feat: add 'coming soon' empty state for projects page & gitignore public dir

- Add animated coming-soon card when no projects exist
- Add Grafana shortcode and gebrauchtwagen-datenbank project
- Add hugo/eliaskohout.de/public/ to .gitignore and remove from tracking

hugo/eliaskohout.de/content/projects/gebrauchtwagen-datenbank.md

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+---
+title: "2 Million Used Cars and What They Tell Us"
+draft: true
+date: 2026-02-12
+tags: ["Scraping", "Data Engineering", "Grafana", "PostgreSQL"]
+summary: "Scraping ~2M used car listings, throwing them into a database, and seeing what shakes out."
+code: ""
+demo: ""
+---
+
+## The Question
+
+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?
+
+Time to find out with data instead of hearsay.
+
+## The Approach
+
+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.
+
+The haul: roughly **2 million listings** from early 2026, downloaded as JSON and
+loaded into a PostgreSQL database. At that point, the recommendation graph
+stopped surfacing new entries — a second pass would likely uncover more, since
+new listings appear daily. But 2M felt like a solid starting point.
+
+## The Data
+
+**2,046,879 listings**, most of them containing the following fields (among others):
+
+`make` · `model` · `model_variant` · `fuel` · `price` · `mileage` · `power_kw` ·
+`transmission_type` · `number_of_cylinders` · `body_type` · `body_color` ·
+`first_registration_date` · `number_of_previous_owners` · `is_roadworthy` ·
+`is_currently_damaged` · `usage_state` · `type` · `zip_code` · `country_code` ·
+`city`
+
+That's enough to get interesting.
+
+About 119,500 listings were missing either price or mileage — not entirely clear
+why, but with nearly 2 million records left, it's barely a dent.
+
+---
+
+## Findings
+
+### Price vs. Mileage
+
+The obvious place to start: how does price relate to mileage?
+
+<!-- dashboard on price vs mileage; scatter plot; clipped for 1,000,000 € and 1,000,000 km -->
+{{< grafana url="https://gr.eliaskohout.de/public-dashboards/0852019305114cd189aedb67dea27721" height="450" >}}
+
+Two hot spots jump out immediately. One in the low-mileage/high-price corner,
+one in the high-mileage/low-price corner — exactly what you'd expect. Expensive
+special cars that barely leave the garage, and daily drivers with six-figure
+odometers priced to move.
+
+The vast majority of listings, though, cluster in relatively low-price and
+low-mileage territory compared to the extremes.
+
+**A note on clipping.** The plot caps at €1,000,000 and 1,000,000 km because the
+*tails get absurd. The highest listed price was €999,999,999 — obviously not
+*real. Six listings exceeded €10 million, none of them serious. A handful
+*between €1M and €10M could be genuine exotics. On the mileage side, the maximum
+*was 100,000,000 km. The highest plausible reading I found was an Iveco truck at
+*897,000 km on the odometer. The roughly 570 listings beyond that appeared to be
+*typos or placeholder values for "mileage unknown."
+
+Across the cleaned dataset, averages land at roughly **€28,400** for price and
+**75,600 km** for mileage. The standard deviations are enormous — €731k and 109k
+km respectively — which tells you just how wide the spread really is.
+
+That gives an overall average ratio of about **€375 per 1,000 km**. In other
+words: for each 1,000 km on the odometer, the average listing costs about €375.
+This isn't a depreciation rate in the strict sense — we're looking at a
+cross-sectional snapshot of listed prices, not tracking individual cars losing
+value over time. But it turns out to be a useful back-of-the-napkin metric for
+comparing brands.
+
+### By Brand
+
+The dataset contains **346 distinct makes**. Of those, 72 (~21%) have more than
+500 listings — enough for halfway meaningful statistics. The rest are too sparse
+to generalize from, so brand-level analysis focuses on these 72.
+
+{{/* dashboard on price per mileage; table with make and euro/km; ordered by price per mileage */}}
+{{< grafana url="https://gr.eliaskohout.de/public-dashboards/1777bb018e9b47639b93ef31d97f9c89" height="450" >}}
+
+The ranking roughly mirrors the common perception of luxury brands — makes with
+a reputation for being expensive also tend to show up with high price-per-km
+values. No surprises there.
+
+But this metric has a blind spot: **age**. Brands with almost no older cars on
+the market look disproportionately expensive per km, simply because their
+listings haven't had time to depreciate. BYD, for example, ranks just below
+Ferrari and Rolls-Royce — not because a BYD is a luxury vehicle, but because the
+average BYD listing is only **0.7 years** old, compared to the overall average
+of **6.7 years**. Leapmotor is even more extreme at **0.5 years**. Give these
+brands a few years to accumulate used inventory at higher mileages, and their
+ratios will settle down considerably.
+
+### Depreciation Curves
+
+You'd expect the price-per-km ratio to fall as mileage increases — older,
+high-mileage cars are cheaper, and the new-car premium fades fast. You'd also
+expect the decline to be roughly exponential: a car loses a percentage of its
+current value per additional kilometer, not a fixed euro amount.
+
+Both hold up in the data:
+
+{{/* dashboard on price vs mileage and price/km vs mileage */}}
+{{< grafana url="https://gr.eliaskohout.de/public-dashboards/e999ce3c237b4cae95b3331331a26261" height="400" >}}
+
+The curves above show average prices over mileage for BMW, Volkswagen, and Fiat.
+The brand-level differences are immediately visible — different starting points,
+different values throughout the decay — but the overall shape is the same: steep
+early depreciation that gradually flattens out.
+
+
+* nur zum ende hin verschwimmen die Grenzen, 200k km kann hier als grobe grenze gesehen werden, ab der die daten etwas chaotischer werden
+* das könnte auch daran liegen, dass es hier einfach weniger datenpunkte gibt und damit die durchschnittbrechnung schlechter wird
+
+* also lass uns genauer auf die verteilungen an diesem Ende der skala schauen
+
+
+### The Survivors: Cars Beyond 250k km
+
+
+
+
+{{/*
+  ==============================================
+  PLAN: Analysis chapters to write
+  ==============================================
+
+  1. Price vs. Mileage Relationship
+     - Scatter/heatmap of price vs. mileage across all listings
+     - Depreciation curves: how fast do different makes lose value?
+     - The "sweet spot": best mileage-to-price ratio by model
+
+  2. The Survivors: Cars Beyond 300k km
+     - Which makes/models appear most often at extreme mileage?
+     - Fuel type breakdown (diesel vs. petrol at high mileage)
+     - Average price of high-mileage cars — are they dirt cheap or still holding value?
+
+     + ausfallrate abschätzen
+
+  4. Fuel & Drivetrain Trends
+     - Fuel type distribution (diesel/petrol/electric/hybrid/LPG)
+     - Price and mileage by fuel type
+     - Are EVs showing up in used markets yet? At what price?
+
+  5. Geography
+     - Listings by country and region (zip code clusters)
+     - Regional price differences for the same model
+     - Where are the cheap cars?
+
+  ==============================================
+*/}}
+