feat: Implement Phase 3 neighbourhood data model

Add schemas, parsers, loaders, and models for Toronto neighbourhood-centric
data including census profiles, crime statistics, and amenities.

Schemas:
- NeighbourhoodRecord, CensusRecord, CrimeRecord, CrimeType
- AmenityType, AmenityRecord, AmenityCount

Models:
- BridgeCMHCNeighbourhood (zone-to-neighbourhood mapping with weights)
- FactCensus, FactCrime, FactAmenities

Parsers:
- TorontoOpenDataParser (CKAN API for neighbourhoods, census, amenities)
- TorontoPoliceParser (crime rates, MCI data)

Loaders:
- load_census_data, load_crime_data, load_amenities
- build_cmhc_neighbourhood_crosswalk (PostGIS area weights)

Also updates CLAUDE.md with projman plugin workflow documentation.

Closes #53, #54, #55, #56, #57, #58, #59

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

portfolio_app/toronto/models/facts.py

@@ -1,11 +1,117 @@
 """SQLAlchemy models for fact tables."""
 
-from sqlalchemy import ForeignKey, Integer, Numeric, String
+from sqlalchemy import ForeignKey, Index, Integer, Numeric, String
 from sqlalchemy.orm import Mapped, mapped_column, relationship
 
 from .base import Base
 
 
+class BridgeCMHCNeighbourhood(Base):
+    """Bridge table for CMHC zone to neighbourhood mapping with area weights.
+
+    Enables disaggregation of CMHC zone-level rental data to neighbourhood level
+    using area-based proportional weights computed via PostGIS.
+    """
+
+    __tablename__ = "bridge_cmhc_neighbourhood"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    cmhc_zone_code: Mapped[str] = mapped_column(String(10), nullable=False)
+    neighbourhood_id: Mapped[int] = mapped_column(Integer, nullable=False)
+    weight: Mapped[float] = mapped_column(
+        Numeric(5, 4), nullable=False
+    )  # 0.0000 to 1.0000
+
+    __table_args__ = (
+        Index("ix_bridge_cmhc_zone", "cmhc_zone_code"),
+        Index("ix_bridge_neighbourhood", "neighbourhood_id"),
+    )
+
+
+class FactCensus(Base):
+    """Census statistics by neighbourhood and year.
+
+    Grain: One row per neighbourhood per census year.
+    """
+
+    __tablename__ = "fact_census"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    neighbourhood_id: Mapped[int] = mapped_column(Integer, nullable=False)
+    census_year: Mapped[int] = mapped_column(Integer, nullable=False)
+    population: Mapped[int | None] = mapped_column(Integer, nullable=True)
+    population_density: Mapped[float | None] = mapped_column(
+        Numeric(10, 2), nullable=True
+    )
+    median_household_income: Mapped[float | None] = mapped_column(
+        Numeric(12, 2), nullable=True
+    )
+    average_household_income: Mapped[float | None] = mapped_column(
+        Numeric(12, 2), nullable=True
+    )
+    unemployment_rate: Mapped[float | None] = mapped_column(
+        Numeric(5, 2), nullable=True
+    )
+    pct_bachelors_or_higher: Mapped[float | None] = mapped_column(
+        Numeric(5, 2), nullable=True
+    )
+    pct_owner_occupied: Mapped[float | None] = mapped_column(
+        Numeric(5, 2), nullable=True
+    )
+    pct_renter_occupied: Mapped[float | None] = mapped_column(
+        Numeric(5, 2), nullable=True
+    )
+    median_age: Mapped[float | None] = mapped_column(Numeric(5, 2), nullable=True)
+    average_dwelling_value: Mapped[float | None] = mapped_column(
+        Numeric(12, 2), nullable=True
+    )
+
+    __table_args__ = (
+        Index("ix_fact_census_neighbourhood_year", "neighbourhood_id", "census_year"),
+    )
+
+
+class FactCrime(Base):
+    """Crime statistics by neighbourhood and year.
+
+    Grain: One row per neighbourhood per year per crime type.
+    """
+
+    __tablename__ = "fact_crime"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    neighbourhood_id: Mapped[int] = mapped_column(Integer, nullable=False)
+    year: Mapped[int] = mapped_column(Integer, nullable=False)
+    crime_type: Mapped[str] = mapped_column(String(50), nullable=False)
+    count: Mapped[int] = mapped_column(Integer, nullable=False)
+    rate_per_100k: Mapped[float | None] = mapped_column(Numeric(10, 2), nullable=True)
+
+    __table_args__ = (
+        Index("ix_fact_crime_neighbourhood_year", "neighbourhood_id", "year"),
+        Index("ix_fact_crime_type", "crime_type"),
+    )
+
+
+class FactAmenities(Base):
+    """Amenity counts by neighbourhood.
+
+    Grain: One row per neighbourhood per amenity type per year.
+    """
+
+    __tablename__ = "fact_amenities"
+
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    neighbourhood_id: Mapped[int] = mapped_column(Integer, nullable=False)
+    amenity_type: Mapped[str] = mapped_column(String(50), nullable=False)
+    count: Mapped[int] = mapped_column(Integer, nullable=False)
+    year: Mapped[int] = mapped_column(Integer, nullable=False)
+
+    __table_args__ = (
+        Index("ix_fact_amenities_neighbourhood_year", "neighbourhood_id", "year"),
+        Index("ix_fact_amenities_type", "amenity_type"),
+    )
+
+
 class FactRentals(Base):
     """Fact table for CMHC rental market data.