lmiranda
eee015efac
Some checks failed
CI / lint-and-test (push) Has been cancelled
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
124 lines
3.9 KiB
Plaintext
124 lines
3.9 KiB
Plaintext
{
|
||
"cells": [
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"# Amenity Radar Chart\n",
|
||
"\n",
|
||
"Spider/radar chart comparing amenity categories for selected neighbourhoods."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 1. Data Reference\n",
|
||
"\n",
|
||
"### Source Tables\n",
|
||
"\n",
|
||
"| Table | Grain | Key Columns |\n",
|
||
"|-------|-------|-------------|\n",
|
||
"| `mart_neighbourhood_amenities` | neighbourhood × year | parks_index, schools_index, transit_index |\n",
|
||
"\n",
|
||
"### SQL Query"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"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_name,\n parks_index,\n schools_index,\n transit_index,\n amenity_index,\n amenity_tier\nFROM public_marts.mart_neighbourhood_amenities\nWHERE year = (SELECT MAX(year) FROM public_marts.mart_neighbourhood_amenities)\nORDER BY amenity_index DESC\n\"\"\"\n\ndf = pd.read_sql(query, engine)\nprint(f\"Loaded {len(df)} neighbourhoods\")"
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Transformation Steps\n",
|
||
"\n",
|
||
"1. Select top 5 and bottom 5 neighbourhoods by amenity index\n",
|
||
"2. Reshape for radar chart format"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"# Select representative neighbourhoods\n",
|
||
"top_5 = df.head(5)\n",
|
||
"bottom_5 = df.tail(5)\n",
|
||
"\n",
|
||
"# Prepare radar data\n",
|
||
"categories = ['Parks', 'Schools', 'Transit']\n",
|
||
"index_columns = ['parks_index', 'schools_index', 'transit_index']"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Sample Output"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": [
|
||
"print(\"Top 5 Amenity-Rich Neighbourhoods:\")\n",
|
||
"display(top_5[['neighbourhood_name', 'parks_index', 'schools_index', 'transit_index', 'amenity_index']])\n",
|
||
"print(\"\\nBottom 5 Underserved Neighbourhoods:\")\n",
|
||
"display(bottom_5[['neighbourhood_name', 'parks_index', 'schools_index', 'transit_index', 'amenity_index']])"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"## 2. Data Visualization\n",
|
||
"\n",
|
||
"### Figure Factory\n",
|
||
"\n",
|
||
"Uses `create_radar` from `portfolio_app.figures.radar`."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"metadata": {},
|
||
"outputs": [],
|
||
"source": "import sys\nsys.path.insert(0, '../..')\n\nfrom portfolio_app.figures.radar import create_comparison_radar\n\n# Compare top neighbourhood vs city average (100)\ntop_hood = top_5.iloc[0]\nmetrics = ['parks_index', 'schools_index', 'transit_index']\n\nfig = create_comparison_radar(\n selected_data=top_hood.to_dict(),\n average_data={'parks_index': 100, 'schools_index': 100, 'transit_index': 100},\n metrics=metrics,\n selected_name=top_hood['neighbourhood_name'],\n average_name='City Average',\n title=f\"Amenity Profile: {top_hood['neighbourhood_name']} vs City Average\",\n)\n\nfig.show()"
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Index Interpretation\n",
|
||
"\n",
|
||
"| Value | Meaning |\n",
|
||
"|-------|--------|\n",
|
||
"| < 100 | Below city average |\n",
|
||
"| = 100 | City average |\n",
|
||
"| > 100 | Above city average |"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"name": "python",
|
||
"version": "3.11.0"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 4
|
||
}
|