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160 lines
7.1 KiB
Markdown
160 lines
7.1 KiB
Markdown
---
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title: "2 Million Used Cars and What They Tell Us"
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draft: true
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date: 2026-02-12
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tags: ["Scraping", "Data Engineering", "Grafana", "PostgreSQL"]
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summary: "Scraping ~2M used car listings, throwing them into a database, and seeing what shakes out."
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code: ""
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demo: ""
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---
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## The Question
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Everyone's heard the legend: a VW Passat that just keeps going at 400,000 km. But is it actually the only car that pulls that off? What other models quietly rack up absurd mileage — and what do they cost? In short: what makes a car *last*, and can you get one without overpaying?
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Time to find out with data instead of hearsay.
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## The Approach
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A major used car platform turned out to be surprisingly cooperative when it came to structured data. Their recommendation engine helpfully links to similar listings — so starting from a search, you can just keep crawling through related results.
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The haul: roughly **2 million listings** from early 2026, downloaded as JSON and
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loaded into a PostgreSQL database. At that point, the recommendation graph
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stopped surfacing new entries — a second pass would likely uncover more, since
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new listings appear daily. But 2M felt like a solid starting point.
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## The Data
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**2,046,879 listings**, most of them containing the following fields (among others):
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`make` · `model` · `model_variant` · `fuel` · `price` · `mileage` · `power_kw` ·
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`transmission_type` · `number_of_cylinders` · `body_type` · `body_color` ·
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`first_registration_date` · `number_of_previous_owners` · `is_roadworthy` ·
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`is_currently_damaged` · `usage_state` · `type` · `zip_code` · `country_code` ·
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`city`
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That's enough to get interesting.
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About 119,500 listings were missing either price or mileage — not entirely clear
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why, but with nearly 2 million records left, it's barely a dent.
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---
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## Findings
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### Price vs. Mileage
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The obvious place to start: how does price relate to mileage?
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<!-- dashboard on price vs mileage; scatter plot; clipped for 1,000,000 € and 1,000,000 km -->
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{{< grafana url="https://gr.eliaskohout.de/public-dashboards/0852019305114cd189aedb67dea27721" height="450" >}}
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Two hot spots jump out immediately. One in the low-mileage/high-price corner,
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one in the high-mileage/low-price corner — exactly what you'd expect. Expensive
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special cars that barely leave the garage, and daily drivers with six-figure
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odometers priced to move.
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The vast majority of listings, though, cluster in relatively low-price and
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low-mileage territory compared to the extremes.
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**A note on clipping.** The plot caps at €1,000,000 and 1,000,000 km because the
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*tails get absurd. The highest listed price was €999,999,999 — obviously not
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*real. Six listings exceeded €10 million, none of them serious. A handful
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*between €1M and €10M could be genuine exotics. On the mileage side, the maximum
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*was 100,000,000 km. The highest plausible reading I found was an Iveco truck at
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*897,000 km on the odometer. The roughly 570 listings beyond that appeared to be
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*typos or placeholder values for "mileage unknown."
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Across the cleaned dataset, averages land at roughly **€28,400** for price and
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**75,600 km** for mileage. The standard deviations are enormous — €731k and 109k
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km respectively — which tells you just how wide the spread really is.
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That gives an overall average ratio of about **€375 per 1,000 km**. In other
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words: for each 1,000 km on the odometer, the average listing costs about €375.
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This isn't a depreciation rate in the strict sense — we're looking at a
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cross-sectional snapshot of listed prices, not tracking individual cars losing
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value over time. But it turns out to be a useful back-of-the-napkin metric for
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comparing brands.
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### By Brand
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The dataset contains **346 distinct makes**. Of those, 72 (~21%) have more than
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500 listings — enough for halfway meaningful statistics. The rest are too sparse
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to generalize from, so brand-level analysis focuses on these 72.
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{{/* dashboard on price per mileage; table with make and euro/km; ordered by price per mileage */}}
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{{< grafana url="https://gr.eliaskohout.de/public-dashboards/1777bb018e9b47639b93ef31d97f9c89" height="450" >}}
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The ranking roughly mirrors the common perception of luxury brands — makes with
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a reputation for being expensive also tend to show up with high price-per-km
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values. No surprises there.
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But this metric has a blind spot: **age**. Brands with almost no older cars on
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the market look disproportionately expensive per km, simply because their
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listings haven't had time to depreciate. BYD, for example, ranks just below
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Ferrari and Rolls-Royce — not because a BYD is a luxury vehicle, but because the
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average BYD listing is only **0.7 years** old, compared to the overall average
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of **6.7 years**. Leapmotor is even more extreme at **0.5 years**. Give these
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brands a few years to accumulate used inventory at higher mileages, and their
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ratios will settle down considerably.
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### Depreciation Curves
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You'd expect the price-per-km ratio to fall as mileage increases — older,
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high-mileage cars are cheaper, and the new-car premium fades fast. You'd also
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expect the decline to be roughly exponential: a car loses a percentage of its
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current value per additional kilometer, not a fixed euro amount.
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Both hold up in the data:
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{{/* dashboard on price vs mileage and price/km vs mileage */}}
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{{< grafana url="https://gr.eliaskohout.de/public-dashboards/e999ce3c237b4cae95b3331331a26261" height="400" >}}
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The curves above show average prices over mileage for BMW, Volkswagen, and Fiat.
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The brand-level differences are immediately visible — different starting points,
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different values throughout the decay — but the overall shape is the same: steep
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early depreciation that gradually flattens out.
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* nur zum ende hin verschwimmen die Grenzen, 200k km kann hier als grobe grenze gesehen werden, ab der die daten etwas chaotischer werden
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* das könnte auch daran liegen, dass es hier einfach weniger datenpunkte gibt und damit die durchschnittbrechnung schlechter wird
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* also lass uns genauer auf die verteilungen an diesem Ende der skala schauen
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### The Survivors: Cars Beyond 250k km
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{{/*
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==============================================
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PLAN: Analysis chapters to write
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==============================================
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1. Price vs. Mileage Relationship
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- Scatter/heatmap of price vs. mileage across all listings
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- Depreciation curves: how fast do different makes lose value?
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- The "sweet spot": best mileage-to-price ratio by model
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2. The Survivors: Cars Beyond 300k km
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- Which makes/models appear most often at extreme mileage?
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- Fuel type breakdown (diesel vs. petrol at high mileage)
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- Average price of high-mileage cars — are they dirt cheap or still holding value?
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+ ausfallrate abschätzen
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4. Fuel & Drivetrain Trends
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- Fuel type distribution (diesel/petrol/electric/hybrid/LPG)
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- Price and mileage by fuel type
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- Are EVs showing up in used markets yet? At what price?
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5. Geography
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- Listings by country and region (zip code clusters)
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- Regional price differences for the same model
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- Where are the cheap cars?
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==============================================
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*/}}
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