fix(get_chartdata): use proper statistics.median for chart metadata

_calculate_metadata()'s inline calc_stats() computed the median as a
naive sorted(data)[len(data) // 2], which returns the upper-middle
value for even-length datasets instead of averaging the two middle
values. A full day is always an even interval count (96 quarter-hours
or 24 hours), so this silently overstated "median" and
"median_position" in nearly every price_stats block of the
get_chartdata response. The rest of the codebase already has a
correct calculate_median() in utils/average.py; this was an isolated
inline duplicate with the bug.

Impact: get_chartdata's price_stats.combined/dayN.median and
median_position now report the statistically correct median for
chart annotations and metadata-driven dashboards.

custom_components/tibber_prices/services/get_chartdata.py

@@ -24,6 +24,7 @@ from __future__ import annotations
 from datetime import datetime, timedelta
 import math
 import re
+import statistics
 from typing import TYPE_CHECKING, Any, Final
 
 import voluptuous as vol
@@ -174,7 +175,12 @@ def _calculate_metadata(
         min_val = min(data)
         max_val = max(data)
         mean_val = sum(data) / len(data)
-        median_val = sorted(data)[len(data) // 2]
+        # CRITICAL: statistics.median() averages the two middle values for
+        # even-length data (the common case: a full day is always an even
+        # number of 15min/hourly intervals). A naive sorted(data)[len//2]
+        # would instead return the upper-middle value, silently overstating
+        # the median for every "combined"/per-day stat block.
+        median_val = statistics.median(data)
 
         # Calculate mean_position and median_position (0-1 scale)
         price_range = max_val - min_val

tests/services/test_get_chartdata_metadata.py

@@ -0,0 +1,77 @@
+"""Tests for get_chartdata metadata statistics calculation."""
+
+from __future__ import annotations
+
+from datetime import UTC, datetime, timedelta
+
+from custom_components.tibber_prices.services.get_chartdata import _calculate_metadata
+
+
+def _make_chart_data(prices: list[float], start: datetime | None = None) -> list[dict]:
+    """Build minimal chart_data entries (start_time + price) for metadata calc."""
+    base = start or datetime(2026, 1, 1, 0, 0, tzinfo=UTC)
+    return [
+        {
+            "start_time": (base + timedelta(minutes=15 * i)).isoformat(),
+            "price_per_kwh": price,
+        }
+        for i, price in enumerate(prices)
+    ]
+
+
+class TestCalculateMetadataMedian:
+    """Regression coverage: median must use proper statistics.median, not naive indexing.
+
+    A naive `sorted(data)[len(data)//2]` returns the upper-middle value for
+    even-length datasets instead of averaging the two middle values. Since a
+    full day always has an even interval count (96 quarter-hours, 24 hours),
+    this bug silently affected nearly every "combined"/per-day median in the
+    chartdata metadata response.
+    """
+
+    def test_median_for_even_length_dataset_is_averaged(self) -> None:
+        """4 known prices: naive impl would report 30.0, correct median is 25.0."""
+        chart_data = _make_chart_data([10.0, 20.0, 30.0, 40.0])
+
+        metadata = _calculate_metadata(
+            chart_data=chart_data,
+            price_field="price_per_kwh",
+            start_time_field="start_time",
+            currency="EUR",
+            resolution="interval",
+            subunit_currency=False,
+        )
+
+        assert metadata["price_stats"]["combined"]["median"] == 25.0
+
+    def test_median_for_odd_length_dataset_is_middle_value(self) -> None:
+        """3 known prices: median is simply the middle value."""
+        chart_data = _make_chart_data([10.0, 20.0, 30.0])
+
+        metadata = _calculate_metadata(
+            chart_data=chart_data,
+            price_field="price_per_kwh",
+            start_time_field="start_time",
+            currency="EUR",
+            resolution="interval",
+            subunit_currency=False,
+        )
+
+        assert metadata["price_stats"]["combined"]["median"] == 20.0
+
+    def test_median_position_reflects_corrected_median(self) -> None:
+        """median_position must be derived from the corrected median, not the naive one."""
+        chart_data = _make_chart_data([10.0, 20.0, 30.0, 40.0])
+
+        metadata = _calculate_metadata(
+            chart_data=chart_data,
+            price_field="price_per_kwh",
+            start_time_field="start_time",
+            currency="EUR",
+            resolution="interval",
+            subunit_currency=False,
+        )
+
+        combined = metadata["price_stats"]["combined"]
+        # median=25.0, min=10.0, max=40.0 -> position = (25-10)/(40-10) = 0.5
+        assert combined["median_position"] == 0.5