🔧 Repair Intelligence · Home Appliances

Appliance error codes,
mapped to ranked repairs.

A structured dataset that turns a fault code on the display into an actionable repair plan — keyed by composite (brand, market, appliance type, code) identity, with every fact traced to an official manufacturer listing.

438
verified codes
13
brands · 2 markets
26
brand × market × type pairs
288
ranked repairs

Why it exists

"What does 5C mean on my Samsung washer, and how do I fix it?" is answered today by ad-riddled content farms with no structure. No developer-ready dataset maps (brand, appliance_type, code) → meaning → ranked fix with honest provenance. ApplianceDB does.

Composite code identity

Samsung washer 5C ≠ Samsung dishwasher 5C ≠ Samsung UK washer 5C. Every record is unique on (brand, market, appliance_type, code).

Manufacturer-directed fixes

Each repair carries an explicit rank_basis. v1 ships the manufacturer's directed remedy with a DIY difficulty tier.

Provenance per row

Every code, fix, and part row carries its source tier and exact source URL — plus dated per-retailer price observations. No memory sourcing, ever.

Facts, not prose

Meanings and steps are paraphrased into original wording — no copyrighted manual text is reproduced.

Coverage each pair ≥ 10 codes

BrandWasherDryerDishwasherRefrigeratorOven/Range
LG1414111618
Samsung16141414
GE1316
Whirlpool181211
Maytag18
Bosch2018
Frigidaire1917
Samsung (UK)26
Hotpoint (UK)17
Indesit (UK)17
Beko (UK)13
Miele (UK)27
Candy (UK)22
Hoover (UK)23

Coverage honesty over width: GE refrigerator (8 codes) and GE combo washer (2) were dropped from v1 for falling below the ≥ 10-per-pair gate rather than padded.

How it's built — the honest part

Get the data

The free developer sample is in the identical schema as the commercial corpus — CSV + Parquet.

FileRowsContents
error_codes.csv438Code registry with meaning, component, cause, severity, source type + URL
repair_procedures.csv288Ranked fixes with difficulty, paraphrased steps, currency-aware cost ranges, and per-row provenance
replacement_parts.csv20Exact OEM part numbers with dated street-price observations in USD and GBP
error_codes_fixes_joined.csv479Pre-joined analytical view for one-file ingestion
brand_recalls.csv69Appliance recalls per brand, cross-referenced from RecallDB with agency provenance
import pandas as pd

df = pd.read_csv("error_codes_fixes_joined.csv")
lg_drain = df[(df["brand"] == "LG") & (df["cause_category"] == "drainage")]
print(lg_drain[["appliance_type", "code", "meaning", "title", "diy_difficulty"]])

Pricing

TierWhat you getPrice
Sample438 codes (this repo + Kaggle) · CSV + ParquetFree
Repair Intelligence SnapshotFull corpus · CSV + Parquet + SQLite · quarterly refresh · instant downloadBuy — $299
Enterprise Integration LicenseSnapshot + commercial embedding rights (warranty / field-service) · parts cross-reference · priority coverageRequest — $2,999

The Snapshot is self-serve: secure Stripe checkout (card / Apple Pay / Google Pay) with instant download after payment. Enterprise is scoped to your platform — tell us what you need and we reply with an invoice.

Licensing & custom coverage: appliancedb.untapped361@silomails.com — if the button above doesn't open your mail app, copy the address and write to us directly (subject: "ApplianceDB licensing").

License

Free sample — ODbL-1.0

This 438-code sample is free for research, education, and benchmarking with attribution and share-alike.

Full / commercial dataset

Separate commercial license included with the paid tiers above — commercial embedding, parts cross-references, and priority coverage requests.

⚠️ Repair steps are educational reference, not a substitute for the manufacturer's service manual. Disconnect power and water before servicing; gas, sealed-refrigerant, and high-voltage work is for qualified technicians only.