CLAUDE.md

@@ -6,8 +6,8 @@ Working context for Claude Code on the Analytics Portfolio project.
 
 ## Project Status
 
-**Current Sprint**: 9 (Neighbourhood Dashboard Transition) - **COMPLETE**
-**Phase**: Toronto Neighbourhood Dashboard - Phase 6 & 7 Done
+**Last Completed Sprint**: 9 (Neighbourhood Dashboard Transition)
+**Current State**: Ready for deployment sprint or new features
 **Branch**: `development` (feature branches merge here)
 
 ---
@@ -121,6 +121,7 @@ portfolio_app/
 │   └── toronto/
 │       ├── dashboard.py     # Dashboard -> /toronto
 │       ├── methodology.py   # Methodology -> /toronto/methodology
+│       ├── tabs/            # 5 tab layouts (overview, housing, safety, demographics, amenities)
 │       └── callbacks/       # Dashboard interactions
 ├── components/              # Shared UI (sidebar, cards, controls)
 │   ├── metric_card.py       # KPI card component
@@ -267,9 +268,9 @@ All scripts in `scripts/`:
 
 | Document | Location | Use When |
 |----------|----------|----------|
-| Project reference | `docs/PROJECT_REFERENCE.md` | Architecture decisions |
-| Dashboard vision | `docs/changes/Change-Toronto-Analysis.md` | Dashboard specification |
-| Implementation plan | `docs/changes/Change-Toronto-Analysis-Reviewed.md` | Sprint planning |
+| Project reference | `docs/PROJECT_REFERENCE.md` | Architecture decisions, completed work |
+| Developer guide | `docs/CONTRIBUTING.md` | How to add pages, blog posts, tabs |
+| Lessons learned | `docs/project-lessons-learned/INDEX.md` | Past issues and solutions |
 
 ---
 
@@ -340,4 +341,4 @@ Every Gitea issue should include:
 
 ---
 
-*Last Updated: Sprint 9*
+*Last Updated: January 2026 (Post-Sprint 9)*

README.md

@@ -1,36 +1,42 @@
 # Analytics Portfolio
 
-A data analytics portfolio showcasing end-to-end data engineering, visualization, and analysis capabilities.
+A personal portfolio website showcasing data engineering and visualization capabilities, featuring an interactive Toronto Neighbourhood Dashboard.
 
-## Projects
+## Live Pages
 
-### Toronto Housing Dashboard
+| Route | Page | Description |
+|-------|------|-------------|
+| `/` | Home | Bio landing page |
+| `/about` | About | Background and experience |
+| `/projects` | Projects | Portfolio project showcase |
+| `/resume` | Resume | Professional CV |
+| `/contact` | Contact | Contact form |
+| `/blog` | Blog | Technical articles |
+| `/blog/{slug}` | Article | Individual blog posts |
+| `/toronto` | Toronto Dashboard | Neighbourhood analysis (5 tabs) |
+| `/toronto/methodology` | Methodology | Dashboard data sources and methods |
+| `/health` | Health | API health check endpoint |
 
-An interactive choropleth dashboard analyzing Toronto's housing market using multi-source data integration.
+## Toronto Neighbourhood Dashboard
 
-**Features:**
-- Purchase market analysis from TRREB monthly reports
-- Rental market analysis from CMHC annual surveys
-- Interactive choropleth maps by district/zone
-- Time series visualization with policy event annotations
-- Purchase/Rental mode toggle
+An interactive choropleth dashboard analyzing Toronto's 158 official neighbourhoods across five dimensions:
 
-**Data Sources:**
-- [TRREB Market Watch](https://trreb.ca/market-data/market-watch/) - Monthly purchase statistics
-- [CMHC Rental Market Survey](https://www.cmhc-schl.gc.ca/professionals/housing-markets-data-and-research/housing-data/data-tables/rental-market) - Annual rental data
+- **Overview**: Composite livability scores, income vs safety scatter
+- **Housing**: Affordability index, rent trends, dwelling types
+- **Safety**: Crime rates, breakdowns by type, trend analysis
+- **Demographics**: Income distribution, age pyramids, population density
+- **Amenities**: Parks, schools, transit accessibility
 
-**Tech Stack:**
-- Python 3.11+ / Dash / Plotly
-- PostgreSQL + PostGIS
-- dbt for data transformation
-- Pydantic for validation
-- SQLAlchemy 2.0
+**Data Sources**:
+- City of Toronto Open Data Portal (neighbourhoods, census profiles, amenities)
+- Toronto Police Service (crime statistics)
+- CMHC Rental Market Survey (rental data by zone)
 
 ## Quick Start
 
 ```bash
 # Clone and setup
-git clone https://github.com/lmiranda/personal-portfolio.git
+git clone https://gitea.hotserv.cloud/lmiranda/personal-portfolio.git
 cd personal-portfolio
 
 # Install dependencies and configure environment
@@ -55,48 +61,72 @@ portfolio_app/
 ├── app.py                 # Dash app factory
 ├── config.py              # Pydantic settings
 ├── pages/
-│   ├── home.py           # Bio landing page (/)
-│   └── toronto/          # Toronto dashboard (/toronto)
+│   ├── home.py            # Bio landing (/)
+│   ├── about.py           # About page
+│   ├── contact.py         # Contact form
+│   ├── projects.py        # Project showcase
+│   ├── resume.py          # Resume/CV
+│   ├── blog/              # Blog system
+│   │   ├── index.py       # Article listing
+│   │   └── article.py     # Article renderer
+│   └── toronto/           # Toronto dashboard
+│       ├── dashboard.py   # Main layout with tabs
+│       ├── methodology.py # Data documentation
+│       ├── tabs/          # Tab layouts (5)
+│       └── callbacks/     # Interaction logic
 ├── components/            # Shared UI components
 ├── figures/               # Plotly figure factories
-└── toronto/               # Toronto data logic
-    ├── parsers/          # PDF/CSV extraction
-    ├── loaders/          # Database operations
-    ├── schemas/          # Pydantic models
-    └── models/           # SQLAlchemy ORM
+├── content/
+│   └── blog/              # Markdown blog articles
+├── toronto/               # Toronto data logic
+│   ├── parsers/           # API data extraction
+│   ├── loaders/           # Database operations
+│   ├── schemas/           # Pydantic models
+│   └── models/            # SQLAlchemy ORM
+└── errors/                # Exception handling
 
 dbt/
 ├── models/
-│   ├── staging/          # 1:1 source tables
-│   ├── intermediate/     # Business logic
-│   └── marts/            # Analytical tables
+│   ├── staging/           # 1:1 source tables
+│   ├── intermediate/      # Business logic
+│   └── marts/             # Analytical tables
+
+notebooks/                 # Data documentation (15 notebooks)
+├── overview/              # Overview tab visualizations
+├── housing/               # Housing tab visualizations
+├── safety/                # Safety tab visualizations
+├── demographics/          # Demographics tab visualizations
+└── amenities/             # Amenities tab visualizations
+
+docs/
+├── PROJECT_REFERENCE.md   # Architecture reference
+├── CONTRIBUTING.md        # Developer guide
+└── project-lessons-learned/
 ```
 
+## Tech Stack
+
+| Layer | Technology |
+|-------|------------|
+| Database | PostgreSQL 16 + PostGIS |
+| Validation | Pydantic 2.x |
+| ORM | SQLAlchemy 2.x |
+| Transformation | dbt-postgres |
+| Data Processing | Pandas, GeoPandas |
+| Visualization | Dash + Plotly |
+| UI Components | dash-mantine-components |
+| Testing | pytest |
+| Python | 3.11+ |
+
 ## Development
 
 ```bash
-make test      # Run tests
-make lint      # Run linter
+make test      # Run pytest
+make lint      # Run ruff linter
 make format    # Format code
 make ci        # Run all checks
-```
-
-## Data Pipeline
-
-```
-Raw Files (PDF/Excel)
-    ↓
-Parsers (pdfplumber, pandas)
-    ↓
-Pydantic Validation
-    ↓
-SQLAlchemy Loaders
-    ↓
-PostgreSQL + PostGIS
-    ↓
-dbt Transformations
-    ↓
-Dash Visualization
+make dbt-run   # Run dbt models
+make dbt-test  # Run dbt tests
 ```
 
 ## Environment Variables
@@ -109,12 +139,19 @@ POSTGRES_USER=portfolio
 POSTGRES_PASSWORD=<secure>
 POSTGRES_DB=portfolio
 DASH_DEBUG=true
+SECRET_KEY=<random>
 ```
 
+## Documentation
+
+- **For developers**: See `docs/CONTRIBUTING.md` for setup and contribution guidelines
+- **For Claude Code**: See `CLAUDE.md` for AI assistant context
+- **Architecture**: See `docs/PROJECT_REFERENCE.md` for technical details
+
 ## License
 
 MIT
 
 ## Author
 
-Leo Miranda - [GitHub](https://github.com/lmiranda) | [LinkedIn](https://linkedin.com/in/yourprofile)
+Leo Miranda

docs/CONTRIBUTING.md

@@ -0,0 +1,480 @@
+# Developer Guide
+
+Instructions for contributing to the Analytics Portfolio project.
+
+---
+
+## Table of Contents
+
+1. [Development Setup](#development-setup)
+2. [Adding a Blog Post](#adding-a-blog-post)
+3. [Adding a New Page](#adding-a-new-page)
+4. [Adding a Dashboard Tab](#adding-a-dashboard-tab)
+5. [Creating Figure Factories](#creating-figure-factories)
+6. [Branch Workflow](#branch-workflow)
+7. [Code Standards](#code-standards)
+
+---
+
+## Development Setup
+
+### Prerequisites
+
+- Python 3.11+ (via pyenv)
+- Docker and Docker Compose
+- Git
+
+### Initial Setup
+
+```bash
+# Clone repository
+git clone https://gitea.hotserv.cloud/lmiranda/personal-portfolio.git
+cd personal-portfolio
+
+# Run setup (creates venv, installs deps, copies .env.example)
+make setup
+
+# Start PostgreSQL + PostGIS
+make docker-up
+
+# Initialize database
+make db-init
+
+# Start development server
+make run
+```
+
+The app runs at `http://localhost:8050`.
+
+### Useful Commands
+
+```bash
+make test       # Run tests
+make lint       # Check code style
+make format     # Auto-format code
+make ci         # Run all checks (lint + test)
+make dbt-run    # Run dbt transformations
+make dbt-test   # Run dbt tests
+```
+
+---
+
+## Adding a Blog Post
+
+Blog posts are Markdown files with YAML frontmatter, stored in `portfolio_app/content/blog/`.
+
+### Step 1: Create the Markdown File
+
+Create a new file in `portfolio_app/content/blog/`:
+
+```bash
+touch portfolio_app/content/blog/your-article-slug.md
+```
+
+The filename becomes the URL slug: `/blog/your-article-slug`
+
+### Step 2: Add Frontmatter
+
+Every blog post requires YAML frontmatter at the top:
+
+```markdown
+---
+title: "Your Article Title"
+date: "2026-01-17"
+description: "A brief description for the article card (1-2 sentences)"
+tags:
+  - data-engineering
+  - python
+  - lessons-learned
+status: published
+---
+
+Your article content starts here...
+```
+
+**Required fields:**
+
+| Field | Description |
+|-------|-------------|
+| `title` | Article title (displayed on cards and page) |
+| `date` | Publication date in `YYYY-MM-DD` format |
+| `description` | Short summary for article listing cards |
+| `tags` | List of tags (displayed as badges) |
+| `status` | `published` or `draft` (drafts are hidden from listing) |
+
+### Step 3: Write Content
+
+Use standard Markdown:
+
+```markdown
+## Section Heading
+
+Regular paragraph text.
+
+### Subsection
+
+- Bullet points
+- Another point
+
+```python
+# Code blocks with syntax highlighting
+def example():
+    return "Hello"
+```
+
+**Bold text** and *italic text*.
+
+> Blockquotes for callouts
+```
+
+### Step 4: Test Locally
+
+```bash
+make run
+```
+
+Visit `http://localhost:8050/blog` to see the article listing.
+Visit `http://localhost:8050/blog/your-article-slug` for the full article.
+
+### Example: Complete Blog Post
+
+```markdown
+---
+title: "Building ETL Pipelines with Python"
+date: "2026-01-17"
+description: "Lessons from building production data pipelines at scale"
+tags:
+  - python
+  - etl
+  - data-engineering
+status: published
+---
+
+When I started building data pipelines, I made every mistake possible...
+
+## The Problem
+
+Most tutorials show toy examples. Real pipelines are different.
+
+### Error Handling
+
+```python
+def safe_transform(df: pd.DataFrame) -> pd.DataFrame:
+    try:
+        return df.apply(transform_row, axis=1)
+    except ValueError as e:
+        logger.error(f"Transform failed: {e}")
+        raise
+```
+
+## Conclusion
+
+Ship something that works, then iterate.
+```
+
+---
+
+## Adding a New Page
+
+Pages use Dash's automatic routing based on file location in `portfolio_app/pages/`.
+
+### Step 1: Create the Page File
+
+```bash
+touch portfolio_app/pages/your_page.py
+```
+
+### Step 2: Register the Page
+
+Every page must call `dash.register_page()`:
+
+```python
+"""Your page description."""
+
+import dash
+import dash_mantine_components as dmc
+
+dash.register_page(
+    __name__,
+    path="/your-page",      # URL path
+    name="Your Page",       # Display name (for nav)
+    title="Your Page Title" # Browser tab title
+)
+
+
+def layout() -> dmc.Container:
+    """Page layout function."""
+    return dmc.Container(
+        dmc.Stack(
+            [
+                dmc.Title("Your Page", order=1),
+                dmc.Text("Page content here."),
+            ],
+            gap="lg",
+        ),
+        size="md",
+        py="xl",
+    )
+```
+
+### Step 3: Page with Dynamic Content
+
+For pages with URL parameters:
+
+```python
+# pages/blog/article.py
+dash.register_page(
+    __name__,
+    path_template="/blog/<slug>",  # Dynamic parameter
+    name="Article",
+)
+
+
+def layout(slug: str = "") -> dmc.Container:
+    """Layout receives URL parameters as arguments."""
+    article = get_article(slug)
+    if not article:
+        return dmc.Text("Article not found")
+
+    return dmc.Container(
+        dmc.Title(article["meta"]["title"]),
+        # ...
+    )
+```
+
+### Step 4: Add Navigation (Optional)
+
+To add the page to the sidebar, edit `portfolio_app/components/sidebar.py`:
+
+```python
+NAV_ITEMS = [
+    {"label": "Home", "href": "/", "icon": "tabler:home"},
+    {"label": "Your Page", "href": "/your-page", "icon": "tabler:star"},
+    # ...
+]
+```
+
+### URL Routing Summary
+
+| File Location | URL |
+|---------------|-----|
+| `pages/home.py` | `/` (if `path="/"`) |
+| `pages/about.py` | `/about` |
+| `pages/blog/index.py` | `/blog` |
+| `pages/blog/article.py` | `/blog/<slug>` |
+| `pages/toronto/dashboard.py` | `/toronto` |
+
+---
+
+## Adding a Dashboard Tab
+
+Dashboard tabs are in `portfolio_app/pages/toronto/tabs/`.
+
+### Step 1: Create Tab Layout
+
+```python
+# pages/toronto/tabs/your_tab.py
+"""Your tab description."""
+
+import dash_mantine_components as dmc
+
+from portfolio_app.figures.choropleth import create_choropleth
+from portfolio_app.toronto.demo_data import get_demo_data
+
+
+def create_your_tab_layout() -> dmc.Stack:
+    """Create the tab layout."""
+    data = get_demo_data()
+
+    return dmc.Stack(
+        [
+            dmc.Grid(
+                [
+                    dmc.GridCol(
+                        # Map on left
+                        create_choropleth(data, "your_metric"),
+                        span=8,
+                    ),
+                    dmc.GridCol(
+                        # KPI cards on right
+                        create_kpi_cards(data),
+                        span=4,
+                    ),
+                ],
+            ),
+            # Charts below
+            create_supporting_charts(data),
+        ],
+        gap="lg",
+    )
+```
+
+### Step 2: Register in Dashboard
+
+Edit `pages/toronto/dashboard.py` to add the tab:
+
+```python
+from portfolio_app.pages.toronto.tabs.your_tab import create_your_tab_layout
+
+# In the tabs list:
+dmc.TabsTab("Your Tab", value="your-tab"),
+
+# In the panels:
+dmc.TabsPanel(create_your_tab_layout(), value="your-tab"),
+```
+
+---
+
+## Creating Figure Factories
+
+Figure factories are in `portfolio_app/figures/`. They create reusable Plotly figures.
+
+### Pattern
+
+```python
+# figures/your_chart.py
+"""Your chart type factory."""
+
+import plotly.express as px
+import plotly.graph_objects as go
+import pandas as pd
+
+
+def create_your_chart(
+    df: pd.DataFrame,
+    x_col: str,
+    y_col: str,
+    title: str = "",
+) -> go.Figure:
+    """Create a your_chart figure.
+
+    Args:
+        df: DataFrame with data.
+        x_col: Column for x-axis.
+        y_col: Column for y-axis.
+        title: Optional chart title.
+
+    Returns:
+        Configured Plotly figure.
+    """
+    fig = px.bar(df, x=x_col, y=y_col, title=title)
+
+    fig.update_layout(
+        template="plotly_white",
+        margin=dict(l=40, r=40, t=40, b=40),
+    )
+
+    return fig
+```
+
+### Export from `__init__.py`
+
+```python
+# figures/__init__.py
+from .your_chart import create_your_chart
+
+__all__ = [
+    "create_your_chart",
+    # ...
+]
+```
+
+---
+
+## Branch Workflow
+
+```
+main (production)
+  ↑
+staging (pre-production)
+  ↑
+development (integration)
+  ↑
+feature/XX-description (your work)
+```
+
+### Creating a Feature Branch
+
+```bash
+# Start from development
+git checkout development
+git pull origin development
+
+# Create feature branch
+git checkout -b feature/10-add-new-page
+
+# Work, commit, push
+git add .
+git commit -m "feat: Add new page"
+git push -u origin feature/10-add-new-page
+```
+
+### Merging
+
+```bash
+# Merge into development
+git checkout development
+git merge feature/10-add-new-page
+git push origin development
+
+# Delete feature branch
+git branch -d feature/10-add-new-page
+git push origin --delete feature/10-add-new-page
+```
+
+**Rules:**
+- Never commit directly to `main` or `staging`
+- Never delete `development`
+- Feature branches are temporary
+
+---
+
+## Code Standards
+
+### Type Hints
+
+Use Python 3.10+ style:
+
+```python
+def process(items: list[str], config: dict[str, int] | None = None) -> bool:
+    ...
+```
+
+### Imports
+
+| Context | Style |
+|---------|-------|
+| Same directory | `from .module import X` |
+| Sibling directory | `from ..schemas.model import Y` |
+| External packages | `import pandas as pd` |
+
+### Formatting
+
+```bash
+make format  # Runs ruff formatter
+make lint    # Checks style
+```
+
+### Docstrings
+
+Google style, only for non-obvious functions:
+
+```python
+def calculate_score(values: list[float], weights: list[float]) -> float:
+    """Calculate weighted score.
+
+    Args:
+        values: Raw metric values.
+        weights: Weight for each metric.
+
+    Returns:
+        Weighted average score.
+    """
+    ...
+```
+
+---
+
+## Questions?
+
+Check `CLAUDE.md` for AI assistant context and architectural decisions.

docs/PROJECT_REFERENCE.md

@@ -1,21 +1,171 @@
 # Portfolio Project Reference
 
 **Project**: Analytics Portfolio
-**Owner**: Leo
-**Status**: Ready for Sprint 1
+**Owner**: Leo Miranda
+**Status**: Sprint 9 Complete (Dashboard Implementation Done)
+**Last Updated**: January 2026
 
 ---
 
 ## Project Overview
 
-Two-project analytics portfolio demonstrating end-to-end data engineering, visualization, and ML capabilities.
+Personal portfolio website with an interactive Toronto Neighbourhood Dashboard demonstrating data engineering, visualization, and analytics capabilities.
 
-| Project | Domain | Key Skills | Phase |
-|---------|--------|------------|-------|
-| **Toronto Housing Dashboard** | Real estate | ETL, dimensional modeling, geospatial, choropleth | Phase 1 (Active) |
-| **Energy Pricing Analysis** | Utility markets | Time series, ML prediction, API integration | Phase 3 (Future) |
+| Component | Description | Status |
+|-----------|-------------|--------|
+| Portfolio Website | Bio, About, Projects, Resume, Contact, Blog | Complete |
+| Toronto Dashboard | 5-tab neighbourhood analysis | Complete |
+| Data Pipeline | dbt models, figure factories | Complete |
+| Deployment | Production deployment | Pending |
 
-**Platform**: Monolithic Dash application on self-hosted VPS (bio landing page + dashboards).
+---
+
+## Completed Work
+
+### Sprint 1-6: Foundation
+- Repository setup, Docker, PostgreSQL + PostGIS
+- Bio landing page implementation
+- Initial data model design
+
+### Sprint 7: Navigation & Theme
+- Sidebar navigation
+- Dark/light theme toggle
+- dash-mantine-components integration
+
+### Sprint 8: Portfolio Website
+- About, Contact, Projects, Resume pages
+- Blog system with Markdown/frontmatter
+- Health endpoint
+
+### Sprint 9: Neighbourhood Dashboard Transition
+- Phase 1: Deleted legacy TRREB code
+- Phase 2: Documentation cleanup
+- Phase 3: New neighbourhood-centric data model
+- Phase 4: dbt model restructuring
+- Phase 5: 5-tab dashboard implementation
+- Phase 6: 15 documentation notebooks
+- Phase 7: Final documentation review
+
+---
+
+## Application Architecture
+
+### URL Routes
+
+| URL | Page | File |
+|-----|------|------|
+| `/` | Home | `pages/home.py` |
+| `/about` | About | `pages/about.py` |
+| `/contact` | Contact | `pages/contact.py` |
+| `/projects` | Projects | `pages/projects.py` |
+| `/resume` | Resume | `pages/resume.py` |
+| `/blog` | Blog listing | `pages/blog/index.py` |
+| `/blog/{slug}` | Article | `pages/blog/article.py` |
+| `/toronto` | Dashboard | `pages/toronto/dashboard.py` |
+| `/toronto/methodology` | Methodology | `pages/toronto/methodology.py` |
+| `/health` | Health check | `pages/health.py` |
+
+### Directory Structure
+
+```
+portfolio_app/
+├── app.py                    # Dash app factory
+├── config.py                 # Pydantic BaseSettings
+├── assets/                   # CSS, images
+├── callbacks/                # Global callbacks (sidebar, theme)
+├── components/               # Shared UI components
+├── content/blog/             # Markdown blog articles
+├── errors/                   # Exception handling
+├── figures/                  # Plotly figure factories
+├── pages/
+│   ├── home.py
+│   ├── about.py
+│   ├── contact.py
+│   ├── projects.py
+│   ├── resume.py
+│   ├── health.py
+│   ├── blog/
+│   │   ├── index.py
+│   │   └── article.py
+│   └── toronto/
+│       ├── dashboard.py
+│       ├── methodology.py
+│       ├── tabs/             # 5 tab layouts
+│       └── callbacks/        # Dashboard interactions
+├── toronto/                  # Data logic
+│   ├── parsers/              # API extraction
+│   ├── loaders/              # Database operations
+│   ├── schemas/              # Pydantic models
+│   ├── models/               # SQLAlchemy ORM
+│   └── demo_data.py          # Sample data
+└── utils/
+    └── markdown_loader.py    # Blog article loading
+```
+
+---
+
+## Toronto Dashboard
+
+### Data Sources
+
+| Source | Data | Format |
+|--------|------|--------|
+| City of Toronto Open Data | Neighbourhoods (158), Census profiles, Parks, Schools, Childcare, TTC | GeoJSON, CSV, API |
+| Toronto Police Service | Crime rates, MCI, Shootings | CSV, API |
+| CMHC | Rental Market Survey | CSV |
+
+### Geographic Model
+
+```
+City of Toronto Neighbourhoods (158) ← Primary analysis unit
+CMHC Zones (~20) ← Rental data (Census Tract aligned)
+```
+
+### Dashboard Tabs
+
+| Tab | Choropleth Metric | Supporting Charts |
+|-----|-------------------|-------------------|
+| Overview | Livability score | Top/Bottom 10 bar, Income vs Safety scatter |
+| Housing | Affordability index | Rent trend line, Tenure breakdown bar |
+| Safety | Crime rate per 100K | Crime breakdown bar, Crime trend line |
+| Demographics | Median income | Age distribution, Population density bar |
+| Amenities | Amenity index | Amenity radar, Transit accessibility bar |
+
+### Star Schema
+
+| Table | Type | Description |
+|-------|------|-------------|
+| `dim_neighbourhood` | Dimension | 158 neighbourhoods with geometry |
+| `dim_time` | Dimension | Date dimension |
+| `dim_cmhc_zone` | Dimension | ~20 CMHC zones with geometry |
+| `fact_census` | Fact | Census indicators by neighbourhood |
+| `fact_crime` | Fact | Crime stats by neighbourhood |
+| `fact_rentals` | Fact | Rental data by CMHC zone |
+| `fact_amenities` | Fact | Amenity counts by neighbourhood |
+
+### dbt Layers
+
+| Layer | Naming | Example |
+|-------|--------|---------|
+| Staging | `stg_{source}__{entity}` | `stg_toronto__neighbourhoods` |
+| Intermediate | `int_{domain}__{transform}` | `int_neighbourhood__demographics` |
+| Marts | `mart_{domain}` | `mart_neighbourhood_overview` |
+
+---
+
+## Tech Stack
+
+| Layer | Technology | Version |
+|-------|------------|---------|
+| Database | PostgreSQL + PostGIS | 16.x |
+| Validation | Pydantic | 2.x |
+| ORM | SQLAlchemy | 2.x |
+| Transformation | dbt-postgres | 1.7+ |
+| Data Processing | Pandas, GeoPandas | Latest |
+| Visualization | Dash + Plotly | 2.14+ |
+| UI Components | dash-mantine-components | Latest |
+| Testing | pytest | 7.0+ |
+| Python | 3.11+ | Via pyenv |
 
 ---
 
@@ -23,293 +173,51 @@ Two-project analytics portfolio demonstrating end-to-end data engineering, visua
 
 | Branch | Purpose | Deploys To |
 |--------|---------|------------|
-| `main` | Production releases only | VPS (production) |
+| `main` | Production releases | VPS (production) |
 | `staging` | Pre-production testing | VPS (staging) |
 | `development` | Active development | Local only |
 
-**Rules**:
-- All feature branches created FROM `development`
-- All feature branches merge INTO `development`
-- `development` → `staging` for testing
-- `staging` → `main` for release
-- Direct commits to `main` or `staging` are forbidden
-- Branch naming: `feature/{sprint}-{description}` or `fix/{issue-id}`
+**Rules:**
+- Feature branches from `development`: `feature/{sprint}-{description}`
+- Merge into `development` when complete
+- `development` → `staging` → `main` for releases
+- Never delete `development`
 
 ---
 
-## Tech Stack (Locked)
+## Code Standards
 
-| Layer | Technology | Version |
-|-------|------------|---------|
-| Database | PostgreSQL + PostGIS | 16.x |
-| Validation | Pydantic | ≥2.0 |
-| ORM | SQLAlchemy | ≥2.0 (2.0-style API only) |
-| Transformation | dbt-postgres | ≥1.7 |
-| Data Processing | Pandas | ≥2.1 |
-| Geospatial | GeoPandas + Shapely | ≥0.14 |
-| Visualization | Dash + Plotly | ≥2.14 |
-| UI Components | dash-mantine-components | Latest stable |
-| Testing | pytest | ≥7.0 |
-| Python | 3.11+ | Via pyenv |
+### Type Hints (Python 3.10+)
 
-**Compatibility Notes**:
-- SQLAlchemy 2.0 + Pydantic 2.0 integrate well—never mix 1.x APIs
-- PostGIS extension required—enable during db init
-- Docker Compose V2 (no `version` field in compose files)
+```python
+def process(items: list[str], config: dict[str, int] | None = None) -> bool:
+    ...
+```
 
----
+### Imports
 
-## Code Conventions
-
-### Import Style
-
-| Context | Style | Example |
-|---------|-------|---------|
-| Same directory | Single dot | `from .neighbourhood import NeighbourhoodParser` |
-| Sibling directory | Double dot | `from ..schemas.neighbourhood import CensusRecord` |
-| External packages | Absolute | `import pandas as pd` |
-
-### Module Separation
-
-| Directory | Contains | Purpose |
-|-----------|----------|---------|
-| `schemas/` | Pydantic models | Data validation |
-| `models/` | SQLAlchemy ORM | Database persistence |
-| `parsers/` | API/CSV extraction | Raw data ingestion |
-| `loaders/` | Database operations | Data loading |
-| `figures/` | Chart factories | Plotly figure generation |
-| `callbacks/` | Dash callbacks | Per-dashboard, in `pages/{dashboard}/callbacks/` |
-| `errors/` | Exceptions + handlers | Error handling |
-
-### Code Standards
-
-- **Type hints**: Mandatory, Python 3.10+ style (`list[str]`, `dict[str, int]`, `X | None`)
-- **Functions**: Single responsibility, verb naming, early returns over nesting
-- **Docstrings**: Google style, minimal—only for non-obvious behavior
-- **Constants**: Module-level for magic values, Pydantic BaseSettings for runtime config
+| Context | Style |
+|---------|-------|
+| Same directory | `from .module import X` |
+| Sibling directory | `from ..schemas.model import Y` |
+| External | `import pandas as pd` |
 
 ### Error Handling
 
 ```python
-# errors/exceptions.py
 class PortfolioError(Exception):
     """Base exception."""
 
 class ParseError(PortfolioError):
-    """PDF/CSV parsing failed."""
+    """Data parsing failed."""
 
 class ValidationError(PortfolioError):
-    """Pydantic or business rule validation failed."""
+    """Validation failed."""
 
 class LoadError(PortfolioError):
-    """Database load operation failed."""
+    """Database load failed."""
 ```
 
-- Decorators for infrastructure concerns (logging, retry, transactions)
-- Explicit handling for domain logic (business rules, recovery strategies)
-
----
-
-## Application Architecture
-
-### Dash Pages Structure
-
-```
-portfolio_app/
-├── app.py                    # Dash app factory with Pages routing
-├── config.py                 # Pydantic BaseSettings
-├── assets/                   # CSS, images (auto-served by Dash)
-├── pages/
-│   ├── home.py              # Bio landing page → /
-│   ├── toronto/
-│   │   ├── dashboard.py     # Layout only → /toronto
-│   │   └── callbacks/       # Interaction logic
-│   └── energy/              # Phase 3
-├── components/              # Shared UI (navbar, footer, cards)
-├── figures/                 # Shared chart factories
-├── toronto/                 # Toronto data logic
-│   ├── parsers/
-│   ├── loaders/
-│   ├── schemas/             # Pydantic
-│   └── models/              # SQLAlchemy
-└── errors/
-```
-
-### URL Routing (Automatic)
-
-| URL | Page | Status |
-|-----|------|--------|
-| `/` | Bio landing page | Sprint 2 |
-| `/toronto` | Toronto Housing Dashboard | Sprint 6 |
-| `/energy` | Energy Pricing Dashboard | Phase 3 |
-
----
-
-## Phase 1: Toronto Neighbourhood Dashboard
-
-### Data Sources
-
-| Track | Source | Format | Geography | Frequency |
-|-------|--------|--------|-----------|-----------|
-| Rentals | CMHC Rental Market Survey | API/CSV | ~20 Zones | Annual |
-| Neighbourhoods | City of Toronto Open Data | GeoJSON/CSV | 158 Neighbourhoods | Census |
-| Policy Events | Curated list | CSV | N/A | Event-based |
-
-### Geographic Reality
-
-```
-┌─────────────────────────────────────────────────────────────────┐
-│ City of Toronto Neighbourhoods (158)                            │ ← Primary analysis unit
-├─────────────────────────────────────────────────────────────────┤
-│ CMHC Zones (~20) — Census Tract aligned                         │ ← Rental data
-└─────────────────────────────────────────────────────────────────┘
-```
-
-### Data Model (Star Schema)
-
-| Table | Type | Keys |
-|-------|------|------|
-| `fact_rentals` | Fact | → dim_time, dim_cmhc_zone |
-| `dim_time` | Dimension | date_key (PK) |
-| `dim_cmhc_zone` | Dimension | zone_key (PK), geometry |
-| `dim_neighbourhood` | Dimension | neighbourhood_id (PK), geometry |
-| `dim_policy_event` | Dimension | event_id (PK) |
-
-### dbt Layer Structure
-
-| Layer | Naming | Purpose |
-|-------|--------|---------|
-| Staging | `stg_{source}__{entity}` | 1:1 source, cleaned, typed |
-| Intermediate | `int_{domain}__{transform}` | Business logic, filtering |
-| Marts | `mart_{domain}` | Final analytical tables |
-
----
-
-## Sprint Overview
-
-| Sprint | Focus | Milestone |
-|--------|-------|-----------|
-| 1-6 | Foundation and initial dashboard | **Launch 1: Bio Live** |
-| 7 | Navigation & theme modernization | — |
-| 8 | Portfolio website expansion | **Launch 2: Website Live** |
-| 9 | Neighbourhood dashboard transition | Cleanup complete |
-| 10+ | Dashboard implementation | **Launch 3: Dashboard Live** |
-
----
-
-## Scope Boundaries
-
-### Phase 1 — Build These
-
-- Bio landing page and portfolio website
-- CMHC rental data processor
-- Toronto neighbourhood data integration
-- PostgreSQL + PostGIS database layer
-- Star schema (facts + dimensions)
-- dbt models with tests
-- Choropleth visualization (Dash)
-- Policy event annotation layer
-
-### Deferred Features
-
-| Feature | Reason | When |
-|---------|--------|------|
-| Historical boundary reconciliation (140→158) | 2021+ data only for V1 | Future phase |
-| ML prediction models | Energy project scope | Phase 3 |
-| Multi-project shared infrastructure | Build first, abstract second | Future |
-
-If a task seems to require deferred features, **stop and flag it**.
-
----
-
-## File Structure
-
-### Root-Level Files (Allowed)
-
-| File | Purpose |
-|------|---------|
-| `README.md` | Project overview |
-| `CLAUDE.md` | AI assistant context |
-| `pyproject.toml` | Python packaging |
-| `.gitignore` | Git ignore rules |
-| `.env.example` | Environment template |
-| `.python-version` | pyenv version |
-| `.pre-commit-config.yaml` | Pre-commit hooks |
-| `docker-compose.yml` | Container orchestration |
-| `Makefile` | Task automation |
-
-### Directory Structure
-
-```
-portfolio/
-├── portfolio_app/           # Monolithic Dash application
-│   ├── app.py
-│   ├── config.py
-│   ├── assets/
-│   ├── pages/
-│   ├── components/
-│   ├── figures/
-│   ├── toronto/
-│   └── errors/
-├── tests/
-├── dbt/
-├── data/
-│   └── toronto/
-│       ├── raw/
-│       ├── processed/       # gitignored
-│       └── reference/
-├── scripts/
-│   ├── db/
-│   ├── docker/
-│   ├── deploy/
-│   ├── dbt/
-│   └── dev/
-├── docs/
-├── notebooks/
-├── backups/                 # gitignored
-└── reports/                 # gitignored
-```
-
-### Gitignored Directories
-
-- `data/*/processed/`
-- `reports/`
-- `backups/`
-- `notebooks/*.html`
-- `.env`
-- `__pycache__/`
-- `.venv/`
-
----
-
-## Makefile Targets
-
-| Target | Purpose |
-|--------|---------|
-| `setup` | Install deps, create .env, init pre-commit |
-| `docker-up` | Start PostgreSQL + PostGIS |
-| `docker-down` | Stop containers |
-| `db-init` | Initialize database schema |
-| `run` | Start Dash dev server |
-| `test` | Run pytest |
-| `dbt-run` | Run dbt models |
-| `dbt-test` | Run dbt tests |
-| `lint` | Run ruff linter |
-| `format` | Run ruff formatter |
-| `ci` | Run all checks |
-| `deploy` | Deploy to production |
-
----
-
-## Script Standards
-
-All scripts in `scripts/`:
-- Include usage comments at top
-- Idempotent where possible
-- Exit codes: 0 = success, 1 = error
-- Use `set -euo pipefail` for bash
-- Log to stdout, errors to stderr
-
 ---
 
 ## Environment Variables
@@ -328,41 +236,52 @@ LOG_LEVEL=INFO
 
 ---
 
-## Success Criteria
+## Makefile Targets
 
-### Launch 1 (Bio Live)
-- [x] Bio page accessible via HTTPS
-- [x] All bio content rendered
-- [x] No placeholder text visible
-- [x] Mobile responsive
-- [x] Social links functional
-
-### Launch 2 (Website Live)
-- [x] Full portfolio website with navigation
-- [x] About, Contact, Projects, Resume, Blog pages
-- [x] Dark mode theme support
-- [x] Sidebar navigation
-
-### Launch 3 (Dashboard Live)
-- [ ] Choropleth renders neighbourhoods and CMHC zones
-- [ ] Rental data visualization works
-- [ ] Time navigation works
-- [ ] Policy event markers visible
-- [ ] Methodology documentation published
-- [ ] Data sources cited
+| Target | Purpose |
+|--------|---------|
+| `setup` | Install deps, create .env, init pre-commit |
+| `docker-up` | Start PostgreSQL + PostGIS |
+| `docker-down` | Stop containers |
+| `db-init` | Initialize database schema |
+| `run` | Start Dash dev server |
+| `test` | Run pytest |
+| `dbt-run` | Run dbt models |
+| `dbt-test` | Run dbt tests |
+| `lint` | Run ruff linter |
+| `format` | Run ruff formatter |
+| `ci` | Run all checks |
 
 ---
 
-## Reference Documents
+## Next Steps
 
-For detailed specifications, see:
+### Deployment (Sprint 10+)
+- [ ] Production Docker configuration
+- [ ] CI/CD pipeline
+- [ ] HTTPS/SSL setup
+- [ ] Domain configuration
 
-| Document | Location | Use When |
-|----------|----------|----------|
-| Dashboard vision | `docs/changes/Change-Toronto-Analysis.md` | Dashboard specification |
-| Implementation plan | `docs/changes/Change-Toronto-Analysis-Reviewed.md` | Sprint planning |
+### Data Enhancement
+- [ ] Connect to live APIs (currently using demo data)
+- [ ] Data refresh automation
+- [ ] Historical data loading
+
+### Future Projects
+- Energy Pricing Analysis dashboard (planned)
 
 ---
 
-*Reference Version: 2.0*
-*Updated: Sprint 9*
+## Related Documents
+
+| Document | Purpose |
+|----------|---------|
+| `README.md` | Quick start guide |
+| `CLAUDE.md` | AI assistant context |
+| `docs/CONTRIBUTING.md` | Developer guide |
+| `notebooks/README.md` | Notebook documentation |
+
+---
+
+*Reference Version: 3.0*
+*Updated: January 2026*

docs/bio_content_v2.md

@@ -1,134 +0,0 @@
-# Portfolio Bio Content
-
-**Version**: 2.0
-**Last Updated**: January 2026
-**Purpose**: Content source for `portfolio_app/pages/home.py`
-
----
-
-## Document Context
-
-| Attribute | Value |
-|-----------|-------|
-| **Parent Document** | `portfolio_project_plan_v5.md` |
-| **Role** | Bio content and social links for landing page |
-| **Consumed By** | `portfolio_app/pages/home.py` |
-
----
-
-## Headline
-
-**Primary**: Leo | Data Engineer & Analytics Developer
-
-**Tagline**: I build data infrastructure that actually gets used.
-
----
-
-## Professional Summary
-
-Over the past 5 years, I've designed and evolved an enterprise analytics platform from scratch—now processing 1B+ rows across 21 tables with Python-based ETL pipelines and dbt-style SQL transformations. The result: 40% efficiency gains, 30% reduction in call abandon rates, and dashboards that executives actually open.
-
-My approach: dimensional modeling (star schema), layered transformations (staging → intermediate → marts), and automation that eliminates manual work. I've built everything from self-service analytics portals to OCR-powered receipt processing systems.
-
-Currently at Summitt Energy supporting multi-market operations across Canada and 8 US states. Previously cut my teeth on IT infrastructure projects at Petrobras (Fortune 500) and the Project Management Institute.
-
----
-
-## Tech Stack
-
-| Category | Technologies |
-|----------|--------------|
-| **Languages** | Python, SQL |
-| **Data Processing** | Pandas, SQLAlchemy, FastAPI |
-| **Databases** | PostgreSQL, MSSQL |
-| **Visualization** | Power BI, Plotly, Dash |
-| **Patterns** | dbt, dimensional modeling, star schema |
-| **Other** | Genesys Cloud |
-
-**Display Format** (for landing page):
-```
-Python (Pandas, SQLAlchemy, FastAPI) • SQL (MSSQL, PostgreSQL) • Power BI • Plotly/Dash • Genesys Cloud • dbt patterns
-```
-
----
-
-## Side Project
-
-**Bandit Labs** — Building automation and AI tooling for small businesses.
-
-*Note: Keep this brief on portfolio; link only if separate landing page exists.*
-
----
-
-## Social Links
-
-| Platform | URL | Icon |
-|----------|-----|------|
-| **LinkedIn** | `https://linkedin.com/in/[USERNAME]` | `lucide-react: Linkedin` |
-| **GitHub** | `https://github.com/[USERNAME]` | `lucide-react: Github` |
-
-> **TODO**: Replace `[USERNAME]` placeholders with actual URLs before bio page launch.
-
----
-
-## Availability Statement
-
-Open to **Senior Data Analyst**, **Analytics Engineer**, and **BI Developer** opportunities in Toronto or remote.
-
----
-
-## Portfolio Projects Section
-
-*Dynamically populated based on deployed projects.*
-
-| Project | Status | Link |
-|---------|--------|------|
-| Toronto Housing Dashboard | In Development | `/toronto` |
-| Energy Pricing Analysis | Planned | `/energy` |
-
-**Display Logic**:
-- Show only projects with `status = deployed`
-- "In Development" projects can show as coming soon or be hidden (user preference)
-
----
-
-## Implementation Notes
-
-### Content Hierarchy for `home.py`
-
-```
-1. Name + Tagline (hero section)
-2. Professional Summary (2-3 paragraphs)
-3. Tech Stack (horizontal chips or inline list)
-4. Portfolio Projects (cards linking to dashboards)
-5. Social Links (icon buttons)
-6. Availability statement (subtle, bottom)
-```
-
-### Styling Recommendations
-
-- Clean, minimal — let the projects speak
-- Dark/light mode support via dash-mantine-components theme
-- No headshot required (optional)
-- Mobile-responsive layout
-
-### Content Updates
-
-When updating bio content:
-1. Edit this document
-2. Update `home.py` to reflect changes
-3. Redeploy
-
----
-
-## Related Documents
-
-| Document | Relationship |
-|----------|--------------|
-| `portfolio_project_plan_v5.md` | Parent — references this for bio content |
-| `portfolio_app/pages/home.py` | Consumer — implements this content |
-
----
-
-*Document Version: 2.0*
-*Updated: January 2026*

docs/changes/Change-Toronto-Analysis-Reviewed.md

@@ -1,276 +0,0 @@
-# Toronto Neighbourhood Dashboard — Implementation Plan
-
-**Document Type:** Execution Guide
-**Target:** Transition from TRREB-based to Neighbourhood-based Dashboard
-**Version:** 2.0 | January 2026
-
----
-
-## Overview
-
-Transition from TRREB district-based housing dashboard to a comprehensive Toronto Neighbourhood Dashboard built around the city's 158 official neighbourhoods.
-
-**Key Changes:**
-- Geographic foundation: TRREB districts (~35) → City Neighbourhoods (158)
-- Data sources: PDF parsing → Open APIs (Toronto Open Data, Toronto Police, CMHC)
-- Scope: Housing-only → 5 thematic tabs (Overview, Housing, Safety, Demographics, Amenities)
-
----
-
-## Phase 1: Repository Cleanup
-
-### Files to DELETE
-
-| File | Reason |
-|------|--------|
-| `portfolio_app/toronto/schemas/trreb.py` | TRREB schema obsolete |
-| `portfolio_app/toronto/parsers/trreb.py` | PDF parsing no longer needed |
-| `portfolio_app/toronto/loaders/trreb.py` | TRREB loading logic obsolete |
-| `dbt/models/staging/stg_trreb__purchases.sql` | TRREB staging obsolete |
-| `dbt/models/intermediate/int_purchases__monthly.sql` | TRREB intermediate obsolete |
-| `dbt/models/marts/mart_toronto_purchases.sql` | Will rebuild for neighbourhood grain |
-
-### Files to MODIFY (Remove TRREB References)
-
-| File | Action |
-|------|--------|
-| `portfolio_app/toronto/schemas/__init__.py` | Remove TRREB imports |
-| `portfolio_app/toronto/parsers/__init__.py` | Remove TRREB parser imports |
-| `portfolio_app/toronto/loaders/__init__.py` | Remove TRREB loader imports |
-| `portfolio_app/toronto/models/facts.py` | Remove `FactPurchases` model |
-| `portfolio_app/toronto/models/dimensions.py` | Remove `DimTRREBDistrict` model |
-| `portfolio_app/toronto/demo_data.py` | Remove TRREB demo data |
-| `dbt/models/sources.yml` | Remove TRREB source definitions |
-| `dbt/models/schema.yml` | Remove TRREB model documentation |
-
-### Files to KEEP (Reusable)
-
-| File | Why |
-|------|-----|
-| `portfolio_app/toronto/schemas/cmhc.py` | CMHC data still used |
-| `portfolio_app/toronto/parsers/cmhc.py` | Reusable with modifications |
-| `portfolio_app/toronto/loaders/base.py` | Generic database utilities |
-| `portfolio_app/toronto/loaders/dimensions.py` | Dimension loading patterns |
-| `portfolio_app/toronto/models/base.py` | SQLAlchemy base class |
-| `portfolio_app/figures/*.py` | All chart factories reusable |
-| `portfolio_app/components/*.py` | All UI components reusable |
-
----
-
-## Phase 2: Documentation Updates
-
-| Document | Action |
-|----------|--------|
-| `CLAUDE.md` | Update data model section, mark transition complete |
-| `docs/PROJECT_REFERENCE.md` | Update architecture, data sources |
-| `docs/toronto_housing_dashboard_spec_v5.md` | Archive or delete |
-| `docs/wbs_sprint_plan_v4.md` | Archive or delete |
-
----
-
-## Phase 3: New Data Model
-
-### Star Schema (Neighbourhood-Centric)
-
-| Table | Type | Description |
-|-------|------|-------------|
-| `dim_neighbourhood` | Central Dimension | 158 neighbourhoods with geometry |
-| `dim_time` | Dimension | Date dimension (keep existing) |
-| `dim_cmhc_zone` | Bridge Dimension | 15 CMHC zones with neighbourhood mapping |
-| `bridge_cmhc_neighbourhood` | Bridge | Zone-to-neighbourhood area weights |
-| `fact_census` | Fact | Census indicators by neighbourhood |
-| `fact_crime` | Fact | Crime stats by neighbourhood |
-| `fact_rentals` | Fact | Rental data by CMHC zone (keep existing) |
-| `fact_amenities` | Fact | Amenity counts by neighbourhood |
-
-### New Schema Files
-
-| File | Contains |
-|------|----------|
-| `toronto/schemas/neighbourhood.py` | NeighbourhoodRecord, CensusRecord, CrimeRecord |
-| `toronto/schemas/amenities.py` | AmenityType enum, AmenityRecord |
-
-### New Parser Files
-
-| File | Data Source | API |
-|------|-------------|-----|
-| `toronto/parsers/toronto_open_data.py` | Neighbourhoods, Census, Parks, Schools, Childcare | Toronto Open Data Portal |
-| `toronto/parsers/toronto_police.py` | Crime Rates, MCI, Shootings | Toronto Police Portal |
-
-### New Loader Files
-
-| File | Purpose |
-|------|---------|
-| `toronto/loaders/neighbourhoods.py` | Load GeoJSON boundaries |
-| `toronto/loaders/census.py` | Load neighbourhood profiles |
-| `toronto/loaders/crime.py` | Load crime statistics |
-| `toronto/loaders/amenities.py` | Load parks, schools, childcare |
-| `toronto/loaders/cmhc_crosswalk.py` | Build CMHC-neighbourhood bridge |
-
----
-
-## Phase 4: dbt Restructuring
-
-### Staging Layer
-
-| Model | Source |
-|-------|--------|
-| `stg_toronto__neighbourhoods` | dim_neighbourhood |
-| `stg_toronto__census` | fact_census |
-| `stg_toronto__crime` | fact_crime |
-| `stg_toronto__amenities` | fact_amenities |
-| `stg_cmhc__rentals` | fact_rentals (modify existing) |
-| `stg_cmhc__zone_crosswalk` | bridge_cmhc_neighbourhood |
-
-### Intermediate Layer
-
-| Model | Purpose |
-|-------|---------|
-| `int_neighbourhood__demographics` | Combined census demographics |
-| `int_neighbourhood__housing` | Housing indicators |
-| `int_neighbourhood__crime_summary` | Aggregated crime by type |
-| `int_neighbourhood__amenity_scores` | Normalized amenity metrics |
-| `int_rentals__neighbourhood_allocated` | CMHC rentals allocated to neighbourhoods |
-
-### Mart Layer (One per Tab)
-
-| Model | Tab | Key Metrics |
-|-------|-----|-------------|
-| `mart_neighbourhood_overview` | Overview | Composite livability score |
-| `mart_neighbourhood_housing` | Housing | Affordability index, rent-to-income |
-| `mart_neighbourhood_safety` | Safety | Crime rates, YoY change |
-| `mart_neighbourhood_demographics` | Demographics | Income, age, diversity |
-| `mart_neighbourhood_amenities` | Amenities | Parks, schools, transit per capita |
-
----
-
-## Phase 5: Dashboard Implementation
-
-### Tab Structure
-
-```
-pages/toronto/
-├── dashboard.py          # Main layout with tab navigation
-├── tabs/
-│   ├── overview.py       # Composite livability
-│   ├── housing.py        # Affordability
-│   ├── safety.py         # Crime
-│   ├── demographics.py   # Population
-│   └── amenities.py      # Services
-└── callbacks/
-    ├── map_callbacks.py
-    ├── chart_callbacks.py
-    └── selection_callbacks.py
-```
-
-### Layout Pattern (All Tabs)
-
-Each tab follows the same structure:
-1. **Choropleth Map** (left) — 158 neighbourhoods, click to select
-2. **KPI Cards** (right) — 3-4 contextual metrics
-3. **Supporting Charts** (bottom) — Trend + comparison visualizations
-4. **Details Panel** (collapsible) — All metrics for selected neighbourhood
-
-### Graphs by Tab
-
-| Tab | Choropleth Metric | Chart 1 | Chart 2 |
-|-----|-------------------|---------|---------|
-| Overview | Livability score | Top/Bottom 10 bar | Income vs Crime scatter |
-| Housing | Affordability index | Rent trend (5yr line) | Dwelling types (pie/bar) |
-| Safety | Crime rate per 100K | Crime breakdown (stacked bar) | Crime trend (5yr line) |
-| Demographics | Median income | Age pyramid | Top languages (bar) |
-| Amenities | Park area per capita | Amenity radar | Transit accessibility (bar) |
-
----
-
-## Phase 6: Jupyter Notebooks
-
-### Purpose
-
-One notebook per graph to document:
-1. **Data Reference** — How the data was built (query, transformation steps, sample output)
-2. **Data Visualization** — Import figure factory, render the graph
-
-### Directory Structure
-
-```
-notebooks/
-├── README.md
-├── overview/
-├── housing/
-├── safety/
-├── demographics/
-└── amenities/
-```
-
-### Notebook Template
-
-```markdown
-# [Graph Name]
-
-## 1. Data Reference
-
-### Source Tables
-- List tables/marts used
-- Grain of each table
-
-### Query
-```sql
-SELECT ... FROM ...
-```
-
-### Transformation Steps
-1. Step description
-2. Step description
-
-### Sample Data
-```python
-df = pd.read_sql(query, engine)
-df.head(10)
-```
-
-## 2. Data Visualization
-
-```python
-from portfolio_app.figures.choropleth import create_choropleth_figure
-fig = create_choropleth_figure(...)
-fig.show()
-```
-```
-
-Create one notebook per graph as each is implemented (15 total across 5 tabs).
-
----
-
-## Phase 7: Final Documentation Review
-
-After all implementation, audit and update:
-
-- [ ] `CLAUDE.md` — Project status, app structure, data model, URL routes
-- [ ] `README.md` — Project description, installation, quick start
-- [ ] `docs/PROJECT_REFERENCE.md` — Architecture matches implementation
-- [ ] Remove or archive legacy spec documents
-
----
-
-## Data Source Reference
-
-| Source | Datasets | URL |
-|--------|----------|-----|
-| Toronto Open Data | Neighbourhoods, Census Profiles, Parks, Schools, Childcare, TTC | open.toronto.ca |
-| Toronto Police | Crime Rates, MCI, Shootings | data.torontopolice.on.ca |
-| CMHC | Rental Market Survey | cmhc-schl.gc.ca |
-
----
-
-## CMHC Zone Mapping Note
-
-CMHC uses 15 zones that don't align with 158 neighbourhoods. Strategy:
-- Create `bridge_cmhc_neighbourhood` with area weights
-- Allocate rental metrics proportionally to overlapping neighbourhoods
-- Document methodology in `/toronto/methodology` page
-
----
-
-*Document Version: 2.0*
-*Trimmed from v1.0 for execution clarity*

docs/changes/Change-Toronto-Analysis.md

@@ -1,423 +0,0 @@
-# Toronto Neighbourhood Dashboard — Deliverables
-
-**Project Type:** Interactive Data Visualization Dashboard  
-**Geographic Scope:** City of Toronto, 158 Official Neighbourhoods  
-**Author:** Leo Miranda  
-**Version:** 1.0 | January 2026
-
----
-
-## Executive Summary
-
-Multi-tab analytics dashboard built around Toronto's official neighbourhood boundaries. The core interaction is a choropleth map where users explore the city through different thematic lenses—housing affordability, safety, demographics, amenities—with supporting visualizations that tell a cohesive story per theme.
-
-**Primary Goals:**
-1. Demonstrate interactive data visualization skills (Plotly/Dash)
-2. Showcase data engineering capabilities (multi-source ETL, dimensional modeling)
-3. Create a portfolio piece with genuine analytical value
-
----
-
-## Part 1: Geographic Foundation (Required First)
-
-| Dataset | Source | Format | Last Updated | Download |
-|---------|--------|--------|--------------|----------|
-| **Neighbourhoods Boundaries** | Toronto Open Data | GeoJSON | 2024 | [Link](https://open.toronto.ca/dataset/neighbourhoods/) |
-| **Neighbourhood Profiles** | Toronto Open Data | CSV | 2021 Census | [Link](https://open.toronto.ca/dataset/neighbourhood-profiles/) |
-
-**Critical Notes:**
-- Toronto uses 158 official neighbourhoods (updated 2024, was 140)
-- GeoJSON includes `AREA_ID` for joining to tabular data
-- Neighbourhood Profiles has 2,400+ indicators per neighbourhood from Census
-
----
-
-## Part 2: Tier 1 — MVP Datasets
-
-| Dataset | Source | Measures Available | Update Freq | Granularity |
-|---------|--------|-------------------|-------------|-------------|
-| **Neighbourhoods GeoJSON** | Toronto Open Data | Boundary polygons, area IDs | Static | Neighbourhood |
-| **Neighbourhood Profiles (full)** | Toronto Open Data | 2,400+ Census indicators | Every 5 years | Neighbourhood |
-| **Neighbourhood Crime Rates** | Toronto Police Portal | MCI rates per 100K by year | Annual | Neighbourhood |
-| **CMHC Rental Market Survey** | CMHC Portal | Avg rent by bedroom, vacancy rate | Annual (Oct) | 15 CMHC Zones |
-| **Parks** | Toronto Open Data | Park locations, area, type | Annual | Point/Polygon |
-
-**Total API/Download Calls:** 5  
-**Data Volume:** ~50MB combined
-
-### Tier 1 Measures to Extract
-
-**From Neighbourhood Profiles:**
-- Population, population density
-- Median household income
-- Age distribution (0-14, 15-24, 25-44, 45-64, 65+)
-- % Immigrants, % Visible minorities
-- Top languages spoken
-- Unemployment rate
-- Education attainment (% with post-secondary)
-- Housing tenure (own vs rent %)
-- Dwelling types distribution
-- Average rent, housing costs as % of income
-
-**From Crime Rates:**
-- Total MCI rate per 100K population
-- Year-over-year crime trend
-
-**From CMHC:**
-- Average monthly rent (1BR, 2BR, 3BR)
-- Vacancy rates
-
-**From Parks:**
-- Park count per neighbourhood
-- Park area per capita
-
----
-
-## Part 3: Tier 2 — Expansion Datasets
-
-| Dataset | Source | Measures Available | Update Freq | Granularity |
-|---------|--------|-------------------|-------------|-------------|
-| **Major Crime Indicators (MCI)** | Toronto Police Portal | Assault, B&E, auto theft, robbery, theft over | Quarterly | Neighbourhood |
-| **Shootings & Firearm Discharges** | Toronto Police Portal | Shooting incidents, injuries, fatalities | Quarterly | Neighbourhood |
-| **Building Permits** | Toronto Open Data | New construction, permits by type | Monthly | Address-level |
-| **Schools** | Toronto Open Data | Public/Catholic, elementary/secondary | Annual | Point |
-| **TTC Routes & Stops** | Toronto Open Data | Route geometry, stop locations | Static | Route/Stop |
-| **Licensed Child Care Centres** | Toronto Open Data | Capacity, ages served, locations | Annual | Point |
-
-### Tier 2 Measures to Extract
-
-**From MCI Details:**
-- Breakdown by crime type (assault, B&E, auto theft, robbery, theft over)
-
-**From Shootings:**
-- Shooting incidents count
-- Injuries/fatalities
-
-**From Building Permits:**
-- New construction permits (trailing 12 months)
-- Permit types distribution
-
-**From Schools:**
-- Schools per 1000 children
-- School type breakdown
-
-**From TTC:**
-- Transit stops within neighbourhood
-- Transit accessibility score
-
-**From Child Care:**
-- Child care spaces per capita
-- Coverage by age group
-
----
-
-## Part 4: Data Sources by Thematic Group
-
-### GROUP A: Housing & Affordability
-
-| Dataset | Tier | Measures | Update Freq |
-|---------|------|----------|-------------|
-| Neighbourhood Profiles (Housing) | 1 | Avg rent, ownership %, dwelling types, housing costs as % of income | Every 5 years |
-| CMHC Rental Market Survey | 1 | Avg rent by bedroom, vacancy rate, rental universe | Annual |
-| Building Permits | 2 | New construction, permits by type | Monthly |
-
-**Calculated Metrics:**
-- Rent-to-Income Ratio (CMHC rent ÷ Census income)
-- Affordability Index (% of income spent on housing)
-
----
-
-### GROUP B: Safety & Crime
-
-| Dataset | Tier | Measures | Update Freq |
-|---------|------|----------|-------------|
-| Neighbourhood Crime Rates | 1 | MCI rates per 100K pop by year | Annual |
-| Major Crime Indicators (MCI) | 2 | Assault, B&E, auto theft, robbery, theft over | Quarterly |
-| Shootings & Firearm Discharges | 2 | Shooting incidents, injuries, fatalities | Quarterly |
-
-**Calculated Metrics:**
-- Year-over-year crime change %
-- Crime type distribution
-
----
-
-### GROUP C: Demographics & Community
-
-| Dataset | Tier | Measures | Update Freq |
-|---------|------|----------|-------------|
-| Neighbourhood Profiles (Demographics) | 1 | Age distribution, household composition, income | Every 5 years |
-| Neighbourhood Profiles (Immigration) | 1 | Immigration status, visible minorities, languages | Every 5 years |
-| Neighbourhood Profiles (Education) | 1 | Education attainment, field of study | Every 5 years |
-| Neighbourhood Profiles (Labour) | 1 | Employment rate, occupation, industry | Every 5 years |
-
----
-
-### GROUP D: Transportation & Mobility
-
-| Dataset | Tier | Measures | Update Freq |
-|---------|------|----------|-------------|
-| Commute Mode (Census) | 1 | % car, transit, walk, bike | Every 5 years |
-| TTC Routes & Stops | 2 | Route geometry, stop locations | Static |
-
-**Calculated Metrics:**
-- Transit accessibility (stops within 500m of neighbourhood centroid)
-
----
-
-### GROUP E: Amenities & Services
-
-| Dataset | Tier | Measures | Update Freq |
-|---------|------|----------|-------------|
-| Parks | 1 | Park locations, area, type | Annual |
-| Schools | 2 | Public/Catholic, elementary/secondary | Annual |
-| Licensed Child Care Centres | 2 | Capacity, ages served | Annual |
-
-**Calculated Metrics:**
-- Park area per capita
-- Schools per 1000 children (ages 5-17)
-- Child care spaces per 1000 children (ages 0-4)
-
----
-
-## Part 5: Tab Structure
-
-### Tab Architecture
-
-```
-┌────────────────────────────────────────────────────────────────┐
-│  [Overview] [Housing] [Safety] [Demographics] [Amenities]      │
-├────────────────────────────────────────────────────────────────┤
-│                                                                │
-│    ┌─────────────────────────────────┐  ┌────────────────┐    │
-│    │                                 │  │  KPI Card 1    │    │
-│    │       CHOROPLETH MAP            │  ├────────────────┤    │
-│    │   (158 Neighbourhoods)          │  │  KPI Card 2    │    │
-│    │                                 │  ├────────────────┤    │
-│    │   Click to select               │  │  KPI Card 3    │    │
-│    │                                 │  └────────────────┘    │
-│    └─────────────────────────────────┘                        │
-│                                                                │
-│    ┌─────────────────────┐  ┌─────────────────────┐           │
-│    │  Supporting Chart 1 │  │  Supporting Chart 2 │           │
-│    │  (Context/Trend)    │  │  (Comparison/Rank)  │           │
-│    └─────────────────────┘  └─────────────────────┘           │
-│                                                                │
-│    [Neighbourhood: Selected Name] ────────────────────────    │
-│    Details panel with all metrics for selected area           │
-└────────────────────────────────────────────────────────────────┘
-```
-
----
-
-### Tab 1: Overview (Default Landing)
-
-**Story:** "How do Toronto neighbourhoods compare across key livability metrics?"
-
-| Element | Content | Data Source |
-|---------|---------|-------------|
-| Map Colour | Composite livability score | Calculated from weighted metrics |
-| KPI Cards | Population, Median Income, Avg Crime Rate | Neighbourhood Profiles, Crime Rates |
-| Chart 1 | Top 10 / Bottom 10 by livability score | Calculated |
-| Chart 2 | Income vs Crime scatter plot | Neighbourhood Profiles, Crime Rates |
-
-**Metric Selector:** Allow user to change map colour by any single metric.
-
----
-
-### Tab 2: Housing & Affordability
-
-**Story:** "Where can you afford to live, and what's being built?"
-
-| Element | Content | Data Source |
-|---------|---------|-------------|
-| Map Colour | Rent-to-Income Ratio (Affordability Index) | CMHC + Census income |
-| KPI Cards | Median Rent (1BR), Vacancy Rate, New Permits (12mo) | CMHC, Building Permits |
-| Chart 1 | Rent trend (5-year line chart by bedroom) | CMHC historical |
-| Chart 2 | Dwelling type breakdown (pie/bar) | Neighbourhood Profiles |
-
-**Metric Selector:** Toggle between rent, ownership %, dwelling types.
-
----
-
-### Tab 3: Safety
-
-**Story:** "How safe is each neighbourhood, and what crimes are most common?"
-
-| Element | Content | Data Source |
-|---------|---------|-------------|
-| Map Colour | Total MCI Rate per 100K | Crime Rates |
-| KPI Cards | Total Crimes, YoY Change %, Shooting Incidents | Crime Rates, Shootings |
-| Chart 1 | Crime type breakdown (stacked bar) | MCI Details |
-| Chart 2 | 5-year crime trend (line chart) | Crime Rates historical |
-
-**Metric Selector:** Toggle between total crime, specific crime types, shootings.
-
----
-
-### Tab 4: Demographics
-
-**Story:** "Who lives here? Age, income, diversity."
-
-| Element | Content | Data Source |
-|---------|---------|-------------|
-| Map Colour | Median Household Income | Neighbourhood Profiles |
-| KPI Cards | Population, % Immigrant, Unemployment Rate | Neighbourhood Profiles |
-| Chart 1 | Age distribution (population pyramid or bar) | Neighbourhood Profiles |
-| Chart 2 | Top languages spoken (horizontal bar) | Neighbourhood Profiles |
-
-**Metric Selector:** Income, immigrant %, age groups, education.
-
----
-
-### Tab 5: Amenities & Services
-
-**Story:** "What's nearby? Parks, schools, child care, transit."
-
-| Element | Content | Data Source |
-|---------|---------|-------------|
-| Map Colour | Park Area per Capita | Parks + Population |
-| KPI Cards | Parks Count, Schools Count, Child Care Spaces | Multiple datasets |
-| Chart 1 | Amenity density comparison (radar or bar) | Calculated |
-| Chart 2 | Transit accessibility (stops within 500m) | TTC Stops |
-
-**Metric Selector:** Parks, schools, child care, transit access.
-
----
-
-## Part 6: Data Pipeline Architecture
-
-### ETL Flow
-
-```
-┌─────────────────┐     ┌─────────────────┐     ┌─────────────────┐
-│   DATA SOURCES  │     │   STAGING LAYER │     │   MART LAYER    │
-│                 │     │                 │     │                 │
-│ Toronto Open    │────▶│ stg_geography   │────▶│ dim_neighbourhood│
-│ Data Portal     │     │ stg_census      │     │ fact_crime      │
-│                 │     │ stg_crime       │     │ fact_housing    │
-│ CMHC Portal     │────▶│ stg_rental      │     │ fact_amenities  │
-│                 │     │ stg_permits     │     │                 │
-│ Toronto Police  │────▶│ stg_amenities   │     │ agg_dashboard   │
-│ Portal          │     │ stg_childcare   │     │ (pre-computed)  │
-└─────────────────┘     └─────────────────┘     └─────────────────┘
-```
-
-### Key Transformations
-
-| Transformation | Description |
-|----------------|-------------|
-| **Geography Standardization** | Ensure all datasets use `neighbourhood_id` (AREA_ID from GeoJSON) |
-| **Census Pivot** | Neighbourhood Profiles is wide format — pivot to metrics per neighbourhood |
-| **CMHC Zone Mapping** | Create crosswalk from 15 CMHC zones to 158 neighbourhoods |
-| **Amenity Aggregation** | Spatial join point data (schools, parks, child care) to neighbourhood polygons |
-| **Rate Calculations** | Normalize counts to per-capita or per-100K |
-
-### Data Refresh Schedule
-
-| Layer | Frequency | Trigger |
-|-------|-----------|---------|
-| Staging (API pulls) | Weekly | Scheduled job |
-| Marts (transforms) | Weekly | Post-staging |
-| Dashboard cache | On-demand | User refresh button |
-
----
-
-## Part 7: Technical Stack
-
-### Core Stack
-
-| Component | Technology | Rationale |
-|-----------|------------|-----------|
-| **Frontend** | Plotly Dash | Production-ready, rapid iteration |
-| **Mapping** | Plotly `choropleth_mapbox` | Native Dash integration |
-| **Data Store** | PostgreSQL + PostGIS | Spatial queries, existing expertise |
-| **ETL** | Python (Pandas, SQLAlchemy) | Existing stack |
-| **Deployment** | Render / Railway | Free tier, easy Dash hosting |
-
-### Alternative (Portfolio Stretch)
-
-| Component | Technology | Why Consider |
-|-----------|------------|--------------|
-| **Frontend** | React + deck.gl | More "modern" for portfolio |
-| **Data Store** | DuckDB | Serverless, embeddable |
-| **ETL** | dbt | Aligns with skills roadmap |
-
----
-
-## Appendix A: Data Source URLs
-
-| Source | URL |
-|--------|-----|
-| Toronto Open Data — Neighbourhoods | https://open.toronto.ca/dataset/neighbourhoods/ |
-| Toronto Open Data — Neighbourhood Profiles | https://open.toronto.ca/dataset/neighbourhood-profiles/ |
-| Toronto Police — Neighbourhood Crime Rates | https://data.torontopolice.on.ca/datasets/neighbourhood-crime-rates-open-data |
-| Toronto Police — MCI | https://data.torontopolice.on.ca/datasets/major-crime-indicators-open-data |
-| Toronto Police — Shootings | https://data.torontopolice.on.ca/datasets/shootings-firearm-discharges-open-data |
-| CMHC Rental Market Survey | https://www.cmhc-schl.gc.ca/professionals/housing-markets-data-and-research/housing-data/data-tables/rental-market |
-| Toronto Open Data — Parks | https://open.toronto.ca/dataset/parks/ |
-| Toronto Open Data — Schools | https://open.toronto.ca/dataset/school-locations-all-types/ |
-| Toronto Open Data — Building Permits | https://open.toronto.ca/dataset/building-permits-cleared-permits/ |
-| Toronto Open Data — Child Care | https://open.toronto.ca/dataset/licensed-child-care-centres/ |
-| Toronto Open Data — TTC Routes | https://open.toronto.ca/dataset/ttc-routes-and-schedules/ |
-
----
-
-## Appendix B: Colour Palettes
-
-### Affordability (Diverging)
-| Status | Hex | Usage |
-|--------|-----|-------|
-| Affordable (<30% income) | `#2ecc71` | Green |
-| Stretched (30-50%) | `#f1c40f` | Yellow |
-| Unaffordable (>50%) | `#e74c3c` | Red |
-
-### Safety (Sequential)
-| Status | Hex | Usage |
-|--------|-----|-------|
-| Safest (lowest crime) | `#27ae60` | Dark green |
-| Moderate | `#f39c12` | Orange |
-| Highest Crime | `#c0392b` | Dark red |
-
-### Demographics — Income (Sequential)
-| Level | Hex | Usage |
-|-------|-----|-------|
-| Highest Income | `#1a5276` | Dark blue |
-| Mid Income | `#5dade2` | Light blue |
-| Lowest Income | `#ecf0f1` | Light gray |
-
-### General Recommendation
-Use **Viridis** or **Plasma** colorscales for perceptually uniform gradients on continuous metrics.
-
----
-
-## Appendix C: Glossary
-
-| Term | Definition |
-|------|------------|
-| **MCI** | Major Crime Indicators — Assault, B&E, Auto Theft, Robbery, Theft Over |
-| **CMHC Zone** | Canada Mortgage and Housing Corporation rental market survey zones (15 in Toronto) |
-| **Rent-to-Income Ratio** | Monthly rent ÷ monthly household income; <30% is considered affordable |
-| **PostGIS** | PostgreSQL extension for geographic data |
-| **Choropleth** | Thematic map where areas are shaded based on a statistical variable |
-
----
-
-## Appendix D: Interview Talking Points
-
-When discussing this project in interviews, emphasize:
-
-1. **Data Engineering:** "I built a multi-source ETL pipeline that standardizes geographic keys across Census data, police data, and CMHC rental surveys—three different granularities I had to reconcile."
-
-2. **Dimensional Modeling:** "The data model follows star schema patterns with a central neighbourhood dimension table and fact tables for crime, housing, and amenities."
-
-3. **dbt Patterns:** "The transformation layer uses staging → intermediate → mart patterns, which I've documented for maintainability."
-
-4. **Business Value:** "The dashboard answers questions like 'Where can a young professional afford to live that's safe and has good transit?' — turning raw data into actionable insights."
-
-5. **Technical Decisions:** "I chose Plotly Dash over a React frontend because it let me iterate faster while maintaining production-quality interactivity. For a portfolio piece, speed to working demo matters."
-
----
-
-*Document Version: 1.0*  
-*Created: January 2026*  
-*Author: Leo Miranda / Claude*