style: redesign article page layout and typography

refactor: rewrite used car article, remove LLM confidence chat draft
2026-02-18 04:21:17 +01:00 · 2026-02-18 04:20:53 +01:00
5 changed files with 412 additions and 219 deletions
--- a/hugo/eliaskohout.de/assets/css/style.css
+++ b/hugo/eliaskohout.de/assets/css/style.css
@@ -100,7 +100,7 @@ svg {
 .page-content {
  position: relative;
  z-index: 1;
-  max-width: 800px;
+  max-width: 720px;
  margin: 4rem auto;
  padding: 0 2rem;
 }
@@ -111,6 +111,53 @@ svg {
  margin-bottom: 2rem;
 }
 /* ── Article Header ── */
 .article-header {
  margin-bottom: 3rem;
  padding-bottom: 2rem;
  border-bottom: 1px solid rgba(255, 255, 255, 0.08);
 }
 .article-header h1 {
  font-size: 2.2rem;
  letter-spacing: 1px;
  line-height: 1.3;
  margin: 0.5rem 0 1rem;
 }
 .article-meta {
  display: flex;
  align-items: center;
  gap: 0.5rem;
  font-size: 0.85rem;
  color: #666;
  text-transform: uppercase;
  letter-spacing: 1px;
 }
 .meta-sep {
  color: #444;
 }
 /* ── Article Footer ── */
 .article-footer {
  margin-top: 4rem;
  padding-top: 2rem;
  padding-bottom: 4rem;
  border-top: 1px solid rgba(255, 255, 255, 0.08);
 }
 .article-footer a {
  color: #888;
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  transition: color 0.2s;
 }
 .article-footer a:hover {
  color: #ff3c3c;
 }
 /* ── Project Grid ── */
 .project-grid {
  display: grid;
@@ -229,48 +276,186 @@ svg {
 /* ── Project Detail ── */
 .project-links {
-  margin: 1rem 0 2rem;
+  margin: 1rem 0 0;
  display: flex;
  gap: 1.5rem;
 }
 .project-links a {
  color: #ff3c3c;
  text-decoration: none;
-  margin-right: 1rem;
+  font-size: 0.9rem;
  letter-spacing: 0.5px;
  transition: opacity 0.2s;
 }
 .project-links a:hover {
-  text-decoration: underline;
+  opacity: 0.7;
 }
 .project-body {
-  line-height: 1.8;
+  line-height: 1.9;
-  color: #ddd;
+  color: #ccc;
  font-size: 1.05rem;
 }
 .project-body h2 {
  color: #fff;
  margin-top: 2rem;
  font-size: 1.4rem;
 }
 /* ── Back Link ── */
 .back-link {
  margin-top: 3rem;
  margin-bottom: 1rem;
  font-size: 1.5rem;
  letter-spacing: 0.5px;
  padding-bottom: 0.5rem;
  border-bottom: 1px solid rgba(255, 255, 255, 0.06);
 }
-.back-link a {
+.project-body h3 {
-  color: #888;
+  color: #eee;
  margin-top: 2.5rem;
  margin-bottom: 0.8rem;
  font-size: 1.2rem;
 }
 .project-body h4 {
  color: #ddd;
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 .project-body p {
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 .project-body a {
  color: #ff3c3c;
  text-decoration: none;
  border-bottom: 1px solid rgba(255, 60, 60, 0.3);
  transition: border-color 0.2s;
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 .project-body strong {
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 .project-body em {
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 /* ── Code Blocks ── */
 .project-body code {
  font-family: 'Geist Mono', monospace;
  font-size: 0.88em;
  background: rgba(255, 255, 255, 0.06);
  padding: 0.15em 0.4em;
  border-radius: 4px;
  color: #e8e8e8;
 }
 .project-body pre {
  background: rgba(255, 255, 255, 0.04);
  border: 1px solid rgba(255, 255, 255, 0.08);
  border-radius: 8px;
  padding: 1.2rem 1.5rem;
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 /* ── Blockquotes ── */
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  margin: 1.5rem 0;
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 /* ── Tables ── */
 .project-body table {
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  margin: 1.5rem 0;
  font-size: 0.9rem;
 }
-.back-link a:hover {
+.project-body thead th {
-  color: #ff3c3c;
+  text-align: left;
  padding: 0.6rem 0.8rem;
  border-bottom: 2px solid rgba(255, 255, 255, 0.15);
  color: #fff;
  font-weight: 600;
  font-size: 0.8rem;
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 .project-body tbody td {
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 }
 .project-body tbody tr:hover {
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 }
 /* ── Horizontal Rules ── */
 .project-body hr {
  border: none;
  height: 1px;
  background: rgba(255, 255, 255, 0.08);
  margin: 3rem 0;
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 /* ── Lists ── */
 .project-body ul, .project-body ol {
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 .project-body li {
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 .grafana-embed iframe {
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 }
 /* ── Responsive ── */
@media (max-width: 600px) {
  .centered h1 { font-size: 2rem; }
-  .page-content { margin: 2rem auto; }
+  .page-content { margin: 2rem auto; padding: 0 1.2rem; }
  .project-grid { grid-template-columns: 1fr; }
  .article-header h1 { font-size: 1.6rem; }
  .project-body { font-size: 0.95rem; }
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--- a/hugo/eliaskohout.de/content/projects/gebrauchtwagen-datenbank.md
+++ b/hugo/eliaskohout.de/content/projects/gebrauchtwagen-datenbank.md
@@ -1,159 +0,0 @@
 ---
 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?
  ==============================================
 */}}
--- a/hugo/eliaskohout.de/content/projects/gebrauchtwagen-datengrube.md
+++ b/hugo/eliaskohout.de/content/projects/gebrauchtwagen-datengrube.md
@@ -0,0 +1,191 @@
 ---
 title: "2 Million Used Cars and What They Tell Us"
 date: 2026-02-18
 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. Each listing carries make, model, fuel type,
 price, mileage, registration date, location, and a handful of other fields —
 enough to get interesting.
 ---
 ## Findings
 ### Price vs. Mileage
 The obvious place to start: how does price relate to mileage?
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/0852019305114cd189aedb67dea27721" height="450" >}}
 Two clusters jump out: low-mileage/high-price (garage queens) and
 high-mileage/low-price (daily drivers priced to move). The vast majority sits in
 modest territory on both axes. The plot caps at €1M and 1M km — beyond that, the
 data is mostly typos and placeholder values.
 Across the cleaned dataset, averages land at roughly **€28,400** and **75,600
 km**. That gives an overall ratio of about **€375 per 1,000 km** — not a
 depreciation rate in the strict sense, but a useful back-of-the-napkin metric
 for comparing brands.
 ### Price per Kilometer by Brand
 Of the **346 distinct makes**, 72 have more than 500 listings — enough for
 meaningful statistics.
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/1777bb018e9b47639b93ef31d97f9c89" height="450" >}}
 The ranking mirrors common perception — luxury brands dominate the top. But it
 has a blind spot: **age**. BYD ranks just below Ferrari and Rolls-Royce, not
 because it's a luxury vehicle, but because the average BYD listing is only **0.7
 years** old (overall average: **6.7 years**). Give these newcomers time to
 accumulate used inventory and their ratios will settle.
 ### Depreciation
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/e999ce3c237b4cae95b3331331a26261" height="400" >}}
 Average prices over mileage for Mercedes-Benz, Toyota, Volkswagen, and Volvo all
 follow the same shape: steep early depreciation that gradually flattens out.
 Brand-level differences show in the starting points and decay rates, but the
 exponential form is universal.
 The first 50k km wipe out **32–39%** of value across all brands — the new-car
 premium evaporating. From 50k to 200k km, depreciation settles into a steadier
 20–30% per bracket.
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/a801062ca49f49d0a1ef4f97ccb550c8" height="400" >}}
 Grouping listings into 50k-km brackets also gives a rough "survival curve" — not
 a true survival rate (it conflates production volume, usage patterns, and actual
 longevity), but the *shape* tells a story. Volvo shows the gentlest decline: 39%
 of listings remain at 100k km, still 6.6% at 250k. Toyota drops steeply early
 but then shows a stubbornly flat tail — 51 listings at 400k, 33 at 450k. Once a
 Toyota survives the initial culling, it apparently just keeps going.
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/38c5b2b61b8542b4aedc91b947253991" height="400" >}}
 Past 250k km, the numbers get chaotic — small sample sizes let a handful of
 collector cars or overpriced outliers distort the averages. Toyota is the most
 striking case: past 250k, depreciation goes consistently *negative* — prices
 *increase* from €7,775 to €13,481 at 450k. The Land Cruiser effect: the Toyotas
 that survive to extreme mileage are the models with cult followings, commanding
 premiums *because* they've proven their durability. Past 250k, survivor bias
 takes over — the remaining cars aren't representative anymore.
 ### The Survivors: Cars Beyond 250k km
 Out of the ~2 million listings, roughly **55,000** have a mileage of 250,000 km
 or more. That's about 3% of the dataset — a small slice, but more than enough to
 work with.
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/f9fcbcca31e64065a8e9970b88a8a999" height="400" >}}
 #### Who Makes It This Far?
 In absolute numbers, the usual suspects lead: Mercedes (8,900 listings),
 Volkswagen (8,200), BMW (6,700), Audi (5,300). Together they account for over
 half of all high-mileage entries. Renault's survivors average 362k km — the
 highest on the list — and BMW and Porsche carry remarkably high average prices
 past 250k (€24,600 and €27,300), hinting at maintained enthusiast cars rather
 than beaters.
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/6c4d0d116ba746f18c908ff5d4037da8" height="400" >}}
 But raw counts are misleading. More telling is what *share* of a brand's
 listings are high-mileage. That flips the picture: **Saab** leads at **32.6%** —
 almost one in three. No new cars since 2012 means the surviving inventory is old
 by definition, but it also speaks to owners who keep these cars running well
 past their expected shelf life. Iveco follows at 21% (commercial vehicles, no
 surprise). Then a cluster at 5–6%: **Volvo, Honda, Subaru, and Mercedes-Benz** —
 the brands enthusiasts *claim* are built to last, and the data is at least
 consistent.
 Notably absent: **Toyota**. Only about 2% of Toyota listings cross 250k — below
 the dataset average. That doesn't mean Toyotas die young; they may get exported
 or simply leave this platform. The data can't distinguish "the car died" from
 "the car left the market."
 #### Diesel vs. Petrol
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/b721ad75bf764693ba6243714899e0f0" height="400" >}}
 Diesel dominates the high-mileage segment: **6.75%** of diesel listings cross
 250k km, compared to just **1.58%** for petrol — a 4× overrepresentation. That's
 consistent with the "diesel lasts longer" narrative, though not proof: diesel
 cars also tend to be driven more (company cars, long-distance commuters).
 The real outlier is **CNG at 10.52%** — higher than diesel, though from a small
 sample of 5,500 listings (mostly fleet cars and taxis). Electric cars and
 hybrids are virtually absent at 0.07% and 0.16% — simply too young to have
 accumulated that kind of mileage.
 #### What Do They Cost?
 {{< grafana url="https://gr.eliaskohout.de/public-dashboards/543b7c49e5f742468f1d90b112cec799" height="400" >}}
 **Porsche** stands alone: a median of **€21,000** even past 250k km — these are
 maintained sports cars that appreciate regardless of mileage. **Land Rover**
 (€11,000 median) and **Iveco** (€12,000) also hold surprising value — cult
 status and commercial utility, respectively.
 Most brands cluster in the €3,000–€8,000 range. At the bottom: **Opel** at
 €2,650, **Peugeot** and **SEAT** at €3,000 — the genuine bargain-bin survivors.
 ---
 ## So What Should You Buy?
 Two million listings, a few dozen queries, and a lot of scatter plots later —
 what's the actual answer?
 It depends on what you're optimizing for.
 **If you want the car that refuses to die:** look at diesel Volvo, Mercedes, or
 Subaru in the 150–200k km range. These brands show up disproportionately at
 extreme mileage, and their survival curves decline more gently than most. A
 diesel Mercedes with 180k km on the clock isn't halfway through its life — it
 might be a third of the way.
 **If you want the best deal per remaining kilometer:** the sweet spot sits around
 100–150k km for most brands. The steepest depreciation is already behind you
 (that 32–39% first-bracket hit), but the car still has plenty of mechanical life
 left. Volkswagen and Opel are the value picks here — median prices in the low
 single-digit thousands, well-understood mechanicals, and parts that are cheap
 and everywhere.
 **If you want something that holds its value no matter what:** Toyota and
 Porsche. Toyota's prices actually *increase* past 250k km — the Land Cruiser
 effect — and Porsche commands a €21k median even at quarter-million mileage.
 You're not buying depreciation; you're buying into a secondary market where
 demand outstrips supply.
 **If you just want cheap and functional:** Opel, SEAT, or Peugeot past 200k km.
 Median prices between €2,650 and €3,000. Nobody will envy your car. Nobody will
 steal it either. And it'll probably keep running.
 One thing the data can't tell you: the condition of any *specific* car. Averages
 are averages. A well-maintained Fiat at 300k km will outlast a neglected BMW at
 100k every time. The numbers here describe the market, not the machine in front
 of you. For that, you still need a mechanic — preferably one who doesn't own a
 dealership.
--- a/hugo/eliaskohout.de/content/projects/llm-confidence-chat.md
+++ b/hugo/eliaskohout.de/content/projects/llm-confidence-chat.md
@@ -1,29 +0,0 @@
 ---
 title: "LLM Confidence Chat Interface"
 draft: true
 date: 2024-06-01
 tags: ["Python", "ML", "Full-Stack"]
 summary: "A chat interface making LLM confidence scores accessible to non-technical users."
 code: "https://github.com/yourusername/project"
 demo: "https://demo.example.com"
 ---
 ## Problem
 Non-technical users have no way to assess how confident an LLM is in its responses.
 ## Approach
 Built an interactive chat interface integrating lm-polygraph for
 uncertainty estimation with an intuitive visualization layer.
 ## Tech Stack
 - Python, FastAPI
 - lm-polygraph
 - React
 ## Challenges & Learnings
 Translating probabilistic outputs into user-friendly visual indicators
 while keeping the interface responsive.
--- a/hugo/eliaskohout.de/layouts/_default/single.html
+++ b/hugo/eliaskohout.de/layouts/_default/single.html
@@ -2,25 +2,30 @@
  {{- partial "background.html" . -}}
  <main class="page-content">
    <header class="article-header">
      <div class="article-meta">
        <time datetime="{{ .Date.Format "2006-01-02" }}">{{ .Date.Format "Jan 2, 2006" }}</time>
        <span class="meta-sep">·</span>
        <span>{{ math.Round (div (countwords .Content) 200.0) }} min read</span>
      </div>
      <h1>{{ .Title }}</h1>
      <p class="tags">
        {{ range .Params.tags }}
          <span class="tag">{{ . }}</span>
        {{ end }}
      </p>
      <div class="project-links">
-      {{ with .Params.code }}<a href="{{ . }}">[Code]</a>{{ end }}
+        {{ with .Params.code }}<a href="{{ . }}">Code ↗</a>{{ end }}
-      {{ with .Params.demo }}<a href="{{ . }}">[Live Demo]</a>{{ end }}
+        {{ with .Params.demo }}<a href="{{ . }}">Live Demo ↗</a>{{ end }}
      </div>
    </header>
    <article class="project-body">
      {{ .Content }}
    </article>
-    <div class="back-link">
+    <footer class="article-footer">
      <a href="/projects/">← all projects</a>
-    </div>
+    </footer>
  </main>
 {{ end }}
Author	SHA1	Message	Date
Elias Kohout	867f67e904	style: redesign article page layout and typography All checks were successful Build and Push Docker Container / build-and-push (push) Successful in 48s Details	2026-02-18 04:21:17 +01:00
Elias Kohout	3a25549811	refactor: rewrite used car article, remove LLM confidence chat draft	2026-02-18 04:20:53 +01:00