chore: Remove TRREB references from Python modules

- Remove DimTRREBDistrict model and FactPurchases model
- Remove TRREBDistrict schema and AreaType enum
- Remove TRREBDistrictParser from geo parsers
- Remove load_trreb_districts from dimension loaders
- Remove create_district_map from choropleth figures
- Remove get_demo_districts and get_demo_purchase_data from demo_data
- Update summary metrics to remove purchase-related metrics
- Update callbacks to remove TRREB-related comments
- Update methodology page to remove TRREB data source section
- Update dashboard data notice to remove TRREB mention

Closes #49

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

portfolio_app/figures/__init__.py

@@ -2,7 +2,6 @@
 
 from .choropleth import (
     create_choropleth_figure,
-    create_district_map,
     create_zone_map,
 )
 from .summary_cards import create_metric_card_figure, create_summary_metrics
@@ -17,7 +16,6 @@ from .time_series import (
 __all__ = [
     # Choropleth
     "create_choropleth_figure",
-    "create_district_map",
     "create_zone_map",
     # Time series
     "create_price_time_series",

portfolio_app/figures/choropleth.py

@@ -115,34 +115,6 @@ def create_choropleth_figure(
     return fig
 
 
-def create_district_map(
-    districts_geojson: dict[str, Any] | None,
-    purchase_data: list[dict[str, Any]],
-    metric: str = "avg_price",
-) -> go.Figure:
-    """Create choropleth map for TRREB districts.
-
-    Args:
-        districts_geojson: GeoJSON for TRREB district boundaries.
-        purchase_data: Purchase statistics by district.
-        metric: Metric to display (avg_price, sales_count, etc.).
-
-    Returns:
-        Plotly Figure object.
-    """
-    hover_columns = ["district_name", "sales_count", "avg_price", "median_price"]
-
-    return create_choropleth_figure(
-        geojson=districts_geojson,
-        data=purchase_data,
-        location_key="district_code",
-        color_column=metric,
-        hover_data=[c for c in hover_columns if c != metric],
-        color_scale="Blues" if "price" in metric else "Greens",
-        title="Toronto Purchase Market by District",
-    )
-
-
 def create_zone_map(
     zones_geojson: dict[str, Any] | None,
     rental_data: list[dict[str, Any]],