fix(waterdata.xarray): drop time_series_id from the flat stats dataset

The stats flat conversion keeps every column, and _handle_stats_nesting
surfaces all outer feature-property keys, so a time_series_id could leak into
the CF dataset as an opaque-UUID variable. Add it to _build_stats's drop set
(alongside computation_id / parent_time_series_id), matching the coverage of
the removed pandas-path hash drop. Test asserts all three are dropped.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: thodson-usgs

dataretrieval/waterdata/xarray.py

@@ -711,7 +711,7 @@ def _build_stats(df, base_meta, service):
     # opaque hash IDs never reach those datasets. This flat path keeps every
     # column, so drop the stats service's hash-valued IDs (and geometry) here to
     # keep the CF dataset free of per-record UUID coordinates.
-    drop = ("geometry", "computation_id", "parent_time_series_id")
+    drop = ("geometry", "computation_id", "parent_time_series_id", "time_series_id")
     flat = df.drop(columns=[c for c in drop if c in df.columns])
     ds = _xr.Dataset.from_dataframe(flat.reset_index(drop=True))
     ds.attrs = _dataset_attrs(service, base_meta)

tests/waterdata_xarray_test.py

@@ -181,12 +181,13 @@ def test_build_stats_drops_hash_columns():
             "parameter_code": ["00060"],
             "computation_id": ["7d70379f-8452-44cd-b026-24dfa11f8503"],
             "parent_time_series_id": ["9cca880dec4846ec8cbdd05f3e22603e"],
+            "time_series_id": ["b026-24dfa11f8503"],
             "p50_va": [120.0],
         }
     )
     ds = wdx._build_stats(df, _meta(), "statistics")
-    assert "computation_id" not in ds.variables
-    assert "parent_time_series_id" not in ds.variables
+    for hash_col in ("computation_id", "parent_time_series_id", "time_series_id"):
+        assert hash_col not in ds.variables
     assert "p50_va" in ds.data_vars