# 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*