lmiranda
fcaefabce8
- Remove DimTRREBDistrict model and FactPurchases model - Remove TRREBDistrict schema and AreaType enum - Remove TRREBDistrictParser from geo parsers - Remove load_trreb_districts from dimension loaders - Remove create_district_map from choropleth figures - Remove get_demo_districts and get_demo_purchase_data from demo_data - Update summary metrics to remove purchase-related metrics - Update callbacks to remove TRREB-related comments - Update methodology page to remove TRREB data source section - Update dashboard data notice to remove TRREB mention Closes #49 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
144 lines
4.2 KiB
Python
144 lines
4.2 KiB
Python
"""Choropleth map figure factory for Toronto housing data."""
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from typing import Any
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import plotly.express as px
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import plotly.graph_objects as go
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def create_choropleth_figure(
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geojson: dict[str, Any] | None,
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data: list[dict[str, Any]],
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location_key: str,
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color_column: str,
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hover_data: list[str] | None = None,
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color_scale: str = "Blues",
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title: str | None = None,
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map_style: str = "carto-positron",
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center: dict[str, float] | None = None,
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zoom: float = 9.5,
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) -> go.Figure:
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"""Create a choropleth map figure.
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Args:
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geojson: GeoJSON FeatureCollection for boundaries.
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data: List of data records with location keys and values.
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location_key: Column name for location identifier.
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color_column: Column name for color values.
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hover_data: Additional columns to show on hover.
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color_scale: Plotly color scale name.
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title: Optional chart title.
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map_style: Mapbox style (carto-positron, open-street-map, etc.).
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center: Map center coordinates {"lat": float, "lon": float}.
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zoom: Initial zoom level.
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Returns:
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Plotly Figure object.
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"""
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# Default center to Toronto
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if center is None:
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center = {"lat": 43.7, "lon": -79.4}
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# Use dark-mode friendly map style by default
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if map_style == "carto-positron":
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map_style = "carto-darkmatter"
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# If no geojson provided, create a placeholder map
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if geojson is None or not data:
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fig = go.Figure(go.Scattermapbox())
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fig.update_layout(
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mapbox={
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"style": map_style,
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"center": center,
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"zoom": zoom,
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},
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margin={"l": 0, "r": 0, "t": 40, "b": 0},
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title=title or "Toronto Housing Map",
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height=500,
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paper_bgcolor="rgba(0,0,0,0)",
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plot_bgcolor="rgba(0,0,0,0)",
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font_color="#c9c9c9",
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)
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fig.add_annotation(
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text="No geometry data available. Complete QGIS digitization to enable map.",
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xref="paper",
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yref="paper",
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x=0.5,
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y=0.5,
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showarrow=False,
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font={"size": 14, "color": "#888888"},
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)
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return fig
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# Create choropleth with data
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import pandas as pd
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df = pd.DataFrame(data)
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# Use dark-mode friendly map style
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effective_map_style = (
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"carto-darkmatter" if map_style == "carto-positron" else map_style
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)
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fig = px.choropleth_mapbox(
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df,
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geojson=geojson,
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locations=location_key,
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featureidkey=f"properties.{location_key}",
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color=color_column,
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color_continuous_scale=color_scale,
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hover_data=hover_data,
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mapbox_style=effective_map_style,
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center=center,
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zoom=zoom,
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opacity=0.7,
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)
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fig.update_layout(
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margin={"l": 0, "r": 0, "t": 40, "b": 0},
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title=title,
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height=500,
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paper_bgcolor="rgba(0,0,0,0)",
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plot_bgcolor="rgba(0,0,0,0)",
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font_color="#c9c9c9",
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coloraxis_colorbar={
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"title": {
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"text": color_column.replace("_", " ").title(),
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"font": {"color": "#c9c9c9"},
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},
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"thickness": 15,
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"len": 0.7,
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"tickfont": {"color": "#c9c9c9"},
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},
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)
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return fig
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def create_zone_map(
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zones_geojson: dict[str, Any] | None,
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rental_data: list[dict[str, Any]],
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metric: str = "avg_rent",
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) -> go.Figure:
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"""Create choropleth map for CMHC zones.
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Args:
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zones_geojson: GeoJSON for CMHC zone boundaries.
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rental_data: Rental statistics by zone.
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metric: Metric to display (avg_rent, vacancy_rate, etc.).
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Returns:
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Plotly Figure object.
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"""
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hover_columns = ["zone_name", "avg_rent", "vacancy_rate", "rental_universe"]
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return create_choropleth_figure(
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geojson=zones_geojson,
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data=rental_data,
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location_key="zone_code",
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color_column=metric,
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hover_data=[c for c in hover_columns if c != metric],
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color_scale="Oranges" if "rent" in metric else "Purples",
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title="Toronto Rental Market by Zone",
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)
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