{"id":331378,"date":"2025-12-05T16:12:45","date_gmt":"2025-12-05T16:12:45","guid":{"rendered":"https:\/\/peraltafinancing.com\/uncategorized\/airbnb-revenue-model-using-mashvisor-lookup-api\/"},"modified":"2025-12-05T16:12:45","modified_gmt":"2025-12-05T16:12:45","slug":"airbnb-revenue-model-using-mashvisor-lookup-api","status":"publish","type":"post","link":"https:\/\/fivemor.com\/?p=331378","title":{"rendered":"Airbnb Revenue Model Using Mashvisor Lookup API"},"content":{"rendered":"<p> <br \/>\n<\/p>\n<div>\n<p><span style=\"font-weight: 400;\">The Mashvisor Lookup API solves the biggest pain in Airbnb revenue modeling: dirty rental data, unreliable scrapers, and inconsistent revenue calculations. As a real estate data API, it returns complete, pre-modeled financial metrics in a single call. No scraping, no manual calculations, no custom data cleaning. Developers can build a full revenue model quickly using this production-ready rental data API.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">For example, a developer building an investor dashboard can fetch monthly revenue, occupancy, and expenses for any U.S. market with a single request\u2014no scraping or manual modeling required. This makes Lookup one of the most efficient property data APIs available to PropTech teams.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This guide walks you through turning a single Lookup API response into a complete Airbnb revenue model.<\/span><\/p>\n<p><b>Why Lookup is the core engine:<\/b><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Returns revenue, occupancy, expenses, cash flow, cap rate, and cash-on-cash metrics<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Works at city, zip, and address levels nationwide<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Pre-modeled metrics reduce complexity and development time<\/span><\/li>\n<\/ul>\n<p><b>Prerequisites:<\/b><\/p>\n<p><b>API Coverage:<\/b><span style=\"font-weight: 400;\"> United States (all 50 states) and international markets including Great Britain (GB), Canada (CA), Spain (ES), Australia (AU), United Arab Emirates (AE), France (FR), South Africa (ZA), Saudi Arabia (SA), Greece (GR).<\/span><\/p>\n<h3><b>Summary<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Mashvisor\u2019s Lookup API provides a complete, production-grade data pipeline for Airbnb underwriting. A single request returns pre-modeled revenue, occupancy, ADR, RevPAR, expenses, NOI, cash flow, and cash-on-cash return, along with sample-size and data-quality indicators.\u00a0<\/span><\/p>\n<p><span style=\"font-weight: 400;\">This guide shows how to transform the Lookup response into a full revenue model, apply financing logic, implement statistical fallbacks across address\/zip\/city levels, and output investment-ready summaries suitable for PropTech applications, valuation engines, and automated underwriting workflows.<\/span><\/p>\n<h2><b>II. How the Lookup API Works<\/b><\/h2>\n<h3><b>A. Minimal API Request\u00a0<\/b><\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-328108 size-large\" src=\"https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1-1024x683.webp\" alt=\"How the Mashvisor lookup api request works\" width=\"1024\" height=\"683\" srcset=\"https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1-1024x683.webp 1024w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1-300x200.webp 300w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1-768x512.webp 768w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1-1170x780.webp 1170w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1-585x390.webp 585w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1-263x175.webp 263w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1-265x177.webp 265w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-1-1.webp 1536w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\"\/><\/p>\n<p><span style=\"font-weight: 400;\">Example:<\/span><\/p>\n<p>\u00a0<\/p>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\">import<\/span><span style=\"font-weight: 400;\"> requests<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">API_KEY = <\/span><span style=\"font-weight: 400;\">\u2018your_api_key\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">BASE_URL = <\/span><span style=\"font-weight: 400;\">\u2018https:\/\/api.mashvisor.com\/v1.1\/client\/rento-calculator\/lookup\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">def<\/span> <b>get_market_data<\/b><span style=\"font-weight: 400;\">(params, api_key=None):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u201c\u201d\u201dFetch Airbnb market data from Mashvisor API.\u201d\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 headers = {<\/span><span style=\"font-weight: 400;\">\u2018x-api-key\u2019<\/span><span style=\"font-weight: 400;\">: api_key <\/span><span style=\"font-weight: 400;\">or<\/span><span style=\"font-weight: 400;\"> API_KEY}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 response = requests.get(BASE_URL, params=params, headers=headers)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 response.raise_for_status()<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">return<\/span><span style=\"font-weight: 400;\"> response.json()<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u00a0<\/p>\n<h3><b>B. Supported Parameters<\/b><\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-328110 size-full\" src=\"https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-2-1.webp\" alt=\"The supported parameters on the Mashvisor lookup API\" width=\"806\" height=\"339\" srcset=\"https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-2-1.webp 806w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-2-1-300x126.webp 300w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-2-1-768x323.webp 768w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-2-1-585x246.webp 585w\" sizes=\"auto, (max-width: 806px) 100vw, 806px\"\/><\/p>\n<h3><b>Analysis levels:<\/b><\/h3>\n<ul>\n<li><span style=\"font-weight: 400;\"> City-level: Best for market screening \u2014 use when sample_size \u2265 80 for top confidence.<\/span><\/li>\n<li><span style=\"font-weight: 400;\"> Zip-level: Best for neighborhood analysis \u2014 require sample_size \u2265 30.<\/span><\/li>\n<li><span style=\"font-weight: 400;\"> Address-level: Best for specific property evaluation \u2014 require sample_size \u2265 15 (requires lat\/lng).<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">With the request structure established, the next step is understanding the shape of the response. Every part of the revenue model is derived directly from this JSON structure.<\/span><\/p>\n<h3><b>C. How Often Is the Historical Dataset Refreshed?<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Mashvisor\u2019s underlying dataset is updated <\/span><b>every day<\/b><span style=\"font-weight: 400;\"> to keep the metrics as accurate as possible. Each refresh incorporates the latest shifts in occupancy trends, pricing movements, and short-term rental supply across major STR platforms. These updated values flow directly into the API, so developers automatically receive the newest figures without needing to take any extra steps.<\/span><\/p>\n<p><em><strong>Read more: <a href=\"https:\/\/www.mashvisor.com\/blog\/airbnb-historical-performance-api\/\" data-wpel-link=\"internal\">How to Use the Historical Performance API<\/a><\/strong><\/em><\/p>\n<h2><b>III. Understanding the Lookup Response<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">The Lookup API returns a structured JSON object containing aggregated Airbnb metrics for the requested location. Each entry inside <\/span><span style=\"font-weight: 400;\">content<\/span><span style=\"font-weight: 400;\"> represents a subgroup of comparable properties (for example, by bedroom\/bath configuration), along with median revenue, occupancy, and sample size. Below is a trimmed preview of the JSON structure returned by the endpoint:<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-328111 size-full\" src=\"https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-3.webp\" alt=\"A typical JSON response\" width=\"484\" height=\"867\" srcset=\"https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-3.webp 484w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-3-167x300.webp 167w\" sizes=\"auto, (max-width: 484px) 100vw, 484px\"\/><\/p>\n<h2><b style=\"font-family: Raleway, sans-serif; font-size: 22px; letter-spacing: 0px;\">IV. How to Build the Airbnb Revenue Model<\/b><\/h2>\n<h3><b>A. Model Structure<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">The Airbnb revenue model consists of five core components:<\/span><\/p>\n<ol>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Property &amp; market context<\/b><span style=\"font-weight: 400;\"> \u2014 Location, value, market ID<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Revenue metrics<\/b><span style=\"font-weight: 400;\"> \u2014 Income, occupancy, nightly rates<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Expense metrics<\/b><span style=\"font-weight: 400;\"> \u2014 Itemized operating costs<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Profitability metrics<\/b><span style=\"font-weight: 400;\"> \u2014 NOI, cash flow, returns<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Metadata<\/b><span style=\"font-weight: 400;\"> \u2014 Sample size, data quality indicators<\/span><\/li>\n<\/ol>\n<h3><b>B. Main Code: build_revenue_model()<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">The revenue model is constructed from five layers: property data, revenue metrics, expenses, profitability, and metadata. Before diving into the full implementation, here is the structural overview so you can understand the shape of the function. The complete production-ready function follows immediately afterward.<\/span><\/p>\n<p>\u00a0<\/p>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\"># Core structure (full function below)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">def<\/span> <b>build_revenue_model<\/b><span style=\"font-weight: 400;\">(api_response, financing_params=None):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 content = api_response[<\/span><span style=\"font-weight: 400;\">\u2018content\u2019<\/span><span style=\"font-weight: 400;\">]<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 model = {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018property\u2019<\/span><span style=\"font-weight: 400;\">: {\u2026}, \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># location, market_id, median_value<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018revenue\u2019<\/span><span style=\"font-weight: 400;\">: {\u2026},\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># monthly\/annual income, nightly rate, occupancy<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">: {\u2026}, \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># itemized operating costs<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">: {\u2026},\u00a0 <\/span><span style=\"font-weight: 400;\"># NOI, cap rate, cash flow placeholders<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018metadata\u2019<\/span><span style=\"font-weight: 400;\">: {\u2026}\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># sample_size, data_quality, analysis_date<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 }<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># Financing logic and recalculations appear in the full implementation below<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">return<\/span><span style=\"font-weight: 400;\"> model<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4><b>Full Implementation<\/b><\/h4>\n<p><span style=\"font-weight: 400;\">The full production-ready implementation contains all field mappings, fallback handling, defensive checks, and optional financing logic used in real integrations.<\/span><\/p>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\">from<\/span><span style=\"font-weight: 400;\"> datetime <\/span><span style=\"font-weight: 400;\">import<\/span><span style=\"font-weight: 400;\"> datetime<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">def<\/span> <b>build_revenue_model<\/b><span style=\"font-weight: 400;\">(api_response, financing_params=None):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u201c\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 Build complete revenue model from Mashvisor lookup API data.<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 Args:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 api_response: JSON response from Mashvisor \/rento-calculator\/lookup<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 financing_params: Optional dict with down_payment_pct, interest_rate, loan_term<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 Returns:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 Complete revenue model dict<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u201c\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> api_response.get(<\/span><span style=\"font-weight: 400;\">\u2018status\u2019<\/span><span style=\"font-weight: 400;\">) != <\/span><span style=\"font-weight: 400;\">\u2018success\u2019<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">raise<\/span><span style=\"font-weight: 400;\"> ValueError(<\/span><span style=\"font-weight: 400;\">\u201cAPI request failed\u201d<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 content = api_response[<\/span><span style=\"font-weight: 400;\">\u2018content\u2019<\/span><span style=\"font-weight: 400;\">]<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 market = content[<\/span><span style=\"font-weight: 400;\">\u2018market\u2019<\/span><span style=\"font-weight: 400;\">]<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 expenses_map = content[<\/span><span style=\"font-weight: 400;\">\u2018expenses_map\u2019<\/span><span style=\"font-weight: 400;\">]<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 maintenance = (<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 expenses_map.get(<\/span><span style=\"font-weight: 400;\">\u2018maintenance\u2019<\/span><span style=\"font-weight: 400;\">) <\/span><span style=\"font-weight: 400;\">or<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 expenses_map.get(<\/span><span style=\"font-weight: 400;\">\u2018maintenace\u2019<\/span><span style=\"font-weight: 400;\">) <\/span><span style=\"font-weight: 400;\">or<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 )<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># \u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2013<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># NEW: data quality threshold mapping (minimal version)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># \u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2013<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 _s = content.get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> _s <\/span><span style=\"font-weight: 400;\">is<\/span> <span style=\"font-weight: 400;\">None<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 dq = <\/span><span style=\"font-weight: 400;\">\u2018unknown\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">elif<\/span><span style=\"font-weight: 400;\"> _s &gt;= <\/span><span style=\"font-weight: 400;\">80<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 dq = <\/span><span style=\"font-weight: 400;\">\u2018high\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">elif<\/span><span style=\"font-weight: 400;\"> _s &gt;= <\/span><span style=\"font-weight: 400;\">30<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 dq = <\/span><span style=\"font-weight: 400;\">\u2018medium\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">elif<\/span><span style=\"font-weight: 400;\"> _s &gt;= <\/span><span style=\"font-weight: 400;\">15<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 dq = <\/span><span style=\"font-weight: 400;\">\u2018low\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">else<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 dq = <\/span><span style=\"font-weight: 400;\">\u2018very_low\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># \u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2014\u2013<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># 1. Property &amp; Location Data<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 model = {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018property\u2019<\/span><span style=\"font-weight: 400;\">: {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018location\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">f\u201d<\/span><span style=\"font-weight: 400;\">{market[<\/span><span style=\"font-weight: 400;\">\u2018city\u2019<\/span><span style=\"font-weight: 400;\">]}<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">{market[<\/span><span style=\"font-weight: 400;\">\u2018state\u2019<\/span><span style=\"font-weight: 400;\">]}<\/span><span style=\"font-weight: 400;\">\u201c<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018market_id\u2019<\/span><span style=\"font-weight: 400;\">: market[<\/span><span style=\"font-weight: 400;\">\u2018id\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018median_value\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018median_home_value\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 },<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># 2. Revenue Projections<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018revenue\u2019<\/span><span style=\"font-weight: 400;\">: {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018monthly_income\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018median_rental_income\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018annual_income\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018median_rental_income\u2019<\/span><span style=\"font-weight: 400;\">] * <\/span><span style=\"font-weight: 400;\">12<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018nightly_rate\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018median_night_rate\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018occupancy_rate\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018median_occupancy_rate\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018revpar\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018revpar\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018guest_capacity\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018median_guests_capacity\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 },<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># 3. Expense Breakdown (all fields documented in expenses_map)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">: {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018monthly_total\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018annual_total\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">] * <\/span><span style=\"font-weight: 400;\">12<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018property_tax\u2019<\/span><span style=\"font-weight: 400;\">: expenses_map[<\/span><span style=\"font-weight: 400;\">\u2018propertyTax\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018maintenance\u2019<\/span><span style=\"font-weight: 400;\">: maintenance,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018management\u2019<\/span><span style=\"font-weight: 400;\">: expenses_map[<\/span><span style=\"font-weight: 400;\">\u2018management\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018rental_income_tax\u2019<\/span><span style=\"font-weight: 400;\">: expenses_map[<\/span><span style=\"font-weight: 400;\">\u2018rentalIncomeTax\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018insurance\u2019<\/span><span style=\"font-weight: 400;\">: expenses_map[<\/span><span style=\"font-weight: 400;\">\u2018insurance\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018utilities\u2019<\/span><span style=\"font-weight: 400;\">: expenses_map[<\/span><span style=\"font-weight: 400;\">\u2018utilities\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018hoa_dues\u2019<\/span><span style=\"font-weight: 400;\">: expenses_map[<\/span><span style=\"font-weight: 400;\">\u2018hoa_dues\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018cleaning\u2019<\/span><span style=\"font-weight: 400;\">: expenses_map[<\/span><span style=\"font-weight: 400;\">\u2018cleaningFees\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 },<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># 4. Pre-Financing Profitability<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">: {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018monthly_noi\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018median_rental_income\u2019<\/span><span style=\"font-weight: 400;\">] \u2013 content[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018annual_noi\u2019<\/span><span style=\"font-weight: 400;\">: (content[<\/span><span style=\"font-weight: 400;\">\u2018median_rental_income\u2019<\/span><span style=\"font-weight: 400;\">] \u2013 content[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">]) * <\/span><span style=\"font-weight: 400;\">12<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018cap_rate\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018cap_rate\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018cash_flow_api\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018cash_flow\u2019<\/span><span style=\"font-weight: 400;\">], \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># from API<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018cash_on_cash_api\u2019<\/span><span style=\"font-weight: 400;\">: content[<\/span><span style=\"font-weight: 400;\">\u2018cash_on_cash\u2019<\/span><span style=\"font-weight: 400;\">], <\/span><span style=\"font-weight: 400;\"># from API<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 },<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># 5. Data Quality Indicators<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018metadata\u2019<\/span><span style=\"font-weight: 400;\">: {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">: content.get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018data_quality\u2019<\/span><span style=\"font-weight: 400;\">: dq,\u00a0 <\/span><span style=\"font-weight: 400;\"># &lt;\u2013 replaced old good\/moderate\/low ternary<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018analysis_date\u2019<\/span><span style=\"font-weight: 400;\">: datetime.now().isoformat(),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018price_to_rent_ratio\u2019<\/span><span style=\"font-weight: 400;\">: content.get(<\/span><span style=\"font-weight: 400;\">\u2018price_to_rent_ratio\u2019<\/span><span style=\"font-weight: 400;\">),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018regulations\u2019<\/span><span style=\"font-weight: 400;\">: market.get(<\/span><span style=\"font-weight: 400;\">\u2018airbnb_regulations\u2019<\/span><span style=\"font-weight: 400;\">),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018city_insights_fallback\u2019<\/span><span style=\"font-weight: 400;\">: content.get(<\/span><span style=\"font-weight: 400;\">\u2018city_insights_fallback\u2019<\/span><span style=\"font-weight: 400;\">),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 }<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 }<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># 6. Add Financing Layer (if provided) \u2013 this is your own logic, not API-dependent<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> financing_params:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 financing = calculate_financing(<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 content[<\/span><span style=\"font-weight: 400;\">\u2018median_home_value\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 financing_params[<\/span><span style=\"font-weight: 400;\">\u2018down_payment_pct\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 financing_params[<\/span><span style=\"font-weight: 400;\">\u2018interest_rate\u2019<\/span><span style=\"font-weight: 400;\">],<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 financing_params.get(<\/span><span style=\"font-weight: 400;\">\u2018loan_term\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">30<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 )<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 model[<\/span><span style=\"font-weight: 400;\">\u2018financing\u2019<\/span><span style=\"font-weight: 400;\">] = financing<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># Recalculate profitability with mortgage<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 monthly_cash_flow = model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018monthly_noi\u2019<\/span><span style=\"font-weight: 400;\">] \u2013 financing[<\/span><span style=\"font-weight: 400;\">\u2018monthly_payment\u2019<\/span><span style=\"font-weight: 400;\">]<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 annual_cash_flow = monthly_cash_flow * <\/span><span style=\"font-weight: 400;\">12<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">].update({<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018monthly_cash_flow\u2019<\/span><span style=\"font-weight: 400;\">: monthly_cash_flow,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018annual_cash_flow\u2019<\/span><span style=\"font-weight: 400;\">: annual_cash_flow,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018cash_on_cash_return\u2019<\/span><span style=\"font-weight: 400;\">: (<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 (annual_cash_flow \/ financing[<\/span><span style=\"font-weight: 400;\">\u2018total_invested\u2019<\/span><span style=\"font-weight: 400;\">]) * <\/span><span style=\"font-weight: 400;\">100<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> financing[<\/span><span style=\"font-weight: 400;\">\u2018total_invested\u2019<\/span><span style=\"font-weight: 400;\">] &gt; <\/span><span style=\"font-weight: 400;\">0<\/span> <span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">None<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 ),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018break_even_months\u2019<\/span><span style=\"font-weight: 400;\">: (<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 financing[<\/span><span style=\"font-weight: 400;\">\u2018total_invested\u2019<\/span><span style=\"font-weight: 400;\">] \/ monthly_cash_flow<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> monthly_cash_flow &gt; <\/span><span style=\"font-weight: 400;\">0<\/span> <span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">None<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 )<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 })<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">return<\/span><span style=\"font-weight: 400;\"> model<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u00a0<\/p>\n<h3><b>C. How the Model Works<\/b><\/h3>\n<p><b>Revenue<\/b><span style=\"font-weight: 400;\"> uses the API\u2019s <\/span><b>median_rental_income<\/b><span style=\"font-weight: 400;\"> directly.<\/span><\/p>\n<p><b>Expenses<\/b><span style=\"font-weight: 400;\"> come from <\/span><b>expenses_map<\/b><span style=\"font-weight: 400;\">, providing itemized monthly costs across all operating categories.<\/span><\/p>\n<p><b>Profitability<\/b><span style=\"font-weight: 400;\"> calculates NOI from revenue minus expenses, then applies financing costs if provided.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">With the model architecture defined, we can now break down the inputs that drive revenue and expenses. These metrics map directly to fields inside the Lookup API response.<\/span><\/p>\n<h2><b>V. Revenue Model Inputs\u00a0<\/b><\/h2>\n<p><b>median_rental_income<\/b><span style=\"font-weight: 400;\">: Expected monthly revenue based on real booking patterns.<\/span><\/p>\n<p><b>median_night_rate<\/b><span style=\"font-weight: 400;\">: Typical nightly rate charged in the market.<\/span><\/p>\n<p><b>median_occupancy_rate<\/b><span style=\"font-weight: 400;\">: Percentage of available nights booked. A 65% Airbnb occupancy rate equals 237 nights per year.<\/span><\/p>\n<p><b>revpar<\/b><span style=\"font-weight: 400;\">: Revenue per available room (nightly rate \u00d7 occupancy rate). Useful for comparing properties with different bedroom counts. Higher RevPAR indicates stronger market positioning.<\/span><\/p>\n<p><b>median_guests_capacity<\/b><span style=\"font-weight: 400;\">: Maximum number of guests the property accommodates, which influences pricing potential.<\/span><\/p>\n<h2><b>VI. Expense Model Inputs\u00a0<\/b><\/h2>\n<h3><b>A. Core Expense Categories\u00a0<\/b><\/h3>\n<p><b>propertyTax<\/b><b>:<\/b><span style=\"font-weight: 400;\"> Based on local tax rates and median home values<\/span><\/p>\n<p><b>management<\/b><b>:<\/b><span style=\"font-weight: 400;\"> Typically 20\u201325% of gross revenue<\/span><\/p>\n<p><b>maintenance<\/b><b>:<\/b><span style=\"font-weight: 400;\"> ~1% of property value annually (STRs experience 2\u20133\u00d7 more wear than traditional rentals)<\/span><\/p>\n<p><b>insurance:<\/b> <span style=\"font-weight: 400;\">Property and liability coverage<\/span><\/p>\n<p><b>utilities<\/b><b>:<\/b><span style=\"font-weight: 400;\"> Internet, electric, water, gas (host pays all utilities in STRs)<\/span><\/p>\n<p><b>hoa_dues:<\/b><span style=\"font-weight: 400;\"> Homeowner association fees (if applicable)<\/span><\/p>\n<p><b>cleaningFees<\/b><b>:<\/b><span style=\"font-weight: 400;\"> Professional cleaning between guests<\/span><\/p>\n<h3><b>B. What\u2019s Not Included<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">The <\/span><a href=\"https:\/\/www.mashvisor.com\/blog\/airbnb-api\/\" data-wpel-link=\"internal\"><span style=\"font-weight: 400;\">Mashvisor Airbnb AP<\/span><\/a><span style=\"font-weight: 400;\">I doesn\u2019t account for:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Furniture and initial setup<\/b><span style=\"font-weight: 400;\">: $10,000-15,000 for a 2-bedroom property<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Airbnb host fees<\/b><span style=\"font-weight: 400;\">: 3% of gross bookings<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Licensing\/permit fees<\/b><span style=\"font-weight: 400;\">: $200-2,000 annually depending on jurisdiction<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Add these costs separately if building a complete investment calculator.<\/span><\/p>\n<h2><b>VII. Financing Layer (Optional)<\/b><\/h2>\n<h3><b>A. What Financing Adds to the Model<\/b><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Monthly mortgage payment<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Down payment and closing costs<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Total cash invested<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Cash-on-cash return (annual cash flow \u00f7 total invested)<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Break-even timeline<\/span><\/li>\n<\/ul>\n<h3><b>B. Code: calculate_financing()<\/b><\/h3>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\">def<\/span> <b>calculate_financing<\/b><span style=\"font-weight: 400;\">(home_value, down_pct, interest_rate, loan_term=<\/span><span style=\"font-weight: 400;\">30<\/span><span style=\"font-weight: 400;\">):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u201c\u201d\u201dCalculate mortgage and investment details (independent of Mashvisor).\u201d\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 down_payment = home_value * (down_pct \/ <\/span><span style=\"font-weight: 400;\">100<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 loan_amount = home_value \u2013 down_payment<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 closing_costs = home_value * <\/span><span style=\"font-weight: 400;\">0.03<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 monthly_rate = interest_rate \/ <\/span><span style=\"font-weight: 400;\">12<\/span><span style=\"font-weight: 400;\"> \/ <\/span><span style=\"font-weight: 400;\">100<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 num_payments = loan_term * <\/span><span style=\"font-weight: 400;\">12<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 monthly_payment = loan_amount * (<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 monthly_rate * (<\/span><span style=\"font-weight: 400;\">1<\/span><span style=\"font-weight: 400;\"> + monthly_rate) ** num_payments<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 ) \/ ((<\/span><span style=\"font-weight: 400;\">1<\/span><span style=\"font-weight: 400;\"> + monthly_rate) ** num_payments \u2013 <\/span><span style=\"font-weight: 400;\">1<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">return<\/span><span style=\"font-weight: 400;\"> {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018down_payment\u2019<\/span><span style=\"font-weight: 400;\">: down_payment,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018loan_amount\u2019<\/span><span style=\"font-weight: 400;\">: loan_amount,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018closing_costs\u2019<\/span><span style=\"font-weight: 400;\">: closing_costs,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018total_invested\u2019<\/span><span style=\"font-weight: 400;\">: down_payment + closing_costs,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018monthly_payment\u2019<\/span><span style=\"font-weight: 400;\">: monthly_payment,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018interest_rate\u2019<\/span><span style=\"font-weight: 400;\">: interest_rate,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018loan_term\u2019<\/span><span style=\"font-weight: 400;\">: loan_term,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 }<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3><b>C. How Financing Integrates<\/b><\/h3>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Call <\/span><span style=\"font-weight: 400;\">calculate_financing()<\/span><span style=\"font-weight: 400;\"> with property value and loan terms<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Subtract monthly mortgage payment from NOI to get actual cash flow<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Calculate cash-on-cash return using total cash invested (down payment + closing costs)<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Once the revenue and financing layers are in place, the last step is ensuring the data is statistically reliable. Sample sizes and fallback logic are essential for building models that hold up in real-world products.<\/span><\/p>\n<h2><b>VIII. Data Quality, Sample Size Rules, and Fallback Logic<\/b><\/h2>\n<h3><b>A. Sample-size Thresholds and Why They Matter<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Use explicit, conservative thresholds to decide which geographic resolution is statistically reliable for modeling:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Address-level: require sample_size \u2265 15 (suitable for specific property evaluation when there are at least 15 comparable short-term rental listings).<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Zip-level: require sample_size \u2265 30 (suitable for neighborhood-level analysis; fewer than 30 comps increases variance).<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">City-level: require sample_size \u2265 80 (suitable for market-level analysis and robust medians).<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">When a resolution\u2019s <\/span><span style=\"font-weight: 400;\">sample_size<\/span><span style=\"font-weight: 400;\"> is below its threshold, the model should fall back to the next coarser resolution and display a data-quality warning to users. Using explicit thresholds reduces surprise from noisy medians and improves real-world reliability.<\/span><\/p>\n<h3><b>B. Fallback Logic (Address \u2192 Zip \u2192 City)<\/b><\/h3>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\">Fallback flow (explicit thresholds)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">Address-level (require sample_size \u2265 <\/span><span style=\"font-weight: 400;\">15<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u2193 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> sample_size &lt; <\/span><span style=\"font-weight: 400;\">15<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">Zip-level (require sample_size \u2265 <\/span><span style=\"font-weight: 400;\">30<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u2193 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> sample_size &lt; <\/span><span style=\"font-weight: 400;\">30<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">City-level (require sample_size \u2265 <\/span><span style=\"font-weight: 400;\">80<\/span> <span style=\"font-weight: 400;\">for<\/span><span style=\"font-weight: 400;\"> top confidence; <\/span><span style=\"font-weight: 400;\">return<\/span><span style=\"font-weight: 400;\"> city-level response but surface warning <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> &lt; <\/span><span style=\"font-weight: 400;\">80<\/span><span style=\"font-weight: 400;\">)<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3><b>C. Code: Fallback Function<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">The fallback function implements multi-level resolution to ensure statistical reliability when the address-level sample size is small. Below is a short, readable overview that shows the behavior and thresholds; the complete production-ready implementation follows immediately after.<\/span><\/p>\n<p>\u00a0<\/p>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\"># Fallback overview (full function below)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">def<\/span> <b>validate_and_fetch_data<\/b><span style=\"font-weight: 400;\">(location, api_key):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u201c\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 Behavior (overview):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u2013 Try address-level (if lat\/lng provided) and require sample_size &gt;= 15<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u2013 If below threshold, fall back to zip-level and require sample_size &gt;= 30<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u2013 If below threshold, fall back to city-level and require sample_size &gt;= 80 for highest confidence<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u2013 Returns a tuple: (response_json, \u2018address-level\u2019 | \u2018zip-level\u2019 | \u2018city-level\u2019)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 Note: see full implementation below for logging, parameter sanitation, and exact request shapes.<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u201c\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">pass<\/span><span style=\"font-weight: 400;\">\u00a0 <\/span><span style=\"font-weight: 400;\"># full implementation directly below<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h4><b>Full Implementation\u00a0<\/b><\/h4>\n<p><span style=\"font-weight: 400;\">The full function performs the same steps, with defensive checks and clear logging so the calling code can surface user-facing warnings when data quality is low.<\/span><\/p>\n<p>\u00a0<\/p>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\">def<\/span> <b>validate_and_fetch_data<\/b><span style=\"font-weight: 400;\">(location, api_key):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u201c\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 Fetch data with automatic fallback for low sample sizes.<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 Resolution thresholds (conservative):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u2013 Address-level: require sample_size &gt;= 15<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u2013 Zip-level: \u00a0 \u00a0 require sample_size &gt;= 30<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u2013 City-level:\u00a0 \u00a0 require sample_size &gt;= 80 (top confidence)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 Returns:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 (response_json, resolution_str) where resolution_str is one of<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u2018address-level\u2019, \u2018zip-level\u2019, \u2018city-level\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u201c\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># Address-level first (if coordinates are provided)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018lat\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> location <\/span><span style=\"font-weight: 400;\">and<\/span> <span style=\"font-weight: 400;\">\u2018lng\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> location:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 response = get_market_data(location, api_key)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 content = response.get(<\/span><span style=\"font-weight: 400;\">\u2018content\u2019<\/span><span style=\"font-weight: 400;\">) <\/span><span style=\"font-weight: 400;\">or<\/span><span style=\"font-weight: 400;\"> {}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> content.get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">) &gt;= <\/span><span style=\"font-weight: 400;\">15<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">return<\/span><span style=\"font-weight: 400;\"> response, <\/span><span style=\"font-weight: 400;\">\u2018address-level\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># log fallback intent<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 print(<\/span><span style=\"font-weight: 400;\">f\u201d[data-quality] address comps=<\/span><span style=\"font-weight: 400;\">{content.get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">)}<\/span><span style=\"font-weight: 400;\"> &lt; 15. Falling back to zip-level.\u201d<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># Fall back to zip code level (if provided)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018zip_code\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> location:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 zip_params = {k: v <\/span><span style=\"font-weight: 400;\">for<\/span><span style=\"font-weight: 400;\"> k, v <\/span><span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> location.items() <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> k <\/span><span style=\"font-weight: 400;\">not<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> [<\/span><span style=\"font-weight: 400;\">\u2018address\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">\u2018lat\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">\u2018lng\u2019<\/span><span style=\"font-weight: 400;\">]}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 response = get_market_data(zip_params, api_key)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 content = response.get(<\/span><span style=\"font-weight: 400;\">\u2018content\u2019<\/span><span style=\"font-weight: 400;\">) <\/span><span style=\"font-weight: 400;\">or<\/span><span style=\"font-weight: 400;\"> {}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> content.get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">) &gt;= <\/span><span style=\"font-weight: 400;\">30<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">return<\/span><span style=\"font-weight: 400;\"> response, <\/span><span style=\"font-weight: 400;\">\u2018zip-level\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 print(<\/span><span style=\"font-weight: 400;\">f\u201d[data-quality] zip comps=<\/span><span style=\"font-weight: 400;\">{content.get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">)}<\/span><span style=\"font-weight: 400;\"> &lt; 30. Falling back to city-level.\u201d<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># Final fallback: city level (state + city required)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 city_params = {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018state\u2019<\/span><span style=\"font-weight: 400;\">: location.get(<\/span><span style=\"font-weight: 400;\">\u2018state\u2019<\/span><span style=\"font-weight: 400;\">),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018city\u2019<\/span><span style=\"font-weight: 400;\">: location.get(<\/span><span style=\"font-weight: 400;\">\u2018city\u2019<\/span><span style=\"font-weight: 400;\">),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018beds\u2019<\/span><span style=\"font-weight: 400;\">: location.get(<\/span><span style=\"font-weight: 400;\">\u2018beds\u2019<\/span><span style=\"font-weight: 400;\">),<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018resource\u2019<\/span><span style=\"font-weight: 400;\">: location.get(<\/span><span style=\"font-weight: 400;\">\u2018resource\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">\u2018airbnb\u2019<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 }<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 response = get_market_data(city_params, api_key)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 content = response.get(<\/span><span style=\"font-weight: 400;\">\u2018content\u2019<\/span><span style=\"font-weight: 400;\">) <\/span><span style=\"font-weight: 400;\">or<\/span><span style=\"font-weight: 400;\"> {}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># Return city-level response in all cases, but callers\/UI should surface a warning<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># if sample_size &lt; 80 (city-level is less reliable below this threshold).<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> content.get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">) &lt; <\/span><span style=\"font-weight: 400;\">80<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 print(<\/span><span style=\"font-weight: 400;\">f\u201d[data-quality] city comps=<\/span><span style=\"font-weight: 400;\">{content.get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">)}<\/span><span style=\"font-weight: 400;\"> &lt; 80. Display low-confidence warning to user.\u201d<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">return<\/span><span style=\"font-weight: 400;\"> response, <\/span><span style=\"font-weight: 400;\">\u2018city-level\u2019<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3><b>D. When to Display Warnings<\/b><\/h3>\n<p><span style=\"font-weight: 400;\">Warnings should be tied directly to the sample-size quality classification:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>very_low (sample_size &lt; 15):<\/b><b><br \/><\/b><span style=\"font-weight: 400;\"> Show a <\/span><i><span style=\"font-weight: 400;\">strong<\/span><\/i><span style=\"font-weight: 400;\"> warning \u2014 address-level data is statistically unreliable.<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> Encourage falling back to ZIP or city level.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>low (15 \u2264 sample_size &lt; 30):<\/b><b><br \/><\/b><span style=\"font-weight: 400;\"> Show a warning \u2014 ZIP-level data has too few comps for stable medians.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>medium (30 \u2264 sample_size &lt; 80):<\/b><b><br \/><\/b><span style=\"font-weight: 400;\"> Show a <\/span><i><span style=\"font-weight: 400;\">soft<\/span><\/i><span style=\"font-weight: 400;\"> warning \u2014 city-level medians are usable but should be presented with a confidence disclaimer.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>high (sample_size \u2265 80):<\/b><b><br \/><\/b><span style=\"font-weight: 400;\"> No warning needed \u2014 data is statistically robust at city level.<\/span><\/li>\n<\/ul>\n<p><b>Pro tip:<\/b><span style=\"font-weight: 400;\"> always display a visual warning (icon or banner) when quality is <\/span><span style=\"font-weight: 400;\">very_low<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">low<\/span><span style=\"font-weight: 400;\">, or <\/span><span style=\"font-weight: 400;\">medium<\/span><span style=\"font-weight: 400;\">, and only suppress warnings at the <\/span><span style=\"font-weight: 400;\">high<\/span><span style=\"font-weight: 400;\"> level.<\/span><\/p>\n<h2><b>IX. Final Output Formatting<\/b><\/h2>\n<h3><b>A. Code: format_revenue_summary()<\/b><\/h3>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\">def<\/span> <b>format_revenue_summary<\/b><span style=\"font-weight: 400;\">(model):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u201c\u201d\u201dCreate readable summary of revenue model\u201d\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 price_to_rent = model[<\/span><span style=\"font-weight: 400;\">\u2018metadata\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018price_to_rent_ratio\u2019<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 regulations = model[<\/span><span style=\"font-weight: 400;\">\u2018metadata\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018regulations\u2019<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># \u2014 NEW: compute sample-size quality label (use model label if present) \u2014<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 sample_size = model[<\/span><span style=\"font-weight: 400;\">\u2018metadata\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018sample_size\u2019<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 quality = model[<\/span><span style=\"font-weight: 400;\">\u2018metadata\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018data_quality\u2019<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">not<\/span><span style=\"font-weight: 400;\"> quality:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> sample_size <\/span><span style=\"font-weight: 400;\">is<\/span> <span style=\"font-weight: 400;\">None<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 quality = <\/span><span style=\"font-weight: 400;\">\u2018unknown\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">else<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">try<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 _s = int(sample_size)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">except<\/span><span style=\"font-weight: 400;\"> (TypeError, ValueError):<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 quality = <\/span><span style=\"font-weight: 400;\">\u2018unknown\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">else<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> _s &gt;= <\/span><span style=\"font-weight: 400;\">80<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 quality = <\/span><span style=\"font-weight: 400;\">\u2018high\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">elif<\/span><span style=\"font-weight: 400;\"> _s &gt;= <\/span><span style=\"font-weight: 400;\">30<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 quality = <\/span><span style=\"font-weight: 400;\">\u2018medium\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">elif<\/span><span style=\"font-weight: 400;\"> _s &gt;= <\/span><span style=\"font-weight: 400;\">15<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 quality = <\/span><span style=\"font-weight: 400;\">\u2018low\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">else<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 quality = <\/span><span style=\"font-weight: 400;\">\u2018very_low\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># \u2014 NEW: prepare explicit warning text based on quality \u2014<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 warning_lines = []<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> quality == <\/span><span style=\"font-weight: 400;\">\u2018very_low\u2019<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 warning_lines.append(<\/span><span style=\"font-weight: 400;\">\u201d \u00a0 \u26a0\ufe0f Data quality: VERY LOW \u2014 insufficient comps at this resolution. Consider a coarser geographic level.\u201d<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">elif<\/span><span style=\"font-weight: 400;\"> quality == <\/span><span style=\"font-weight: 400;\">\u2018low\u2019<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 warning_lines.append(<\/span><span style=\"font-weight: 400;\">\u201d \u00a0 \u26a0\ufe0f Data quality: LOW \u2014 medians may be unstable; use caution or fall back to zip\/city analysis.\u201d<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">elif<\/span><span style=\"font-weight: 400;\"> quality == <\/span><span style=\"font-weight: 400;\">\u2018medium\u2019<\/span><span style=\"font-weight: 400;\">:<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 \u00a0 \u00a0 warning_lines.append(<\/span><span style=\"font-weight: 400;\">\u201d \u00a0 \u2139\ufe0f Data quality: MEDIUM \u2014 directional insights only; consider additional validation.\u201d<\/span><span style=\"font-weight: 400;\">)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># \u2018high\u2019 -&gt; no warning line<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\"># \u2014 ORIGINAL FSTRING (with minimal edits to inject quality + warnings) \u2014<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">return<\/span> <span style=\"font-weight: 400;\">f\u201d\u201d\u201d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u2554\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2557<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u2551\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 AIRBNB REVENUE MODEL \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u2551<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u255a\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u2550\u255d<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\ud83d\udccd PROPERTY<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Location: <\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018property\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018location\u2019<\/span><span style=\"font-weight: 400;\">]}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Market ID: <\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018property\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018market_id\u2019<\/span><span style=\"font-weight: 400;\">]}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Median Value: $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018property\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018median_value\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\ud83d\udcb0 REVENUE PROJECTIONS<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Monthly Income:\u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018revenue\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018monthly_income\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Annual Income: \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018revenue\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018annual_income\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Nightly Rate:\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018revenue\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018nightly_rate\u2019<\/span><span style=\"font-weight: 400;\">]:<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Occupancy Rate:\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018revenue\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018occupancy_rate\u2019<\/span><span style=\"font-weight: 400;\">]}<\/span><span style=\"font-weight: 400;\">%<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 RevPAR:\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018revenue\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018revpar\u2019<\/span><span style=\"font-weight: 400;\">]:<\/span><span style=\"font-weight: 400;\">.2<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Guest Capacity:\u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018revenue\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018guest_capacity\u2019<\/span><span style=\"font-weight: 400;\">]}<\/span><span style=\"font-weight: 400;\"> guests<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\ud83d\udcb8 MONTHLY EXPENSES<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Total: \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018monthly_total\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 \u251c\u2500 Property Tax: \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018property_tax\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 \u251c\u2500 Management: \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018management\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 \u251c\u2500 Maintenance:\u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018maintenance\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 \u251c\u2500 Insurance:\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018insurance\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 \u251c\u2500 Utilities:\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018utilities\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 \u251c\u2500 HOA Dues: \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018hoa_dues\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 \u2514\u2500 Cleaning: \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018expenses\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018cleaning\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018\ud83c\udfe6 FINANCING\u2019<\/span> <span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018 \u00a0 Down Payment ({}%):\u00a0 \u00a0 ${:,.0f}\u2019<\/span><span style=\"font-weight: 400;\">.format(<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 model[<\/span><span style=\"font-weight: 400;\">\u2018financing\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018down_payment\u2019<\/span><span style=\"font-weight: 400;\">] \/ model[<\/span><span style=\"font-weight: 400;\">\u2018property\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018median_value\u2019<\/span><span style=\"font-weight: 400;\">] * <\/span><span style=\"font-weight: 400;\">100<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 model[<\/span><span style=\"font-weight: 400;\">\u2018financing\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018down_payment\u2019<\/span><span style=\"font-weight: 400;\">]<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">) <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018 \u00a0 Loan Amount: \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 ${:,.0f}\u2019<\/span><span style=\"font-weight: 400;\">.format(model[<\/span><span style=\"font-weight: 400;\">\u2018financing\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018loan_amount\u2019<\/span><span style=\"font-weight: 400;\">]) <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018 \u00a0 Monthly Mortgage:\u00a0 \u00a0 \u00a0 ${:,.0f}\u2019<\/span><span style=\"font-weight: 400;\">.format(model[<\/span><span style=\"font-weight: 400;\">\u2018financing\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018monthly_payment\u2019<\/span><span style=\"font-weight: 400;\">]) <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018 \u00a0 Interest Rate: \u00a0 \u00a0 \u00a0 \u00a0 {}%\u2019<\/span><span style=\"font-weight: 400;\">.format(model[<\/span><span style=\"font-weight: 400;\">\u2018financing\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018interest_rate\u2019<\/span><span style=\"font-weight: 400;\">]) <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\ud83d\udcca PROFITABILITY<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Monthly NOI: \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 $<\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018monthly_noi\u2019<\/span><span style=\"font-weight: 400;\">]:,<\/span><span style=\"font-weight: 400;\">.0<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018 \u00a0 Monthly Cash Flow: \u00a0 \u00a0 ${:,.0f}\u2019<\/span><span style=\"font-weight: 400;\">.format(model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018monthly_cash_flow\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">)) <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018 \u00a0 Annual Cash Flow:\u00a0 \u00a0 \u00a0 ${:,.0f}\u2019<\/span><span style=\"font-weight: 400;\">.format(model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018annual_cash_flow\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">)) <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Cap Rate:\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018cap_rate\u2019<\/span><span style=\"font-weight: 400;\">]}<\/span><span style=\"font-weight: 400;\">%<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018 \u00a0 Cash-on-Cash Return: \u00a0 {:.1f}%\u2019<\/span><span style=\"font-weight: 400;\">.format(model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018cash_on_cash_return\u2019<\/span><span style=\"font-weight: 400;\">, <\/span><span style=\"font-weight: 400;\">0<\/span><span style=\"font-weight: 400;\">)) <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">\u2018 \u00a0 Break-Even Timeline: \u00a0 {} months\u2019<\/span><span style=\"font-weight: 400;\">.format(int(model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">][<\/span><span style=\"font-weight: 400;\">\u2018break_even_months\u2019<\/span><span style=\"font-weight: 400;\">])) <\/span><span style=\"font-weight: 400;\">if<\/span> <span style=\"font-weight: 400;\">\u2018financing\u2019<\/span> <span style=\"font-weight: 400;\">in<\/span><span style=\"font-weight: 400;\"> model <\/span><span style=\"font-weight: 400;\">and<\/span><span style=\"font-weight: 400;\"> model[<\/span><span style=\"font-weight: 400;\">\u2018profitability\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018break_even_months\u2019<\/span><span style=\"font-weight: 400;\">) <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\ud83d\udcc8 DATA QUALITY<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Sample Size: \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">{sample_size}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Data Quality:\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">{quality.title() <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> isinstance(quality, str) <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u2018N\/A\u2019<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> \u00a0 Price-to-Rent Ratio: \u00a0 <\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">f\u201d<\/span><span style=\"font-weight: 400;\">{price_to_rent:<\/span><span style=\"font-weight: 400;\">.1<\/span><span style=\"font-weight: 400;\">f}<\/span><span style=\"font-weight: 400;\">\u201c<\/span> <span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> price_to_rent <\/span><span style=\"font-weight: 400;\">is<\/span> <span style=\"font-weight: 400;\">not<\/span> <span style=\"font-weight: 400;\">None<\/span> <span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201cN\/A\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{<\/span><span style=\"font-weight: 400;\">f\u201d \u00a0 \u26a0\ufe0f\u00a0 Regulatory Note:\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">{regulations}<\/span><span style=\"font-weight: 400;\">\u201c<\/span> <span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> regulations <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201c\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">{(<\/span><span style=\"font-weight: 400;\">\u2018\\\\n\u2019<\/span><span style=\"font-weight: 400;\">.join(warning_lines) + <\/span><span style=\"font-weight: 400;\">\u2018\\\\n\u2019<\/span><span style=\"font-weight: 400;\">) <\/span><span style=\"font-weight: 400;\">if<\/span><span style=\"font-weight: 400;\"> warning_lines <\/span><span style=\"font-weight: 400;\">else<\/span> <span style=\"font-weight: 400;\">\u201d<\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">Generated: <\/span><span style=\"font-weight: 400;\">{model[<\/span><span style=\"font-weight: 400;\">\u2018metadata\u2019<\/span><span style=\"font-weight: 400;\">].get(<\/span><span style=\"font-weight: 400;\">\u2018analysis_date\u2019<\/span><span style=\"font-weight: 400;\">)}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">Data Source: Mashvisor API<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u201c\u201d\u201d<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3><b>B. Complete Usage Example<\/b><\/h3>\n<table>\n<tbody>\n<tr>\n<td><span style=\"font-weight: 400;\"># Define location and financing parameters<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">location = {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018state\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">\u2018TX\u2019<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018city\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">\u2018Austin\u2019<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018zip_code\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">\u201878701\u2019<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018beds\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">2<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018baths\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">2<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018resource\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">\u2018airbnb\u2019<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">financing = {<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018down_payment_pct\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">25<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018interest_rate\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">6.5<\/span><span style=\"font-weight: 400;\">,<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">\u00a0 \u00a0 <\/span><span style=\"font-weight: 400;\">\u2018loan_term\u2019<\/span><span style=\"font-weight: 400;\">: <\/span><span style=\"font-weight: 400;\">30<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">}<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"># Get data from Mashvisor lookup endpoint<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">api_response = get_market_data(location)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"># Build revenue model from lookup response + financing layer<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">revenue_model = build_revenue_model(api_response, financing)<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"># Display formatted model<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\">print(format_revenue_summary(revenue_model))<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h3><b>C. Model Flow<\/b><\/h3>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-328112 size-large\" src=\"https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-4-683x1024.webp\" alt=\"revenue model flow\" width=\"683\" height=\"1024\" srcset=\"https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-4-683x1024.webp 683w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-4-200x300.webp 200w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-4-768x1152.webp 768w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-4-585x878.webp 585w, https:\/\/www.mashvisor.com\/blog\/wp-content\/uploads\/2025\/12\/unnamed-4.webp 1024w\" sizes=\"auto, (max-width: 683px) 100vw, 683px\"\/><\/p>\n<h2><b>X.How Mashvisor Lookup API Compares to Zillow &amp; AirDna<\/b><\/h2>\n<p><b>AirDNA:<\/b><b><br \/><\/b><span style=\"font-weight: 400;\">AirDna provides strong top-level market analytics but does not return property-level financial metrics (NOI, cash flow, expenses, cash-on-cash) in a single API call. Developers must combine multiple datasets and calculate profitability manually.<\/span><\/p>\n<p><b>Zillow:<\/b><b><br \/><\/b><span style=\"font-weight: 400;\">Zillow offers property data and rental estimates but does not provide short-term rental income, occupancy rates, RevPAR, or Airbnb-specific expenses. It is not designed for STR financial modeling.<\/span><\/p>\n<p><b>Mashvisor Lookup:<\/b><b><br \/><\/b><span style=\"font-weight: 400;\">Unlike both, Lookup returns <\/span><i><span style=\"font-weight: 400;\">complete, pre-modeled Airbnb financials<\/span><\/i><span style=\"font-weight: 400;\"> \u2014 revenue, occupancy, itemized expenses, profitability metrics, RevPAR, and data-quality flags \u2014 ready for direct use in production applications.<\/span><\/p>\n<h2><b>Conclusion: Mashvisor Lookup API Is the Fastest Path to a Production-Ready Airbnb Model<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">The <\/span><a href=\"https:\/\/www.mashvisor.com\/blog\/best-airbnb-data-api\/\" data-wpel-link=\"internal\"><span style=\"font-weight: 400;\">Mashvisor API <\/span><\/a><span style=\"font-weight: 400;\">provides everything needed to build reliable Airbnb revenue models:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Complete financial data<\/b><span style=\"font-weight: 400;\"> in a single API call \u2014 no scraping, no data cleaning<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Pre-calculated metrics<\/b><span style=\"font-weight: 400;\"> including NOI, cap rate, and cash-on-cash return<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Nationwide coverage<\/b><span style=\"font-weight: 400;\"> across all 50 US states plus select international markets<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Quality indicators<\/b><span style=\"font-weight: 400;\"> via sample sizes and fallback logic for reliable projections<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><b>Production-ready<\/b><span style=\"font-weight: 400;\"> within hours, not months of custom development<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Build models that use API data directly, handle low sample sizes gracefully, display quality indicators prominently, calculate financing impact accurately, and present results in actionable formats.<\/span><\/p>\n<p><a href=\"https:\/\/www.mashvisor.com\/data-api\" data-wpel-link=\"external\" rel=\"external noopener noreferrer\"><b>Start using the Mashvisor AP<\/b><span style=\"font-weight: 400;\">I<\/span><\/a><span style=\"font-weight: 400;\"> today with a <\/span><b>1-week free trial<\/b><span style=\"font-weight: 400;\"> that includes <\/span><b>30 credits<\/b><span style=\"font-weight: 400;\"> for real market queries.<\/span><\/p>\n<\/p><\/div>\n\n","protected":false},"excerpt":{"rendered":"<p>The Mashvisor Lookup API solves the biggest pain in Airbnb revenue modeling: dirty rental data, unreliable scrapers, and inconsistent revenue calculations. As a real estate data API, it returns complete, pre-modeled financial metrics in a single call. No scraping, no manual calculations, no custom data cleaning. Developers can build a full revenue model quickly using [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":331379,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[157296,157297,157298,157299,98882,96,157295],"tags":[19396,13966,41975,139492,1168,3461],"dealstore":[],"offerexpiration":[],"class_list":["post-331378","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-airbnb-analysis","category-airbnb-analytics","category-airbnb-api","category-airbnb-data","category-guides","category-investing","category-real-estate-api-data-solutions","tag-airbnb","tag-api","tag-lookup","tag-mashvisor","tag-model","tag-revenue"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.4 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Airbnb Revenue Model Using Mashvisor Lookup API - Som2ny Network<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fivemor.com\/?p=331378\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Airbnb Revenue Model Using Mashvisor Lookup API - Som2ny Network\" \/>\n<meta property=\"og:description\" content=\"The Mashvisor Lookup API solves the biggest pain in Airbnb revenue modeling: dirty rental data, unreliable scrapers, and inconsistent revenue calculations. 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