lmiranda
c9cf744d84
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>
62 lines
1.4 KiB
Python
62 lines
1.4 KiB
Python
"""Plotly figure factories for data visualization."""
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from .bar_charts import (
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create_horizontal_bar,
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create_ranking_bar,
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create_stacked_bar,
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)
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from .choropleth import (
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create_choropleth_figure,
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create_zone_map,
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)
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from .demographics import (
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create_age_pyramid,
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create_donut_chart,
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create_income_distribution,
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)
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from .radar import (
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create_comparison_radar,
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create_radar_figure,
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)
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from .scatter import (
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create_bubble_chart,
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create_scatter_figure,
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)
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from .summary_cards import create_metric_card_figure, create_summary_metrics
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from .time_series import (
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add_policy_markers,
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create_market_comparison_chart,
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create_price_time_series,
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create_time_series_with_events,
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create_volume_time_series,
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)
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__all__ = [
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# Choropleth
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"create_choropleth_figure",
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"create_zone_map",
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# Time series
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"create_price_time_series",
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"create_volume_time_series",
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"create_market_comparison_chart",
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"create_time_series_with_events",
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"add_policy_markers",
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# Summary
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"create_metric_card_figure",
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"create_summary_metrics",
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# Bar charts
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"create_ranking_bar",
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"create_stacked_bar",
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"create_horizontal_bar",
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# Scatter plots
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"create_scatter_figure",
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"create_bubble_chart",
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# Radar charts
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"create_radar_figure",
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"create_comparison_radar",
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# Demographics
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"create_age_pyramid",
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"create_donut_chart",
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"create_income_distribution",
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]
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