]:
return {"items": []}
hours = released["HOLD_HOURS"]
total = len(released)
total_qty = _safe_int(released["QTY"].sum())
buckets = [
("<4h", hours < 4),
@@ -479,7 +480,7 @@ def _derive_duration(df: pd.DataFrame) -> Dict[str, Any]:
for label, mask in buckets:
count = int(mask.sum())
qty = _safe_int(released.loc[mask, "QTY"].sum())
pct = round((count / total * 100) if total > 0 else 0, 2)
pct = round((qty / total_qty * 100) if total_qty > 0 else 0, 2)
items.append({"range": label, "count": count, "qty": qty, "pct": pct})
return {"items": items}