chore: Delete legacy TRREB dbt models

- Delete stg_trreb__purchases.sql and stg_dimensions__trreb_districts.sql
- Delete int_purchases__monthly.sql
- Delete mart_toronto_purchases.sql and mart_toronto_market_summary.sql
- Update _sources.yml to remove fact_purchases and dim_trreb_district
- Update _staging.yml to remove TRREB staging models
- Update _intermediate.yml to remove int_purchases__monthly
- Update _marts.yml to remove purchase-related marts

Closes #48

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

dbt/models/intermediate/_intermediate.yml

@@ -1,17 +1,6 @@
 version: 2
 
 models:
-  - name: int_purchases__monthly
-    description: "Purchase data enriched with time and district dimensions"
-    columns:
-      - name: purchase_id
-        tests:
-          - unique
-          - not_null
-      - name: district_code
-        tests:
-          - not_null
-
   - name: int_rentals__annual
     description: "Rental data enriched with time and zone dimensions"
     columns:

dbt/models/intermediate/int_purchases__monthly.sql

@@ -1,62 +0,0 @@
--- Intermediate: Monthly purchase data enriched with dimensions
--- Joins purchases with time and district dimensions for analysis
-
-with purchases as (
-    select * from {{ ref('stg_trreb__purchases') }}
-),
-
-time_dim as (
-    select * from {{ ref('stg_dimensions__time') }}
-),
-
-district_dim as (
-    select * from {{ ref('stg_dimensions__trreb_districts') }}
-),
-
-enriched as (
-    select
-        p.purchase_id,
-
-        -- Time attributes
-        t.date_key,
-        t.full_date,
-        t.year,
-        t.month,
-        t.quarter,
-        t.month_name,
-
-        -- District attributes
-        d.district_key,
-        d.district_code,
-        d.district_name,
-        d.area_type,
-
-        -- Metrics
-        p.sales_count,
-        p.dollar_volume,
-        p.avg_price,
-        p.median_price,
-        p.new_listings,
-        p.active_listings,
-        p.days_on_market,
-        p.sale_to_list_ratio,
-
-        -- Calculated metrics
-        case
-            when p.active_listings > 0
-            then round(p.sales_count::numeric / p.active_listings, 3)
-            else null
-        end as absorption_rate,
-
-        case
-            when p.sales_count > 0
-            then round(p.active_listings::numeric / p.sales_count, 1)
-            else null
-        end as months_of_inventory
-
-    from purchases p
-    inner join time_dim t on p.date_key = t.date_key
-    inner join district_dim d on p.district_key = d.district_key
-)
-
-select * from enriched

dbt/models/marts/_marts.yml

@@ -1,15 +1,6 @@
 version: 2
 
 models:
-  - name: mart_toronto_purchases
-    description: "Final mart for Toronto purchase/sales analysis by district and time"
-    columns:
-      - name: purchase_id
-        description: "Unique purchase record identifier"
-        tests:
-          - unique
-          - not_null
-
   - name: mart_toronto_rentals
     description: "Final mart for Toronto rental market analysis by zone and time"
     columns:
@@ -18,6 +9,3 @@ models:
         tests:
           - unique
           - not_null
-
-  - name: mart_toronto_market_summary
-    description: "Combined market summary aggregating purchases and rentals at Toronto level"

dbt/models/marts/mart_toronto_market_summary.sql

@@ -1,81 +0,0 @@
--- Mart: Toronto Market Summary
--- Aggregated view combining purchase and rental market indicators
--- Grain: One row per year-month
-
-with purchases_agg as (
-    select
-        year,
-        month,
-        month_name,
-        quarter,
-
-        -- Aggregate purchase metrics across all districts
-        sum(sales_count) as total_sales,
-        sum(dollar_volume) as total_dollar_volume,
-        round(avg(avg_price), 0) as avg_price_all_districts,
-        round(avg(median_price), 0) as median_price_all_districts,
-        sum(new_listings) as total_new_listings,
-        sum(active_listings) as total_active_listings,
-        round(avg(days_on_market), 0) as avg_days_on_market,
-        round(avg(sale_to_list_ratio), 2) as avg_sale_to_list_ratio,
-        round(avg(absorption_rate), 3) as avg_absorption_rate,
-        round(avg(months_of_inventory), 1) as avg_months_of_inventory,
-        round(avg(avg_price_yoy_pct), 2) as avg_price_yoy_pct
-
-    from {{ ref('mart_toronto_purchases') }}
-    group by year, month, month_name, quarter
-),
-
-rentals_agg as (
-    select
-        year,
-
-        -- Aggregate rental metrics across all zones (all bedroom types)
-        round(avg(avg_rent), 0) as avg_rent_all_zones,
-        round(avg(vacancy_rate), 2) as avg_vacancy_rate,
-        round(avg(rent_change_pct), 2) as avg_rent_change_pct,
-        sum(rental_universe) as total_rental_universe
-
-    from {{ ref('mart_toronto_rentals') }}
-    group by year
-),
-
-final as (
-    select
-        p.year,
-        p.month,
-        p.month_name,
-        p.quarter,
-
-        -- Purchase market indicators
-        p.total_sales,
-        p.total_dollar_volume,
-        p.avg_price_all_districts,
-        p.median_price_all_districts,
-        p.total_new_listings,
-        p.total_active_listings,
-        p.avg_days_on_market,
-        p.avg_sale_to_list_ratio,
-        p.avg_absorption_rate,
-        p.avg_months_of_inventory,
-        p.avg_price_yoy_pct,
-
-        -- Rental market indicators (annual, so join on year)
-        r.avg_rent_all_zones,
-        r.avg_vacancy_rate,
-        r.avg_rent_change_pct,
-        r.total_rental_universe,
-
-        -- Affordability indicator (price to rent ratio)
-        case
-            when r.avg_rent_all_zones > 0
-            then round(p.avg_price_all_districts / (r.avg_rent_all_zones * 12), 1)
-            else null
-        end as price_to_annual_rent_ratio
-
-    from purchases_agg p
-    left join rentals_agg r on p.year = r.year
-)
-
-select * from final
-order by year desc, month desc

dbt/models/marts/mart_toronto_purchases.sql

@@ -1,79 +0,0 @@
--- Mart: Toronto Purchase Market Analysis
--- Final analytical table for purchase/sales data visualization
--- Grain: One row per district per month
-
-with purchases as (
-    select * from {{ ref('int_purchases__monthly') }}
-),
-
--- Add year-over-year calculations
-with_yoy as (
-    select
-        p.*,
-
-        -- Previous year same month values
-        lag(p.avg_price, 12) over (
-            partition by p.district_code
-            order by p.date_key
-        ) as avg_price_prev_year,
-
-        lag(p.sales_count, 12) over (
-            partition by p.district_code
-            order by p.date_key
-        ) as sales_count_prev_year,
-
-        lag(p.median_price, 12) over (
-            partition by p.district_code
-            order by p.date_key
-        ) as median_price_prev_year
-
-    from purchases p
-),
-
-final as (
-    select
-        purchase_id,
-        date_key,
-        full_date,
-        year,
-        month,
-        quarter,
-        month_name,
-        district_key,
-        district_code,
-        district_name,
-        area_type,
-        sales_count,
-        dollar_volume,
-        avg_price,
-        median_price,
-        new_listings,
-        active_listings,
-        days_on_market,
-        sale_to_list_ratio,
-        absorption_rate,
-        months_of_inventory,
-
-        -- Year-over-year changes
-        case
-            when avg_price_prev_year > 0
-            then round(((avg_price - avg_price_prev_year) / avg_price_prev_year) * 100, 2)
-            else null
-        end as avg_price_yoy_pct,
-
-        case
-            when sales_count_prev_year > 0
-            then round(((sales_count - sales_count_prev_year)::numeric / sales_count_prev_year) * 100, 2)
-            else null
-        end as sales_count_yoy_pct,
-
-        case
-            when median_price_prev_year > 0
-            then round(((median_price - median_price_prev_year) / median_price_prev_year) * 100, 2)
-            else null
-        end as median_price_yoy_pct
-
-    from with_yoy
-)
-
-select * from final

dbt/models/staging/_sources.yml

@@ -2,20 +2,10 @@ version: 2
 
 sources:
   - name: toronto_housing
-    description: "Toronto housing data loaded from TRREB and CMHC sources"
+    description: "Toronto housing data loaded from CMHC and City of Toronto sources"
     database: portfolio
     schema: public
     tables:
-      - name: fact_purchases
-        description: "TRREB monthly purchase/sales statistics by district"
-        columns:
-          - name: id
-            description: "Primary key"
-          - name: date_key
-            description: "Foreign key to dim_time"
-          - name: district_key
-            description: "Foreign key to dim_trreb_district"
-
       - name: fact_rentals
         description: "CMHC annual rental survey data by zone and bedroom type"
         columns:
@@ -32,14 +22,6 @@ sources:
           - name: date_key
             description: "Primary key (YYYYMMDD format)"
 
-      - name: dim_trreb_district
-        description: "TRREB district dimension with geometry"
-        columns:
-          - name: district_key
-            description: "Primary key"
-          - name: district_code
-            description: "TRREB district code"
-
       - name: dim_cmhc_zone
         description: "CMHC zone dimension with geometry"
         columns:
@@ -49,7 +31,7 @@ sources:
             description: "CMHC zone code"
 
       - name: dim_neighbourhood
-        description: "City of Toronto neighbourhoods (reference only)"
+        description: "City of Toronto neighbourhoods (158 official boundaries)"
         columns:
           - name: neighbourhood_id
             description: "Primary key"

dbt/models/staging/_staging.yml

@@ -1,23 +1,6 @@
 version: 2
 
 models:
-  - name: stg_trreb__purchases
-    description: "Staged TRREB purchase/sales data from fact_purchases"
-    columns:
-      - name: purchase_id
-        description: "Unique identifier for purchase record"
-        tests:
-          - unique
-          - not_null
-      - name: date_key
-        description: "Date dimension key (YYYYMMDD)"
-        tests:
-          - not_null
-      - name: district_key
-        description: "TRREB district dimension key"
-        tests:
-          - not_null
-
   - name: stg_cmhc__rentals
     description: "Staged CMHC rental market data from fact_rentals"
     columns:
@@ -44,20 +27,6 @@ models:
           - unique
           - not_null
 
-  - name: stg_dimensions__trreb_districts
-    description: "Staged TRREB district dimension"
-    columns:
-      - name: district_key
-        description: "District dimension key"
-        tests:
-          - unique
-          - not_null
-      - name: district_code
-        description: "TRREB district code (e.g., W01, C01)"
-        tests:
-          - unique
-          - not_null
-
   - name: stg_dimensions__cmhc_zones
     description: "Staged CMHC zone dimension"
     columns:

dbt/models/staging/stg_dimensions__trreb_districts.sql

@@ -1,19 +0,0 @@
--- Staged TRREB district dimension
--- Source: dim_trreb_district table
--- Grain: One row per district
-
-with source as (
-    select * from {{ source('toronto_housing', 'dim_trreb_district') }}
-),
-
-staged as (
-    select
-        district_key,
-        district_code,
-        district_name,
-        area_type,
-        geometry
-    from source
-)
-
-select * from staged

dbt/models/staging/stg_trreb__purchases.sql

@@ -1,25 +0,0 @@
--- Staged TRREB purchase/sales data
--- Source: fact_purchases table loaded from TRREB Market Watch PDFs
--- Grain: One row per district per month
-
-with source as (
-    select * from {{ source('toronto_housing', 'fact_purchases') }}
-),
-
-staged as (
-    select
-        id as purchase_id,
-        date_key,
-        district_key,
-        sales_count,
-        dollar_volume,
-        avg_price,
-        median_price,
-        new_listings,
-        active_listings,
-        avg_dom as days_on_market,
-        avg_sp_lp as sale_to_list_ratio
-    from source
-)
-
-select * from staged