feat: Complete Phase 5 dashboard implementation

Implement full 5-tab Toronto Neighbourhood Dashboard with real data
connectivity:

Dashboard Structure:
- Overview tab with livability scores and rankings
- Housing tab with affordability metrics
- Safety tab with crime statistics
- Demographics tab with population/income data
- Amenities tab with parks, schools, transit

Figure Factories (portfolio_app/figures/):
- bar_charts.py: ranking, stacked, horizontal bars
- scatter.py: scatter plots, bubble charts
- radar.py: spider/radar charts
- demographics.py: donut, age pyramid, income distribution

Service Layer (portfolio_app/toronto/services/):
- neighbourhood_service.py: queries dbt marts for all tab data
- geometry_service.py: generates GeoJSON from PostGIS
- Graceful error handling when database unavailable

Callbacks (portfolio_app/pages/toronto/callbacks/):
- map_callbacks.py: choropleth updates, map click handling
- chart_callbacks.py: supporting chart updates
- selection_callbacks.py: dropdown handlers, KPI updates

Data Pipeline (scripts/data/):
- load_toronto_data.py: orchestration script with CLI flags

Lessons Learned:
- Graceful error handling in service layers
- Modular callback structure for multi-tab dashboards
- Figure factory pattern for reusable charts

Closes: #64, #65, #66, #67, #68, #69, #70

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
2026-01-17 11:46:18 -05:00
parent 3054441630
commit c9cf744d84
27 changed files with 4377 additions and 1770 deletions

View File

@@ -1,9 +1,27 @@
"""Plotly figure factories for data visualization."""
from .bar_charts import (
create_horizontal_bar,
create_ranking_bar,
create_stacked_bar,
)
from .choropleth import (
create_choropleth_figure,
create_zone_map,
)
from .demographics import (
create_age_pyramid,
create_donut_chart,
create_income_distribution,
)
from .radar import (
create_comparison_radar,
create_radar_figure,
)
from .scatter import (
create_bubble_chart,
create_scatter_figure,
)
from .summary_cards import create_metric_card_figure, create_summary_metrics
from .time_series import (
add_policy_markers,
@@ -26,4 +44,18 @@ __all__ = [
# Summary
"create_metric_card_figure",
"create_summary_metrics",
# Bar charts
"create_ranking_bar",
"create_stacked_bar",
"create_horizontal_bar",
# Scatter plots
"create_scatter_figure",
"create_bubble_chart",
# Radar charts
"create_radar_figure",
"create_comparison_radar",
# Demographics
"create_age_pyramid",
"create_donut_chart",
"create_income_distribution",
]