An investment dashboard consolidates multiple data dimensions — market health, yield potential, and affordability — into a single view. Here's how to build one using ZipMarketData's three core endpoints.

Data Architecture

The dashboard needs three parallel API calls for a given ZIP code:

  1. GET /market-stats?zip_code=X — price, DOM, temperature
  2. GET /rental-yield?zip_code=X&bedrooms=2 — yield, rent, cap rate
  3. GET /property-estimate?zip_code=X — full investment projection

Parallel Fetch in Python

import asyncio, httpx async def fetch_all(zip_code: str, key: str): headers = {"x-rapidapi-proxy-secret": key} base = "https://zipmarketdata.com" async with httpx.AsyncClient() as c: stats, yield_, est = await asyncio.gather( c.get(f"{base}/market-stats", params={"zip_code": zip_code}, headers=headers), c.get(f"{base}/rental-yield", params={"zip_code": zip_code, "bedrooms": 2}, headers=headers), c.get(f"{base}/property-estimate", params={"zip_code": zip_code}, headers=headers), ) return { "market": stats.json(), "rental": yield_.json(), "investment": est.json() }

Scoring Logic

Combine the three data sources into a composite investment score: 40% weight on gross yield, 30% on YoY price trend, 20% on market temperature, 10% on DOM relative to metro average. Normalise each component to 0–100 and compute weighted average for a single actionable score per ZIP.