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development #95

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lmiranda merged 89 commits from development into staging 2026-02-01 21:32:42 +00:00
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14 changed files with 79 additions and 54 deletions
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8
notebooks/amenities/amenity_index_choropleth.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_amenities` | neighbourhood × year | amenity_index, total_amenities_per_1000, amenity_tier, geometry |\n",
"| `mart_neighbourhood_amenities` | neighbourhood \u00d7 year | amenity_index, total_amenities_per_1000, amenity_tier, geometry |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/amenities/transit_accessibility_bar.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_amenities` | neighbourhood × year | transit_per_1000, transit_index, transit_count |\n",
"| `mart_neighbourhood_amenities` | neighbourhood \u00d7 year | transit_per_1000, transit_index, transit_count |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/demographics/age_distribution.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_demographics` | neighbourhood × year | median_age, age_index, city_avg_age |\n",
"| `mart_neighbourhood_demographics` | neighbourhood \u00d7 year | median_age, age_index, city_avg_age |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/demographics/income_choropleth.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_demographics` | neighbourhood × year | median_household_income, income_index, income_quintile, geometry |\n",
"| `mart_neighbourhood_demographics` | neighbourhood \u00d7 year | median_household_income, income_index, income_quintile, geometry |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/demographics/population_density_bar.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_demographics` | neighbourhood × year | population_density, population, land_area_sqkm |\n",
"| `mart_neighbourhood_demographics` | neighbourhood \u00d7 year | population_density, population, land_area_sqkm |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/housing/affordability_choropleth.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_housing` | neighbourhood × year | affordability_index, rent_to_income_pct, avg_rent_2bed, geometry |\n",
"| `mart_neighbourhood_housing` | neighbourhood \u00d7 year | affordability_index, rent_to_income_pct, avg_rent_2bed, geometry |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/housing/rent_trend_line.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_housing` | neighbourhood × year | year, avg_rent_2bed, rent_yoy_change_pct |\n",
"| `mart_neighbourhood_housing` | neighbourhood \u00d7 year | year, avg_rent_2bed, rent_yoy_change_pct |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"# City-wide average rent by year\n",
"query = \"\"\"\n",

8
notebooks/housing/tenure_breakdown_bar.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_housing` | neighbourhood × year | pct_owner_occupied, pct_renter_occupied, income_quintile |\n",
"| `mart_neighbourhood_housing` | neighbourhood \u00d7 year | pct_owner_occupied, pct_renter_occupied, income_quintile |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/overview/income_safety_scatter.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_overview` | neighbourhood × year | neighbourhood_name, median_household_income, safety_score, population |\n",
"| `mart_neighbourhood_overview` | neighbourhood \u00d7 year | neighbourhood_name, median_household_income, safety_score, population |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

29
notebooks/overview/livability_choropleth.ipynb
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@@ -29,34 +29,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"import os\n",
"\n",
"# Connect to database\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",
" neighbourhood_id,\n",
" neighbourhood_name,\n",
" geometry,\n",
" year,\n",
" livability_score,\n",
" safety_score,\n",
" affordability_score,\n",
" amenity_score,\n",
" population,\n",
" median_household_income\n",
"FROM public_marts.mart_neighbourhood_overview\n",
"WHERE year = (SELECT MAX(year) FROM public_marts.mart_neighbourhood_overview)\n",
"ORDER BY livability_score DESC\n",
"\"\"\"\n",
"\n",
"df = pd.read_sql(query, engine)\n",
"print(f\"Loaded {len(df)} neighbourhoods\")"
]
"source": "import pandas as pd\nfrom sqlalchemy import create_engine\nfrom dotenv import load_dotenv\nimport os\n\n# Load .env from project root\nload_dotenv('../../.env')\n\nengine = create_engine(os.environ.get('DATABASE_URL'))\n\nquery = \"\"\"\nSELECT\n neighbourhood_id,\n neighbourhood_name,\n geometry,\n year,\n livability_score,\n safety_score,\n affordability_score,\n amenity_score,\n population,\n median_household_income\nFROM public_marts.mart_neighbourhood_overview\nWHERE year = (SELECT MAX(year) FROM public_marts.mart_neighbourhood_overview)\nORDER BY livability_score DESC\n\"\"\"\n\ndf = pd.read_sql(query, engine)\nprint(f\"Loaded {len(df)} neighbourhoods\")"
},
{
"cell_type": "markdown",

8
notebooks/overview/top_bottom_10_bar.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_overview` | neighbourhood × year | neighbourhood_name, livability_score |\n",
"| `mart_neighbourhood_overview` | neighbourhood \u00d7 year | neighbourhood_name, livability_score |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/safety/crime_breakdown_bar.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_safety` | neighbourhood × year | assault_count, auto_theft_count, break_enter_count, robbery_count, etc. |\n",
"| `mart_neighbourhood_safety` | neighbourhood \u00d7 year | assault_count, auto_theft_count, break_enter_count, robbery_count, etc. |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/safety/crime_rate_choropleth.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_safety` | neighbourhood × year | crime_rate_per_100k, crime_index, safety_tier, geometry |\n",
"| `mart_neighbourhood_safety` | neighbourhood \u00d7 year | crime_rate_per_100k, crime_index, safety_tier, geometry |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",

8
notebooks/safety/crime_trend_line.ipynb
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@@ -19,7 +19,7 @@
"\n",
"| Table | Grain | Key Columns |\n",
"|-------|-------|-------------|\n",
"| `mart_neighbourhood_safety` | neighbourhood × year | year, crime_rate_per_100k, crime_yoy_change_pct |\n",
"| `mart_neighbourhood_safety` | neighbourhood \u00d7 year | year, crime_rate_per_100k, crime_yoy_change_pct |\n",
"\n",
"### SQL Query"
]
@@ -32,9 +32,13 @@
"source": [
"import pandas as pd\n",
"from sqlalchemy import create_engine\n",
"from dotenv import load_dotenv\n",
"import os\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL', 'postgresql://portfolio:portfolio@localhost:5432/portfolio'))\n",
"# Load .env from project root\n",
"load_dotenv('../../.env')\n",
"\n",
"engine = create_engine(os.environ.get('DATABASE_URL'))\n",
"\n",
"query = \"\"\"\n",
"SELECT\n",