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personal-portfolio/portfolio_app/figures/toronto/choropleth.py
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refactor: multi-dashboard structural migration
- Rename dbt project from toronto_housing to portfolio
- Restructure dbt models into domain subdirectories:
  - shared/ for cross-domain dimensions (dim_time)
  - staging/toronto/, intermediate/toronto/, marts/toronto/
- Update SQLAlchemy models for raw_toronto schema
- Add explicit cross-schema FK relationships for FactRentals
- Namespace figure factories under figures/toronto/
- Namespace notebooks under notebooks/toronto/
- Update Makefile with domain-specific targets and env loading
- Update all documentation for multi-dashboard structure

This enables adding new dashboard projects (e.g., /football, /energy)
without structural conflicts or naming collisions.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-01 19:08:20 -05:00

144 lines
4.2 KiB
Python

"""Choropleth map figure factory for Toronto housing data."""
from typing import Any
import plotly.express as px
import plotly.graph_objects as go
def create_choropleth_figure(
geojson: dict[str, Any] | None,
data: list[dict[str, Any]],
location_key: str,
color_column: str,
hover_data: list[str] | None = None,
color_scale: str = "Blues",
title: str | None = None,
map_style: str = "carto-positron",
center: dict[str, float] | None = None,
zoom: float = 9.5,
) -> go.Figure:
"""Create a choropleth map figure.
Args:
geojson: GeoJSON FeatureCollection for boundaries.
data: List of data records with location keys and values.
location_key: Column name for location identifier.
color_column: Column name for color values.
hover_data: Additional columns to show on hover.
color_scale: Plotly color scale name.
title: Optional chart title.
map_style: Mapbox style (carto-positron, open-street-map, etc.).
center: Map center coordinates {"lat": float, "lon": float}.
zoom: Initial zoom level.
Returns:
Plotly Figure object.
"""
# Default center to Toronto
if center is None:
center = {"lat": 43.7, "lon": -79.4}
# Use dark-mode friendly map style by default
if map_style == "carto-positron":
map_style = "carto-darkmatter"
# If no geojson provided, create a placeholder map
if geojson is None or not data:
fig = go.Figure(go.Scattermapbox())
fig.update_layout(
mapbox={
"style": map_style,
"center": center,
"zoom": zoom,
},
margin={"l": 0, "r": 0, "t": 40, "b": 0},
title=title or "Toronto Housing Map",
height=500,
paper_bgcolor="rgba(0,0,0,0)",
plot_bgcolor="rgba(0,0,0,0)",
font_color="#c9c9c9",
)
fig.add_annotation(
text="No geometry data available. Complete QGIS digitization to enable map.",
xref="paper",
yref="paper",
x=0.5,
y=0.5,
showarrow=False,
font={"size": 14, "color": "#888888"},
)
return fig
# Create choropleth with data
import pandas as pd
df = pd.DataFrame(data)
# Use dark-mode friendly map style
effective_map_style = (
"carto-darkmatter" if map_style == "carto-positron" else map_style
)
fig = px.choropleth_mapbox(
df,
geojson=geojson,
locations=location_key,
featureidkey=f"properties.{location_key}",
color=color_column,
color_continuous_scale=color_scale,
hover_data=hover_data,
mapbox_style=effective_map_style,
center=center,
zoom=zoom,
opacity=0.7,
)
fig.update_layout(
margin={"l": 0, "r": 0, "t": 40, "b": 0},
title=title,
height=500,
paper_bgcolor="rgba(0,0,0,0)",
plot_bgcolor="rgba(0,0,0,0)",
font_color="#c9c9c9",
coloraxis_colorbar={
"title": {
"text": color_column.replace("_", " ").title(),
"font": {"color": "#c9c9c9"},
},
"thickness": 15,
"len": 0.7,
"tickfont": {"color": "#c9c9c9"},
},
)
return fig
def create_zone_map(
zones_geojson: dict[str, Any] | None,
rental_data: list[dict[str, Any]],
metric: str = "avg_rent",
) -> go.Figure:
"""Create choropleth map for CMHC zones.
Args:
zones_geojson: GeoJSON for CMHC zone boundaries.
rental_data: Rental statistics by zone.
metric: Metric to display (avg_rent, vacancy_rate, etc.).
Returns:
Plotly Figure object.
"""
hover_columns = ["zone_name", "avg_rent", "vacancy_rate", "rental_universe"]
return create_choropleth_figure(
geojson=zones_geojson,
data=rental_data,
location_key="zone_code",
color_column=metric,
hover_data=[c for c in hover_columns if c != metric],
color_scale="Oranges" if "rent" in metric else "Purples",
title="Toronto Rental Market by Zone",
)