What these datasets are
Every dataset on this site is real, structured data, not a mockup. I pull listings from a source site, clean the fields, load them into Postgres, and put a working dashboard on top so you can filter, sort, and chart it the way you would in a spreadsheet, only faster. Each one gets its own dashboard: maps, charts, filters, and a sortable table, tailored to whatever fields that source actually has.
I built this specific demo to show what a scraped dataset looks like once it's actually usable, not just a CSV sitting in a folder.
How I build them
The pipeline behind a dataset like this has three parts, and I build all three:
Datasets
Four are available today. More ship over time — this grid is built to grow, so every new dataset just shows up here as its own card.
Price, beds, baths, sqft, location, and days-on-market across nationwide listings, with a map, charts, and a 3D price explorer on top.
Explore datasetListings with brokerage, media, price-cut history and county codes — plus a coverage page that measures the scrape against realtor.com’s own published totals, and a CSV/JSON download of the real rows.
Explore datasetEvery listing carries Zillow’s own Zestimate and rent estimate, so this one is built around the gaps: what sellers ask versus what the platform thinks a home is worth, and what each listing would return as a rental.
Explore datasetThree point-in-time scrapes of the same marketplace, so this one is built around change: which listings raised their nightly rate, which gained reviews — the nearest thing to evidence a stay actually happened — and which quietly disappeared between crawls.
Explore datasetI haven't picked the source yet. Tell me what you'd want scraped and it could be the next one to ship here.
What you get when you hire me
A finished project includes the scraper or automation source code, the cleaned data in whichever format you asked for, and a short handover call or write-up on how to run and schedule it. If you want a dashboard on top, like this one, I scope that separately once I know what questions you're trying to answer with the data. The starting point is always a free scope and quote, so you know the shape of the work before committing to it.
Frequently asked questions
Will a scraper work on my site?
Almost always, unless the target renders through a login wall a bot can’t pass or blocks every known automation fingerprint. I check the site’s structure and anti-bot setup before quoting, so you know the answer before paying for anything.
Do you need my login to build this?
Only if the data sits behind one. For public listing pages like the datasets shown here, no credentials are needed at all — the bot reads what any visitor can see.
What happens when the target site changes its layout?
Scrapers built on CSS selectors break when a site redesigns. I write mine against stable structural anchors where possible and hand over the source, so a broken selector is a five-minute fix, not a rebuild.
Can I run the scraper myself after delivery?
Yes. You get the full source — Python & Playwright script, or a UI.Vision/Automa recipe if we go no-code — plus setup notes, so it runs on your machine or a scheduled server with no ongoing dependency on me.
Is scraping a site like Redfin legal?
I can’t answer that for your specific case. I build the technical pipeline; whether you scrape a given site, and how you use the data, is governed by that site’s terms of service and robots.txt — that decision and its risk sit with you.
How long does a project like this take?
A single-site scraper with cleaned CSV or Postgres output usually ships in a few days. A dashboard like the ones you can explore here — map, charts, filters, scheduled refresh — runs longer depending on how many data sources feed it.
Have a site you need turned into structured data? I'll scope it for free before you commit to anything.
Request a free scope and quote