Eurostat Data Browser — Apparel, Textiles & Trade (PRODCOM, COMEXT)

Two verified observations pulled during the August 2026 research pass, exactly as they land in your warehouse.

 dataset       | geo       | nace_r2 | indic_bt | s_adj | unit | time     | value
 sts_trtu_m    | EU27_2020 | G47     | VOL_SLS  | CA    | I21  | 2026-06  | 105.5

 dataset       | geo       | coicop | unit                  | time    | value
 prc_hicp_manr | EU27_2020 | CP031  | annual rate of change | 2025-12 | 0.3

The first row is calendar-adjusted EU retail volume of sales, index 2021=100, for June 2026. The second is the December 2025 HICP annual rate of change for the CP031 Clothing subclass: euro-area clothing inflation running at 0.3 percent. Every row carries its full dimension key — dataset code, geography, classification node, adjustment flag, unit and period — so nothing arrives as an unlabeled number.

Eleven documented dimensions cover every apparel-relevant family in the warehouse. Definitions below are marked verified against live responses, not inferred from documentation.

Three axes define the envelope.

Geography: EU-27 and euro-area aggregates (EU27_2020, EA20), all EU member states, plus numerous non-EU partner and reporter countries — enough to model both intra-EU flows and imports from major sourcing markets.

Temporal: Comext detailed trade files run from January 1988 to the latest reference month. Retail turnover and HICP series stretch back into the 1990s; the August 2026 verification pull confirmed observations through June 2026. Europroms adds annual production series.

Granularity: country × product classification × period, at monthly, quarterly and annual frequencies depending on the dataset. The scale behind it: 8,150 dataflows listed in the SDMX structure as of August 2026, with individual apparel-relevant datasets ranging from thousands to millions of observations.

API, files, or your warehouse. Daily, weekly, or hourly.

Seven of Datadory's eight personas carry this feed in their apparel, accessories & luxury goods packs — the widest persona reach of any dataset in the slice.

1. Market Researchers & Consultants — official EU production, trade and price series for market sizing and import-competition monitoring; the persona pack scores it relevance 3 with the use case "official EU production, trade and price series."
2. Journalists, Academics & Students — Eurostat remains the default citation for European apparel statistics, with methodology and provenance attached to every figure.
3. Data Scientists & ML Engineers — PRODCOM and Comext queries become exogenous features for demand models; relevance 3, use case "PRODCOM and COMEXT queries via API for EU apparel." See data scientists use cases.
4. Developers & Data Product Builders — consistent dimension keys across 8,150 dataflows make pipelines boring in the good way. See developers builders use cases.
5. E-commerce Operators — EU demand indices and clothing-price trends feed assortment and promotion planning.
6. Investors & Quant Researchers — trade-flow and production trends serve as sector-level signals ahead of reported results.
7. Competitive Intelligence & Product Teams — sector dashboards tracking who produces what, where, and at what price trajectory.

Four concrete jobs, each mapped to a specific dataset family inside the warehouse.

Size EU wearing-apparel markets. Europroms sold production (DS-059367) on the PRODCOM list gives country-level manufacture of wearing apparel, spliced against exports and imports so domestic output and traded supply separate cleanly.

Monitor import competition. Comext DS-059322 carries EU trade since 2002 at HS2-4-6 and CN8 detail — CN8 code 14131000 resolves to a single product line — while DS-059330 aggregates by CN sections for faster screening. History to January 1988 supports decade-scale sourcing-shift analysis.

Read consumer demand. Retail turnover for NACE G47 (with G477 specialised retail isolating clothing stores) arrives as deflator-adjusted turnover (NETTUR) or volume of sales (VOL_SLS), indexed 2021=100 and calendar-adjustable.

Price it. HICP annual rates for ECOICOP subclass CP031 put a number on clothing inflation — 0.3 percent year-on-year for the euro area in December 2025.

For bilateral apparel flows the nearest rival is Trade Map from the International Trade Centre: its richer tier adds quantities, unit values and tariff indicators across roughly 220 territories, but registration gates the detail. This feed counters with deeper history (Comext from January 1988 versus Trade Map's shorter runs), full CN8 product resolution and no account wall between you and the numbers.

On prices, the comparison is geographic: BLS Public Data API's CPI Apparel Series serves the United States (CUSR0000SAA monthly since January 1947) where this feed serves European HICP clothing indices. Houses modelling both sides of the Atlantic run the two together rather than choosing. The head-to-head lives at vs BLS Public Data API — CPI Apparel Series.

Within the same industry slice, Eurostat Database — Bulk Download (Eurobase) ships the same warehouse as whole-domain files; this feed wins when you want filtered, keyed, current observations instead of everything.

Three caveats from the verification pass, stated plainly.

First, dimension codes move. Legacy identifiers still circulate in older material — DS-066341 now returns nothing, and DS-059322 / DS-059330 are the current homes for CN-level trade. Datadory maintains the mapping so your queries follow the living codes, not the retired ones.

Second, size cuts both ways. An unfiltered query against Europroms DS-059367 returned a 19.4 MB payload; the dimensions (freq, reporter, product, indicators, TIME_PERIOD) reward deliberate filtering. Delivered feeds arrive pre-scoped to the product lines you name.

Third, one gap stayed open: the exact PRODCOM sold-production dataset code covering NACE C14 wearing apparel was not located among the 8,150 dataflows and needs confirmation before any production dependency. We flag gaps like this rather than papering over them — see the note rail below for related pages that cover adjacent ground.