fix: preserve polars datetime timezones during serialization

altair/utils/core.py

@@ -481,7 +481,12 @@ def sanitize_narwhals_dataframe(
         elif dtype == nw.Date:
             columns.append(nw.col(name).dt.to_string(local_iso_fmt_string))
         elif dtype == nw.Datetime:
-            columns.append(nw.col(name).dt.to_string(f"{local_iso_fmt_string}%.f"))
+            # Preserve timezone information when present so Vega-Lite can disambiguate
+            # repeated local times during DST transitions.
+            fmt = f"{local_iso_fmt_string}%.f"
+            if getattr(dtype, "time_zone", None) is not None:
+                fmt = f"{fmt}%z"
+            columns.append(nw.col(name).dt.to_string(fmt))
         elif dtype == nw.Duration:
             msg = (
                 f'Field "{name}" has type "{dtype}" which is '

tests/__init__.py

@@ -136,6 +136,18 @@ def windows_has_tzdata() -> bool:
     https://duckdb.org/
 """
 
+skip_requires_polars: pytest.MarkDecorator = pytest.mark.skipif(
+    find_spec("polars") is None, reason="`polars` not installed."
+)
+"""
+``pytest.mark.skipif`` decorator.
+
+Applies when `polars`_ import would fail.
+
+.. _polars:
+    https://pola.rs/
+"""
+
 
 @overload
 def skip_requires_pyarrow(

tests/utils/test_utils.py

@@ -11,7 +11,7 @@
     sanitize_narwhals_dataframe,
     sanitize_pandas_dataframe,
 )
-from tests import skip_requires_pyarrow
+from tests import skip_requires_polars, skip_requires_pyarrow
 
 
 def test_infer_vegalite_type():
@@ -168,6 +168,30 @@ def test_sanitize_pyarrow_table_columns() -> None:
     json.dumps(values)
 
 
+@skip_requires_polars
+def test_sanitize_polars_datetime_timezone_preserved() -> None:
+    import polars as pl
+
+    start = pl.datetime(2023, 11, 5, time_zone="US/Mountain")
+    df = pl.DataFrame(
+        {
+            "datetime": pl.datetime_range(
+                start, start.dt.offset_by("3h"), "1h", closed="both", eager=True
+            ),
+            "value": [10, 20, 30, 40],
+        }
+    )
+
+    sanitized = sanitize_narwhals_dataframe(nw.from_native(df, eager_only=True))
+
+    assert sanitized.rows(named=True) == [
+        {"datetime": "2023-11-05T00:00:00-0600", "value": 10},
+        {"datetime": "2023-11-05T01:00:00-0600", "value": 20},
+        {"datetime": "2023-11-05T01:00:00-0700", "value": 30},
+        {"datetime": "2023-11-05T02:00:00-0700", "value": 40},
+    ]
+
+
 def test_sanitize_dataframe_colnames():
     df = pd.DataFrame(np.arange(12).reshape(4, 3))